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diff --git a/LEGAL_NOTICE.md b/LEGAL_NOTICE.md index a2d0806c..50a1d141 100644 --- a/LEGAL_NOTICE.md +++ b/LEGAL_NOTICE.md @@ -1,46 +1,55 @@ ## Legal Notice -This repository is _not_ associated with or endorsed by providers of the APIs contained in this GitHub repository. This project is intended **for educational purposes only**. This is just a little personal project. Sites may contact me to improve their security or request the removal of their site from this repository. - -Please note the following: - -## Legal Notice +This repository is **not associated with or endorsed** by the providers of the APIs contained herein. This project is intended **for educational purposes only**. It is a personal project aimed at learning and exploration. Owners of any included sites or services may contact me to improve their security or request the removal of their content from this repository. ### **Affiliation Disclaimer** -This repository is not associated with or endorsed by the providers of the APIs contained in this repository. The project is intended for educational purposes only. The APIs, services, trademarks, and other intellectual property mentioned in this repository are the property of their respective owners, with no claim of ownership or affiliation by this project. + +This repository is not associated with or endorsed by any of the API providers mentioned herein. All trademarks, API services, and other intellectual property referenced are the property of their respective owners. No claim of ownership or affiliation is made by this project. ### **Liability Limitation** -Under no circumstances shall the author of this repository be liable for any direct, indirect, incidental, special, consequential, or punitive damages, including but not limited to, loss of profits, data, or use, arising out of or in connection with the repository, regardless of whether such damages were foreseeable and whether the author was advised of the possibility of such damages. + +Under no circumstances shall the author of this repository be liable for any direct, indirect, incidental, special, consequential, or punitive damages—including but not limited to loss of profits, data, or use—arising out of or in connection with the repository. This limitation applies regardless of whether such damages were foreseeable or whether the author was advised of the possibility of such damages. ### **No Warranties** -The repository is provided on an "as is" and "as available" basis without any warranties of any kind, either express or implied, including but not limited to, implied warranties of merchantability, fitness for a particular purpose, or non-infringement. + +This repository is provided on an "as is" and "as available" basis without any warranties of any kind, express or implied. This includes, but is not limited to, implied warranties of merchantability, fitness for a particular purpose, and non-infringement. ### **User Responsibility** -Users assume all risk for their use of this repository and are solely responsible for any damage or loss, including but not limited to financial loss, of any kind, to any party, that results from the use or misuse of the repository and its contents. + +Users assume all risks associated with the use of this repository. They are solely responsible for any damage or loss—including financial loss—that results from the use or misuse of the repository and its contents. ### **Legal Compliance** -Users are responsible for ensuring their use of the repository and its contents complies with all local, state, national, and international laws and regulations. + +Users are responsible for ensuring that their use of the repository and its contents complies with all applicable local, state, national, and international laws and regulations. ### **Indemnification** -Users agree to indemnify, defend, and hold harmless the author from any claims, liabilities, damages, losses, or expenses, including legal fees, arising out of or in any way connected with their use of this repository, violation of these terms, or infringement of any intellectual property or other rights of any person or entity. + +Users agree to indemnify, defend, and hold harmless the author from any claims, liabilities, damages, losses, or expenses—including legal fees—arising out of or in any way connected with their use of this repository, violation of these terms, or infringement of any intellectual property or other rights of any person or entity. ### **No Endorsement** + The inclusion of third-party content does not imply endorsement or recommendation of such content by the author. ### **Governing Law and Jurisdiction** -Any disputes arising out of or related to the use of this repository shall be governed by the laws of the author's jurisdiction, without regard to its conflict of law principles. + +Any disputes arising out of or related to the use of this repository shall be governed by the laws of the author's jurisdiction, without regard to conflict of law principles. ### **Severability** -If any provision of this notice is found to be unlawful, void, or unenforceable, then that provision shall be deemed severable from this notice and shall not affect the validity and enforceability of any remaining provisions. + +If any provision of this notice is found to be unlawful, void, or unenforceable, that provision shall be deemed severable from this notice and shall not affect the validity and enforceability of the remaining provisions. ### **Acknowledgment of Understanding** + By using this repository, users acknowledge that they have read, understood, and agree to be bound by these terms. ### **Updates and Changes** + The author reserves the right to modify, update, or remove any content, information, or features in this repository at any time without prior notice. Users are responsible for regularly reviewing the content and any changes made to this repository. ### **Unforeseen Consequences** -The author of this repository is not responsible for any consequences, damages, or losses arising from the use or misuse of this repository or the content provided by the third-party APIs. Users are solely responsible for their actions and any repercussions that may follow. + +The author is not responsible for any consequences, damages, or losses arising from the use or misuse of this repository or the content provided by third-party APIs. Users are solely responsible for their actions and any repercussions that may follow. ### **Educational Purpose** -Please note that this project and its content are provided strictly for educational purposes. Users acknowledge that they are using the APIs and models at their own risk and agree to comply with any applicable laws and regulations. + +This project and its content are provided strictly for educational purposes. Users acknowledge that they are using the APIs and models at their own risk and agree to comply with all applicable laws and regulations. @@ -1,18 +1,22 @@ +  <a href="https://trendshift.io/repositories/1692" target="_blank"><img src="https://trendshift.io/api/badge/repositories/1692" alt="xtekky%2Fgpt4free | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> --- -Written by [@xtekky](https://github.com/xtekky) & maintained by [@hlohaus](https://github.com/hlohaus) +<p align="center"><strong>Written by <a href="https://github.com/xtekky">@xtekky</a></strong></p> <div id="top"></div> -> By using this repository or any code related to it, you agree to the [legal notice](https://github.com/xtekky/gpt4free/blob/main/LEGAL_NOTICE.md). The author is **not responsible for the usage of this repository nor endorses it**, nor is the author responsible for any copies, forks, re-uploads made by other users, or anything else related to GPT4Free. This is the author's only account and repository. To prevent impersonation or irresponsible actions, please comply with the GNU GPL license this Repository uses. +> [!IMPORTANT] +> By using this repository or any code related to it, you agree to the [legal notice](LEGAL_NOTICE.md). The author is **not responsible for the usage of this repository nor endorses it**, nor is the author responsible for any copies, forks, re-uploads made by other users, or anything else related to GPT4Free. This is the author's only account and repository. To prevent impersonation or irresponsible actions, please comply with the GNU GPL license this Repository uses. -> [!Warning] > _"gpt4free"_ serves as a **PoC** (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control. +> [!WARNING] +> _"gpt4free"_ serves as a **PoC** (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control. -> [!Note] > <sup><strong>Lastet version:</strong></sup> [](https://pypi.org/project/g4f) [](https://hub.docker.com/r/hlohaus789/g4f) +> [!NOTE] +> <sup><strong>Latest version:</strong></sup> [](https://pypi.org/project/g4f) [](https://hub.docker.com/r/hlohaus789/g4f) > <sup><strong>Stats:</strong></sup> [](https://pepy.tech/project/g4f) [](https://pepy.tech/project/g4f) ```sh @@ -24,64 +28,57 @@ docker pull hlohaus789/g4f ``` ## 🆕 What's New + - **For comprehensive details on new features and updates, please refer to our [Releases](https://github.com/xtekky/gpt4free/releases) page** + - **Installation Guide for Windows (.exe):** 💻 [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe) + - **Join our Telegram Channel:** 📨 [telegram.me/g4f_channel](https://telegram.me/g4f_channel) + - **Join our Discord Group:** 💬 [discord.gg/XfybzPXPH5](https://discord.gg/5E39JUWUFa) -- Added `gpt-4o`, simply use `gpt-4o` in `chat.completion.create`. -- Installation Guide for Windows (.exe): 💻 [#installation-guide-for-windows](#installation-guide-for-windows-exe) -- Join our Telegram Channel: 📨 [telegram.me/g4f_channel](https://telegram.me/g4f_channel) -- Join our Discord Group: 💬 [discord.gg/XfybzPXPH5](https://discord.gg/XfybzPXPH5) -- `g4f` now supports 100% local inference: 🧠 [local-docs](https://g4f.mintlify.app/docs/core/usage/local) ## 🔻 Site Takedown Is your site on this repository and you want to take it down? Send an email to takedown@g4f.ai with proof it is yours and it will be removed as fast as possible. To prevent reproduction please secure your API. 😉 ## 🚀 Feedback and Todo - -You can always leave some feedback here: https://forms.gle/FeWV9RLEedfdkmFN6 - -As per the survey, here is a list of improvements to come - -- [x] Update the repository to include the new openai library syntax (ex: `Openai()` class) | completed, use `g4f.client.Client` -- [ ] Golang implementation -- [ ] 🚧 Improve Documentation (in /docs & Guides, Howtos, & Do video tutorials) -- [x] Improve the provider status list & updates -- [ ] Tutorials on how to reverse sites to write your own wrapper (PoC only ofc) -- [x] Improve the Bing wrapper. (Wait and Retry or reuse conversation) -- [ ] 🚧 Write a standard provider performance test to improve the stability -- [ ] Potential support and development of local models -- [ ] 🚧 Improve compatibility and error handling +**You can always leave some feedback here:** https://forms.gle/FeWV9RLEedfdkmFN6 + +**As per the survey, here is a list of improvements to come** + - [x] Update the repository to include the new openai library syntax (ex: `Openai()` class) | completed, use `g4f.client.Client` + - [ ] Golang implementation + - [ ] 🚧 Improve Documentation (in /docs & Guides, Howtos, & Do video tutorials) + - [x] Improve the provider status list & updates + - [ ] Tutorials on how to reverse sites to write your own wrapper (PoC only ofc) + - [x] Improve the Bing wrapper. (Wait and Retry or reuse conversation) + - [ ] 🚧 Write a standard provider performance test to improve the stability + - [ ] Potential support and development of local models + - [ ] 🚧 Improve compatibility and error handling ## 📚 Table of Contents - -- [🆕 What's New](#-whats-new) -- [📚 Table of Contents](#-table-of-contents) -- [🛠️ Getting Started](#-getting-started) - - [Docker Container Guide](#docker-container-guide) - - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe) - - [Use python](#use-python) - - [Prerequisites](#prerequisites) - - [Install using PyPI package:](#install-using-pypi-package) - - [Install from source:](#install-from-source) - - [Install using Docker:](#install-using-docker) -- [💡 Usage](#-usage) - - [Text Generation](#text-generation) - - [Image Generation](#image-generation) - - [Web UI](#web-ui) - - [Interference API](#interference-api) - - [Configuration](#configuration) -- [🚀 Providers and Models](#-providers-and-models) - - [GPT-4](#gpt-4) - - [GPT-3.5](#gpt-35) - - [Other](#other) - - [Models](#models) -- [🔗 Powered by gpt4free](#-powered-by-gpt4free) -- [🤝 Contribute](#-contribute) - - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider) - - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code) -- [🙌 Contributors](#-contributors) -- [©️ Copyright](#-copyright) -- [⭐ Star History](#-star-history) -- [📄 License](#-license) + - [🆕 What's New](#-whats-new) + - [📚 Table of Contents](#-table-of-contents) + - [🛠️ Getting Started](#-getting-started) + - [Docker Container Guide](#docker-container-guide) + - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe) + - [Use python](#use-python) + - [Prerequisites](#prerequisites) + - [Install using PyPI package](#install-using-pypi-package) + - [Install from source](#install-from-source) + - [Install using Docker](#install-using-docker) + - [💡 Usage](#-usage) + - [Text Generation](#text-generation) + - [Image Generation](#image-generation) + - [Web UI](#web-ui) + - [Interference API](#interference-api) + - [Local Inference](docs/local.md) + - [Configuration](#configuration) + - [🚀 Providers and Models](docs/providers-and-models.md) + - [🔗 Powered by gpt4free](#-powered-by-gpt4free) + - [🤝 Contribute](#-contribute) + - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider) + - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code) + - [🙌 Contributors](#-contributors) + - [©️ Copyright](#-copyright) + - [⭐ Star History](#-star-history) + - [📄 License](#-license) ## 🛠️ Getting Started @@ -125,15 +122,15 @@ To ensure the seamless operation of our application, please follow the instructi By following these steps, you should be able to successfully install and run the application on your Windows system. If you encounter any issues during the installation process, please refer to our Issue Tracker or try to get contact over Discord for assistance. -Run the **Webview UI** on other Platfroms: +Run the **Webview UI** on other Platforms: -- [/docs/guides/webview](https://github.com/xtekky/gpt4free/blob/main/docs/webview.md) +- [/docs/guides/webview](docs/webview.md) ##### Use your smartphone: Run the Web UI on Your Smartphone: -- [/docs/guides/phone](https://github.com/xtekky/gpt4free/blob/main/docs/guides/phone.md) +- [/docs/guides/phone](docs/guides/phone.md) #### Use python @@ -149,17 +146,16 @@ pip install -U g4f[all] ``` How do I install only parts or do disable parts? -Use partial requirements: [/docs/requirements](https://github.com/xtekky/gpt4free/blob/main/docs/requirements.md) +Use partial requirements: [/docs/requirements](docs/requirements.md) ##### Install from source: How do I load the project using git and installing the project requirements? -Read this tutorial and follow it step by step: [/docs/git](https://github.com/xtekky/gpt4free/blob/main/docs/git.md) +Read this tutorial and follow it step by step: [/docs/git](docs/git.md) ##### Install using Docker: - How do I build and run composer image from source? -Use docker-compose: [/docs/docker](https://github.com/xtekky/gpt4free/blob/main/docs/docker.md) +Use docker-compose: [/docs/docker](docs/docker.md) ## 💡 Usage @@ -172,7 +168,7 @@ client = Client() response = client.chat.completions.create( model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello"}], - ... + # Add any other necessary parameters ) print(response.choices[0].message.content) ``` @@ -182,49 +178,43 @@ Hello! How can I assist you today? ``` #### Image Generation - ```python from g4f.client import Client client = Client() response = client.images.generate( - model="gemini", - prompt="a white siamese cat", - ... + model="dall-e-3", + prompt="a white siamese cat", + # Add any other necessary parameters ) + image_url = response.data[0].url +print(f"Generated image URL: {image_url}") ``` -[](https://github.com/xtekky/gpt4free/blob/main/docs/client.md) +[](docs/client.md) **Full Documentation for Python API** - -- New AsyncClient API from G4F: [/docs/async_client](https://github.com/xtekky/gpt4free/blob/main/docs/async_client.md) -- Client API like the OpenAI Python library: [/docs/client](https://github.com/xtekky/gpt4free/blob/main/docs/client.md) -- Legacy API with python modules: [/docs/legacy](https://github.com/xtekky/gpt4free/blob/main/docs/legacy.md) + - **Async Client API from G4F:** [/docs/async_client](docs/async_client.md) + - **Client API like the OpenAI Python library:** [/docs/client](docs/client.md) + - **Legacy API with python modules:** [/docs/legacy](docs/legacy.md) #### Web UI - -To start the web interface, type the following codes in python: - +**To start the web interface, type the following codes in python:** ```python from g4f.gui import run_gui + run_gui() ``` - or execute the following command: - ```bash python -m g4f.cli gui -port 8080 -debug ``` #### Interference API - You can use the Interference API to serve other OpenAI integrations with G4F. - -See docs: [/docs/interference](https://github.com/xtekky/gpt4free/blob/main/docs/interference.md) - -Access with: http://localhost:1337/v1 +**See docs:** [/docs/interference](docs/interference-api.md) +**Access with:** http://localhost:1337/v1 ### Configuration @@ -318,139 +308,6 @@ export G4F_PROXY="http://host:port" set G4F_PROXY=http://host:port ``` -## 🚀 Providers and Models - -### GPT-4 - -| Website | Provider | GPT-3.5 | GPT-4 | Stream | Status | Auth | -| -------------------------------------- | ------------------------- | ------- | ----- | ------ | ---------------------------------------------------------- | ----- | -| [bing.com](https://bing.com/chat) | `g4f.Provider.Bing` | ❌ | ✔️ | ✔️ |  | ❌ | -| [chatgpt.ai](https://chatgpt.ai) | `g4f.Provider.ChatgptAi` | ❌ | ✔️ | ✔️ |  | ❌ | -| [liaobots.site](https://liaobots.site) | `g4f.Provider.Liaobots` | ✔️ | ✔️ | ✔️ |  | ❌ | -| [chatgpt.com](https://chatgpt.com) | `g4f.Provider.OpenaiChat` | ✔️ | ✔️ | ✔️ |  | ❌+✔️ | -| [raycast.com](https://raycast.com) | `g4f.Provider.Raycast` | ✔️ | ✔️ | ✔️ |  | ✔️ | -| [beta.theb.ai](https://beta.theb.ai) | `g4f.Provider.Theb` | ✔️ | ✔️ | ✔️ |  | ❌ | -| [you.com](https://you.com) | `g4f.Provider.You` | ✔️ | ✔️ | ✔️ |  | ❌ | - -## Best OpenSource Models - -While we wait for gpt-5, here is a list of new models that are at least better than gpt-3.5-turbo. **Some are better than gpt-4**. Expect this list to grow. - -| Website | Provider | parameters | better than | -| ---------------------------------------------------------------------------------------- | ----------------------------------- | ----------------- | ------------------ | -| [claude-3-opus](https://anthropic.com/) | `g4f.Provider.You` | ?B | gpt-4-0125-preview | -| [command-r+](https://txt.cohere.com/command-r-plus-microsoft-azure/) | `g4f.Provider.HuggingChat` | 104B | gpt-4-0314 | -| [llama-3-70b](https://meta.ai/) | `g4f.Provider.Llama` or `DeepInfra` | 70B | gpt-4-0314 | -| [claude-3-sonnet](https://anthropic.com/) | `g4f.Provider.You` | ?B | gpt-4-0314 | -| [reka-core](https://chat.reka.ai/) | `g4f.Provider.Reka` | 21B | gpt-4-vision | -| [dbrx-instruct](https://www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm) | `g4f.Provider.DeepInfra` | 132B / 36B active | gpt-3.5-turbo | -| [mixtral-8x22b](https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1) | `g4f.Provider.DeepInfra` | 176B / 44b active | gpt-3.5-turbo | - -### GPT-3.5 - -| Website | Provider | GPT-3.5 | GPT-4 | Stream | Status | Auth | -| ---------------------------------------------------------- | ----------------------------- | ------- | ----- | ------ | ---------------------------------------------------------- | ---- | -| [chat3.aiyunos.top](https://chat3.aiyunos.top/) | `g4f.Provider.AItianhuSpace` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chat10.aichatos.xyz](https://chat10.aichatos.xyz) | `g4f.Provider.Aichatos` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatforai.store](https://chatforai.store) | `g4f.Provider.ChatForAi` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgpt4online.org](https://chatgpt4online.org) | `g4f.Provider.Chatgpt4Online` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgpt-free.cc](https://www.chatgpt-free.cc) | `g4f.Provider.ChatgptNext` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgptx.de](https://chatgptx.de) | `g4f.Provider.ChatgptX` | ✔️ | ❌ | ✔️ |  | ❌ | -| [duckduckgo.com](https://duckduckgo.com/duckchat) | `g4f.Provider.DDG` | ✔️ | ❌ | ✔️ |  | ❌ | -| [feedough.com](https://www.feedough.com) | `g4f.Provider.Feedough` | ✔️ | ❌ | ✔️ |  | ❌ | -| [flowgpt.com](https://flowgpt.com/chat) | `g4f.Provider.FlowGpt` | ✔️ | ❌ | ✔️ |  | ❌ | -| [freegptsnav.aifree.site](https://freegptsnav.aifree.site) | `g4f.Provider.FreeGpt` | ✔️ | ❌ | ✔️ |  | ❌ | -| [gpttalk.ru](https://gpttalk.ru) | `g4f.Provider.GptTalkRu` | ✔️ | ❌ | ✔️ |  | ❌ | -| [koala.sh](https://koala.sh) | `g4f.Provider.Koala` | ✔️ | ❌ | ✔️ |  | ❌ | -| [app.myshell.ai](https://app.myshell.ai/chat) | `g4f.Provider.MyShell` | ✔️ | ❌ | ✔️ |  | ❌ | -| [perplexity.ai](https://www.perplexity.ai) | `g4f.Provider.PerplexityAi` | ✔️ | ❌ | ✔️ |  | ❌ | -| [poe.com](https://poe.com) | `g4f.Provider.Poe` | ✔️ | ❌ | ✔️ |  | ✔️ | -| [talkai.info](https://talkai.info) | `g4f.Provider.TalkAi` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chat.vercel.ai](https://chat.vercel.ai) | `g4f.Provider.Vercel` | ✔️ | ❌ | ✔️ |  | ❌ | -| [aitianhu.com](https://www.aitianhu.com) | `g4f.Provider.AItianhu` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgpt.bestim.org](https://chatgpt.bestim.org) | `g4f.Provider.Bestim` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatbase.co](https://www.chatbase.co) | `g4f.Provider.ChatBase` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgptdemo.info](https://chatgptdemo.info/chat) | `g4f.Provider.ChatgptDemo` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chat.chatgptdemo.ai](https://chat.chatgptdemo.ai) | `g4f.Provider.ChatgptDemoAi` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chatgptfree.ai](https://chatgptfree.ai) | `g4f.Provider.ChatgptFree` | ✔️ | ❌ | ❌ |  | ❌ | -| [chatgptlogin.ai](https://chatgptlogin.ai) | `g4f.Provider.ChatgptLogin` | ✔️ | ❌ | ✔️ |  | ❌ | -| [chat.3211000.xyz](https://chat.3211000.xyz) | `g4f.Provider.Chatxyz` | ✔️ | ❌ | ✔️ |  | ❌ | -| [gpt6.ai](https://gpt6.ai) | `g4f.Provider.Gpt6` | ✔️ | ❌ | ✔️ |  | ❌ | -| [gptchatly.com](https://gptchatly.com) | `g4f.Provider.GptChatly` | ✔️ | ❌ | ❌ |  | ❌ | -| [ai18.gptforlove.com](https://ai18.gptforlove.com) | `g4f.Provider.GptForLove` | ✔️ | ❌ | ✔️ |  | ❌ | -| [gptgo.ai](https://gptgo.ai) | `g4f.Provider.GptGo` | ✔️ | ❌ | ✔️ |  | ❌ | -| [gptgod.site](https://gptgod.site) | `g4f.Provider.GptGod` | ✔️ | ❌ | ✔️ |  | ❌ | -| [onlinegpt.org](https://onlinegpt.org) | `g4f.Provider.OnlineGpt` | ✔️ | ❌ | ✔️ |  | ❌ | - -### Other - -| Website | Provider | Stream | Status | Auth | -| -------------------------------------------------------------------------------------------- | ----------------------------- | ------ | ---------------------------------------------------------- | ---- | -| [openchat.team](https://openchat.team) | `g4f.Provider.Aura` | ✔️ |  | ❌ | -| [blackbox.ai](https://www.blackbox.ai) | `g4f.Provider.Blackbox` | ✔️ |  | ❌ | -| [cohereforai-c4ai-command-r-plus.hf.space](https://cohereforai-c4ai-command-r-plus.hf.space) | `g4f.Provider.Cohere` | ✔️ |  | ❌ | -| [deepinfra.com](https://deepinfra.com) | `g4f.Provider.DeepInfra` | ✔️ |  | ❌ | -| [free.chatgpt.org.uk](https://free.chatgpt.org.uk) | `g4f.Provider.FreeChatgpt` | ✔️ |  | ❌ | -| [gemini.google.com](https://gemini.google.com) | `g4f.Provider.Gemini` | ✔️ |  | ✔️ | -| [ai.google.dev](https://ai.google.dev) | `g4f.Provider.GeminiPro` | ✔️ |  | ✔️ | -| [gemini-chatbot-sigma.vercel.app](https://gemini-chatbot-sigma.vercel.app) | `g4f.Provider.GeminiProChat` | ✔️ |  | ❌ | -| [developers.sber.ru](https://developers.sber.ru/gigachat) | `g4f.Provider.GigaChat` | ✔️ |  | ✔️ | -| [console.groq.com](https://console.groq.com/playground) | `g4f.Provider.Groq` | ✔️ |  | ✔️ | -| [huggingface.co](https://huggingface.co/chat) | `g4f.Provider.HuggingChat` | ✔️ |  | ❌ | -| [huggingface.co](https://huggingface.co/chat) | `g4f.Provider.HuggingFace` | ✔️ |  | ❌ | -| [llama2.ai](https://www.llama2.ai) | `g4f.Provider.Llama` | ✔️ |  | ❌ | -| [meta.ai](https://www.meta.ai) | `g4f.Provider.MetaAI` | ✔️ |  | ❌ | -| [openrouter.ai](https://openrouter.ai) | `g4f.Provider.OpenRouter` | ✔️ |  | ✔️ | -| [labs.perplexity.ai](https://labs.perplexity.ai) | `g4f.Provider.PerplexityLabs` | ✔️ |  | ❌ | -| [pi.ai](https://pi.ai/talk) | `g4f.Provider.Pi` | ✔️ |  | ❌ | -| [replicate.com](https://replicate.com) | `g4f.Provider.Replicate` | ✔️ |  | ❌ | -| [theb.ai](https://theb.ai) | `g4f.Provider.ThebApi` | ✔️ |  | ✔️ | -| [whiterabbitneo.com](https://www.whiterabbitneo.com) | `g4f.Provider.WhiteRabbitNeo` | ✔️ |  | ✔️ | -| [bard.google.com](https://bard.google.com) | `g4f.Provider.Bard` | ❌ |  | ✔️ | - -### Models - -| Model | Base Provider | Provider | Website | -| -------------------------- | ------------- | ------------------------ | ----------------------------------------------- | -| gpt-3.5-turbo | OpenAI | 8+ Providers | [openai.com](https://openai.com/) | -| gpt-4 | OpenAI | 2+ Providers | [openai.com](https://openai.com/) | -| gpt-4-turbo | OpenAI | g4f.Provider.Bing | [openai.com](https://openai.com/) | -| Llama-2-7b-chat-hf | Meta | 2+ Providers | [llama.meta.com](https://llama.meta.com/) | -| Llama-2-13b-chat-hf | Meta | 2+ Providers | [llama.meta.com](https://llama.meta.com/) | -| Llama-2-70b-chat-hf | Meta | 3+ Providers | [llama.meta.com](https://llama.meta.com/) | -| Meta-Llama-3-8b-instruct | Meta | 1+ Providers | [llama.meta.com](https://llama.meta.com/) | -| Meta-Llama-3-70b-instruct | Meta | 2+ Providers | [llama.meta.com](https://llama.meta.com/) | -| CodeLlama-34b-Instruct-hf | Meta | g4f.Provider.HuggingChat | [llama.meta.com](https://llama.meta.com/) | -| CodeLlama-70b-Instruct-hf | Meta | 2+ Providers | [llama.meta.com](https://llama.meta.com/) | -| Mixtral-8x7B-Instruct-v0.1 | Huggingface | 4+ Providers | [huggingface.co](https://huggingface.co/) | -| Mistral-7B-Instruct-v0.1 | Huggingface | 3+ Providers | [huggingface.co](https://huggingface.co/) | -| Mistral-7B-Instruct-v0.2 | Huggingface | g4f.Provider.DeepInfra | [huggingface.co](https://huggingface.co/) | -| zephyr-orpo-141b-A35b-v0.1 | Huggingface | 2+ Providers | [huggingface.co](https://huggingface.co/) | -| dolphin-2.6-mixtral-8x7b | Huggingface | g4f.Provider.DeepInfra | [huggingface.co](https://huggingface.co/) | -| gemini | Google | g4f.Provider.Gemini | [gemini.google.com](https://gemini.google.com/) | -| gemini-pro | Google | 2+ Providers | [gemini.google.com](https://gemini.google.com/) | -| claude-v2 | Anthropic | 1+ Providers | [anthropic.com](https://www.anthropic.com/) | -| claude-3-opus | Anthropic | g4f.Provider.You | [anthropic.com](https://www.anthropic.com/) | -| claude-3-sonnet | Anthropic | g4f.Provider.You | [anthropic.com](https://www.anthropic.com/) | -| lzlv_70b_fp16_hf | Huggingface | g4f.Provider.DeepInfra | [huggingface.co](https://huggingface.co/) | -| airoboros-70b | Huggingface | g4f.Provider.DeepInfra | [huggingface.co](https://huggingface.co/) | -| openchat_3.5 | Huggingface | 2+ Providers | [huggingface.co](https://huggingface.co/) | -| pi | Inflection | g4f.Provider.Pi | [inflection.ai](https://inflection.ai/) | - -### Image and Vision Models - -| Label | Provider | Image Model | Vision Model | Website | -| ------------------------- | ------------------------- | ----------------- | --------------- | ---------------------------------------------- | -| Microsoft Copilot in Bing | `g4f.Provider.Bing` | dall-e-3 | gpt-4-vision | [bing.com](https://bing.com/chat) | -| DeepInfra | `g4f.Provider.DeepInfra` | stability-ai/sdxl | llava-1.5-7b-hf | [deepinfra.com](https://deepinfra.com) | -| Gemini | `g4f.Provider.Gemini` | ✔️ | ✔️ | [gemini.google.com](https://gemini.google.com) | -| Gemini API | `g4f.Provider.GeminiPro` | ❌ | gemini-1.5-pro | [ai.google.dev](https://ai.google.dev) | -| Meta AI | `g4f.Provider.MetaAI` | ✔️ | ❌ | [meta.ai](https://www.meta.ai) | -| OpenAI ChatGPT | `g4f.Provider.OpenaiChat` | dall-e-3 | gpt-4-vision | [chatgpt.com](https://chatgpt.com) | -| Reka | `g4f.Provider.Reka` | ❌ | ✔️ | [chat.reka.ai](https://chat.reka.ai/) | -| Replicate | `g4f.Provider.Replicate` | stability-ai/sdxl | llava-v1.6-34b | [replicate.com](https://replicate.com) | -| You.com | `g4f.Provider.You` | dall-e-3 | ✔️ | [you.com](https://you.com) | - ## 🔗 Powered by gpt4free <table> @@ -879,23 +736,46 @@ While we wait for gpt-5, here is a list of new models that are at least better t </a> </td> </tr> + <tr> + <td> + <a href="https://github.com/yjg30737/pyqt-openai"> + <b>VividNode (pyqt-openai)</b> + </a> + </td> + <td> + <a href="https://github.com/yjg30737/pyqt-openai/stargazers"> + <img alt="Stars" src="https://img.shields.io/github/stars/yjg30737/pyqt-openai?style=flat-square&labelColor=343b41" /> + </a> + </td> + <td> + <a href="https://github.com/yjg30737/pyqt-openai/network/members"> + <img alt="Forks" src="https://img.shields.io/github/forks/yjg30737/pyqt-openai?style=flat-square&labelColor=343b41" /> + </a> + </td> + <td> + <a href="https://github.com/yjg30737/pyqt-openai/issues"> + <img alt="Issues" src="https://img.shields.io/github/issues/yjg30737/pyqt-openai?style=flat-square&labelColor=343b41" /> + </a> + </td> + <td> + <a href="https://github.com/yjg30737/pyqt-openai/pulls"> + <img alt="Pull Requests" src="https://img.shields.io/github/issues-pr/yjg30737/pyqt-openai?style=flat-square&labelColor=343b41" /> + </a> + </td> + </tr> </tbody> </table> ## 🤝 Contribute - We welcome contributions from the community. Whether you're adding new providers or features, or simply fixing typos and making small improvements, your input is valued. Creating a pull request is all it takes – our co-pilot will handle the code review process. Once all changes have been addressed, we'll merge the pull request into the main branch and release the updates at a later time. ###### Guide: How do i create a new Provider? - -- Read: [/docs/guides/create_provider](https://github.com/xtekky/gpt4free/blob/main/docs/guides/create_provider.md) + - Read: [Create Provider Guide](docs/guides/create_provider.md) ###### Guide: How can AI help me with writing code? - -- Read: [/docs/guides/help_me](https://github.com/xtekky/gpt4free/blob/main/docs/guides/help_me.md) + - Read: [AI Assistance Guide](docs/guides/help_me.md) ## 🙌 Contributors - A list of all contributors is available [here](https://github.com/xtekky/gpt4free/graphs/contributors) <a href="https://github.com/xtekky" target="_blank"><img src="https://avatars.githubusercontent.com/u/98614666?v=4&s=45" width="45" title="xtekky"></a> @@ -985,4 +865,7 @@ This project is licensed under <a href="https://github.com/xtekky/gpt4free/blob/ </tr> </table> +--- + <p align="right">(<a href="#top">🔼 Back to top</a>)</p> + diff --git a/docker-compose.yml b/docker-compose.yml index 1b99ba97..3f8bc4ea 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -12,4 +12,6 @@ services: ports: - '8080:8080' - '1337:1337' - - '7900:7900'
\ No newline at end of file + - '7900:7900' + environment: + - OLLAMA_HOST=host.docker.internal diff --git a/docs/async_client.md b/docs/async_client.md index 003cfb20..0719a463 100644 --- a/docs/async_client.md +++ b/docs/async_client.md @@ -1,166 +1,395 @@ -# How to Use the G4F AsyncClient API - -The AsyncClient API is the asynchronous counterpart to the standard G4F Client API. It offers the same functionality as the synchronous API, but with the added benefit of improved performance due to its asynchronous nature. - -Designed to maintain compatibility with the existing OpenAI API, the G4F AsyncClient API ensures a seamless transition for users already familiar with the OpenAI client. +# G4F - Async client API Guide +The G4F async client API is a powerful asynchronous interface for interacting with various AI models. This guide provides comprehensive information on how to use the API effectively, including setup, usage examples, best practices, and important considerations for optimal performance. + + +## Compatibility Note +The G4F async client API is designed to be compatible with the OpenAI API, making it easy for developers familiar with OpenAI's interface to transition to G4F. + +## Table of Contents + - [Introduction](#introduction) + - [Key Features](#key-features) + - [Getting Started](#getting-started) + - [Initializing the Client](#initializing-the-client) + - [Creating Chat Completions](#creating-chat-completions) + - [Configuration](#configuration) + - [Usage Examples](#usage-examples) + - [Text Completions](#text-completions) + - [Streaming Completions](#streaming-completions) + - [Using a Vision Model](#using-a-vision-model) + - [Image Generation](#image-generation) + - [Concurrent Tasks](#concurrent-tasks-with-asynciogather) + - [Available Models and Providers](#available-models-and-providers) + - [Error Handling and Best Practices](#error-handling-and-best-practices) + - [Rate Limiting and API Usage](#rate-limiting-and-api-usage) + - [Conclusion](#conclusion) + + + +## Introduction +The G4F async client API is an asynchronous version of the standard G4F Client API. It offers the same functionality as the synchronous API but with improved performance due to its asynchronous nature. This guide will walk you through the key features and usage of the G4F async client API. + ## Key Features + - **Custom Providers**: Use custom providers for enhanced flexibility. + - **ChatCompletion Interface**: Interact with chat models through the ChatCompletion class. + - **Streaming Responses**: Get responses iteratively as they are received. + - **Non-Streaming Responses**: Generate complete responses in a single call. + - **Image Generation and Vision Models**: Support for image-related tasks. -The G4F AsyncClient API offers several key features: - -- **Custom Providers:** The G4F Client API allows you to use custom providers. This feature enhances the flexibility of the API, enabling it to cater to a wide range of use cases. -- **ChatCompletion Interface:** The G4F package provides an interface for interacting with chat models through the ChatCompletion class. This class provides methods for creating both streaming and non-streaming responses. -- **Streaming Responses:** The ChatCompletion.create method can return a response iteratively as and when they are received if the stream parameter is set to True. -- **Non-Streaming Responses:** The ChatCompletion.create method can also generate non-streaming responses. -- **Image Generation and Vision Models:** The G4F Client API also supports image generation and vision models, expanding its utility beyond text-based interactions. - -## Initializing the Client - -To utilize the G4F `AsyncClient`, you need to create a new instance. Below is an example showcasing how to initialize the client with custom providers: + +## Getting Started +### Initializing the Client +**To use the G4F `Client`, create a new instance:** ```python -from g4f.client import AsyncClient -from g4f.Provider import BingCreateImages, OpenaiChat, Gemini +from g4f.client import Client +from g4f.Provider import OpenaiChat, Gemini -client = AsyncClient( +client = Client( provider=OpenaiChat, image_provider=Gemini, - ... + # Add other parameters as needed ) ``` -In this example: -- `provider` specifies the primary provider for generating text completions. -- `image_provider` specifies the provider for image-related functionalities. -## Configuration +## Creating Chat Completions +**Here’s an improved example of creating chat completions:** +```python +response = await async_client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + # Add other parameters as needed +) +``` + +**This example:** + - Asks a specific question `Say this is a test` + - Configures various parameters like temperature and max_tokens for more control over the output + - Disables streaming for a complete response -You can configure the `AsyncClient` with additional settings, such as an API key for your provider and a proxy for all outgoing requests: +You can adjust these parameters based on your specific needs. + +### Configuration +**Configure the `Client` with additional settings:** ```python -from g4f.client import AsyncClient - -client = AsyncClient( +client = Client( api_key="your_api_key_here", proxies="http://user:pass@host", - ... + # Add other parameters as needed ) ``` -- `api_key`: Your API key for the provider. -- `proxies`: The proxy configuration for routing requests. - -## Using AsyncClient + +## Usage Examples ### Text Completions +**Generate text completions using the ChatCompletions endpoint:** +```python +import asyncio +from g4f.client import Client -You can use the `ChatCompletions` endpoint to generate text completions. Here’s how you can do it: +async def main(): + client = Client() + + response = await client.chat.completions.async_create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + ) + + print(response.choices[0].message.content) -```python -response = await client.chat.completions.create( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "Say this is a test"}], - ... -) -print(response.choices[0].message.content) +asyncio.run(main()) ``` + + ### Streaming Completions +**Process responses incrementally as they are generated:** +```python +import asyncio +from g4f.client import Client -The `AsyncClient` also supports streaming completions. This allows you to process the response incrementally as it is generated: +async def main(): + client = Client() + + stream = await client.chat.completions.async_create( + model="gpt-4", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ], + stream=True, + ) + + async for chunk in stream: + if chunk.choices[0].delta.content: + print(chunk.choices[0].delta.content, end="") + +asyncio.run(main()) +``` + + +### Using a Vision Model +**Analyze an image and generate a description:** ```python -stream = client.chat.completions.create( - model="gpt-4", - messages=[{"role": "user", "content": "Say this is a test"}], - stream=True, - ... -) -async for chunk in stream: - if chunk.choices[0].delta.content: - print(chunk.choices[0].delta.content or "", end="") +import g4f +import requests +import asyncio +from g4f.client import Client + +async def main(): + client = Client() + + image = requests.get("https://raw.githubusercontent.com/xtekky/gpt4free/refs/heads/main/docs/cat.jpeg", stream=True).raw + + response = await client.chat.completions.async_create( + model=g4f.models.default, + provider=g4f.Provider.Bing, + messages=[ + { + "role": "user", + "content": "What's in this image?" + } + ], + image=image + ) + + print(response.choices[0].message.content) + +asyncio.run(main()) ``` -In this example: -- `stream=True` enables streaming of the response. + -### Example: Using a Vision Model +### Image Generation +**Generate images using a specified prompt:** +```python +import asyncio +from g4f.client import Client -The following code snippet demonstrates how to use a vision model to analyze an image and generate a description based on the content of the image. This example shows how to fetch an image, send it to the model, and then process the response. +async def main(): + client = Client() + + response = await client.images.async_generate( + prompt="a white siamese cat", + model="flux" + ) + + image_url = response.data[0].url + print(f"Generated image URL: {image_url}") +asyncio.run(main()) +``` + + + +#### Base64 Response Format ```python -import requests +import asyncio from g4f.client import Client -from g4f.Provider import Bing -client = AsyncClient( - provider=Bing -) +async def main(): + client = Client() + + response = await client.images.async_generate( + prompt="a white siamese cat", + model="flux", + response_format="b64_json" + ) + + base64_text = response.data[0].b64_json + print(base64_text) -image = requests.get("https://my_website/image.jpg", stream=True).raw -# Or: image = open("local_path/image.jpg", "rb") +asyncio.run(main()) +``` -response = client.chat.completions.create( - "", - messages=[{"role": "user", "content": "what is in this picture?"}], - image=image -) -print(response.choices[0].message.content) + + +### Concurrent Tasks with asyncio.gather +**Execute multiple tasks concurrently:** +```python +import asyncio +from g4f.client import Client + +async def main(): + client = Client() + + task1 = client.chat.completions.async_create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + ) + + task2 = client.images.async_generate( + model="flux", + prompt="a white siamese cat" + ) + + chat_response, image_response = await asyncio.gather(task1, task2) + + print("Chat Response:") + print(chat_response.choices[0].message.content) + + print("Image Response:") + print(image_response.data[0].url) + +asyncio.run(main()) ``` -### Image Generation: + + +## Available Models and Providers +The G4F AsyncClient supports a wide range of AI models and providers, allowing you to choose the best option for your specific use case. **Here's a brief overview of the available models and providers:** + +### Models + - GPT-3.5-Turbo + - GPT-4 + - DALL-E 3 + - Gemini + - Claude (Anthropic) + - And more... + + -You can generate images using a specified prompt: +### Providers + - OpenAI + - Google (for Gemini) + - Anthropic + - Bing + - Custom providers + + +**To use a specific model or provider, specify it when creating the client or in the API call:** ```python -response = await client.images.generate( - model="dall-e-3", - prompt="a white siamese cat", - ... +client = AsyncClient(provider=g4f.Provider.OpenaiChat) + +# or + +response = await client.chat.completions.async_create( + model="gpt-4", + provider=g4f.Provider.Bing, + messages=[ + { + "role": "user", + "content": "Hello, world!" + } + ] ) +``` + + + +## Error Handling and Best Practices +Implementing proper error handling and following best practices is crucial when working with the G4F AsyncClient API. This ensures your application remains robust and can gracefully handle various scenarios. **Here are some key practices to follow:** -image_url = response.data[0].url +1. **Use try-except blocks to catch and handle exceptions:** +```python +try: + response = await client.chat.completions.async_create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Hello, world!" + } + ] + ) +except Exception as e: + print(f"An error occurred: {e}") ``` -#### Base64 as the response format +2. **Check the response status and handle different scenarios:** +```python +if response.choices: + print(response.choices[0].message.content) +else: + print("No response generated") +``` +3. **Implement retries for transient errors:** ```python -response = await client.images.generate( - prompt="a cool cat", - response_format="b64_json" -) +import asyncio +from tenacity import retry, stop_after_attempt, wait_exponential -base64_text = response.data[0].b64_json +@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10)) +async def make_api_call(): + # Your API call here + pass ``` -### Example usage with asyncio.gather + -Start two tasks at the same time: +## Rate Limiting and API Usage +When working with the G4F AsyncClient API, it's important to implement rate limiting and monitor your API usage. This helps ensure fair usage, prevents overloading the service, and optimizes your application's performance. Here are some key strategies to consider: + +1. **Implement rate limiting in your application:** ```python import asyncio +from aiolimiter import AsyncLimiter -from g4f.client import AsyncClient -from g4f.Provider import BingCreateImages, OpenaiChat, Gemini +rate_limit = AsyncLimiter(max_rate=10, time_period=1) # 10 requests per second -async def main(): - client = AsyncClient( - provider=OpenaiChat, - image_provider=Gemini, - # other parameters... - ) +async def make_api_call(): + async with rate_limit: + # Your API call here + pass +``` - task1 = client.chat.completions.create( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "Say this is a test"}], - ) - task2 = client.images.generate( - model="dall-e-3", - prompt="a white siamese cat", - ) - responses = await asyncio.gather(task1, task2) + - print(responses) +2. **Monitor your API usage and implement logging:** +```python +import logging -asyncio.run(main()) -```
\ No newline at end of file +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +async def make_api_call(): + try: + response = await client.chat.completions.async_create(...) + logger.info(f"API call successful. Tokens used: {response.usage.total_tokens}") + except Exception as e: + logger.error(f"API call failed: {e}") +``` + + + +3. **Use caching to reduce API calls for repeated queries:** +```python +from functools import lru_cache + +@lru_cache(maxsize=100) +def get_cached_response(query): + # Your API call here + pass +``` + +## Conclusion +The G4F async client API provides a powerful and flexible way to interact with various AI models asynchronously. By leveraging its features and following best practices, you can build efficient and responsive applications that harness the power of AI for text generation, image analysis, and image creation. + +Remember to handle errors gracefully, implement rate limiting, and monitor your API usage to ensure optimal performance and reliability in your applications. + +--- + +[Return to Home](/) diff --git a/docs/client.md b/docs/client.md index a889443c..388b2e4b 100644 --- a/docs/client.md +++ b/docs/client.md @@ -1,31 +1,52 @@ -### G4F - Client API - -#### Introduction +# G4F Client API Guide + + +## Table of Contents + - [Introduction](#introduction) + - [Getting Started](#getting-started) + - [Switching to G4F Client](#switching-to-g4f-client) + - [Initializing the Client](#initializing-the-client) + - [Creating Chat Completions](#creating-chat-completions) + - [Configuration](#configuration) + - [Usage Examples](#usage-examples) + - [Text Completions](#text-completions) + - [Streaming Completions](#streaming-completions) + - [Image Generation](#image-generation) + - [Creating Image Variations](#creating-image-variations) + - [Advanced Usage](#advanced-usage) + - [Using a List of Providers with RetryProvider](#using-a-list-of-providers-with-retryprovider) + - [Using GeminiProVision](#using-geminiprovision) + - [Using a Vision Model](#using-a-vision-model) + - [Command-line Chat Program](#command-line-chat-program) + + + +## Introduction Welcome to the G4F Client API, a cutting-edge tool for seamlessly integrating advanced AI capabilities into your Python applications. This guide is designed to facilitate your transition from using the OpenAI client to the G4F Client, offering enhanced features while maintaining compatibility with the existing OpenAI API. -#### Getting Started - -**Switching to G4F Client:** - -To begin using the G4F Client, simply update your import statement in your Python code: +## Getting Started +### Switching to G4F Client +**To begin using the G4F Client, simply update your import statement in your Python code:** -Old Import: +**Old Import:** ```python from openai import OpenAI ``` -New Import: + + +**New Import:** ```python from g4f.client import Client as OpenAI ``` -The G4F Client preserves the same familiar API interface as OpenAI, ensuring a smooth transition process. + -### Initializing the Client - -To utilize the G4F Client, create an new instance. Below is an example showcasing custom providers: +The G4F Client preserves the same familiar API interface as OpenAI, ensuring a smooth transition process. +## Initializing the Client +To utilize the G4F Client, create a new instance. **Below is an example showcasing custom providers:** ```python from g4f.client import Client from g4f.Provider import BingCreateImages, OpenaiChat, Gemini @@ -33,143 +54,244 @@ from g4f.Provider import BingCreateImages, OpenaiChat, Gemini client = Client( provider=OpenaiChat, image_provider=Gemini, - ... + # Add any other necessary parameters ) ``` -## Configuration +## Creating Chat Completions +**Here’s an improved example of creating chat completions:** +```python +response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + # Add any other necessary parameters +) +``` + +**This example:** + - Asks a specific question `Say this is a test` + - Configures various parameters like temperature and max_tokens for more control over the output + - Disables streaming for a complete response -You can set an "api_key" for your provider in the client. -And you also have the option to define a proxy for all outgoing requests: +You can adjust these parameters based on your specific needs. + +## Configuration +**You can set an `api_key` for your provider in the client and define a proxy for all outgoing requests:** ```python from g4f.client import Client client = Client( - api_key="...", + api_key="your_api_key_here", proxies="http://user:pass@host", - ... + # Add any other necessary parameters ) ``` -#### Usage Examples + -**Text Completions:** +## Usage Examples +### Text Completions +**Generate text completions using the `ChatCompletions` endpoint:** +```python +from g4f.client import Client -You can use the `ChatCompletions` endpoint to generate text completions as follows: +client = Client() -```python response = client.chat.completions.create( model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "Say this is a test"}], - ... + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + # Add any other necessary parameters ) + print(response.choices[0].message.content) ``` -Also streaming are supported: + +### Streaming Completions +**Process responses incrementally as they are generated:** ```python +from g4f.client import Client + +client = Client() + stream = client.chat.completions.create( model="gpt-4", - messages=[{"role": "user", "content": "Say this is a test"}], + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ], stream=True, - ... ) + for chunk in stream: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content or "", end="") ``` -**Image Generation:** - -Generate images using a specified prompt: + +### Image Generation +**Generate images using a specified prompt:** ```python +from g4f.client import Client + +client = Client() + response = client.images.generate( - model="dall-e-3", - prompt="a white siamese cat", - ... + model="flux", + prompt="a white siamese cat" + # Add any other necessary parameters ) image_url = response.data[0].url + +print(f"Generated image URL: {image_url}") ``` -**Creating Image Variations:** -Create variations of an existing image: +#### Base64 Response Format +```python +from g4f.client import Client + +client = Client() +response = client.images.generate( + model="flux", + prompt="a white siamese cat", + response_format="b64_json" +) + +base64_text = response.data[0].b64_json +print(base64_text) +``` + + + +### Creating Image Variations +**Create variations of an existing image:** ```python +from g4f.client import Client + +client = Client() + response = client.images.create_variation( image=open("cat.jpg", "rb"), - model="bing", - ... + model="bing" + # Add any other necessary parameters ) image_url = response.data[0].url + +print(f"Generated image URL: {image_url}") ``` -Original / Variant: -[](/docs/client.md) [](/docs/client.md) + -#### Use a list of providers with RetryProvider +## Advanced Usage +### Using a List of Providers with RetryProvider ```python from g4f.client import Client from g4f.Provider import RetryProvider, Phind, FreeChatgpt, Liaobots - import g4f.debug + g4f.debug.logging = True +g4f.debug.version_check = False client = Client( provider=RetryProvider([Phind, FreeChatgpt, Liaobots], shuffle=False) ) + response = client.chat.completions.create( model="", - messages=[{"role": "user", "content": "Hello"}], + messages=[ + { + "role": "user", + "content": "Hello" + } + ] ) -print(response.choices[0].message.content) -``` -``` -Using RetryProvider provider -Using Phind provider -How can I assist you today? +print(response.choices[0].message.content) ``` -#### Advanced example using GeminiProVision - + +### Using GeminiProVision ```python from g4f.client import Client from g4f.Provider.GeminiPro import GeminiPro client = Client( - api_key="...", + api_key="your_api_key_here", provider=GeminiPro ) + response = client.chat.completions.create( model="gemini-pro-vision", - messages=[{"role": "user", "content": "What are on this image?"}], + messages=[ + { + "role": "user", + "content": "What are on this image?" + } + ], image=open("docs/waterfall.jpeg", "rb") ) + print(response.choices[0].message.content) ``` -``` -User: What are on this image? -``` - -``` -Bot: There is a waterfall in the middle of a jungle. There is a rainbow over... + +### Using a Vision Model +**Analyze an image and generate a description:** +```python +import g4f +import requests +from g4f.client import Client + +image = requests.get("https://raw.githubusercontent.com/xtekky/gpt4free/refs/heads/main/docs/cat.jpeg", stream=True).raw +# Or: image = open("docs/cat.jpeg", "rb") + +client = Client() + +response = client.chat.completions.create( + model=g4f.models.default, + messages=[ + { + "role": "user", + "content": "What are on this image?" + } + ], + provider=g4f.Provider.Bing, + image=image + # Add any other necessary parameters +) + +print(response.choices[0].message.content) ``` -#### Advanced example: A command-line program + +## Command-line Chat Program +**Here's an example of a simple command-line chat program using the G4F Client:** ```python import g4f from g4f.client import Client # Initialize the GPT client with the desired provider -client = Client(provider=g4f.Provider.Bing) +client = Client() # Initialize an empty conversation history messages = [] @@ -177,7 +299,7 @@ messages = [] while True: # Get user input user_input = input("You: ") - + # Check if the user wants to exit the chat if user_input.lower() == "exit": print("Exiting chat...") @@ -199,8 +321,13 @@ while True: # Update the conversation history with GPT's response messages.append({"role": "assistant", "content": gpt_response}) + except Exception as e: print(f"An error occurred: {e}") ``` + +This guide provides a comprehensive overview of the G4F Client API, demonstrating its versatility in handling various AI tasks, from text generation to image analysis and creation. By leveraging these features, you can build powerful and responsive applications that harness the capabilities of advanced AI models. + -[Return to Home](/)
\ No newline at end of file +--- +[Return to Home](/) diff --git a/docs/docker.md b/docs/docker.md index db33b925..e1caaf3d 100644 --- a/docs/docker.md +++ b/docs/docker.md @@ -1,45 +1,114 @@ -### G4F - Docker Setup -Easily set up and run the G4F project using Docker without the hassle of manual dependency installation. +# G4F Docker Setup -1. **Prerequisites:** - - [Install Docker](https://docs.docker.com/get-docker/) - - [Install Docker Compose](https://docs.docker.com/compose/install/) +## Table of Contents + - [Prerequisites](#prerequisites) + - [Installation and Setup](#installation-and-setup) + - [Testing the API](#testing-the-api) + - [Troubleshooting](#troubleshooting) + - [Stopping the Service](#stopping-the-service) -2. **Clone the Repository:** -```bash -git clone https://github.com/xtekky/gpt4free.git -``` +## Prerequisites +**Before you begin, ensure you have the following installed on your system:** + - [Docker](https://docs.docker.com/get-docker/) + - [Docker Compose](https://docs.docker.com/compose/install/) + - Python 3.7 or higher + - pip (Python package manager) -3. **Navigate to the Project Directory:** +**Note:** If you encounter issues with Docker, you can run the project directly using Python. -```bash -cd gpt4free -``` +## Installation and Setup + +### Docker Method (Recommended) +1. **Clone the Repository** + ```bash + git clone https://github.com/xtekky/gpt4free.git + cd gpt4free + ``` + +2. **Build and Run with Docker Compose** + ```bash + docker-compose up --build + ``` + +3. **Access the API** + The server will be accessible at `http://localhost:1337` + +### Non-Docker Method +If you encounter issues with Docker, you can run the project directly using Python: + +1. **Clone the Repository** + ```bash + git clone https://github.com/xtekky/gpt4free.git + cd gpt4free + ``` + +2. **Install Dependencies** + ```bash + pip install -r requirements.txt + ``` -4. **Build the Docker Image:** +3. **Run the Server** + ```bash + python -m g4f.api.run + ``` +4. **Access the API** + The server will be accessible at `http://localhost:1337` + +## Testing the API +**You can test the API using curl or by creating a simple Python script:** +### Using curl ```bash -docker pull selenium/node-chrome -docker-compose build +curl -X POST -H "Content-Type: application/json" -d '{"prompt": "What is the capital of France?"}' http://localhost:1337/chat/completions ``` -5. **Start the Service:** +### Using Python +**Create a file named `test_g4f.py` with the following content:** +```python +import requests + +url = "http://localhost:1337/v1/chat/completions" +body = { + "model": "gpt-3.5-turbo", + "stream": False, + "messages": [ + {"role": "assistant", "content": "What can you do?"} + ] +} + +json_response = requests.post(url, json=body).json().get('choices', []) + +for choice in json_response: + print(choice.get('message', {}).get('content', '')) +``` +**Run the script:** ```bash -docker-compose up +python test_g4f.py ``` -Your server will now be accessible at `http://localhost:1337`. Interact with the API or run tests as usual. +## Troubleshooting +- If you encounter issues with Docker, try running the project directly using Python as described in the Non-Docker Method. +- Ensure that you have the necessary permissions to run Docker commands. You might need to use `sudo` or add your user to the `docker` group. +- If the server doesn't start, check the logs for any error messages and ensure all dependencies are correctly installed. -To stop the Docker containers, simply run: +**_For more detailed information on API endpoints and usage, refer to the [G4F API documentation](docs/interference-api.md)._** + + +## Stopping the Service + +### Docker Method +**To stop the Docker containers, use the following command:** ```bash docker-compose down ``` -> [!Note] -> Changes made to local files reflect in the Docker container due to volume mapping in `docker-compose.yml`. However, if you add or remove dependencies, rebuild the Docker image using `docker-compose build`. +### Non-Docker Method +If you're running the server directly with Python, you can stop it by pressing Ctrl+C in the terminal where it's running. + +--- -[Return to Home](/)
\ No newline at end of file +[Return to Home](/) diff --git a/docs/git.md b/docs/git.md index 89137ffc..33a0ff42 100644 --- a/docs/git.md +++ b/docs/git.md @@ -1,66 +1,129 @@ -### G4F - Installation Guide -Follow these steps to install G4F from the source code: +# G4F - Git Installation Guide -1. **Clone the Repository:** +This guide provides step-by-step instructions for installing G4F from the source code using Git. -```bash -git clone https://github.com/xtekky/gpt4free.git -``` -2. **Navigate to the Project Directory:** +## Table of Contents -```bash -cd gpt4free -``` +1. [Prerequisites](#prerequisites) +2. [Installation Steps](#installation-steps) + 1. [Clone the Repository](#1-clone-the-repository) + 2. [Navigate to the Project Directory](#2-navigate-to-the-project-directory) + 3. [Set Up a Python Virtual Environment](#3-set-up-a-python-virtual-environment-recommended) + 4. [Activate the Virtual Environment](#4-activate-the-virtual-environment) + 5. [Install Dependencies](#5-install-dependencies) + 6. [Verify Installation](#6-verify-installation) +3. [Usage](#usage) +4. [Troubleshooting](#troubleshooting) +5. [Additional Resources](#additional-resources) -3. **(Optional) Create a Python Virtual Environment:** +--- -It's recommended to isolate your project dependencies. You can follow the [Python official documentation](https://docs.python.org/3/tutorial/venv.html) for virtual environments. +## Prerequisites -```bash -python3 -m venv venv -``` +Before you begin, ensure you have the following installed on your system: +- Git +- Python 3.7 or higher +- pip (Python package installer) -4. **Activate the Virtual Environment:** - -- On Windows: +## Installation Steps +### 1. Clone the Repository +**Open your terminal and run the following command to clone the G4F repository:** ```bash -.\venv\Scripts\activate +git clone https://github.com/xtekky/gpt4free.git ``` -- On macOS and Linux: +### 2. Navigate to the Project Directory +**Change to the project directory:** +```bash +cd gpt4free +``` +### 3. Set Up a Python Virtual Environment (Recommended) +**It's best practice to use a virtual environment to manage project dependencies:** ```bash -source venv/bin/activate +python3 -m venv venv ``` -5. **Install Minimum Requirements:** +### 4. Activate the Virtual Environment +**Activate the virtual environment based on your operating system:** +- **Windows:** + ```bash + .\venv\Scripts\activate + ``` -Install the minimum required packages: +- **macOS and Linux:** + ```bash + source venv/bin/activate + ``` +### 5. Install Dependencies +**You have two options for installing dependencies:** + +#### Option A: Install Minimum Requirements +**For a lightweight installation, use:** ```bash pip install -r requirements-min.txt ``` -6. **Or Install All Packages from `requirements.txt`:** - -If you prefer, you can install all packages listed in `requirements.txt`: - +#### Option B: Install All Packages +**For a full installation with all features, use:** ```bash pip install -r requirements.txt ``` -7. **Start Using the Repository:** - +### 6. Verify Installation You can now create Python scripts and utilize the G4F functionalities. Here's a basic example: -Create a `test.py` file in the root folder and start using the repository: - +**Create a `g4f-test.py` file in the root folder and start using the repository:** ```python import g4f # Your code here ``` -[Return to Home](/)
\ No newline at end of file +## Usage +**After installation, you can start using G4F in your Python scripts. Here's a basic example:** +```python +import g4f + +# Your G4F code here +# For example: +from g4f.client import Client + +client = Client() + +response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": "Say this is a test" + } + ] + # Add any other necessary parameters +) + +print(response.choices[0].message.content) +``` + +## Troubleshooting +**If you encounter any issues during installation or usage:** + 1. Ensure all prerequisites are correctly installed. + 2. Check that you're in the correct directory and the virtual environment is activated. + 3. Try reinstalling the dependencies. + 4. Consult the [G4F documentation](https://github.com/xtekky/gpt4free) for more detailed information. + +## Additional Resources + - [G4F GitHub Repository](https://github.com/xtekky/gpt4free) + - [Python Virtual Environments Guide](https://docs.python.org/3/tutorial/venv.html) + - [pip Documentation](https://pip.pypa.io/en/stable/) + +--- + +**_For more information or support, please visit the [G4F GitHub Issues page](https://github.com/xtekky/gpt4free/issues)._** + + +--- +[Return to Home](/) diff --git a/docs/interference-api.md b/docs/interference-api.md new file mode 100644 index 00000000..2e18e7b5 --- /dev/null +++ b/docs/interference-api.md @@ -0,0 +1,162 @@ +# G4F - Interference API Usage Guide + + +## Table of Contents + - [Introduction](#introduction) + - [Running the Interference API](#running-the-interference-api) + - [From PyPI Package](#from-pypi-package) + - [From Repository](#from-repository) + - [Using the Interference API](#using-the-interference-api) + - [Basic Usage](#basic-usage) + - [With OpenAI Library](#with-openai-library) + - [With Requests Library](#with-requests-library) + - [Key Points](#key-points) + - [Conclusion](#conclusion) + + +## Introduction +The G4F Interference API is a powerful tool that allows you to serve other OpenAI integrations using G4F (Gpt4free). It acts as a proxy, translating requests intended for the OpenAI API into requests compatible with G4F providers. This guide will walk you through the process of setting up, running, and using the Interference API effectively. + + +## Running the Interference API +**You can run the Interference API in two ways:** using the PyPI package or from the repository. + + +### From PyPI Package +**To run the Interference API directly from the G4F PyPI package, use the following Python code:** + +```python +from g4f.api import run_api + +run_api() +``` + + +### From Repository +**If you prefer to run the Interference API from the cloned repository, you have two options:** + +1. **Using the command line:** +```bash +g4f api +``` + +2. **Using Python:** +```bash +python -m g4f.api.run +``` + +**Once running, the API will be accessible at:** `http://localhost:1337/v1` + + +## Using the Interference API + +### Basic Usage +**You can interact with the Interference API using curl commands for both text and image generation:** + +**For text generation:** +```bash +curl -X POST "http://localhost:1337/v1/chat/completions" \ + -H "Content-Type: application/json" \ + -d '{ + "messages": [ + { + "role": "user", + "content": "Hello" + } + ], + "model": "gpt-3.5-turbo" + }' +``` + +**For image generation:** +1. **url:** +```bash +curl -X POST "http://localhost:1337/v1/images/generate" \ + -H "Content-Type: application/json" \ + -d '{ + "prompt": "a white siamese cat", + "model": "flux", + "response_format": "url" + }' +``` + +2. **b64_json** +```bash +curl -X POST "http://localhost:1337/v1/images/generate" \ + -H "Content-Type: application/json" \ + -d '{ + "prompt": "a white siamese cat", + "model": "flux", + "response_format": "b64_json" + }' +``` + + +### With OpenAI Library + +**You can use the Interference API with the OpenAI Python library by changing the `base_url`:** +```python +from openai import OpenAI + +client = OpenAI( + api_key="", + base_url="http://localhost:1337/v1" +) + +response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Write a poem about a tree"}], + stream=True, +) + +if isinstance(response, dict): + # Not streaming + print(response.choices[0].message.content) +else: + # Streaming + for token in response: + content = token.choices[0].delta.content + if content is not None: + print(content, end="", flush=True) + +``` + + +### With Requests Library + +**You can also send requests directly to the Interference API using the `requests` library:** +```python +import requests + +url = "http://localhost:1337/v1/chat/completions" + +body = { + "model": "gpt-3.5-turbo", + "stream": False, + "messages": [ + {"role": "assistant", "content": "What can you do?"} + ] +} + +json_response = requests.post(url, json=body).json().get('choices', []) + +for choice in json_response: + print(choice.get('message', {}).get('content', '')) + +``` + +## Key Points + - The Interference API translates OpenAI API requests into G4F provider requests. + - It can be run from either the PyPI package or the cloned repository. + - The API supports usage with the OpenAI Python library by changing the `base_url`. + - Direct requests can be sent to the API endpoints using libraries like `requests`. + - Both text and image generation are supported. + + +## Conclusion +The G4F Interference API provides a seamless way to integrate G4F with existing OpenAI-based applications and tools. By following this guide, you should now be able to set up, run, and use the Interference API effectively. Whether you're using it for text generation, image creation, or as a drop-in replacement for OpenAI in your projects, the Interference API offers flexibility and power for your AI-driven applications. + + +--- + +[Return to Home](/) diff --git a/docs/interference.md b/docs/interference.md deleted file mode 100644 index b140f66a..00000000 --- a/docs/interference.md +++ /dev/null @@ -1,69 +0,0 @@ -### Interference openai-proxy API - -#### Run interference API from PyPi package - -```python -from g4f.api import run_api - -run_api() -``` - -#### Run interference API from repo - -Run server: - -```sh -g4f api -``` - -or - -```sh -python -m g4f.api.run -``` - -```python -from openai import OpenAI - -client = OpenAI( - api_key="", - # Change the API base URL to the local interference API - base_url="http://localhost:1337/v1" -) - - response = client.chat.completions.create( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "write a poem about a tree"}], - stream=True, - ) - - if isinstance(response, dict): - # Not streaming - print(response.choices[0].message.content) - else: - # Streaming - for token in response: - content = token.choices[0].delta.content - if content is not None: - print(content, end="", flush=True) -``` - -#### API usage (POST) -Send the POST request to /v1/chat/completions with body containing the `model` method. This example uses python with requests library: -```python -import requests -url = "http://localhost:1337/v1/chat/completions" -body = { - "model": "gpt-3.5-turbo-16k", - "stream": False, - "messages": [ - {"role": "assistant", "content": "What can you do?"} - ] -} -json_response = requests.post(url, json=body).json().get('choices', []) - -for choice in json_response: - print(choice.get('message', {}).get('content', '')) -``` - -[Return to Home](/)
\ No newline at end of file diff --git a/docs/local.md b/docs/local.md new file mode 100644 index 00000000..2cedd1a9 --- /dev/null +++ b/docs/local.md @@ -0,0 +1,164 @@ + +### G4F - Local Usage Guide + + +### Table of Contents +1. [Introduction](#introduction) +2. [Required Dependencies](#required-dependencies) +3. [Basic Usage Example](#basic-usage-example) +4. [Supported Models](#supported-models) +5. [Performance Considerations](#performance-considerations) +6. [Troubleshooting](#troubleshooting) + +#### Introduction +This guide explains how to use g4f to run language models locally. G4F (GPT4Free) allows you to interact with various language models on your local machine, providing a flexible and private solution for natural language processing tasks. + +## Usage + +#### Local inference +How to use g4f to run language models locally + +#### Required dependencies +**Make sure to install the required dependencies by running:** +```bash +pip install g4f[local] +``` +or +```bash +pip install -U gpt4all +``` + + + +#### Basic usage example +```python +from g4f.local import LocalClient + +client = LocalClient() +response = client.chat.completions.create( + model = 'orca-mini-3b', + messages = [{"role": "user", "content": "hi"}], + stream = True +) + +for token in response: + print(token.choices[0].delta.content or "") +``` + +Upon first use, there will be a prompt asking you if you wish to download the model. If you respond with `y`, g4f will go ahead and download the model for you. + +You can also manually place supported models into `./g4f/local/models/` + + +**You can get a list of the current supported models by running:** +```python +from g4f.local import LocalClient + +client = LocalClient() +client.list_models() +``` + +```json +{ + "mistral-7b": { + "path": "mistral-7b-openorca.gguf2.Q4_0.gguf", + "ram": "8", + "prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n", + "system": "<|im_start|>system\nYou are MistralOrca, a large language model trained by Alignment Lab AI. For multi-step problems, write out your reasoning for each step.\n<|im_end|>" + }, + "mistral-7b-instruct": { + "path": "mistral-7b-instruct-v0.1.Q4_0.gguf", + "ram": "8", + "prompt": "[INST] %1 [/INST]", + "system": None + }, + "gpt4all-falcon": { + "path": "gpt4all-falcon-newbpe-q4_0.gguf", + "ram": "8", + "prompt": "### Instruction:\n%1\n### Response:\n", + "system": None + }, + "orca-2": { + "path": "orca-2-13b.Q4_0.gguf", + "ram": "16", + "prompt": None, + "system": None + }, + "wizardlm-13b": { + "path": "wizardlm-13b-v1.2.Q4_0.gguf", + "ram": "16", + "prompt": None, + "system": None + }, + "nous-hermes-llama2": { + "path": "nous-hermes-llama2-13b.Q4_0.gguf", + "ram": "16", + "prompt": "### Instruction:\n%1\n### Response:\n", + "system": None + }, + "gpt4all-13b-snoozy": { + "path": "gpt4all-13b-snoozy-q4_0.gguf", + "ram": "16", + "prompt": None, + "system": None + }, + "mpt-7b-chat": { + "path": "mpt-7b-chat-newbpe-q4_0.gguf", + "ram": "8", + "prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n", + "system": "<|im_start|>system\n- You are a helpful assistant chatbot trained by MosaicML.\n- You answer questions.\n- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.\n- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.<|im_end|>" + }, + "orca-mini-3b": { + "path": "orca-mini-3b-gguf2-q4_0.gguf", + "ram": "4", + "prompt": "### User:\n%1\n### Response:\n", + "system": "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n" + }, + "replit-code-3b": { + "path": "replit-code-v1_5-3b-newbpe-q4_0.gguf", + "ram": "4", + "prompt": "%1", + "system": None + }, + "starcoder": { + "path": "starcoder-newbpe-q4_0.gguf", + "ram": "4", + "prompt": "%1", + "system": None + }, + "rift-coder-7b": { + "path": "rift-coder-v0-7b-q4_0.gguf", + "ram": "8", + "prompt": "%1", + "system": None + }, + "all-MiniLM-L6-v2": { + "path": "all-MiniLM-L6-v2-f16.gguf", + "ram": "1", + "prompt": None, + "system": None + }, + "mistral-7b-german": { + "path": "em_german_mistral_v01.Q4_0.gguf", + "ram": "8", + "prompt": "USER: %1 ASSISTANT: ", + "system": "Du bist ein hilfreicher Assistent. " + } +} +``` + +#### Performance Considerations +**When running language models locally, consider the following:** + - RAM requirements vary by model size (see the 'ram' field in the model list). + - CPU/GPU capabilities affect inference speed. + - Disk space is needed to store the model files. + +#### Troubleshooting +**Common issues and solutions:** + 1. **Model download fails**: Check your internet connection and try again. + 2. **Out of memory error**: Choose a smaller model or increase your system's RAM. + 3. **Slow inference**: Consider using a GPU or a more powerful CPU. + + + +[Return to Home](/) diff --git a/docs/providers-and-models.md b/docs/providers-and-models.md new file mode 100644 index 00000000..b3dbd9f1 --- /dev/null +++ b/docs/providers-and-models.md @@ -0,0 +1,239 @@ + +# G4F - Providers and Models + +This document provides an overview of various AI providers and models, including text generation, image generation, and vision capabilities. It aims to help users navigate the diverse landscape of AI services and choose the most suitable option for their needs. + +## Table of Contents + - [Providers](#providers) + - [Models](#models) + - [Text Models](#text-models) + - [Image Models](#image-models) + - [Vision Models](#vision-models) + - [Conclusion and Usage Tips](#conclusion-and-usage-tips) + +--- +## Providers +| Provider | Text Models | Image Models | Vision Models | Stream | Status | Auth | +|----------|-------------|--------------|---------------|--------|--------|------| +|[ai4chat.co](https://www.ai4chat.co)|`g4f.Provider.Ai4Chat`|`gpt-4`|❌|❌|✔||❌| +|[chat.ai365vip.com](https://chat.ai365vip.com)|`g4f.Provider.AI365VIP`|`gpt-3.5-turbo, gpt-4o`|❌|❌|?||❌| +|[aichatfree.info](https://aichatfree.info)|`g4f.Provider.AIChatFree`|`gemini-pro`|❌|❌|✔||❌| +|[aichatonline.org](https://aichatonline.org)|`g4f.Provider.AiChatOnline`|`gpt-4o-mini`|❌|❌|?||❌| +|[ai-chats.org](https://ai-chats.org)|`g4f.Provider.AiChats`|`gpt-4`|`dalle`|❌|?||❌| +|[api.airforce](https://api.airforce)|`g4f.Provider.AiMathGPT`|`llama-3.1-70b`|❌|❌|✔||❌| +|[api.airforce](https://api.airforce)|`g4f.Provider.Airforce`|`gpt-4, gpt-4-turbo, gpt-4o-mini, gpt-3.5-turbo, gpt-4o, claude-3-haiku, claude-3-sonnet, claude-3-5-sonnet, claude-3-opus, llama-3-70b, llama-3-8b, llama-2-13b, llama-3.1-405b, llama-3.1-70b, llama-3.1-8b, llamaguard-2-8b, llamaguard-7b, llama-3.2-90b, mixtral-8x7b mixtral-8x22b, mistral-7b, qwen-1.5-7b, qwen-1.5-14b, qwen-1.5-72b, qwen-1.5-110b, qwen-2-72b, gemma-2b, gemma-2-9b, gemma-2-27b, gemini-flash, gemini-pro, deepseek, mixtral-8x7b-dpo, yi-34b, wizardlm-2-8x22b, solar-10.7b, mythomax-l2-13b, cosmosrp`|`flux, flux-realism', flux-anime, flux-3d, flux-disney, flux-pixel, flux-4o, any-dark, dalle-3`|❌|✔||❌| +|[aiuncensored.info](https://www.aiuncensored.info)|`g4f.Provider.AIUncensored`|✔|✔|❌|✔||❌| +|[allyfy.chat](https://allyfy.chat/)|`g4f.Provider.Allyfy`|`gpt-3.5-turbo`|❌|❌|✔||❌| +|[amigochat.io/chat](https://amigochat.io/chat/)|`g4f.Provider.AmigoChat`|`gpt-4o, gpt-4o-mini, o1, o1-mini, claude-3.5-sonnet, llama-3.2-90b, llama-3.1-405b, gemini-pro`|`flux-pro, flux-realism, dalle-3`|❌|✔||❌| +|[openchat.team](https://openchat.team/)|`g4f.Provider.Aura`|✔|❌|❌|?||❌| +|[bing.com](https://bing.com/chat)|`g4f.Provider.Bing`|`gpt-4`|✔|`gpt-4-vision`|✔||❌+✔| +|[bing.com/images](https://www.bing.com/images/create)|`g4f.Provider.BingCreateImages`|`❌|✔|❌|❌||✔| +|[blackbox.ai](https://www.blackbox.ai)|`g4f.Provider.Blackbox`|`blackboxai, blackboxai-pro, gemini-flash, llama-3.1-8b, llama-3.1-70b, gpt-4o, gemini-pro, claude-3.5-sonnet`|`flux`|✔|✔||❌| +|[chatgot.one](https://www.chatgot.one/)|`g4f.Provider.ChatGot`|`gemini-pro`|❌|❌|✔||❌| +|[chatgpt.com](https://chatgpt.com)|`g4f.Provider.ChatGpt`|`?`|`?`|`?`|?| |❌| +|[chatgpt.es](https://chatgpt.es)|`g4f.Provider.ChatGptEs`|`gpt-4o, gpt-4o-mini`|❌|❌|✔||❌| +|[chatgpt4online.org](https://chatgpt4online.org)|`g4f.Provider.Chatgpt4Online`|`gpt-4`|❌|❌|✔||❌| +|[chatgpt4o.one](https://chatgpt4o.one)|`g4f.Provider.Chatgpt4o`|✔|❌|❌|❌||❌| +|[chatgptfree.ai](https://chatgptfree.ai)|`g4f.Provider.ChatgptFree`|`gpt-4o-mini`|❌|❌|?||❌| +|[app.chathub.gg](https://app.chathub.gg)|`g4f.Provider.ChatHub`|`llama-3.1-8b, mixtral-8x7b, gemma-2, sonar-online`|❌|❌|✔||❌| +|[chatify-ai.vercel.app](https://chatify-ai.vercel.app)|`g4f.Provider.ChatifyAI`|`llama-3.1-8b`|❌|❌|✔||❌| +|[playground.ai.cloudflare.com](https://playground.ai.cloudflare.com)|`g4f.Provider.Cloudflare`|`german-7b, gemma-7b, llama-2-7b, llama-3-8b, llama-3.1-8b, llama-3.2-11b, llama-3.2-1b, llama-3.2-3b, mistral-7b, openchat-3.5, phi-2, qwen-1.5-0.5b, qwen-1.5-1.8b, qwen-1.5-14b, qwen-1.5-7b, tinyllama-1.1b, cybertron-7b`|❌|❌|✔||❌| +|[aiuncensored.info](https://www.aiuncensored.info)|`g4f.Provider.DarkAI`|`gpt-4o, gpt-3.5-turbo, llama-3-70b, llama-3-405b`|❌|❌|✔||❌| +|[duckduckgo.com](https://duckduckgo.com/duckchat/v1/chat)|`g4f.Provider.DDG`|`gpt-4o-mini, claude-3-haiku, llama-3.1-70b, mixtral-8x7b`|❌|❌|✔||❌| +|[deepinfra.com](https://deepinfra.com)|`g4f.Provider.DeepInfra`|✔|❌|❌|✔||✔| +|[deepinfra.com/chat](https://deepinfra.com/chat)|`g4f.Provider.DeepInfraChat`|`llama-3.1-405b, llama-3.1-70b, llama-3.1-8B, mixtral-8x22b, mixtral-8x7b, wizardlm-2-8x22b, wizardlm-2-7b, qwen-2-72b, phi-3-medium-4k, gemma-2b-27b, minicpm-llama-3-v2.5, mistral-7b, lzlv_70b, openchat-3.6-8b, phind-codellama-34b-v2, dolphin-2.9.1-llama-3-70b`|❌|`minicpm-llama-3-v2.5`|❌||❌| +|[deepinfra.com](https://deepinfra.com)|`g4f.Provider.DeepInfraImage`|❌|✔|❌|❌||✔| +|[deepinfra.com](https://deepinfra.com)|`g4f.Provider.Editee`|`claude-3.5-sonnet, gpt-4o, gemini-pro, mistral-large`|❌|❌|✔||❌| +|[flowgpt.com](https://flowgpt.com/chat)|`g4f.Provider.FlowGpt`|✔||❌|✔||❌| +|[chat10.free2gpt.xyz](chat10.free2gpt.xyz)|`g4f.Provider.Free2GPT`|`llama-3.1-70b`|❌|❌|✔||❌| +|[chat.chatgpt.org.uk](https://chat.chatgpt.org.uk)|`g4f.Provider.FreeChatgpt`|`qwen-1.5-14b, sparkdesk-v1.1, qwen-2-7b, glm-4-9b, glm-3-6b, yi-1.5-9b`|❌|❌|✔||❌| +|[freegptsnav.aifree.site](https://freegptsnav.aifree.site)|`g4f.Provider.FreeGpt`|`llama-3.1-70b`|❌|❌|✔||❌| +|[free.netfly.top](https://free.netfly.top)|`g4f.Provider.FreeNetfly`|✔|❌|❌|?||❌| +|[gemini.google.com](https://gemini.google.com)|`g4f.Provider.Gemini`|✔|❌|❌|✔||✔| +|[ai.google.dev](https://ai.google.dev)|`g4f.Provider.GeminiPro`|✔|❌|✔|?||✔| +|[app.giz.ai](https://app.giz.ai/assistant/)|`g4f.Provider.GizAI`|`gemini-flash, gemini-pro, gpt-4o-mini, gpt-4o, claude-3.5-sonnet, claude-3-haiku, llama-3.1-70b, llama-3.1-8b, mistral-large`|`sdxl, sd-1.5, sd-3.5, dalle-3, flux-schnell, flux1-pro`|❌|✔||❌| +|[developers.sber.ru](https://developers.sber.ru/gigachat)|`g4f.Provider.GigaChat`|✔|❌|❌|✔||✔| +|[gprochat.com](https://gprochat.com)|`g4f.Provider.GPROChat`|`gemini-pro`|❌|❌|✔||❌| +|[console.groq.com/playground](https://console.groq.com/playground)|`g4f.Provider.Groq`|✔|❌|❌|?||✔| +|[huggingface.co/chat](https://huggingface.co/chat)|`g4f.Provider.HuggingChat`|`llama-3.1-70b, command-r-plus, qwen-2-72b, llama-3.2-11b, hermes-3, mistral-nemo, phi-3.5-mini`|❌|❌|✔||❌| +|[huggingface.co](https://huggingface.co/chat)|`g4f.Provider.HuggingFace`|✔|❌|❌|✔||❌| +|[koala.sh/chat](https://koala.sh/chat)|`g4f.Provider.Koala`|`gpt-4o-mini`|❌|❌|?||❌| +|[liaobots.work](https://liaobots.work)|`g4f.Provider.Liaobots`|`gpt-3.5-turbo, gpt-4o-mini, gpt-4o, gpt-4-turbo, grok-2, grok-2-mini, claude-3-opus, claude-3-sonnet, claude-3-5-sonnet, claude-3-haiku, claude-2.1, gemini-flash, gemini-pro`|❌|❌|✔||❌| +|[magickpen.com](https://magickpen.com)|`g4f.Provider.MagickPen`|`gpt-4o-mini`|❌|❌|✔||❌| +|[meta.ai](https://www.meta.ai)|`g4f.Provider.MetaAI`|✔|✔|?|?||✔| +|[app.myshell.ai/chat](https://app.myshell.ai/chat)|`g4f.Provider.MyShell`|✔|❌|?|?||❌| +|[nexra.aryahcr.cc/bing](https://nexra.aryahcr.cc/documentation/bing/en)|`g4f.Provider.NexraBing`|✔|❌|❌|✔||❌| +|[nexra.aryahcr.cc/blackbox](https://nexra.aryahcr.cc/documentation/blackbox/en)|`g4f.Provider.NexraBlackbox`|`blackboxai` |❌|❌|✔||❌| +|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3, gpt-4o` |❌|❌|✔||❌| +|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE`|❌|`dalle`|❌|❌||❌| +|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE2`|❌|`dalle-2`|❌|❌||❌| +|[nexra.aryahcr.cc/emi](https://nexra.aryahcr.cc/documentation/emi/en)|`g4f.Provider.NexraEmi`|❌|`emi`|❌|❌||❌| +|[nexra.aryahcr.cc/flux-pro](https://nexra.aryahcr.cc/documentation/flux-pro/en)|`g4f.Provider.NexraFluxPro`|❌|`flux-pro`|❌|❌||❌| +|[nexra.aryahcr.cc/gemini-pro](https://nexra.aryahcr.cc/documentation/gemini-pro/en)|`g4f.Provider.NexraGeminiPro`|`gemini-pro`|❌|❌|❌||❌| +|[nexra.aryahcr.cc/midjourney](https://nexra.aryahcr.cc/documentation/midjourney/en)|`g4f.Provider.NexraMidjourney`|❌|`midjourney`|❌|❌||❌| +|[nexra.aryahcr.cc/prodia](https://nexra.aryahcr.cc/documentation/prodia/en)|`g4f.Provider.NexraProdiaAI`|❌|✔|❌|❌||❌| +|[nexra.aryahcr.cc/qwen](https://nexra.aryahcr.cc/documentation/qwen/en)|`g4f.Provider.NexraQwen`|`qwen`|❌|❌|✔||❌| +|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSD15`|❌|`sd-1.5`|❌|❌||❌ +|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSDLora`|❌|`sdxl-lora`|❌|❌||❌ +|[nexra.aryahcr.cc/stable-diffusion](https://nexra.aryahcr.cc/documentation/stable-diffusion/en)|`g4f.Provider.NexraSDTurbo`|❌|`sdxl-turbo`|❌|❌||❌ +|[openrouter.ai](https://openrouter.ai)|`g4f.Provider.OpenRouter`|✔|❌|?|?||❌| +|[platform.openai.com](https://platform.openai.com/)|`g4f.Provider.Openai`|✔|❌|✔|||✔| +|[chatgpt.com](https://chatgpt.com/)|`g4f.Provider.OpenaiChat`|`gpt-4o, gpt-4o-mini, gpt-4`|❌|✔|||✔| +|[www.perplexity.ai)](https://www.perplexity.ai)|`g4f.Provider.PerplexityAi`|✔|❌|❌|?||❌| +|[perplexity.ai](https://www.perplexity.ai)|`g4f.Provider.PerplexityApi`|✔|❌|❌|?||✔| +|[labs.perplexity.ai](https://labs.perplexity.ai)|`g4f.Provider.PerplexityLabs`|`sonar-online, sonar-chat, llama-3.1-8b, llama-3.1-70b`|❌|❌|?||❌| +|[pi.ai/talk](https://pi.ai/talk)|`g4f.Provider.Pi`|`pi`|❌|❌|?||❌| +|[]()|`g4f.Provider.Pizzagpt`|`gpt-4o-mini`|❌|❌|✔||❌| +|[poe.com](https://poe.com)|`g4f.Provider.Poe`|✔|❌|❌|?||✔| +|[app.prodia.com](https://app.prodia.com)|`g4f.Provider.Prodia`|❌|✔|❌|❌||❌| +|[raycast.com](https://raycast.com)|`g4f.Provider.Raycast`|✔|❌|❌|✔||✔| +|[chat.reka.ai](https://chat.reka.ai/)|`g4f.Provider.Reka`|✔|❌|✔|✔||✔| +|[replicate.com](https://replicate.com)|`g4f.Provider.Replicate`|✔|❌|❌|?||✔| +|[replicate.com](https://replicate.com)|`g4f.Provider.ReplicateHome`|`llama-3-70b, mixtral-8x7b, llava-13b`|`flux-schnell, sdxl, sdxl, playground-v2.5`|❌|✔||❌| +|[replicate.com](https://replicate.com)|`g4f.Provider.RubiksAI`|`llama-3.1-70b, gpt-4o-mini`|❌|❌|✔||❌| +|[talkai.info](https://talkai.info)|`g4f.Provider.TalkAi`|✔|❌|❌|✔||❌| +|[teach-anything.com](https://www.teach-anything.com)|`g4f.Provider.TeachAnything`|`llama-3.1-70b`|❌|❌|✔||❌| +|[beta.theb.ai](https://beta.theb.ai)|`g4f.Provider.Theb`|✔|❌|❌|✔||✔| +|[beta.theb.ai](https://beta.theb.ai)|`g4f.Provider.ThebApi`|✔|❌|❌|✔||✔| +|[console.upstage.ai/playground/chat](https://console.upstage.ai/playground/chat)|`g4f.Provider.Upstage`|`solar-pro, solar-mini`|❌|❌|✔||❌| +|[whiterabbitneo.com](https://www.whiterabbitneo.com)|`g4f.Provider.WhiteRabbitNeo`|✔|❌|❌|?||✔| +|[you.com](https://you.com)|`g4f.Provider.You`|✔|✔|✔|✔||❌+✔| + +## Models + +### Text Models +| Model | Base Provider | Providers | Website | +|-------|---------------|-----------|---------| +|gpt-3|OpenAI|1+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-base)| +|gpt-3.5-turbo|OpenAI|5+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-3-5-turbo)| +|gpt-4|OpenAI|7+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)| +|gpt-4-turbo|OpenAI|3+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)| +|gpt-4o|OpenAI|10+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)| +|gpt-4o-mini|OpenAI|14+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o-mini)| +|o1|OpenAI|1+ Providers|[platform.openai.com](https://openai.com/index/introducing-openai-o1-preview/)| +|o1-mini|OpenAI|2+ Providers|[platform.openai.com](https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/)| +|llama-2-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-2-7b)| +|llama-2-13b|Meta Llama|1+ Providers|[llama.com](https://www.llama.com/llama2/)| +|llama-3-8b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)| +|llama-3-70b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)| +|llama-3.1-8b|Meta Llama|7+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)| +|llama-3.1-70b|Meta Llama|14+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)| +|llama-3.1-405b|Meta Llama|5+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)| +|llama-3.2-1b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-3.2-1B)| +|llama-3.2-3b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/blog/llama32)| +|llama-3.2-11b|Meta Llama|3+ Providers|[ai.meta.com](https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/)| +|llama-3.2-90b|Meta Llama|2+ Providers|[ai.meta.com](https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/)| +|llamaguard-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/LlamaGuard-7b)| +|llamaguard-2-8b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Meta-Llama-Guard-2-8B)| +|mistral-7b|Mistral AI|4+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)| +|mixtral-8x7b|Mistral AI|6+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-of-experts/)| +|mixtral-8x22b|Mistral AI|3+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-8x22b/)| +|mistral-nemo|Mistral AI|2+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)| +|mistral-large|Mistral AI|2+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)| +|mixtral-8x7b-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)| +|yi-34b|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B)| +|hermes-3|NousResearch|2+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)| +|gemini|Google DeepMind|1+ Providers|[deepmind.google](http://deepmind.google/technologies/gemini/)| +|gemini-flash|Google DeepMind|4+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)| +|gemini-pro|Google DeepMind|10+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)| +|gemma-2b|Google|5+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2b)| +|gemma-2b-9b|Google|1+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-9b)| +|gemma-2b-27b|Google|2+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-27b)| +|gemma-7b|Google|1+ Providers|[huggingface.co](https://huggingface.co/google/gemma-7b)| +|gemma-2|Google|2+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)| +|gemma_2_27b|Google|1+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)| +|claude-2.1|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)| +|claude-3-haiku|Anthropic|4+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)| +|claude-3-sonnet|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)| +|claude-3-opus|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)| +|claude-3.5-sonnet|Anthropic|6+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)| +|blackboxai|Blackbox AI|2+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)| +|blackboxai-pro|Blackbox AI|1+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)| +|yi-1.5-9b|01-ai|1+ Providers|[huggingface.co](https://huggingface.co/01-ai/Yi-1.5-9B)| +|phi-2|Microsoft|1+ Providers|[huggingface.co](https://huggingface.co/microsoft/phi-2)| +|phi-3-medium-4k|Microsoft|1+ Providers|[huggingface.co](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct)| +|phi-3.5-mini|Microsoft|2+ Providers|[huggingface.co](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct)| +|dbrx-instruct|Databricks|1+ Providers|[huggingface.co](https://huggingface.co/databricks/dbrx-instruct)| +|command-r-plus|CohereForAI|1+ Providers|[docs.cohere.com](https://docs.cohere.com/docs/command-r-plus)| +|sparkdesk-v1.1|iFlytek|1+ Providers|[xfyun.cn](https://www.xfyun.cn/doc/spark/Guide.html)| +|qwen|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen)| +|qwen-1.5-0.5b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-0.5B)| +|qwen-1.5-7b|Qwen|2+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-7B)| +|qwen-1.5-14b|Qwen|3+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-14B)| +|qwen-1.5-72b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-72B)| +|qwen-1.5-110b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-110B)| +|qwen-1.5-1.8b|Qwen|1+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen1.5-1.8B)| +|qwen-2-72b|Qwen|4+ Providers|[huggingface.co](https://huggingface.co/Qwen/Qwen2-72B)| +|glm-3-6b|Zhipu AI|1+ Providers|[github.com/THUDM/ChatGLM3](https://github.com/THUDM/ChatGLM3)| +|glm-4-9B|Zhipu AI|1+ Providers|[github.com/THUDM/GLM-4](https://github.com/THUDM/GLM-4)| +|solar-1-mini|Upstage|1+ Providers|[upstage.ai/](https://www.upstage.ai/feed/product/solarmini-performance-report)| +|solar-10-7b|Upstage|1+ Providers|[huggingface.co](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)| +|solar-pro|Upstage|1+ Providers|[huggingface.co](https://huggingface.co/upstage/solar-pro-preview-instruct)| +|pi|Inflection|1+ Providers|[inflection.ai](https://inflection.ai/blog/inflection-2-5)| +|deepseek|DeepSeek|1+ Providers|[deepseek.com](https://www.deepseek.com/)| +|wizardlm-2-7b|WizardLM|1+ Providers|[huggingface.co](https://huggingface.co/dreamgen/WizardLM-2-7B)| +|wizardlm-2-8x22b|WizardLM|2+ Providers|[huggingface.co](https://huggingface.co/alpindale/WizardLM-2-8x22B)| +|sh-n-7b|Together|1+ Providers|[huggingface.co](https://huggingface.co/togethercomputer/StripedHyena-Nous-7B)| +|llava-13b|Yorickvp|1+ Providers|[huggingface.co](https://huggingface.co/liuhaotian/llava-v1.5-13b)| +|minicpm-llama-3-v2.5|OpenBMB|1+ Providers|[huggingface.co](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5)| +|lzlv-70b|Lzlv|1+ Providers|[huggingface.co](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf)| +|openchat-3.5|OpenChat|1+ Providers|[huggingface.co](https://huggingface.co/openchat/openchat_3.5)| +|openchat-3.6-8b|OpenChat|1+ Providers|[huggingface.co](https://huggingface.co/openchat/openchat-3.6-8b-20240522)| +|phind-codellama-34b-v2|Phind|1+ Providers|[huggingface.co](https://huggingface.co/Phind/Phind-CodeLlama-34B-v2)| +|dolphin-2.9.1-llama-3-70b|Cognitive Computations|1+ Providers|[huggingface.co](https://huggingface.co/cognitivecomputations/dolphin-2.9.1-llama-3-70b)| +|grok-2-mini|x.ai|1+ Providers|[x.ai](https://x.ai/blog/grok-2)| +|grok-2|x.ai|1+ Providers|[x.ai](https://x.ai/blog/grok-2)| +|sonar-online|Perplexity AI|2+ Providers|[docs.perplexity.ai](https://docs.perplexity.ai/)| +|sonar-chat|Perplexity AI|1+ Providers|[docs.perplexity.ai](https://docs.perplexity.ai/)| +|mythomax-l2-13b|Gryphe|1+ Providers|[huggingface.co](https://huggingface.co/Gryphe/MythoMax-L2-13b)| +|cosmosrp|Gryphe|1+ Providers|[huggingface.co](https://huggingface.co/PawanKrd/CosmosRP-8k)| +|german-7b|TheBloke|1+ Providers|[huggingface.co](https://huggingface.co/TheBloke/DiscoLM_German_7b_v1-GGUF)| +|tinyllama-1.1b|TinyLlama|1+ Providers|[huggingface.co](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)| +|cybertron-7b|TheBloke|1+ Providers|[huggingface.co](https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16)| + +### Image Models +| Model | Base Provider | Providers | Website | +|-------|---------------|-----------|---------| +|sdxl|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/en/using-diffusers/sdxl)| +|sdxl-lora|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/blog/lcm_lora)| +|sdxl-turbo|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/stabilityai/sdxl-turbo)| +|sd-1.5|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/runwayml/stable-diffusion-v1-5)| +|sd-3|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/stable_diffusion_3)| +|sd-3.5|Stability AI|1+ Providers|[stability.ai](https://stability.ai/news/introducing-stable-diffusion-3-5)| +|playground-v2.5|Playground AI|1+ Providers|[huggingface.co](https://huggingface.co/playgroundai/playground-v2.5-1024px-aesthetic)| +|flux|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)| +|flux-pro|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)| +|flux-realism|Flux AI|2+ Providers|[]()| +|flux-anime|Flux AI|1+ Providers|[]()| +|flux-3d|Flux AI|1+ Providers|[]()| +|flux-disney|Flux AI|1+ Providers|[]()| +|flux-pixel|Flux AI|1+ Providers|[]()| +|flux-4o|Flux AI|1+ Providers|[]()| +|flux-schnell|Black Forest Labs|2+ Providers|[huggingface.co](https://huggingface.co/black-forest-labs/FLUX.1-schnell)| +|dalle|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e/)| +|dalle-2|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e-2/)| +|emi||1+ Providers|[]()| +|any-dark||1+ Providers|[]()| +|midjourney|Midjourney|1+ Providers|[docs.midjourney.com](https://docs.midjourney.com/docs/model-versions)| + +### Vision Models +| Model | Base Provider | Providers | Website | +|-------|---------------|-----------|---------| +|gpt-4-vision|OpenAI|1+ Providers|[openai.com](https://openai.com/research/gpt-4v-system-card)| +|gemini-pro-vision|Google DeepMind|1+ Providers | [deepmind.google](https://deepmind.google/technologies/gemini/)| +|blackboxai|Blackbox AI|1+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)| +|minicpm-llama-3-v2.5|OpenBMB|1+ Providers | [huggingface.co](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5)| + +## Conclusion and Usage Tips +This document provides a comprehensive overview of various AI providers and models available for text generation, image generation, and vision tasks. **When choosing a provider or model, consider the following factors:** + 1. **Availability**: Check the status of the provider to ensure it's currently active and accessible. + 2. **Model Capabilities**: Different models excel at different tasks. Choose a model that best fits your specific needs, whether it's text generation, image creation, or vision-related tasks. + 3. **Authentication**: Some providers require authentication, while others don't. Consider this when selecting a provider for your project. + 4. **Streaming Support**: If real-time responses are important for your application, prioritize providers that offer streaming capabilities. + 5. **Vision Models**: For tasks requiring image understanding or multimodal interactions, look for providers offering vision models. + +Remember to stay updated with the latest developments in the AI field, as new models and providers are constantly emerging and evolving. + +--- + +[Return to Home](/) diff --git a/docs/requirements.md b/docs/requirements.md index a4137a64..f5c598ca 100644 --- a/docs/requirements.md +++ b/docs/requirements.md @@ -38,13 +38,10 @@ Install required package for loading cookies from browser: ``` pip install browser_cookie3 ``` -Install curl_cffi for better protection from being blocked: -``` -pip install curl_cffi -``` Install all packages and uninstall this package for disabling the webdriver: ``` pip uninstall undetected-chromedriver ``` -[Return to Home](/)
\ No newline at end of file +--- +[Return to Home](/) diff --git a/etc/tool/create_provider.py b/etc/tool/create_provider.py index 797089cd..7a9827a8 100644 --- a/etc/tool/create_provider.py +++ b/etc/tool/create_provider.py @@ -33,14 +33,35 @@ from __future__ import annotations from aiohttp import ClientSession from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from .helper import format_prompt -class ChatGpt(AsyncGeneratorProvider): - url = "https://chat-gpt.com" +class {name}(AsyncGeneratorProvider, ProviderModelMixin): + label = "" + url = "https://example.com" + api_endpoint = "https://example.com/api/completion" working = True - supports_gpt_35_turbo = True + needs_auth = False + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = '' + models = ['', ''] + + model_aliases = { + "alias1": "model1", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model @classmethod async def create_async_generator( @@ -50,19 +71,21 @@ class ChatGpt(AsyncGeneratorProvider): proxy: str = None, **kwargs ) -> AsyncResult: - headers = { - "authority": "chat-gpt.com", + model = cls.get_model(model) + + headers = {{ + "authority": "example.com", "accept": "application/json", "origin": cls.url, - "referer": f"{cls.url}/chat", - } + "referer": f"{{cls.url}}/chat", + }} async with ClientSession(headers=headers) as session: prompt = format_prompt(messages) - data = { + data = {{ "prompt": prompt, - "purpose": "", - } - async with session.post(f"{cls.url}/api/chat", json=data, proxy=proxy) as response: + "model": model, + }} + async with session.post(f"{{cls.url}}/api/chat", json=data, proxy=proxy) as response: response.raise_for_status() async for chunk in response.content: if chunk: @@ -78,7 +101,7 @@ Create a provider from a cURL command. The command is: {command} ``` A example for a provider: -```py +```python {example} ``` The name for the provider class: diff --git a/etc/unittest/__main__.py b/etc/unittest/__main__.py index 351c2bb3..ee748917 100644 --- a/etc/unittest/__main__.py +++ b/etc/unittest/__main__.py @@ -4,8 +4,8 @@ from .backend import * from .main import * from .model import * from .client import * -from .async_client import * +from .client import * from .include import * from .integration import * -unittest.main()
\ No newline at end of file +unittest.main() diff --git a/etc/unittest/async_client.py b/etc/unittest/async_client.py deleted file mode 100644 index a49b90ed..00000000 --- a/etc/unittest/async_client.py +++ /dev/null @@ -1,56 +0,0 @@ -import unittest - -from g4f.client import AsyncClient, ChatCompletion, ChatCompletionChunk -from .mocks import AsyncGeneratorProviderMock, ModelProviderMock, YieldProviderMock - -DEFAULT_MESSAGES = [{'role': 'user', 'content': 'Hello'}] - -class AsyncTestPassModel(unittest.IsolatedAsyncioTestCase): - - async def test_response(self): - client = AsyncClient(provider=AsyncGeneratorProviderMock) - response = await client.chat.completions.create(DEFAULT_MESSAGES, "") - self.assertIsInstance(response, ChatCompletion) - self.assertEqual("Mock", response.choices[0].message.content) - - async def test_pass_model(self): - client = AsyncClient(provider=ModelProviderMock) - response = await client.chat.completions.create(DEFAULT_MESSAGES, "Hello") - self.assertIsInstance(response, ChatCompletion) - self.assertEqual("Hello", response.choices[0].message.content) - - async def test_max_tokens(self): - client = AsyncClient(provider=YieldProviderMock) - messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = await client.chat.completions.create(messages, "Hello", max_tokens=1) - self.assertIsInstance(response, ChatCompletion) - self.assertEqual("How ", response.choices[0].message.content) - response = await client.chat.completions.create(messages, "Hello", max_tokens=2) - self.assertIsInstance(response, ChatCompletion) - self.assertEqual("How are ", response.choices[0].message.content) - - async def test_max_stream(self): - client = AsyncClient(provider=YieldProviderMock) - messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = client.chat.completions.create(messages, "Hello", stream=True) - async for chunk in response: - self.assertIsInstance(chunk, ChatCompletionChunk) - if chunk.choices[0].delta.content is not None: - self.assertIsInstance(chunk.choices[0].delta.content, str) - messages = [{'role': 'user', 'content': chunk} for chunk in ["You ", "You ", "Other", "?"]] - response = client.chat.completions.create(messages, "Hello", stream=True, max_tokens=2) - response = [chunk async for chunk in response] - self.assertEqual(len(response), 3) - for chunk in response: - if chunk.choices[0].delta.content is not None: - self.assertEqual(chunk.choices[0].delta.content, "You ") - - async def test_stop(self): - client = AsyncClient(provider=YieldProviderMock) - messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = await client.chat.completions.create(messages, "Hello", stop=["and"]) - self.assertIsInstance(response, ChatCompletion) - self.assertEqual("How are you?", response.choices[0].message.content) - -if __name__ == '__main__': - unittest.main()
\ No newline at end of file diff --git a/etc/unittest/client.py b/etc/unittest/client.py index ec8aa4b7..54e2091f 100644 --- a/etc/unittest/client.py +++ b/etc/unittest/client.py @@ -5,52 +5,54 @@ from .mocks import AsyncGeneratorProviderMock, ModelProviderMock, YieldProviderM DEFAULT_MESSAGES = [{'role': 'user', 'content': 'Hello'}] -class TestPassModel(unittest.TestCase): +class AsyncTestPassModel(unittest.IsolatedAsyncioTestCase): - def test_response(self): + async def test_response(self): client = Client(provider=AsyncGeneratorProviderMock) - response = client.chat.completions.create(DEFAULT_MESSAGES, "") + response = await client.chat.completions.async_create(DEFAULT_MESSAGES, "") self.assertIsInstance(response, ChatCompletion) self.assertEqual("Mock", response.choices[0].message.content) - def test_pass_model(self): + async def test_pass_model(self): client = Client(provider=ModelProviderMock) - response = client.chat.completions.create(DEFAULT_MESSAGES, "Hello") + response = await client.chat.completions.async_create(DEFAULT_MESSAGES, "Hello") self.assertIsInstance(response, ChatCompletion) self.assertEqual("Hello", response.choices[0].message.content) - def test_max_tokens(self): + async def test_max_tokens(self): client = Client(provider=YieldProviderMock) messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = client.chat.completions.create(messages, "Hello", max_tokens=1) + response = await client.chat.completions.async_create(messages, "Hello", max_tokens=1) self.assertIsInstance(response, ChatCompletion) self.assertEqual("How ", response.choices[0].message.content) - response = client.chat.completions.create(messages, "Hello", max_tokens=2) + response = await client.chat.completions.async_create(messages, "Hello", max_tokens=2) self.assertIsInstance(response, ChatCompletion) self.assertEqual("How are ", response.choices[0].message.content) - def test_max_stream(self): + async def test_max_stream(self): client = Client(provider=YieldProviderMock) messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = client.chat.completions.create(messages, "Hello", stream=True) - for chunk in response: + response = await client.chat.completions.async_create(messages, "Hello", stream=True) + async for chunk in response: self.assertIsInstance(chunk, ChatCompletionChunk) if chunk.choices[0].delta.content is not None: self.assertIsInstance(chunk.choices[0].delta.content, str) messages = [{'role': 'user', 'content': chunk} for chunk in ["You ", "You ", "Other", "?"]] - response = client.chat.completions.create(messages, "Hello", stream=True, max_tokens=2) - response = list(response) - self.assertEqual(len(response), 3) - for chunk in response: + response = await client.chat.completions.async_create(messages, "Hello", stream=True, max_tokens=2) + response_list = [] + async for chunk in response: + response_list.append(chunk) + self.assertEqual(len(response_list), 3) + for chunk in response_list: if chunk.choices[0].delta.content is not None: self.assertEqual(chunk.choices[0].delta.content, "You ") - def test_stop(self): + async def test_stop(self): client = Client(provider=YieldProviderMock) messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]] - response = client.chat.completions.create(messages, "Hello", stop=["and"]) + response = await client.chat.completions.async_create(messages, "Hello", stop=["and"]) self.assertIsInstance(response, ChatCompletion) self.assertEqual("How are you?", response.choices[0].message.content) if __name__ == '__main__': - unittest.main()
\ No newline at end of file + unittest.main() diff --git a/g4f/Provider/AI365VIP.py b/g4f/Provider/AI365VIP.py index 2dcc8d1c..511ad568 100644 --- a/g4f/Provider/AI365VIP.py +++ b/g4f/Provider/AI365VIP.py @@ -10,17 +10,15 @@ from .helper import format_prompt class AI365VIP(AsyncGeneratorProvider, ProviderModelMixin): url = "https://chat.ai365vip.com" api_endpoint = "/api/chat" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True + working = False default_model = 'gpt-3.5-turbo' models = [ 'gpt-3.5-turbo', + 'gpt-3.5-turbo-16k', 'gpt-4o', - 'claude-3-haiku-20240307', ] model_aliases = { - "claude-3-haiku": "claude-3-haiku-20240307", + "gpt-3.5-turbo": "gpt-3.5-turbo-16k", } @classmethod diff --git a/g4f/Provider/AIChatFree.py b/g4f/Provider/AIChatFree.py new file mode 100644 index 00000000..71c04681 --- /dev/null +++ b/g4f/Provider/AIChatFree.py @@ -0,0 +1,76 @@ +from __future__ import annotations + +import time +from hashlib import sha256 + +from aiohttp import BaseConnector, ClientSession + +from ..errors import RateLimitError +from ..requests import raise_for_status +from ..requests.aiohttp import get_connector +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin + + +class AIChatFree(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://aichatfree.info/" + working = True + supports_stream = True + supports_message_history = True + default_model = 'gemini-pro' + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + connector: BaseConnector = None, + **kwargs, + ) -> AsyncResult: + headers = { + "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:122.0) Gecko/20100101 Firefox/122.0", + "Accept": "*/*", + "Accept-Language": "en-US,en;q=0.5", + "Accept-Encoding": "gzip, deflate, br", + "Content-Type": "text/plain;charset=UTF-8", + "Referer": f"{cls.url}/", + "Origin": cls.url, + "Sec-Fetch-Dest": "empty", + "Sec-Fetch-Mode": "cors", + "Sec-Fetch-Site": "same-origin", + "Connection": "keep-alive", + "TE": "trailers", + } + async with ClientSession( + connector=get_connector(connector, proxy), headers=headers + ) as session: + timestamp = int(time.time() * 1e3) + data = { + "messages": [ + { + "role": "model" if message["role"] == "assistant" else "user", + "parts": [{"text": message["content"]}], + } + for message in messages + ], + "time": timestamp, + "pass": None, + "sign": generate_signature(timestamp, messages[-1]["content"]), + } + async with session.post( + f"{cls.url}/api/generate", json=data, proxy=proxy + ) as response: + if response.status == 500: + if "Quota exceeded" in await response.text(): + raise RateLimitError( + f"Response {response.status}: Rate limit reached" + ) + await raise_for_status(response) + async for chunk in response.content.iter_any(): + yield chunk.decode(errors="ignore") + + +def generate_signature(time: int, text: str, secret: str = ""): + message = f"{time}:{text}:{secret}" + return sha256(message.encode()).hexdigest() diff --git a/g4f/Provider/AIUncensored.py b/g4f/Provider/AIUncensored.py new file mode 100644 index 00000000..d653191c --- /dev/null +++ b/g4f/Provider/AIUncensored.py @@ -0,0 +1,112 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt +from ..image import ImageResponse + +class AIUncensored(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://www.aiuncensored.info" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'ai_uncensored' + chat_models = [default_model] + image_models = ['ImageGenerator'] + models = [*chat_models, *image_models] + + api_endpoints = { + 'ai_uncensored': "https://twitterclone-i0wr.onrender.com/api/chat", + 'ImageGenerator': "https://twitterclone-4e8t.onrender.com/api/image" + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + if model in cls.chat_models: + async with ClientSession(headers={"content-type": "application/json"}) as session: + data = { + "messages": [ + {"role": "user", "content": format_prompt(messages)} + ], + "stream": stream + } + async with session.post(cls.api_endpoints[model], json=data, proxy=proxy) as response: + response.raise_for_status() + if stream: + async for chunk in cls._handle_streaming_response(response): + yield chunk + else: + yield await cls._handle_non_streaming_response(response) + elif model in cls.image_models: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": cls.url, + "pragma": "no-cache", + "priority": "u=1, i", + "referer": f"{cls.url}/", + "sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "cross-site", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36" + } + async with ClientSession(headers=headers) as session: + prompt = messages[0]['content'] + data = {"prompt": prompt} + async with session.post(cls.api_endpoints[model], json=data, proxy=proxy) as response: + response.raise_for_status() + result = await response.json() + image_url = result.get('image_url', '') + if image_url: + yield ImageResponse(image_url, alt=prompt) + else: + yield "Failed to generate image. Please try again." + + @classmethod + async def _handle_streaming_response(cls, response): + async for line in response.content: + line = line.decode('utf-8').strip() + if line.startswith("data: "): + if line == "data: [DONE]": + break + try: + json_data = json.loads(line[6:]) + if 'data' in json_data: + yield json_data['data'] + except json.JSONDecodeError: + pass + + @classmethod + async def _handle_non_streaming_response(cls, response): + response_json = await response.json() + return response_json.get('content', "Sorry, I couldn't generate a response.") + + @classmethod + def validate_response(cls, response: str) -> str: + return response diff --git a/g4f/Provider/Ai4Chat.py b/g4f/Provider/Ai4Chat.py new file mode 100644 index 00000000..1096279d --- /dev/null +++ b/g4f/Provider/Ai4Chat.py @@ -0,0 +1,88 @@ +from __future__ import annotations + +import json +import re +import logging +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class Ai4Chat(AsyncGeneratorProvider, ProviderModelMixin): + label = "AI4Chat" + url = "https://www.ai4chat.co" + api_endpoint = "https://www.ai4chat.co/generate-response" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4' + models = [default_model] + + model_aliases = {} + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": "https://www.ai4chat.co", + "pragma": "no-cache", + "priority": "u=1, i", + "referer": "https://www.ai4chat.co/gpt/talkdirtytome", + "sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36" + } + + async with ClientSession(headers=headers) as session: + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ] + } + + try: + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + result = await response.text() + + json_result = json.loads(result) + + message = json_result.get("message", "") + + clean_message = re.sub(r'<[^>]+>', '', message) + + yield clean_message + except Exception as e: + logging.exception("Error while calling AI 4Chat API: %s", e) + yield f"Error: {e}" diff --git a/g4f/Provider/AiChatOnline.py b/g4f/Provider/AiChatOnline.py index 152a7d31..26aacef6 100644 --- a/g4f/Provider/AiChatOnline.py +++ b/g4f/Provider/AiChatOnline.py @@ -12,10 +12,7 @@ class AiChatOnline(AsyncGeneratorProvider, ProviderModelMixin): url = "https://aichatonlineorg.erweima.ai" api_endpoint = "/aichatonline/api/chat/gpt" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' - supports_message_history = False @classmethod async def grab_token( diff --git a/g4f/Provider/AiChats.py b/g4f/Provider/AiChats.py index 10127d4f..08492e24 100644 --- a/g4f/Provider/AiChats.py +++ b/g4f/Provider/AiChats.py @@ -12,7 +12,6 @@ class AiChats(AsyncGeneratorProvider, ProviderModelMixin): url = "https://ai-chats.org" api_endpoint = "https://ai-chats.org/chat/send2/" working = True - supports_gpt_4 = True supports_message_history = True default_model = 'gpt-4' models = ['gpt-4', 'dalle'] diff --git a/g4f/Provider/AiMathGPT.py b/g4f/Provider/AiMathGPT.py new file mode 100644 index 00000000..90931691 --- /dev/null +++ b/g4f/Provider/AiMathGPT.py @@ -0,0 +1,74 @@ +from __future__ import annotations + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class AiMathGPT(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://aimathgpt.forit.ai" + api_endpoint = "https://aimathgpt.forit.ai/api/ai" + working = True + supports_stream = False + supports_system_message = True + supports_message_history = True + + default_model = 'llama3' + models = ['llama3'] + + model_aliases = {"llama-3.1-70b": "llama3",} + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.9', + 'cache-control': 'no-cache', + 'content-type': 'application/json', + 'origin': cls.url, + 'pragma': 'no-cache', + 'priority': 'u=1, i', + 'referer': f'{cls.url}/', + 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + 'sec-fetch-dest': 'empty', + 'sec-fetch-mode': 'cors', + 'sec-fetch-site': 'same-origin', + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36' + } + + async with ClientSession(headers=headers) as session: + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "model": model + } + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_data = await response.json() + filtered_response = response_data['result']['response'] + yield filtered_response diff --git a/g4f/Provider/Airforce.py b/g4f/Provider/Airforce.py new file mode 100644 index 00000000..015766f4 --- /dev/null +++ b/g4f/Provider/Airforce.py @@ -0,0 +1,245 @@ +from __future__ import annotations +import random +import json +import re +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse + +def split_long_message(message: str, max_length: int = 4000) -> list[str]: + return [message[i:i+max_length] for i in range(0, len(message), max_length)] + +class Airforce(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://api.airforce" + image_api_endpoint = "https://api.airforce/imagine2" + text_api_endpoint = "https://api.airforce/chat/completions" + working = True + + default_model = 'llama-3-70b-chat' + + supports_stream = True + supports_system_message = True + supports_message_history = True + + text_models = [ + 'claude-3-haiku-20240307', + 'claude-3-sonnet-20240229', + 'claude-3-5-sonnet-20240620', + 'claude-3-opus-20240229', + 'chatgpt-4o-latest', + 'gpt-4', + 'gpt-4-turbo', + 'gpt-4o-mini-2024-07-18', + 'gpt-4o-mini', + 'gpt-3.5-turbo', + 'gpt-3.5-turbo-0125', + 'gpt-3.5-turbo-1106', + default_model, + 'llama-3-70b-chat-turbo', + 'llama-3-8b-chat', + 'llama-3-8b-chat-turbo', + 'llama-3-70b-chat-lite', + 'llama-3-8b-chat-lite', + 'llama-2-13b-chat', + 'llama-3.1-405b-turbo', + 'llama-3.1-70b-turbo', + 'llama-3.1-8b-turbo', + 'LlamaGuard-2-8b', + 'Llama-Guard-7b', + 'Llama-3.2-90B-Vision-Instruct-Turbo', + 'Mixtral-8x7B-Instruct-v0.1', + 'Mixtral-8x22B-Instruct-v0.1', + 'Mistral-7B-Instruct-v0.1', + 'Mistral-7B-Instruct-v0.2', + 'Mistral-7B-Instruct-v0.3', + 'Qwen1.5-7B-Chat', + 'Qwen1.5-14B-Chat', + 'Qwen1.5-72B-Chat', + 'Qwen1.5-110B-Chat', + 'Qwen2-72B-Instruct', + 'gemma-2b-it', + 'gemma-2-9b-it', + 'gemma-2-27b-it', + 'gemini-1.5-flash', + 'gemini-1.5-pro', + 'deepseek-llm-67b-chat', + 'Nous-Hermes-2-Mixtral-8x7B-DPO', + 'Nous-Hermes-2-Yi-34B', + 'WizardLM-2-8x22B', + 'SOLAR-10.7B-Instruct-v1.0', + 'MythoMax-L2-13b', + 'cosmosrp', + ] + + image_models = [ + 'flux', + 'flux-realism', + 'flux-anime', + 'flux-3d', + 'flux-disney', + 'flux-pixel', + 'flux-4o', + 'any-dark', + ] + + models = [ + *text_models, + *image_models, + ] + + model_aliases = { + "claude-3-haiku": "claude-3-haiku-20240307", + "claude-3-sonnet": "claude-3-sonnet-20240229", + "gpt-4o": "chatgpt-4o-latest", + "llama-3-70b": "llama-3-70b-chat", + "llama-3-8b": "llama-3-8b-chat", + "mixtral-8x7b": "Mixtral-8x7B-Instruct-v0.1", + "qwen-1.5-7b": "Qwen1.5-7B-Chat", + "gemma-2b": "gemma-2b-it", + "gemini-flash": "gemini-1.5-flash", + "mythomax-l2-13b": "MythoMax-L2-13b", + "solar-10.7b": "SOLAR-10.7B-Instruct-v1.0", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases.get(model, cls.default_model) + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + seed: int = None, + size: str = "1:1", + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + if model in cls.image_models: + async for result in cls._generate_image(model, messages, proxy, seed, size): + yield result + elif model in cls.text_models: + async for result in cls._generate_text(model, messages, proxy, stream): + yield result + + @classmethod + async def _generate_image( + cls, + model: str, + messages: Messages, + proxy: str = None, + seed: int = None, + size: str = "1:1", + **kwargs + ) -> AsyncResult: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "origin": "https://llmplayground.net", + "user-agent": "Mozilla/5.0" + } + + if seed is None: + seed = random.randint(0, 100000) + + prompt = messages[-1]['content'] + + async with ClientSession(headers=headers) as session: + params = { + "model": model, + "prompt": prompt, + "size": size, + "seed": seed + } + async with session.get(f"{cls.image_api_endpoint}", params=params, proxy=proxy) as response: + response.raise_for_status() + content_type = response.headers.get('Content-Type', '').lower() + + if 'application/json' in content_type: + async for chunk in response.content.iter_chunked(1024): + if chunk: + yield chunk.decode('utf-8') + elif 'image' in content_type: + image_data = b"" + async for chunk in response.content.iter_chunked(1024): + if chunk: + image_data += chunk + image_url = f"{cls.image_api_endpoint}?model={model}&prompt={prompt}&size={size}&seed={seed}" + alt_text = f"Generated image for prompt: {prompt}" + yield ImageResponse(images=image_url, alt=alt_text) + + @classmethod + async def _generate_text( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "authorization": "Bearer missing api key", + "content-type": "application/json", + "user-agent": "Mozilla/5.0" + } + + async with ClientSession(headers=headers) as session: + formatted_prompt = cls._format_messages(messages) + prompt_parts = split_long_message(formatted_prompt) + full_response = "" + + for part in prompt_parts: + data = { + "messages": [{"role": "user", "content": part}], + "model": model, + "max_tokens": 4096, + "temperature": 1, + "top_p": 1, + "stream": stream + } + async with session.post(cls.text_api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + part_response = "" + if stream: + async for line in response.content: + if line: + line = line.decode('utf-8').strip() + if line.startswith("data: ") and line != "data: [DONE]": + json_data = json.loads(line[6:]) + content = json_data['choices'][0]['delta'].get('content', '') + part_response += content + else: + json_data = await response.json() + content = json_data['choices'][0]['message']['content'] + part_response = content + + part_response = re.sub( + r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+", + '', + part_response + ) + + part_response = re.sub( + r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+", + '', + part_response + ) + + full_response += part_response + yield full_response + + @classmethod + def _format_messages(cls, messages: Messages) -> str: + return " ".join([msg['content'] for msg in messages]) diff --git a/g4f/Provider/Allyfy.py b/g4f/Provider/Allyfy.py index 8733b1ec..bf607df4 100644 --- a/g4f/Provider/Allyfy.py +++ b/g4f/Provider/Allyfy.py @@ -9,10 +9,9 @@ from .helper import format_prompt class Allyfy(AsyncGeneratorProvider): - url = "https://chatbot.allyfy.chat" - api_endpoint = "/api/v1/message/stream/super/chat" + url = "https://allyfy.chat" + api_endpoint = "https://chatbot.allyfy.chat/api/v1/message/stream/super/chat" working = True - supports_gpt_35_turbo = True @classmethod async def create_async_generator( @@ -53,7 +52,7 @@ class Allyfy(AsyncGeneratorProvider): "packageName": "com.cch.allyfy.webh", } } - async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response: + async with session.post(f"{cls.api_endpoint}", json=data, proxy=proxy) as response: response.raise_for_status() full_response = [] async for line in response.content: diff --git a/g4f/Provider/AmigoChat.py b/g4f/Provider/AmigoChat.py new file mode 100644 index 00000000..f5027111 --- /dev/null +++ b/g4f/Provider/AmigoChat.py @@ -0,0 +1,189 @@ +from __future__ import annotations + +import json +import uuid +from aiohttp import ClientSession, ClientTimeout, ClientResponseError + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt +from ..image import ImageResponse + +class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://amigochat.io/chat/" + chat_api_endpoint = "https://api.amigochat.io/v1/chat/completions" + image_api_endpoint = "https://api.amigochat.io/v1/images/generations" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o-mini' + + chat_models = [ + 'gpt-4o', + default_model, + 'o1-preview', + 'o1-mini', + 'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo', + 'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo', + 'claude-3-sonnet-20240229', + 'gemini-1.5-pro', + ] + + image_models = [ + 'flux-pro/v1.1', + 'flux-realism', + 'flux-pro', + 'dalle-e-3', + ] + + models = [*chat_models, *image_models] + + model_aliases = { + "o1": "o1-preview", + "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo", + "llama-3.2-90b": "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", + "claude-3.5-sonnet": "claude-3-sonnet-20240229", + "gemini-pro": "gemini-1.5-pro", + + "flux-pro": "flux-pro/v1.1", + "dalle-3": "dalle-e-3", + } + + persona_ids = { + 'gpt-4o': "gpt", + 'gpt-4o-mini': "amigo", + 'o1-preview': "openai-o-one", + 'o1-mini': "openai-o-one-mini", + 'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo': "llama-three-point-one", + 'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo': "llama-3-2", + 'claude-3-sonnet-20240229': "claude", + 'gemini-1.5-pro': "gemini-1-5-pro", + 'flux-pro/v1.1': "flux-1-1-pro", + 'flux-realism': "flux-realism", + 'flux-pro': "flux-pro", + 'dalle-e-3': "dalle-three", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def get_personaId(cls, model: str) -> str: + return cls.persona_ids[model] + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + stream: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + device_uuid = str(uuid.uuid4()) + max_retries = 3 + retry_count = 0 + + while retry_count < max_retries: + try: + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "authorization": "Bearer", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": cls.url, + "pragma": "no-cache", + "priority": "u=1, i", + "referer": f"{cls.url}/", + "sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + "x-device-language": "en-US", + "x-device-platform": "web", + "x-device-uuid": device_uuid, + "x-device-version": "1.0.32" + } + + async with ClientSession(headers=headers) as session: + if model in cls.chat_models: + # Chat completion + data = { + "messages": [{"role": m["role"], "content": m["content"]} for m in messages], + "model": model, + "personaId": cls.get_personaId(model), + "frequency_penalty": 0, + "max_tokens": 4000, + "presence_penalty": 0, + "stream": stream, + "temperature": 0.5, + "top_p": 0.95 + } + + timeout = ClientTimeout(total=300) # 5 minutes timeout + async with session.post(cls.chat_api_endpoint, json=data, proxy=proxy, timeout=timeout) as response: + if response.status not in (200, 201): + error_text = await response.text() + raise Exception(f"Error {response.status}: {error_text}") + + async for line in response.content: + line = line.decode('utf-8').strip() + if line.startswith('data: '): + if line == 'data: [DONE]': + break + try: + chunk = json.loads(line[6:]) # Remove 'data: ' prefix + if 'choices' in chunk and len(chunk['choices']) > 0: + choice = chunk['choices'][0] + if 'delta' in choice: + content = choice['delta'].get('content') + elif 'text' in choice: + content = choice['text'] + else: + content = None + if content: + yield content + except json.JSONDecodeError: + pass + else: + # Image generation + prompt = messages[-1]['content'] + data = { + "prompt": prompt, + "model": model, + "personaId": cls.get_personaId(model) + } + async with session.post(cls.image_api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + + response_data = await response.json() + + if "data" in response_data: + image_urls = [] + for item in response_data["data"]: + if "url" in item: + image_url = item["url"] + image_urls.append(image_url) + if image_urls: + yield ImageResponse(image_urls, prompt) + else: + yield None + + break + + except (ClientResponseError, Exception) as e: + retry_count += 1 + if retry_count >= max_retries: + raise e + device_uuid = str(uuid.uuid4()) diff --git a/g4f/Provider/Aura.py b/g4f/Provider/Aura.py index 4a8d0a55..e2c56754 100644 --- a/g4f/Provider/Aura.py +++ b/g4f/Provider/Aura.py @@ -9,7 +9,7 @@ from ..webdriver import WebDriver class Aura(AsyncGeneratorProvider): url = "https://openchat.team" - working = True + working = False @classmethod async def create_async_generator( @@ -46,4 +46,4 @@ class Aura(AsyncGeneratorProvider): async with session.post(f"{cls.url}/api/chat", json=data, proxy=proxy) as response: response.raise_for_status() async for chunk in response.content.iter_any(): - yield chunk.decode(error="ignore")
\ No newline at end of file + yield chunk.decode(error="ignore") diff --git a/g4f/Provider/Bing.py b/g4f/Provider/Bing.py index 4056f9ff..f04b1a54 100644 --- a/g4f/Provider/Bing.py +++ b/g4f/Provider/Bing.py @@ -37,7 +37,6 @@ class Bing(AsyncGeneratorProvider, ProviderModelMixin): url = "https://bing.com/chat" working = True supports_message_history = True - supports_gpt_4 = True default_model = "Balanced" default_vision_model = "gpt-4-vision" models = [getattr(Tones, key) for key in Tones.__dict__ if not key.startswith("__")] diff --git a/g4f/Provider/Binjie.py b/g4f/Provider/Binjie.py deleted file mode 100644 index 90f9ec3c..00000000 --- a/g4f/Provider/Binjie.py +++ /dev/null @@ -1,65 +0,0 @@ -from __future__ import annotations - -import random -from ..requests import StreamSession - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, format_prompt - - -class Binjie(AsyncGeneratorProvider): - url = "https://chat18.aichatos8.com" - working = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - @staticmethod - async def create_async_generator( - model: str, - messages: Messages, - proxy: str = None, - timeout: int = 120, - **kwargs, - ) -> AsyncResult: - async with StreamSession( - headers=_create_header(), proxies={"https": proxy}, timeout=timeout - ) as session: - payload = _create_payload(messages, **kwargs) - async with session.post("https://api.binjie.fun/api/generateStream", json=payload) as response: - response.raise_for_status() - async for chunk in response.iter_content(): - if chunk: - chunk = chunk.decode() - if "sorry, 您的ip已由于触发防滥用检测而被封禁" in chunk: - raise RuntimeError("IP address is blocked by abuse detection.") - yield chunk - - -def _create_header(): - return { - "accept" : "application/json, text/plain, */*", - "content-type" : "application/json", - "origin" : "https://chat18.aichatos8.com", - "referer" : "https://chat18.aichatos8.com/" - } - - -def _create_payload( - messages: Messages, - system_message: str = "", - user_id: int = None, - **kwargs -): - if not user_id: - user_id = random.randint(1690000544336, 2093025544336) - return { - "prompt": format_prompt(messages), - "network": True, - "system": system_message, - "withoutContext": False, - "stream": True, - "userId": f"#/chat/{user_id}" - } - diff --git a/g4f/Provider/Bixin123.py b/g4f/Provider/Bixin123.py deleted file mode 100644 index 694a2eff..00000000 --- a/g4f/Provider/Bixin123.py +++ /dev/null @@ -1,89 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession -import json -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..typing import AsyncResult, Messages -from .helper import format_prompt - -class Bixin123(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://chat.bixin123.com" - api_endpoint = "https://chat.bixin123.com/api/chatgpt/chat-process" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - - default_model = 'gpt-3.5-turbo-0125' - models = ['gpt-3.5-turbo-0125', 'gpt-3.5-turbo-16k-0613', 'gpt-4-turbo', 'qwen-turbo'] - - model_aliases = { - "gpt-3.5-turbo": "gpt-3.5-turbo-0125", - "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - elif model in cls.model_aliases: - return cls.model_aliases[model] - else: - return cls.default_model - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - model = cls.get_model(model) - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "fingerprint": "988148794", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/chat", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - "x-website-domain": "chat.bixin123.com", - } - - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "prompt": prompt, - "options": { - "usingNetwork": False, - "file": "" - } - } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - response_text = await response.text() - - lines = response_text.strip().split("\n") - last_json = None - for line in reversed(lines): - try: - last_json = json.loads(line) - break - except json.JSONDecodeError: - pass - - if last_json: - text = last_json.get("text", "") - yield text - else: - yield "" diff --git a/g4f/Provider/Blackbox.py b/g4f/Provider/Blackbox.py index 9fab4a09..4052893a 100644 --- a/g4f/Provider/Blackbox.py +++ b/g4f/Provider/Blackbox.py @@ -1,43 +1,122 @@ from __future__ import annotations +import asyncio +import aiohttp +import random +import string +import json import uuid -import secrets import re -import base64 -from aiohttp import ClientSession -from typing import AsyncGenerator, Optional +from typing import Optional, AsyncGenerator, Union + +from aiohttp import ClientSession, ClientResponseError from ..typing import AsyncResult, Messages, ImageType -from ..image import to_data_uri, ImageResponse from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse, to_data_uri + class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): + label = "Blackbox AI" url = "https://www.blackbox.ai" + api_endpoint = "https://www.blackbox.ai/api/chat" working = True - default_model = 'blackbox' + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'blackboxai' + image_models = ['ImageGeneration'] models = [ default_model, - "gemini-1.5-flash", + 'blackboxai-pro', + *image_models, "llama-3.1-8b", 'llama-3.1-70b', 'llama-3.1-405b', - 'ImageGeneration', + 'gpt-4o', + 'gemini-pro', + 'gemini-1.5-flash', + 'claude-sonnet-3.5', + 'PythonAgent', + 'JavaAgent', + 'JavaScriptAgent', + 'HTMLAgent', + 'GoogleCloudAgent', + 'AndroidDeveloper', + 'SwiftDeveloper', + 'Next.jsAgent', + 'MongoDBAgent', + 'PyTorchAgent', + 'ReactAgent', + 'XcodeAgent', + 'AngularJSAgent', ] - - model_aliases = { - "gemini-flash": "gemini-1.5-flash", - } - - agent_mode_map = { - 'ImageGeneration': {"mode": True, "id": "ImageGenerationLV45LJp", "name": "Image Generation"}, + + agentMode = { + 'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}, } - model_id_map = { - "blackbox": {}, + trendingAgentMode = { + "blackboxai": {}, "gemini-1.5-flash": {'mode': True, 'id': 'Gemini'}, "llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"}, 'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"}, - 'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"} + 'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"}, + 'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"}, + 'PythonAgent': {'mode': True, 'id': "Python Agent"}, + 'JavaAgent': {'mode': True, 'id': "Java Agent"}, + 'JavaScriptAgent': {'mode': True, 'id': "JavaScript Agent"}, + 'HTMLAgent': {'mode': True, 'id': "HTML Agent"}, + 'GoogleCloudAgent': {'mode': True, 'id': "Google Cloud Agent"}, + 'AndroidDeveloper': {'mode': True, 'id': "Android Developer"}, + 'SwiftDeveloper': {'mode': True, 'id': "Swift Developer"}, + 'Next.jsAgent': {'mode': True, 'id': "Next.js Agent"}, + 'MongoDBAgent': {'mode': True, 'id': "MongoDB Agent"}, + 'PyTorchAgent': {'mode': True, 'id': "PyTorch Agent"}, + 'ReactAgent': {'mode': True, 'id': "React Agent"}, + 'XcodeAgent': {'mode': True, 'id': "Xcode Agent"}, + 'AngularJSAgent': {'mode': True, 'id': "AngularJS Agent"}, + } + + userSelectedModel = { + "gpt-4o": "gpt-4o", + "gemini-pro": "gemini-pro", + 'claude-sonnet-3.5': "claude-sonnet-3.5", + } + + model_prefixes = { + 'gpt-4o': '@GPT-4o', + 'gemini-pro': '@Gemini-PRO', + 'claude-sonnet-3.5': '@Claude-Sonnet-3.5', + 'PythonAgent': '@Python Agent', + 'JavaAgent': '@Java Agent', + 'JavaScriptAgent': '@JavaScript Agent', + 'HTMLAgent': '@HTML Agent', + 'GoogleCloudAgent': '@Google Cloud Agent', + 'AndroidDeveloper': '@Android Developer', + 'SwiftDeveloper': '@Swift Developer', + 'Next.jsAgent': '@Next.js Agent', + 'MongoDBAgent': '@MongoDB Agent', + 'PyTorchAgent': '@PyTorch Agent', + 'ReactAgent': '@React Agent', + 'XcodeAgent': '@Xcode Agent', + 'AngularJSAgent': '@AngularJS Agent', + 'blackboxai-pro': '@BLACKBOXAI-PRO', + 'ImageGeneration': '@Image Generation', + } + + model_referers = { + "blackboxai": "/?model=blackboxai", + "gpt-4o": "/?model=gpt-4o", + "gemini-pro": "/?model=gemini-pro", + "claude-sonnet-3.5": "/?model=claude-sonnet-3.5" + } + + model_aliases = { + "gemini-flash": "gemini-1.5-flash", + "claude-3.5-sonnet": "claude-sonnet-3.5", + "flux": "ImageGeneration", } @classmethod @@ -49,14 +128,41 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): else: return cls.default_model - @classmethod - async def download_image_to_base64_url(cls, url: str) -> str: - async with ClientSession() as session: - async with session.get(url) as response: - image_data = await response.read() - base64_data = base64.b64encode(image_data).decode('utf-8') - mime_type = response.headers.get('Content-Type', 'image/jpeg') - return f"data:{mime_type};base64,{base64_data}" + @staticmethod + def generate_random_string(length: int = 7) -> str: + characters = string.ascii_letters + string.digits + return ''.join(random.choices(characters, k=length)) + + @staticmethod + def generate_next_action() -> str: + return uuid.uuid4().hex + + @staticmethod + def generate_next_router_state_tree() -> str: + router_state = [ + "", + { + "children": [ + "(chat)", + { + "children": [ + "__PAGE__", + {} + ] + } + ] + }, + None, + None, + True + ] + return json.dumps(router_state) + + @staticmethod + def clean_response(text: str) -> str: + pattern = r'^\$\@\$v=undefined-rv1\$\@\$' + cleaned_text = re.sub(pattern, '', text) + return cleaned_text @classmethod async def create_async_generator( @@ -64,93 +170,203 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin): model: str, messages: Messages, proxy: Optional[str] = None, - image: Optional[ImageType] = None, - image_name: Optional[str] = None, + image: ImageType = None, + image_name: str = None, + web_search: bool = False, **kwargs - ) -> AsyncGenerator[AsyncResult, None]: + ) -> AsyncGenerator[Union[str, ImageResponse], None]: + """ + Creates an asynchronous generator for streaming responses from Blackbox AI. + + Parameters: + model (str): Model to use for generating responses. + messages (Messages): Message history. + proxy (Optional[str]): Proxy URL, if needed. + image (ImageType): Image data to be processed, if any. + image_name (str): Name of the image file, if an image is provided. + web_search (bool): Enables or disables web search mode. + **kwargs: Additional keyword arguments. + + Yields: + Union[str, ImageResponse]: Segments of the generated response or ImageResponse objects. + """ + if image is not None: - messages[-1]["data"] = { - "fileText": image_name, - "imageBase64": to_data_uri(image), - "title": str(uuid.uuid4()) + messages[-1]['data'] = { + 'fileText': '', + 'imageBase64': to_data_uri(image), + 'title': image_name } + messages[-1]['content'] = 'FILE:BB\n$#$\n\n$#$\n' + messages[-1]['content'] + + model = cls.get_model(model) + + chat_id = cls.generate_random_string() + next_action = cls.generate_next_action() + next_router_state_tree = cls.generate_next_router_state_tree() - headers = { - "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36", - "Accept": "*/*", - "Accept-Language": "en-US,en;q=0.5", - "Accept-Encoding": "gzip, deflate, br", - "Referer": cls.url, - "Content-Type": "application/json", - "Origin": cls.url, - "DNT": "1", - "Sec-GPC": "1", - "Alt-Used": "www.blackbox.ai", - "Connection": "keep-alive", + agent_mode = cls.agentMode.get(model, {}) + trending_agent_mode = cls.trendingAgentMode.get(model, {}) + + prefix = cls.model_prefixes.get(model, "") + + formatted_prompt = "" + for message in messages: + role = message.get('role', '').capitalize() + content = message.get('content', '') + if role and content: + formatted_prompt += f"{role}: {content}\n" + + if prefix: + formatted_prompt = f"{prefix} {formatted_prompt}".strip() + + referer_path = cls.model_referers.get(model, f"/?model={model}") + referer_url = f"{cls.url}{referer_path}" + + common_headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.9', + 'cache-control': 'no-cache', + 'origin': cls.url, + 'pragma': 'no-cache', + 'priority': 'u=1, i', + 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + 'sec-fetch-dest': 'empty', + 'sec-fetch-mode': 'cors', + 'sec-fetch-site': 'same-origin', + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) ' + 'AppleWebKit/537.36 (KHTML, like Gecko) ' + 'Chrome/129.0.0.0 Safari/537.36' } - async with ClientSession(headers=headers) as session: - random_id = secrets.token_hex(16) - random_user_id = str(uuid.uuid4()) - - model = cls.get_model(model) # Resolve the model alias - - data = { - "messages": messages, - "id": random_id, - "userId": random_user_id, - "codeModelMode": True, - "agentMode": cls.agent_mode_map.get(model, {}), - "trendingAgentMode": {}, - "isMicMode": False, - "isChromeExt": False, - "playgroundMode": False, - "webSearchMode": False, - "userSystemPrompt": "", - "githubToken": None, - "trendingAgentModel": cls.model_id_map.get(model, {}), - "maxTokens": None - } + headers_api_chat = { + 'Content-Type': 'application/json', + 'Referer': referer_url + } + headers_api_chat_combined = {**common_headers, **headers_api_chat} + + payload_api_chat = { + "messages": [ + { + "id": chat_id, + "content": formatted_prompt, + "role": "user", + "data": messages[-1].get('data') + } + ], + "id": chat_id, + "previewToken": None, + "userId": None, + "codeModelMode": True, + "agentMode": agent_mode, + "trendingAgentMode": trending_agent_mode, + "isMicMode": False, + "userSystemPrompt": None, + "maxTokens": 1024, + "playgroundTopP": 0.9, + "playgroundTemperature": 0.5, + "isChromeExt": False, + "githubToken": None, + "clickedAnswer2": False, + "clickedAnswer3": False, + "clickedForceWebSearch": False, + "visitFromDelta": False, + "mobileClient": False, + "webSearchMode": web_search, + "userSelectedModel": cls.userSelectedModel.get(model, model) + } + + headers_chat = { + 'Accept': 'text/x-component', + 'Content-Type': 'text/plain;charset=UTF-8', + 'Referer': f'{cls.url}/chat/{chat_id}?model={model}', + 'next-action': next_action, + 'next-router-state-tree': next_router_state_tree, + 'next-url': '/' + } + headers_chat_combined = {**common_headers, **headers_chat} + + data_chat = '[]' + + async with ClientSession(headers=common_headers) as session: + try: + async with session.post( + cls.api_endpoint, + headers=headers_api_chat_combined, + json=payload_api_chat, + proxy=proxy + ) as response_api_chat: + response_api_chat.raise_for_status() + text = await response_api_chat.text() + cleaned_response = cls.clean_response(text) + + if model in cls.image_models: + match = re.search(r'!\[.*?\]\((https?://[^\)]+)\)', cleaned_response) + if match: + image_url = match.group(1) + image_response = ImageResponse(images=image_url, alt="Generated Image") + yield image_response + else: + yield cleaned_response + else: + if web_search: + match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL) + if match: + source_part = match.group(1).strip() + answer_part = cleaned_response[match.end():].strip() + try: + sources = json.loads(source_part) + source_formatted = "**Source:**\n" + for item in sources: + title = item.get('title', 'No Title') + link = item.get('link', '#') + position = item.get('position', '') + source_formatted += f"{position}. [{title}]({link})\n" + final_response = f"{answer_part}\n\n{source_formatted}" + except json.JSONDecodeError: + final_response = f"{answer_part}\n\nSource information is unavailable." + else: + final_response = cleaned_response + else: + if '$~~~$' in cleaned_response: + final_response = cleaned_response.split('$~~~$')[0].strip() + else: + final_response = cleaned_response + + yield final_response + except ClientResponseError as e: + error_text = f"Error {e.status}: {e.message}" + try: + error_response = await e.response.text() + cleaned_error = cls.clean_response(error_response) + error_text += f" - {cleaned_error}" + except Exception: + pass + yield error_text + except Exception as e: + yield f"Unexpected error during /api/chat request: {str(e)}" + + chat_url = f'{cls.url}/chat/{chat_id}?model={model}' - async with session.post( - f"{cls.url}/api/chat", json=data, proxy=proxy - ) as response: - response.raise_for_status() - full_response = "" - buffer = "" - image_base64_url = None - async for chunk in response.content.iter_any(): - if chunk: - decoded_chunk = chunk.decode() - cleaned_chunk = re.sub(r'\$@\$.+?\$@\$|\$@\$', '', decoded_chunk) - - buffer += cleaned_chunk - - # Check if there's a complete image line in the buffer - image_match = re.search(r'!\[Generated Image\]\((https?://[^\s\)]+)\)', buffer) - if image_match: - image_url = image_match.group(1) - # Download the image and convert to base64 URL - image_base64_url = await cls.download_image_to_base64_url(image_url) - - # Remove the image line from the buffer - buffer = re.sub(r'!\[Generated Image\]\(https?://[^\s\)]+\)', '', buffer) - - # Send text line by line - lines = buffer.split('\n') - for line in lines[:-1]: - if line.strip(): - full_response += line + '\n' - yield line + '\n' - buffer = lines[-1] # Keep the last incomplete line in the buffer - - # Send the remaining buffer if it's not empty - if buffer.strip(): - full_response += buffer - yield buffer - - # If an image was found, send it as ImageResponse - if image_base64_url: - alt_text = "Generated Image" - image_response = ImageResponse(image_base64_url, alt=alt_text) - yield image_response + try: + async with session.post( + chat_url, + headers=headers_chat_combined, + data=data_chat, + proxy=proxy + ) as response_chat: + response_chat.raise_for_status() + pass + except ClientResponseError as e: + error_text = f"Error {e.status}: {e.message}" + try: + error_response = await e.response.text() + cleaned_error = cls.clean_response(error_response) + error_text += f" - {cleaned_error}" + except Exception: + pass + yield error_text + except Exception as e: + yield f"Unexpected error during /chat/{chat_id} request: {str(e)}" diff --git a/g4f/Provider/ChatGpt.py b/g4f/Provider/ChatGpt.py new file mode 100644 index 00000000..b5a78b9a --- /dev/null +++ b/g4f/Provider/ChatGpt.py @@ -0,0 +1,225 @@ +from __future__ import annotations + +from ..typing import Messages, CreateResult +from ..providers.base_provider import AbstractProvider, ProviderModelMixin + +import time, uuid, random, json +from requests import Session + +from .openai.new import ( + get_config, + get_answer_token, + process_turnstile, + get_requirements_token +) + +def format_conversation(messages: list): + conversation = [] + + for message in messages: + conversation.append({ + 'id': str(uuid.uuid4()), + 'author': { + 'role': message['role'], + }, + 'content': { + 'content_type': 'text', + 'parts': [ + message['content'], + ], + }, + 'metadata': { + 'serialization_metadata': { + 'custom_symbol_offsets': [], + }, + }, + 'create_time': round(time.time(), 3), + }) + + return conversation + +def init_session(user_agent): + session = Session() + + cookies = { + '_dd_s': '', + } + + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.8', + 'cache-control': 'no-cache', + 'pragma': 'no-cache', + 'priority': 'u=0, i', + 'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"', + 'sec-ch-ua-arch': '"arm"', + 'sec-ch-ua-bitness': '"64"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-model': '""', + 'sec-ch-ua-platform': '"macOS"', + 'sec-ch-ua-platform-version': '"14.4.0"', + 'sec-fetch-dest': 'document', + 'sec-fetch-mode': 'navigate', + 'sec-fetch-site': 'none', + 'sec-fetch-user': '?1', + 'upgrade-insecure-requests': '1', + 'user-agent': user_agent, + } + + session.get('https://chatgpt.com/', cookies=cookies, headers=headers) + + return session + +class ChatGpt(AbstractProvider, ProviderModelMixin): + label = "ChatGpt" + working = True + supports_message_history = True + supports_system_message = True + supports_stream = True + models = [ + 'gpt-4o', + 'gpt-4o-mini', + 'gpt-4', + 'gpt-4-turbo', + 'chatgpt-4o-latest', + ] + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + **kwargs + ) -> CreateResult: + + if model in [ + 'gpt-4o', + 'gpt-4o-mini', + 'gpt-4', + 'gpt-4-turbo', + 'chatgpt-4o-latest' + ]: + model = 'auto' + + elif model in [ + 'gpt-3.5-turbo' + ]: + model = 'text-davinci-002-render-sha' + + else: + raise ValueError(f"Invalid model: {model}") + + user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36' + session: Session = init_session(user_agent) + + config = get_config(user_agent) + pow_req = get_requirements_token(config) + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.8', + 'content-type': 'application/json', + 'oai-device-id': f'{uuid.uuid4()}', + 'oai-language': 'en-US', + 'origin': 'https://chatgpt.com', + 'priority': 'u=1, i', + 'referer': 'https://chatgpt.com/', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + 'sec-fetch-dest': 'empty', + 'sec-fetch-mode': 'cors', + 'sec-fetch-site': 'same-origin', + 'sec-gpc': '1', + 'user-agent': f'{user_agent}' + } + + response = session.post('https://chatgpt.com/backend-anon/sentinel/chat-requirements', + headers=headers, json={'p': pow_req}) + + if response.status_code != 200: + print(f"Request failed with status: {response.status_code}") + print(f"Response content: {response.content}") + return + + response_data = response.json() + if "detail" in response_data and "Unusual activity" in response_data["detail"]: + print(f"Blocked due to unusual activity: {response_data['detail']}") + return + + turnstile = response_data.get('turnstile', {}) + turnstile_required = turnstile.get('required') + pow_conf = response_data.get('proofofwork', {}) + + if turnstile_required: + turnstile_dx = turnstile.get('dx') + turnstile_token = process_turnstile(turnstile_dx, pow_req) + + headers = headers | { + 'openai-sentinel-turnstile-token' : turnstile_token, + 'openai-sentinel-chat-requirements-token': response_data.get('token'), + 'openai-sentinel-proof-token' : get_answer_token( + pow_conf.get('seed'), pow_conf.get('difficulty'), config + ) + } + + json_data = { + 'action': 'next', + 'messages': format_conversation(messages), + 'parent_message_id': str(uuid.uuid4()), + 'model': 'auto', + 'timezone_offset_min': -120, + 'suggestions': [ + 'Can you help me create a personalized morning routine that would help increase my productivity throughout the day? Start by asking me about my current habits and what activities energize me in the morning.', + 'Could you help me plan a relaxing day that focuses on activities for rejuvenation? To start, can you ask me what my favorite forms of relaxation are?', + 'I have a photoshoot tomorrow. Can you recommend me some colors and outfit options that will look good on camera?', + 'Make up a 5-sentence story about "Sharky", a tooth-brushing shark superhero. Make each sentence a bullet point.', + ], + 'history_and_training_disabled': False, + 'conversation_mode': { + 'kind': 'primary_assistant', + }, + 'force_paragen': False, + 'force_paragen_model_slug': '', + 'force_nulligen': False, + 'force_rate_limit': False, + 'reset_rate_limits': False, + 'websocket_request_id': str(uuid.uuid4()), + 'system_hints': [], + 'force_use_sse': True, + 'conversation_origin': None, + 'client_contextual_info': { + 'is_dark_mode': True, + 'time_since_loaded': random.randint(22,33), + 'page_height': random.randint(600, 900), + 'page_width': random.randint(500, 800), + 'pixel_ratio': 2, + 'screen_height': random.randint(800, 1200), + 'screen_width': random.randint(1200, 2000), + }, + } + + time.sleep(2) + + response = session.post('https://chatgpt.com/backend-anon/conversation', + headers=headers, json=json_data, stream=True) + + replace = '' + for line in response.iter_lines(): + if line: + decoded_line = line.decode() + print(f"Received line: {decoded_line}") + if decoded_line.startswith('data:'): + json_string = decoded_line[6:] + if json_string.strip(): + try: + data = json.loads(json_string) + except json.JSONDecodeError as e: + print(f"Error decoding JSON: {e}, content: {json_string}") + continue + + if data.get('message').get('author').get('role') == 'assistant': + tokens = (data.get('message').get('content').get('parts')[0]) + + yield tokens.replace(replace, '') + + replace = tokens diff --git a/g4f/Provider/ChatGptEs.py b/g4f/Provider/ChatGptEs.py new file mode 100644 index 00000000..a060ecb1 --- /dev/null +++ b/g4f/Provider/ChatGptEs.py @@ -0,0 +1,84 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import os +import json +import re + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class ChatGptEs(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://chatgpt.es" + api_endpoint = "https://chatgpt.es/wp-admin/admin-ajax.php" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o' + models = ['gpt-4o', 'gpt-4o-mini', 'chatgpt-4o-latest'] + + model_aliases = { + "gpt-4o": "chatgpt-4o-latest", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "authority": "chatgpt.es", + "accept": "application/json", + "origin": cls.url, + "referer": f"{cls.url}/chat", + "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + } + + async with ClientSession(headers=headers) as session: + initial_response = await session.get(cls.url) + nonce_ = re.findall(r'data-nonce="(.+?)"', await initial_response.text())[0] + post_id = re.findall(r'data-post-id="(.+?)"', await initial_response.text())[0] + + conversation_history = [ + "Human: strictly respond in the same language as my prompt, preferably English" + ] + + for message in messages[:-1]: + if message['role'] == "user": + conversation_history.append(f"Human: {message['content']}") + else: + conversation_history.append(f"AI: {message['content']}") + + payload = { + '_wpnonce': nonce_, + 'post_id': post_id, + 'url': cls.url, + 'action': 'wpaicg_chat_shortcode_message', + 'message': messages[-1]['content'], + 'bot_id': '0', + 'chatbot_identity': 'shortcode', + 'wpaicg_chat_client_id': os.urandom(5).hex(), + 'wpaicg_chat_history': json.dumps(conversation_history) + } + + async with session.post(cls.api_endpoint, headers=headers, data=payload) as response: + response.raise_for_status() + result = await response.json() + yield result['data'] diff --git a/g4f/Provider/ChatHub.py b/g4f/Provider/ChatHub.py new file mode 100644 index 00000000..3b762687 --- /dev/null +++ b/g4f/Provider/ChatHub.py @@ -0,0 +1,84 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class ChatHub(AsyncGeneratorProvider, ProviderModelMixin): + label = "ChatHub" + url = "https://app.chathub.gg" + api_endpoint = "https://app.chathub.gg/api/v3/chat/completions" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'meta/llama3.1-8b' + models = [ + 'meta/llama3.1-8b', + 'mistral/mixtral-8x7b', + 'google/gemma-2', + 'perplexity/sonar-online', + ] + + model_aliases = { + "llama-3.1-8b": "meta/llama3.1-8b", + "mixtral-8x7b": "mistral/mixtral-8x7b", + "gemma-2": "google/gemma-2", + "sonar-online": "perplexity/sonar-online", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'accept': '*/*', + 'accept-language': 'en-US,en;q=0.9', + 'content-type': 'application/json', + 'origin': cls.url, + 'referer': f"{cls.url}/chat/cloud-llama3.1-8b", + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36', + 'x-app-id': 'web' + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + "model": model, + "messages": [{"role": "user", "content": prompt}], + "tools": [] + } + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8') + if decoded_line.startswith('data:'): + try: + data = json.loads(decoded_line[5:]) + if data['type'] == 'text-delta': + yield data['textDelta'] + elif data['type'] == 'done': + break + except json.JSONDecodeError: + continue diff --git a/g4f/Provider/Chatgpt4Online.py b/g4f/Provider/Chatgpt4Online.py index 8c058fdc..627facf6 100644 --- a/g4f/Provider/Chatgpt4Online.py +++ b/g4f/Provider/Chatgpt4Online.py @@ -12,13 +12,15 @@ class Chatgpt4Online(AsyncGeneratorProvider): url = "https://chatgpt4online.org" api_endpoint = "/wp-json/mwai-ui/v1/chats/submit" working = True - supports_gpt_4 = True + + default_model = 'gpt-4' + models = [default_model] async def get_nonce(headers: dict) -> str: async with ClientSession(headers=headers) as session: async with session.post(f"https://chatgpt4online.org/wp-json/mwai/v1/start_session") as response: return (await response.json())["restNonce"] - + @classmethod async def create_async_generator( cls, diff --git a/g4f/Provider/Chatgpt4o.py b/g4f/Provider/Chatgpt4o.py index f3dc8a15..7730fc84 100644 --- a/g4f/Provider/Chatgpt4o.py +++ b/g4f/Provider/Chatgpt4o.py @@ -9,11 +9,16 @@ from .helper import format_prompt class Chatgpt4o(AsyncProvider, ProviderModelMixin): url = "https://chatgpt4o.one" - supports_gpt_4 = True working = True _post_id = None _nonce = None - default_model = 'gpt-4o' + default_model = 'gpt-4o-mini-2024-07-18' + models = [ + 'gpt-4o-mini-2024-07-18', + ] + model_aliases = { + "gpt-4o-mini": "gpt-4o-mini-2024-07-18", + } @classmethod diff --git a/g4f/Provider/ChatgptFree.py b/g4f/Provider/ChatgptFree.py index 95efa865..d2837594 100644 --- a/g4f/Provider/ChatgptFree.py +++ b/g4f/Provider/ChatgptFree.py @@ -10,7 +10,6 @@ from .helper import format_prompt class ChatgptFree(AsyncGeneratorProvider, ProviderModelMixin): url = "https://chatgptfree.ai" - supports_gpt_4 = True working = True _post_id = None _nonce = None diff --git a/g4f/Provider/ChatifyAI.py b/g4f/Provider/ChatifyAI.py new file mode 100644 index 00000000..7e43b065 --- /dev/null +++ b/g4f/Provider/ChatifyAI.py @@ -0,0 +1,79 @@ +from __future__ import annotations + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class ChatifyAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://chatify-ai.vercel.app" + api_endpoint = "https://chatify-ai.vercel.app/api/chat" + working = True + supports_stream = False + supports_system_message = True + supports_message_history = True + + default_model = 'llama-3.1' + models = [default_model] + model_aliases = { + "llama-3.1-8b": "llama-3.1", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases.get(model, cls.default_model) + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": cls.url, + "pragma": "no-cache", + "priority": "u=1, i", + "referer": f"{cls.url}/", + "sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36" + } + async with ClientSession(headers=headers) as session: + data = { + "messages": [{"role": "user", "content": format_prompt(messages)}] + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_text = await response.text() + + filtered_response = cls.filter_response(response_text) + yield filtered_response + + @staticmethod + def filter_response(response_text: str) -> str: + parts = response_text.split('"') + + text_parts = parts[1::2] + + clean_text = ''.join(text_parts) + + return clean_text diff --git a/g4f/Provider/Cloudflare.py b/g4f/Provider/Cloudflare.py new file mode 100644 index 00000000..e78bbcd0 --- /dev/null +++ b/g4f/Provider/Cloudflare.py @@ -0,0 +1,212 @@ +from __future__ import annotations + +import asyncio +import json +import uuid +import cloudscraper +from typing import AsyncGenerator +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class Cloudflare(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://playground.ai.cloudflare.com" + api_endpoint = "https://playground.ai.cloudflare.com/api/inference" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = '@cf/meta/llama-3.1-8b-instruct' + models = [ + '@cf/deepseek-ai/deepseek-math-7b-instruct', # Specific answer + + + '@cf/thebloke/discolm-german-7b-v1-awq', + + + '@cf/tiiuae/falcon-7b-instruct', # Specific answer + + + '@hf/google/gemma-7b-it', + + + '@cf/meta/llama-2-7b-chat-fp16', + '@cf/meta/llama-2-7b-chat-int8', + + '@cf/meta/llama-3-8b-instruct', + '@cf/meta/llama-3-8b-instruct-awq', + default_model, + '@hf/meta-llama/meta-llama-3-8b-instruct', + + '@cf/meta/llama-3.1-8b-instruct-awq', + '@cf/meta/llama-3.1-8b-instruct-fp8', + '@cf/meta/llama-3.2-11b-vision-instruct', + '@cf/meta/llama-3.2-1b-instruct', + '@cf/meta/llama-3.2-3b-instruct', + + '@cf/mistral/mistral-7b-instruct-v0.1', + '@hf/mistral/mistral-7b-instruct-v0.2', + + '@cf/openchat/openchat-3.5-0106', + + '@cf/microsoft/phi-2', + + '@cf/qwen/qwen1.5-0.5b-chat', + '@cf/qwen/qwen1.5-1.8b-chat', + '@cf/qwen/qwen1.5-14b-chat-awq', + '@cf/qwen/qwen1.5-7b-chat-awq', + + '@cf/defog/sqlcoder-7b-2', # Specific answer + + '@cf/tinyllama/tinyllama-1.1b-chat-v1.0', + + '@cf/fblgit/una-cybertron-7b-v2-bf16', + ] + + model_aliases = { + "german-7b-v1": "@cf/thebloke/discolm-german-7b-v1-awq", + + + "gemma-7b": "@hf/google/gemma-7b-it", + + + "llama-2-7b": "@cf/meta/llama-2-7b-chat-fp16", + "llama-2-7b": "@cf/meta/llama-2-7b-chat-int8", + + "llama-3-8b": "@cf/meta/llama-3-8b-instruct", + "llama-3-8b": "@cf/meta/llama-3-8b-instruct-awq", + "llama-3-8b": "@cf/meta/llama-3.1-8b-instruct", + "llama-3-8b": "@hf/meta-llama/meta-llama-3-8b-instruct", + + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-awq", + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-fp8", + "llama-3.1-8b": "@cf/meta/llama-3.1-8b-instruct-fp8", + + "llama-3.2-11b": "@cf/meta/llama-3.2-11b-vision-instruct", + "llama-3.2-1b": "@cf/meta/llama-3.2-1b-instruct", + "llama-3.2-3b": "@cf/meta/llama-3.2-3b-instruct", + + + "mistral-7b": "@cf/mistral/mistral-7b-instruct-v0.1", + "mistral-7b": "@hf/mistral/mistral-7b-instruct-v0.2", + + + "openchat-3.5": "@cf/openchat/openchat-3.5-0106", + + + "phi-2": "@cf/microsoft/phi-2", + + + "qwen-1.5-0.5b": "@cf/qwen/qwen1.5-0.5b-chat", + "qwen-1.5-1.8b": "@cf/qwen/qwen1.5-1.8b-chat", + "qwen-1.5-14b": "@cf/qwen/qwen1.5-14b-chat-awq", + "qwen-1.5-7b": "@cf/qwen/qwen1.5-7b-chat-awq", + + + "tinyllama-1.1b": "@cf/tinyllama/tinyllama-1.1b-chat-v1.0", + + + "cybertron-7b": "@cf/fblgit/una-cybertron-7b-v2-bf16", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + max_tokens: str = 2048, + stream: bool = True, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept': 'text/event-stream', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Content-Type': 'application/json', + 'Origin': cls.url, + 'Pragma': 'no-cache', + 'Referer': f'{cls.url}/', + 'Sec-Ch-Ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + 'Sec-Ch-Ua-Mobile': '?0', + 'Sec-Ch-Ua-Platform': '"Linux"', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36', + } + + cookies = { + '__cf_bm': uuid.uuid4().hex, + } + + scraper = cloudscraper.create_scraper() + + prompt = format_prompt(messages) + data = { + "messages": [ + {"role": "system", "content": "You are a helpful assistant"}, + {"role": "user", "content": prompt} + ], + "lora": None, + "model": model, + "max_tokens": max_tokens, + "stream": stream + } + + max_retries = 3 + for attempt in range(max_retries): + try: + response = scraper.post( + cls.api_endpoint, + headers=headers, + cookies=cookies, + json=data, + stream=True, + proxies={'http': proxy, 'https': proxy} if proxy else None + ) + + if response.status_code == 403: + await asyncio.sleep(2 ** attempt) + continue + + response.raise_for_status() + + for line in response.iter_lines(): + if line.startswith(b'data: '): + if line == b'data: [DONE]': + break + try: + content = json.loads(line[6:].decode('utf-8'))['response'] + yield content + except Exception: + continue + break + except Exception as e: + if attempt == max_retries - 1: + raise + + @classmethod + async def create_async( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> str: + full_response = "" + async for response in cls.create_async_generator(model, messages, proxy, **kwargs): + full_response += response + return full_response diff --git a/g4f/Provider/CodeNews.py b/g4f/Provider/CodeNews.py deleted file mode 100644 index 05ec7a45..00000000 --- a/g4f/Provider/CodeNews.py +++ /dev/null @@ -1,94 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession -from asyncio import sleep - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class CodeNews(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://codenews.cc" - api_endpoint = "https://codenews.cc/chatxyz13" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = False - supports_stream = True - supports_system_message = False - supports_message_history = False - - default_model = 'free_gpt' - models = ['free_gpt', 'gpt-4o-mini', 'deepseek-coder', 'chatpdf'] - - model_aliases = { - "glm-4": "free_gpt", - "gpt-3.5-turbo": "chatpdf", - "deepseek": "deepseek-coder", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - elif model in cls.model_aliases: - return cls.model_aliases[model] - else: - return cls.default_model - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - model = cls.get_model(model) - - headers = { - "accept": "application/json, text/javascript, */*; q=0.01", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/x-www-form-urlencoded; charset=UTF-8", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/chatgpt", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - "x-requested-with": "XMLHttpRequest", - } - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "chatgpt_input": prompt, - "qa_type2": model, - "chatgpt_version_value": "20240804", - "enable_web_search": "0", - "enable_agent": "0", - "dy_video_text_extract": "0", - "enable_summary": "0", - } - async with session.post(cls.api_endpoint, data=data, proxy=proxy) as response: - response.raise_for_status() - json_data = await response.json() - chat_id = json_data["data"]["id"] - - headers["content-type"] = "application/x-www-form-urlencoded; charset=UTF-8" - data = {"current_req_count": "2"} - - while True: - async with session.post(f"{cls.url}/chat_stream", headers=headers, data=data, proxy=proxy) as response: - response.raise_for_status() - json_data = await response.json() - if json_data["data"]: - yield json_data["data"] - break - else: - await sleep(1) # Затримка перед наступним запитом diff --git a/g4f/Provider/DDG.py b/g4f/Provider/DDG.py index c8c36fc9..43cc39c0 100644 --- a/g4f/Provider/DDG.py +++ b/g4f/Provider/DDG.py @@ -2,115 +2,107 @@ from __future__ import annotations import json import aiohttp -import asyncio -from typing import Optional -import base64 +from aiohttp import ClientSession -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import get_connector from ..typing import AsyncResult, Messages -from ..requests.raise_for_status import raise_for_status -from ..providers.conversation import BaseConversation +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + class DDG(AsyncGeneratorProvider, ProviderModelMixin): - url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9haWNoYXQ=").decode("utf-8") + url = "https://duckduckgo.com" + api_endpoint = "https://duckduckgo.com/duckchat/v1/chat" working = True - supports_gpt_35_turbo = True + supports_stream = True + supports_system_message = True supports_message_history = True default_model = "gpt-4o-mini" - models = ["gpt-4o-mini", "claude-3-haiku-20240307", "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", "mistralai/Mixtral-8x7B-Instruct-v0.1"] + models = [ + "gpt-4o-mini", + "claude-3-haiku-20240307", + "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", + "mistralai/Mixtral-8x7B-Instruct-v0.1" + ] model_aliases = { "claude-3-haiku": "claude-3-haiku-20240307", "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1" } - # Obfuscated URLs and headers - status_url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9kdWNrY2hhdC92MS9zdGF0dXM=").decode("utf-8") - chat_url = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS9kdWNrY2hhdC92MS9jaGF0").decode("utf-8") - referer = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS8=").decode("utf-8") - origin = base64.b64decode("aHR0cHM6Ly9kdWNrZHVja2dvLmNvbQ==").decode("utf-8") - - user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36' - headers = { - 'User-Agent': user_agent, - 'Accept': 'text/event-stream', - 'Accept-Language': 'en-US,en;q=0.5', - 'Accept-Encoding': 'gzip, deflate, br, zstd', - 'Referer': referer, - 'Content-Type': 'application/json', - 'Origin': origin, - 'Connection': 'keep-alive', - 'Cookie': 'dcm=3', - 'Sec-Fetch-Dest': 'empty', - 'Sec-Fetch-Mode': 'cors', - 'Sec-Fetch-Site': 'same-origin', - 'Pragma': 'no-cache', - 'TE': 'trailers' - } + @classmethod + def get_model(cls, model: str) -> str: + return cls.model_aliases.get(model, model) if model in cls.model_aliases else cls.default_model @classmethod - async def get_vqd(cls, session: aiohttp.ClientSession) -> Optional[str]: - try: - async with session.get(cls.status_url, headers={"x-vqd-accept": "1"}) as response: - await raise_for_status(response) - return response.headers.get("x-vqd-4") - except Exception as e: - print(f"Error getting VQD: {e}") - return None + async def get_vqd(cls): + status_url = "https://duckduckgo.com/duckchat/v1/status" + + headers = { + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + 'Accept': 'text/event-stream', + 'x-vqd-accept': '1' + } + + async with aiohttp.ClientSession() as session: + try: + async with session.get(status_url, headers=headers) as response: + if response.status == 200: + return response.headers.get("x-vqd-4") + else: + print(f"Error: Status code {response.status}") + return None + except Exception as e: + print(f"Error getting VQD: {e}") + return None @classmethod async def create_async_generator( cls, model: str, messages: Messages, + conversation: dict = None, proxy: str = None, - connector: aiohttp.BaseConnector = None, - conversation: Conversation = None, - return_conversation: bool = False, **kwargs ) -> AsyncResult: - async with aiohttp.ClientSession(headers=cls.headers, connector=get_connector(connector, proxy)) as session: - vqd_4 = None - if conversation is not None and len(messages) > 1: - vqd_4 = conversation.vqd_4 - messages = [*conversation.messages, messages[-2], messages[-1]] - else: - for _ in range(3): # Try up to 3 times to get a valid VQD - vqd_4 = await cls.get_vqd(session) - if vqd_4: - break - await asyncio.sleep(1) # Wait a bit before retrying - - if not vqd_4: - raise Exception("Failed to obtain a valid VQD token") - - messages = [messages[-1]] # Only use the last message for new conversations - - payload = { - 'model': cls.get_model(model), - 'messages': [{'role': m['role'], 'content': m['content']} for m in messages] + model = cls.get_model(model) + + headers = { + 'accept': 'text/event-stream', + 'content-type': 'application/json', + 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + } + + vqd = conversation.get('vqd') if conversation else await cls.get_vqd() + if not vqd: + raise Exception("Failed to obtain VQD token") + + headers['x-vqd-4'] = vqd + + if conversation: + message_history = conversation.get('messages', []) + message_history.append({"role": "user", "content": format_prompt(messages)}) + else: + message_history = [{"role": "user", "content": format_prompt(messages)}] + + async with ClientSession(headers=headers) as session: + data = { + "model": model, + "messages": message_history } - - async with session.post(cls.chat_url, json=payload, headers={"x-vqd-4": vqd_4}) as response: - await raise_for_status(response) - if return_conversation: - yield Conversation(vqd_4, messages) - - async for line in response.content: - if line.startswith(b"data: "): - chunk = line[6:] - if chunk.startswith(b"[DONE]"): - break - try: - data = json.loads(chunk) - if "message" in data and data["message"]: - yield data["message"] - except json.JSONDecodeError: - print(f"Failed to decode JSON: {chunk}") -class Conversation(BaseConversation): - def __init__(self, vqd_4: str, messages: Messages) -> None: - self.vqd_4 = vqd_4 - self.messages = messages + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8') + if decoded_line.startswith('data: '): + json_str = decoded_line[6:] + if json_str == '[DONE]': + break + try: + json_data = json.loads(json_str) + if 'message' in json_data: + yield json_data['message'] + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/DarkAI.py b/g4f/Provider/DarkAI.py new file mode 100644 index 00000000..6ffb615e --- /dev/null +++ b/g4f/Provider/DarkAI.py @@ -0,0 +1,85 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class DarkAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://www.aiuncensored.info" + api_endpoint = "https://darkai.foundation/chat" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'gpt-4o' + models = [ + default_model, # Uncensored + 'gpt-3.5-turbo', # Uncensored + 'llama-3-70b', # Uncensored + 'llama-3-405b', + ] + + model_aliases = { + "llama-3.1-70b": "llama-3-70b", + "llama-3.1-405b": "llama-3-405b", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "accept": "text/event-stream", + "content-type": "application/json", + "origin": "https://www.aiuncensored.info", + "referer": "https://www.aiuncensored.info/", + "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" + } + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + "query": prompt, + "model": model, + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + full_text = "" + async for chunk in response.content: + if chunk: + try: + chunk_str = chunk.decode().strip() + if chunk_str.startswith('data: '): + chunk_data = json.loads(chunk_str[6:]) + if chunk_data['event'] == 'text-chunk': + full_text += chunk_data['data']['text'] + elif chunk_data['event'] == 'stream-end': + if full_text: + yield full_text.strip() + return + except json.JSONDecodeError: + print(f"Failed to decode JSON: {chunk_str}") + except Exception as e: + print(f"Error processing chunk: {e}") + + if full_text: + yield full_text.strip() diff --git a/g4f/Provider/DeepInfraChat.py b/g4f/Provider/DeepInfraChat.py new file mode 100644 index 00000000..b8cc6ab8 --- /dev/null +++ b/g4f/Provider/DeepInfraChat.py @@ -0,0 +1,142 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import json + +from ..typing import AsyncResult, Messages, ImageType +from ..image import to_data_uri +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://deepinfra.com/chat" + api_endpoint = "https://api.deepinfra.com/v1/openai/chat/completions" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct' + models = [ + 'meta-llama/Meta-Llama-3.1-405B-Instruct', + 'meta-llama/Meta-Llama-3.1-70B-Instruct', + 'meta-llama/Meta-Llama-3.1-8B-Instruct', + 'mistralai/Mixtral-8x22B-Instruct-v0.1', + 'mistralai/Mixtral-8x7B-Instruct-v0.1', + 'microsoft/WizardLM-2-8x22B', + 'microsoft/WizardLM-2-7B', + 'Qwen/Qwen2-72B-Instruct', + 'microsoft/Phi-3-medium-4k-instruct', + 'google/gemma-2-27b-it', + 'openbmb/MiniCPM-Llama3-V-2_5', # Image upload is available + 'mistralai/Mistral-7B-Instruct-v0.3', + 'lizpreciatior/lzlv_70b_fp16_hf', + 'openchat/openchat-3.6-8b', + 'Phind/Phind-CodeLlama-34B-v2', + 'cognitivecomputations/dolphin-2.9.1-llama-3-70b', + ] + model_aliases = { + "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct", + "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", + "llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct", + "mixtral-8x22b": "mistralai/Mixtral-8x22B-Instruct-v0.1", + "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", + "wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B", + "wizardlm-2-7b": "microsoft/WizardLM-2-7B", + "qwen-2-72b": "Qwen/Qwen2-72B-Instruct", + "phi-3-medium-4k": "microsoft/Phi-3-medium-4k-instruct", + "gemma-2b-27b": "google/gemma-2-27b-it", + "minicpm-llama-3-v2.5": "openbmb/MiniCPM-Llama3-V-2_5", # Image upload is available + "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", + "lzlv-70b": "lizpreciatior/lzlv_70b_fp16_hf", + "openchat-3.6-8b": "openchat/openchat-3.6-8b", + "phind-codellama-34b-v2": "Phind/Phind-CodeLlama-34B-v2", + "dolphin-2.9.1-llama-3-70b": "cognitivecomputations/dolphin-2.9.1-llama-3-70b", + } + + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + image: ImageType = None, + image_name: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Content-Type': 'application/json', + 'Origin': 'https://deepinfra.com', + 'Pragma': 'no-cache', + 'Referer': 'https://deepinfra.com/', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-site', + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36', + 'X-Deepinfra-Source': 'web-embed', + 'accept': 'text/event-stream', + 'sec-ch-ua': '"Not;A=Brand";v="24", "Chromium";v="128"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"', + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + 'model': model, + 'messages': [ + {'role': 'system', 'content': 'Be a helpful assistant'}, + {'role': 'user', 'content': prompt} + ], + 'stream': True + } + + if model == 'openbmb/MiniCPM-Llama3-V-2_5' and image is not None: + data['messages'][-1]['content'] = [ + { + 'type': 'image_url', + 'image_url': { + 'url': to_data_uri(image) + } + }, + { + 'type': 'text', + 'text': messages[-1]['content'] + } + ] + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for line in response.content: + if line: + decoded_line = line.decode('utf-8').strip() + if decoded_line.startswith('data:'): + json_part = decoded_line[5:].strip() + if json_part == '[DONE]': + break + try: + data = json.loads(json_part) + choices = data.get('choices', []) + if choices: + delta = choices[0].get('delta', {}) + content = delta.get('content', '') + if content: + yield content + except json.JSONDecodeError: + print(f"JSON decode error: {json_part}") diff --git a/g4f/Provider/DeepInfraImage.py b/g4f/Provider/DeepInfraImage.py index 46a5c2e2..cee608ce 100644 --- a/g4f/Provider/DeepInfraImage.py +++ b/g4f/Provider/DeepInfraImage.py @@ -11,7 +11,8 @@ class DeepInfraImage(AsyncGeneratorProvider, ProviderModelMixin): url = "https://deepinfra.com" parent = "DeepInfra" working = True - default_model = 'stability-ai/sdxl' + needs_auth = True + default_model = '' image_models = [default_model] @classmethod @@ -76,4 +77,4 @@ class DeepInfraImage(AsyncGeneratorProvider, ProviderModelMixin): if not images: raise RuntimeError(f"Response: {data}") images = images[0] if len(images) == 1 else images - return ImageResponse(images, prompt)
\ No newline at end of file + return ImageResponse(images, prompt) diff --git a/g4f/Provider/Editee.py b/g4f/Provider/Editee.py new file mode 100644 index 00000000..8ac2324a --- /dev/null +++ b/g4f/Provider/Editee.py @@ -0,0 +1,77 @@ +from __future__ import annotations + +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class Editee(AsyncGeneratorProvider, ProviderModelMixin): + label = "Editee" + url = "https://editee.com" + api_endpoint = "https://editee.com/submit/chatgptfree" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'claude' + models = ['claude', 'gpt4', 'gemini' 'mistrallarge'] + + model_aliases = { + "claude-3.5-sonnet": "claude", + "gpt-4o": "gpt4", + "gemini-pro": "gemini", + "mistral-large": "mistrallarge", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Accept": "application/json, text/plain, */*", + "Accept-Language": "en-US,en;q=0.9", + "Cache-Control": "no-cache", + "Content-Type": "application/json", + "Origin": cls.url, + "Pragma": "no-cache", + "Priority": "u=1, i", + "Referer": f"{cls.url}/chat-gpt", + "Sec-CH-UA": '"Chromium";v="129", "Not=A?Brand";v="8"', + "Sec-CH-UA-Mobile": '?0', + "Sec-CH-UA-Platform": '"Linux"', + "Sec-Fetch-Dest": 'empty', + "Sec-Fetch-Mode": 'cors', + "Sec-Fetch-Site": 'same-origin', + "User-Agent": 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36', + "X-Requested-With": 'XMLHttpRequest', + } + + async with ClientSession(headers=headers) as session: + prompt = format_prompt(messages) + data = { + "user_input": prompt, + "context": " ", + "template_id": "", + "selected_model": model + } + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + response_data = await response.json() + yield response_data['text'] diff --git a/g4f/Provider/FlowGpt.py b/g4f/Provider/FlowGpt.py index d823a7ab..1a45997b 100644 --- a/g4f/Provider/FlowGpt.py +++ b/g4f/Provider/FlowGpt.py @@ -12,8 +12,7 @@ from ..requests.raise_for_status import raise_for_status class FlowGpt(AsyncGeneratorProvider, ProviderModelMixin): url = "https://flowgpt.com/chat" - working = True - supports_gpt_35_turbo = True + working = False supports_message_history = True supports_system_message = True default_model = "gpt-3.5-turbo" diff --git a/g4f/Provider/FluxAirforce.py b/g4f/Provider/FluxAirforce.py deleted file mode 100644 index fe003a61..00000000 --- a/g4f/Provider/FluxAirforce.py +++ /dev/null @@ -1,82 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, ClientResponseError -from urllib.parse import urlencode -import io - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..image import ImageResponse, is_accepted_format - -class FluxAirforce(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://flux.api.airforce/" - api_endpoint = "https://api.airforce/v1/imagine2" - working = True - default_model = 'flux-realism' - models = [ - 'flux', - 'flux-realism', - 'flux-anime', - 'flux-3d', - 'flux-disney' - ] - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "accept": "*/*", - "accept-language": "en-US,en;q=0.9", - "origin": "https://flux.api.airforce", - "priority": "u=1, i", - "referer": "https://flux.api.airforce/", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" - } - - prompt = messages[-1]['content'] if messages else "" - - params = { - "prompt": prompt, - "size": kwargs.get("size", "1:1"), - "seed": kwargs.get("seed"), - "model": model - } - - params = {k: v for k, v in params.items() if v is not None} - - try: - async with ClientSession(headers=headers) as session: - async with session.get(f"{cls.api_endpoint}", params=params, proxy=proxy) as response: - response.raise_for_status() - - content = await response.read() - - if response.content_type.startswith('image/'): - image_url = str(response.url) - yield ImageResponse(image_url, prompt) - else: - try: - text = content.decode('utf-8', errors='ignore') - yield f"Error: {text}" - except Exception as decode_error: - yield f"Error: Unable to decode response - {str(decode_error)}" - - except ClientResponseError as e: - yield f"Error: HTTP {e.status}: {e.message}" - except Exception as e: - yield f"Unexpected error: {str(e)}" - - finally: - if not session.closed: - await session.close() diff --git a/g4f/Provider/FreeNetfly.py b/g4f/Provider/FreeNetfly.py index d0543176..ada5d51a 100644 --- a/g4f/Provider/FreeNetfly.py +++ b/g4f/Provider/FreeNetfly.py @@ -13,8 +13,6 @@ class FreeNetfly(AsyncGeneratorProvider, ProviderModelMixin): url = "https://free.netfly.top" api_endpoint = "/api/openai/v1/chat/completions" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = 'gpt-3.5-turbo' models = [ 'gpt-3.5-turbo', diff --git a/g4f/Provider/GPROChat.py b/g4f/Provider/GPROChat.py new file mode 100644 index 00000000..a33c9571 --- /dev/null +++ b/g4f/Provider/GPROChat.py @@ -0,0 +1,67 @@ +from __future__ import annotations +import hashlib +import time +from aiohttp import ClientSession +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class GPROChat(AsyncGeneratorProvider, ProviderModelMixin): + label = "GPROChat" + url = "https://gprochat.com" + api_endpoint = "https://gprochat.com/api/generate" + working = True + supports_stream = True + supports_message_history = True + default_model = 'gemini-pro' + + @staticmethod + def generate_signature(timestamp: int, message: str) -> str: + secret_key = "2BC120D4-BB36-1B60-26DE-DB630472A3D8" + hash_input = f"{timestamp}:{message}:{secret_key}" + signature = hashlib.sha256(hash_input.encode('utf-8')).hexdigest() + return signature + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + timestamp = int(time.time() * 1000) + prompt = format_prompt(messages) + sign = cls.generate_signature(timestamp, prompt) + + headers = { + "accept": "*/*", + "origin": cls.url, + "referer": f"{cls.url}/", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36", + "content-type": "text/plain;charset=UTF-8" + } + + data = { + "messages": [{"role": "user", "parts": [{"text": prompt}]}], + "time": timestamp, + "pass": None, + "sign": sign + } + + async with ClientSession(headers=headers) as session: + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() + async for chunk in response.content.iter_any(): + if chunk: + yield chunk.decode() diff --git a/g4f/Provider/GeminiPro.py b/g4f/Provider/GeminiPro.py index b225c26c..06bf69ee 100644 --- a/g4f/Provider/GeminiPro.py +++ b/g4f/Provider/GeminiPro.py @@ -54,6 +54,7 @@ class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin): "parts": [{"text": message["content"]}] } for message in messages + if message["role"] != "system" ] if image is not None: image = to_bytes(image) @@ -73,6 +74,13 @@ class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin): "topK": kwargs.get("top_k"), } } + system_prompt = "\n".join( + message["content"] + for message in messages + if message["role"] == "system" + ) + if system_prompt: + data["system_instruction"] = {"parts": {"text": system_prompt}} async with session.post(url, params=params, json=data) as response: if not response.ok: data = await response.json() diff --git a/g4f/Provider/GizAI.py b/g4f/Provider/GizAI.py new file mode 100644 index 00000000..127edc9e --- /dev/null +++ b/g4f/Provider/GizAI.py @@ -0,0 +1,151 @@ +from __future__ import annotations + +import json +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from ..image import ImageResponse +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + +class GizAI(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://app.giz.ai/assistant/" + api_endpoint = "https://app.giz.ai/api/data/users/inferenceServer.infer" + working = True + + supports_system_message = True + supports_message_history = True + + # Chat models + default_model = 'chat-gemini-flash' + chat_models = [ + default_model, + 'chat-gemini-pro', + 'chat-gpt4m', + 'chat-gpt4', + 'claude-sonnet', + 'claude-haiku', + 'llama-3-70b', + 'llama-3-8b', + 'mistral-large', + 'chat-o1-mini' + ] + + # Image models + image_models = [ + 'flux1', + 'sdxl', + 'sd', + 'sd35', + ] + + models = [*chat_models, *image_models] + + model_aliases = { + # Chat model aliases + "gemini-flash": "chat-gemini-flash", + "gemini-pro": "chat-gemini-pro", + "gpt-4o-mini": "chat-gpt4m", + "gpt-4o": "chat-gpt4", + "claude-3.5-sonnet": "claude-sonnet", + "claude-3-haiku": "claude-haiku", + "llama-3.1-70b": "llama-3-70b", + "llama-3.1-8b": "llama-3-8b", + "o1-mini": "chat-o1-mini", + # Image model aliases + "sd-1.5": "sd", + "sd-3.5": "sd35", + "flux-schnell": "flux1", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def is_image_model(cls, model: str) -> bool: + return model in cls.image_models + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Content-Type': 'application/json', + 'Origin': 'https://app.giz.ai', + 'Pragma': 'no-cache', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36', + 'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"' + } + + async with ClientSession() as session: + if cls.is_image_model(model): + # Image generation + prompt = messages[-1]["content"] + data = { + "model": model, + "input": { + "width": "1024", + "height": "1024", + "steps": 4, + "output_format": "webp", + "batch_size": 1, + "mode": "plan", + "prompt": prompt + } + } + async with session.post( + cls.api_endpoint, + headers=headers, + data=json.dumps(data), + proxy=proxy + ) as response: + response.raise_for_status() + response_data = await response.json() + if response_data.get('status') == 'completed' and response_data.get('output'): + for url in response_data['output']: + yield ImageResponse(images=url, alt="Generated Image") + else: + # Chat completion + data = { + "model": model, + "input": { + "messages": [ + { + "type": "human", + "content": format_prompt(messages) + } + ], + "mode": "plan" + }, + "noStream": True + } + async with session.post( + cls.api_endpoint, + headers=headers, + data=json.dumps(data), + proxy=proxy + ) as response: + response.raise_for_status() + result = await response.json() + yield result.get('output', '') diff --git a/g4f/Provider/GptTalkRu.py b/g4f/Provider/GptTalkRu.py deleted file mode 100644 index 6a59484f..00000000 --- a/g4f/Provider/GptTalkRu.py +++ /dev/null @@ -1,59 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, BaseConnector - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider -from .helper import get_random_string, get_connector -from ..requests import raise_for_status, get_args_from_browser, WebDriver -from ..webdriver import has_seleniumwire -from ..errors import MissingRequirementsError - -class GptTalkRu(AsyncGeneratorProvider): - url = "https://gpttalk.ru" - working = True - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - connector: BaseConnector = None, - webdriver: WebDriver = None, - **kwargs - ) -> AsyncResult: - if not model: - model = "gpt-3.5-turbo" - if not has_seleniumwire: - raise MissingRequirementsError('Install "selenium-wire" package') - args = get_args_from_browser(f"{cls.url}", webdriver) - args["headers"]["accept"] = "application/json, text/plain, */*" - async with ClientSession(connector=get_connector(connector, proxy), **args) as session: - async with session.get("https://gpttalk.ru/getToken") as response: - await raise_for_status(response) - public_key = (await response.json())["response"]["key"]["publicKey"] - random_string = get_random_string(8) - data = { - "model": model, - "modelType": 1, - "prompt": messages, - "responseType": "stream", - "security": { - "randomMessage": random_string, - "shifrText": encrypt(public_key, random_string) - } - } - async with session.post(f"{cls.url}/gpt2", json=data, proxy=proxy) as response: - await raise_for_status(response) - async for chunk in response.content.iter_any(): - yield chunk.decode(errors="ignore") - -def encrypt(public_key: str, value: str) -> str: - from Crypto.Cipher import PKCS1_v1_5 - from Crypto.PublicKey import RSA - import base64 - rsa_key = RSA.importKey(public_key) - cipher = PKCS1_v1_5.new(rsa_key) - return base64.b64encode(cipher.encrypt(value.encode())).decode()
\ No newline at end of file diff --git a/g4f/Provider/HuggingChat.py b/g4f/Provider/HuggingChat.py index 76c76a35..7ebbf570 100644 --- a/g4f/Provider/HuggingChat.py +++ b/g4f/Provider/HuggingChat.py @@ -1,6 +1,7 @@ from __future__ import annotations -import json, requests, re +import json +import requests from curl_cffi import requests as cf_reqs from ..typing import CreateResult, Messages @@ -12,26 +13,27 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): working = True supports_stream = True default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct" + models = [ 'meta-llama/Meta-Llama-3.1-70B-Instruct', - 'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8', - 'CohereForAI/c4ai-command-r-plus', - 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', - '01-ai/Yi-1.5-34B-Chat', - 'mistralai/Mistral-7B-Instruct-v0.3', - 'microsoft/Phi-3-mini-4k-instruct', + 'CohereForAI/c4ai-command-r-plus-08-2024', + 'Qwen/Qwen2.5-72B-Instruct', + 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF', + 'meta-llama/Llama-3.2-11B-Vision-Instruct', + 'NousResearch/Hermes-3-Llama-3.1-8B', + 'mistralai/Mistral-Nemo-Instruct-2407', + 'microsoft/Phi-3.5-mini-instruct', ] model_aliases = { "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8", - "command-r-plus": "CohereForAI/c4ai-command-r-plus", - "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", - "mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", - "yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat", - "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", - "phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct", + "command-r-plus": "CohereForAI/c4ai-command-r-plus-08-2024", + "qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct", + "nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", + "llama-3.2-11b": "meta-llama/Llama-3.2-11B-Vision-Instruct", + "hermes-3": "NousResearch/Hermes-3-Llama-3.1-8B", + "mistral-nemo": "mistralai/Mistral-Nemo-Instruct-2407", + "phi-3.5-mini": "microsoft/Phi-3.5-mini-instruct", } @classmethod @@ -72,17 +74,18 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36', } - print(model) json_data = { 'model': model, } response = session.post('https://huggingface.co/chat/conversation', json=json_data) - conversationId = response.json()['conversationId'] + if response.status_code != 200: + raise RuntimeError(f"Request failed with status code: {response.status_code}, response: {response.text}") - response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=01',) + conversationId = response.json().get('conversationId') + response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=11') - data: list = (response.json())["nodes"][1]["data"] + data: list = response.json()["nodes"][1]["data"] keys: list[int] = data[data[0]["messages"]] message_keys: dict = data[keys[0]] messageId: str = data[message_keys["id"]] @@ -123,22 +126,26 @@ class HuggingChat(AbstractProvider, ProviderModelMixin): files=files, ) - first_token = True + full_response = "" for line in response.iter_lines(): - line = json.loads(line) + if not line: + continue + try: + line = json.loads(line) + except json.JSONDecodeError as e: + print(f"Failed to decode JSON: {line}, error: {e}") + continue if "type" not in line: raise RuntimeError(f"Response: {line}") elif line["type"] == "stream": - token = line["token"] - if first_token: - token = token.lstrip().replace('\u0000', '') - first_token = False - else: - token = token.replace('\u0000', '') - - yield token + token = line["token"].replace('\u0000', '') + full_response += token elif line["type"] == "finalAnswer": break + + full_response = full_response.replace('<|im_end|', '').replace('\u0000', '').strip() + + yield full_response diff --git a/g4f/Provider/HuggingFace.py b/g4f/Provider/HuggingFace.py index 74957862..586e5f5f 100644 --- a/g4f/Provider/HuggingFace.py +++ b/g4f/Provider/HuggingFace.py @@ -9,33 +9,16 @@ from .helper import get_connector from ..errors import RateLimitError, ModelNotFoundError from ..requests.raise_for_status import raise_for_status +from .HuggingChat import HuggingChat + class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin): url = "https://huggingface.co/chat" working = True needs_auth = True supports_message_history = True - default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct" - models = [ - 'meta-llama/Meta-Llama-3.1-70B-Instruct', - 'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8', - 'CohereForAI/c4ai-command-r-plus', - 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', - '01-ai/Yi-1.5-34B-Chat', - 'mistralai/Mistral-7B-Instruct-v0.3', - 'microsoft/Phi-3-mini-4k-instruct', - ] - - model_aliases = { - "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8", - "command-r-plus": "CohereForAI/c4ai-command-r-plus", - "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", - "mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", - "yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat", - "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3", - "phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct", - } + default_model = HuggingChat.default_model + models = HuggingChat.models + model_aliases = HuggingChat.model_aliases @classmethod def get_model(cls, model: str) -> str: diff --git a/g4f/Provider/Koala.py b/g4f/Provider/Koala.py index 0e810083..0dd76b71 100644 --- a/g4f/Provider/Koala.py +++ b/g4f/Provider/Koala.py @@ -10,10 +10,10 @@ from .helper import get_random_string, get_connector from ..requests import raise_for_status class Koala(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://koala.sh" + url = "https://koala.sh/chat" + api_endpoint = "https://koala.sh/api/gpt/" working = True supports_message_history = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' @classmethod @@ -26,17 +26,17 @@ class Koala(AsyncGeneratorProvider, ProviderModelMixin): **kwargs: Any ) -> AsyncGenerator[Dict[str, Union[str, int, float, List[Dict[str, Any]], None]], None]: if not model: - model = "gpt-3.5-turbo" + model = "gpt-4o-mini" headers = { "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:122.0) Gecko/20100101 Firefox/122.0", "Accept": "text/event-stream", "Accept-Language": "de,en-US;q=0.7,en;q=0.3", "Accept-Encoding": "gzip, deflate, br", - "Referer": f"{cls.url}/chat", + "Referer": f"{cls.url}", "Flag-Real-Time-Data": "false", "Visitor-ID": get_random_string(20), - "Origin": cls.url, + "Origin": "https://koala.sh", "Alt-Used": "koala.sh", "Sec-Fetch-Dest": "empty", "Sec-Fetch-Mode": "cors", @@ -67,7 +67,7 @@ class Koala(AsyncGeneratorProvider, ProviderModelMixin): "model": model, } - async with session.post(f"{cls.url}/api/gpt/", json=data, proxy=proxy) as response: + async with session.post(f"{cls.api_endpoint}", json=data, proxy=proxy) as response: await raise_for_status(response) async for chunk in cls._parse_event_stream(response): yield chunk diff --git a/g4f/Provider/Liaobots.py b/g4f/Provider/Liaobots.py index 8a9f46b1..56f765de 100644 --- a/g4f/Provider/Liaobots.py +++ b/g4f/Provider/Liaobots.py @@ -9,6 +9,15 @@ from .helper import get_connector from ..requests import raise_for_status models = { + "gpt-3.5-turbo": { + "id": "gpt-3.5-turbo", + "name": "GPT-3.5-Turbo", + "model": "ChatGPT", + "provider": "OpenAI", + "maxLength": 48000, + "tokenLimit": 14000, + "context": "16K", + }, "gpt-4o-mini-free": { "id": "gpt-4o-mini-free", "name": "GPT-4o-Mini-Free", @@ -36,32 +45,41 @@ models = { "tokenLimit": 7800, "context": "8K", }, - "gpt-4-turbo-2024-04-09": { - "id": "gpt-4-turbo-2024-04-09", - "name": "GPT-4-Turbo", + "gpt-4o-2024-08-06": { + "id": "gpt-4o-2024-08-06", + "name": "GPT-4o", "model": "ChatGPT", "provider": "OpenAI", "maxLength": 260000, "tokenLimit": 126000, "context": "128K", }, - "gpt-4o-2024-08-06": { - "id": "gpt-4o-2024-08-06", - "name": "GPT-4o", + "gpt-4-turbo-2024-04-09": { + "id": "gpt-4-turbo-2024-04-09", + "name": "GPT-4-Turbo", "model": "ChatGPT", "provider": "OpenAI", "maxLength": 260000, "tokenLimit": 126000, "context": "128K", }, - "gpt-4-0613": { - "id": "gpt-4-0613", - "name": "GPT-4-0613", - "model": "ChatGPT", - "provider": "OpenAI", - "maxLength": 32000, - "tokenLimit": 7600, - "context": "8K", + "grok-2": { + "id": "grok-2", + "name": "Grok-2", + "model": "Grok", + "provider": "x.ai", + "maxLength": 400000, + "tokenLimit": 100000, + "context": "100K", + }, + "grok-2-mini": { + "id": "grok-2-mini", + "name": "Grok-2-mini", + "model": "Grok", + "provider": "x.ai", + "maxLength": 400000, + "tokenLimit": 100000, + "context": "100K", }, "claude-3-opus-20240229": { "id": "claude-3-opus-20240229", @@ -90,18 +108,18 @@ models = { "tokenLimit": 200000, "context": "200K", }, - "claude-3-sonnet-20240229": { - "id": "claude-3-sonnet-20240229", - "name": "Claude-3-Sonnet", + "claude-3-5-sonnet-20240620": { + "id": "claude-3-5-sonnet-20240620", + "name": "Claude-3.5-Sonnet", "model": "Claude", "provider": "Anthropic", "maxLength": 800000, "tokenLimit": 200000, "context": "200K", }, - "claude-3-5-sonnet-20240620": { - "id": "claude-3-5-sonnet-20240620", - "name": "Claude-3.5-Sonnet", + "claude-3-sonnet-20240229": { + "id": "claude-3-sonnet-20240229", + "name": "Claude-3-Sonnet", "model": "Claude", "provider": "Anthropic", "maxLength": 800000, @@ -126,17 +144,8 @@ models = { "tokenLimit": 200000, "context": "200K", }, - "gemini-1.0-pro-latest": { - "id": "gemini-1.0-pro-latest", - "name": "Gemini-Pro", - "model": "Gemini", - "provider": "Google", - "maxLength": 120000, - "tokenLimit": 30000, - "context": "32K", - }, - "gemini-1.5-flash-latest": { - "id": "gemini-1.5-flash-latest", + "gemini-1.5-flash-002": { + "id": "gemini-1.5-flash-002", "name": "Gemini-1.5-Flash-1M", "model": "Gemini", "provider": "Google", @@ -144,8 +153,8 @@ models = { "tokenLimit": 1000000, "context": "1024K", }, - "gemini-1.5-pro-latest": { - "id": "gemini-1.5-pro-latest", + "gemini-1.5-pro-002": { + "id": "gemini-1.5-pro-002", "name": "Gemini-1.5-Pro-1M", "model": "Gemini", "provider": "Google", @@ -161,28 +170,27 @@ class Liaobots(AsyncGeneratorProvider, ProviderModelMixin): working = True supports_message_history = True supports_system_message = True - supports_gpt_4 = True - default_model = "gpt-4o" + default_model = "gpt-3.5-turbo" models = list(models.keys()) model_aliases = { "gpt-4o-mini": "gpt-4o-mini-free", "gpt-4o": "gpt-4o-free", - "gpt-4-turbo": "gpt-4-turbo-2024-04-09", "gpt-4o": "gpt-4o-2024-08-06", + + "gpt-4-turbo": "gpt-4-turbo-2024-04-09", "gpt-4": "gpt-4-0613", "claude-3-opus": "claude-3-opus-20240229", "claude-3-opus": "claude-3-opus-20240229-aws", "claude-3-opus": "claude-3-opus-20240229-gcp", "claude-3-sonnet": "claude-3-sonnet-20240229", - "claude-3-5-sonnet": "claude-3-5-sonnet-20240620", + "claude-3.5-sonnet": "claude-3-5-sonnet-20240620", "claude-3-haiku": "claude-3-haiku-20240307", "claude-2.1": "claude-2.1", - "gemini-pro": "gemini-1.0-pro-latest", - "gemini-flash": "gemini-1.5-flash-latest", - "gemini-pro": "gemini-1.5-pro-latest", + "gemini-flash": "gemini-1.5-flash-002", + "gemini-pro": "gemini-1.5-pro-002", } _auth_code = "" diff --git a/g4f/Provider/LiteIcoding.py b/g4f/Provider/LiteIcoding.py deleted file mode 100644 index 69294a57..00000000 --- a/g4f/Provider/LiteIcoding.py +++ /dev/null @@ -1,113 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession, ClientResponseError -import re -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class LiteIcoding(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://lite.icoding.ink" - api_endpoint = "/api/v1/gpt/message" - working = True - supports_gpt_4 = True - default_model = "gpt-4o" - models = [ - 'gpt-4o', - 'gpt-4-turbo', - 'claude-3', - 'claude-3.5', - 'gemini-1.5', - ] - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "Accept": "*/*", - "Accept-Language": "en-US,en;q=0.9", - "Authorization": "Bearer aa3020ee873e40cb8b3f515a0708ebc4", - "Connection": "keep-alive", - "Content-Type": "application/json;charset=utf-8", - "DNT": "1", - "Origin": cls.url, - "Referer": f"{cls.url}/", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - "User-Agent": ( - "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) " - "Chrome/126.0.0.0 Safari/537.36" - ), - "sec-ch-ua": '"Not/A)Brand";v="8", "Chromium";v="126"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - } - - data = { - "model": model, - "chatId": "-1", - "messages": [ - { - "role": msg["role"], - "content": msg["content"], - "time": msg.get("time", ""), - "attachments": msg.get("attachments", []), - } - for msg in messages - ], - "plugins": [], - "systemPrompt": "", - "temperature": 0.5, - } - - async with ClientSession(headers=headers) as session: - try: - async with session.post( - f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy - ) as response: - response.raise_for_status() - buffer = "" - full_response = "" - def decode_content(data): - bytes_array = bytes([int(b, 16) ^ 255 for b in data.split()]) - return bytes_array.decode('utf-8') - async for chunk in response.content.iter_any(): - if chunk: - buffer += chunk.decode() - while "\n\n" in buffer: - part, buffer = buffer.split("\n\n", 1) - if part.startswith("data: "): - content = part[6:].strip() - if content and content != "[DONE]": - content = content.strip('"') - # Decoding each content block - decoded_content = decode_content(content) - full_response += decoded_content - full_response = ( - full_response.replace('""', '') # Handle double quotes - .replace('" "', ' ') # Handle space within quotes - .replace("\\n\\n", "\n\n") - .replace("\\n", "\n") - .replace('\\"', '"') - .strip() - ) - # Add filter to remove unwanted text - filtered_response = re.sub(r'\n---\n.*', '', full_response, flags=re.DOTALL) - # Remove extra quotes at the beginning and end - cleaned_response = filtered_response.strip().strip('"') - yield cleaned_response - - except ClientResponseError as e: - raise RuntimeError( - f"ClientResponseError {e.status}: {e.message}, url={e.request_info.url}, data={data}" - ) from e - - except Exception as e: - raise RuntimeError(f"Unexpected error: {str(e)}") from e diff --git a/g4f/Provider/Llama.py b/g4f/Provider/Llama.py deleted file mode 100644 index 235c0994..00000000 --- a/g4f/Provider/Llama.py +++ /dev/null @@ -1,91 +0,0 @@ -from __future__ import annotations - -from aiohttp import ClientSession - -from ..typing import AsyncResult, Messages -from ..requests.raise_for_status import raise_for_status -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin - - -class Llama(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://www.llama2.ai" - working = False - supports_message_history = True - default_model = "meta/meta-llama-3-70b-instruct" - models = [ - "meta/llama-2-7b-chat", - "meta/llama-2-13b-chat", - "meta/llama-2-70b-chat", - "meta/meta-llama-3-8b-instruct", - "meta/meta-llama-3-70b-instruct", - ] - model_aliases = { - "meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct", - "meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct", - "meta-llama/Llama-2-7b-chat-hf": "meta/llama-2-7b-chat", - "meta-llama/Llama-2-13b-chat-hf": "meta/llama-2-13b-chat", - "meta-llama/Llama-2-70b-chat-hf": "meta/llama-2-70b-chat", - } - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - system_message: str = "You are a helpful assistant.", - temperature: float = 0.75, - top_p: float = 0.9, - max_tokens: int = 8000, - **kwargs - ) -> AsyncResult: - headers = { - "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0", - "Accept": "*/*", - "Accept-Language": "de,en-US;q=0.7,en;q=0.3", - "Accept-Encoding": "gzip, deflate, br", - "Referer": f"{cls.url}/", - "Content-Type": "text/plain;charset=UTF-8", - "Origin": cls.url, - "Connection": "keep-alive", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - "Pragma": "no-cache", - "Cache-Control": "no-cache", - "TE": "trailers" - } - async with ClientSession(headers=headers) as session: - system_messages = [message["content"] for message in messages if message["role"] == "system"] - if system_messages: - system_message = "\n".join(system_messages) - messages = [message for message in messages if message["role"] != "system"] - prompt = format_prompt(messages) - data = { - "prompt": prompt, - "model": cls.get_model(model), - "systemPrompt": system_message, - "temperature": temperature, - "topP": top_p, - "maxTokens": max_tokens, - "image": None - } - started = False - async with session.post(f"{cls.url}/api", json=data, proxy=proxy) as response: - await raise_for_status(response) - async for chunk in response.content.iter_any(): - if not chunk: - continue - if not started: - chunk = chunk.lstrip() - started = True - yield chunk.decode(errors="ignore") - -def format_prompt(messages: Messages): - messages = [ - f"[INST] {message['content']} [/INST]" - if message["role"] == "user" - else message["content"] - for message in messages - ] - return "\n".join(messages) + "\n" diff --git a/g4f/Provider/MagickPen.py b/g4f/Provider/MagickPen.py index eab70536..7f1751dd 100644 --- a/g4f/Provider/MagickPen.py +++ b/g4f/Provider/MagickPen.py @@ -1,72 +1,53 @@ from __future__ import annotations +from aiohttp import ClientSession +import hashlib import time import random -import hashlib import re -from aiohttp import ClientSession - +import json from ..typing import AsyncResult, Messages from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from .helper import format_prompt class MagickPen(AsyncGeneratorProvider, ProviderModelMixin): url = "https://magickpen.com" - api_endpoint_free = "https://api.magickpen.com/chat/free" - api_endpoint_ask = "https://api.magickpen.com/ask" + api_endpoint = "https://api.magickpen.com/ask" working = True - supports_gpt_4 = True - supports_stream = False - - default_model = 'free' - models = ['free', 'ask'] + supports_stream = True + supports_system_message = True + supports_message_history = True - model_aliases = { - "gpt-4o-mini": "free", - "gpt-4o-mini": "ask", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - elif model in cls.model_aliases: - return cls.model_aliases[model] - else: - return cls.default_model + default_model = 'gpt-4o-mini' + models = ['gpt-4o-mini'] @classmethod - async def get_secrets(cls): - url = 'https://magickpen.com/_nuxt/02c76dc.js' + async def fetch_api_credentials(cls) -> tuple: + url = "https://magickpen.com/_nuxt/bf709a9ce19f14e18116.js" async with ClientSession() as session: async with session.get(url) as response: - if response.status == 200: - text = await response.text() - x_api_secret_match = re.search(r'"X-API-Secret":"([^"]+)"', text) - secret_match = re.search(r'secret:\s*"([^"]+)"', text) - - x_api_secret = x_api_secret_match.group(1) if x_api_secret_match else None - secret = secret_match.group(1) if secret_match else None - - # Generate timestamp and nonce dynamically - timestamp = str(int(time.time() * 1000)) - nonce = str(random.random()) - - # Generate signature - signature_parts = ["TGDBU9zCgM", timestamp, nonce] - signature_string = "".join(sorted(signature_parts)) - signature = hashlib.md5(signature_string.encode()).hexdigest() - - return { - 'X-API-Secret': x_api_secret, - 'signature': signature, - 'timestamp': timestamp, - 'nonce': nonce, - 'secret': secret - } - else: - print(f"Error while fetching the file: {response.status}") - return None + text = await response.text() + + pattern = r'"X-API-Secret":"(\w+)"' + match = re.search(pattern, text) + X_API_SECRET = match.group(1) if match else None + + timestamp = str(int(time.time() * 1000)) + nonce = str(random.random()) + + s = ["TGDBU9zCgM", timestamp, nonce] + s.sort() + signature_string = ''.join(s) + signature = hashlib.md5(signature_string.encode()).hexdigest() + + pattern = r'secret:"(\w+)"' + match = re.search(pattern, text) + secret = match.group(1) if match else None + + if X_API_SECRET and timestamp and nonce and secret: + return X_API_SECRET, signature, timestamp, nonce, secret + else: + raise Exception("Unable to extract all the necessary data from the JavaScript file.") @classmethod async def create_async_generator( @@ -77,54 +58,30 @@ class MagickPen(AsyncGeneratorProvider, ProviderModelMixin): **kwargs ) -> AsyncResult: model = cls.get_model(model) + X_API_SECRET, signature, timestamp, nonce, secret = await cls.fetch_api_credentials() - secrets = await cls.get_secrets() - if not secrets: - raise Exception("Failed to obtain necessary secrets") - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "nonce": secrets['nonce'], - "origin": "https://magickpen.com", - "pragma": "no-cache", - "priority": "u=1, i", - "referer": "https://magickpen.com/", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "secret": secrets['secret'], - "signature": secrets['signature'], - "timestamp": secrets['timestamp'], - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - "x-api-secret": secrets['X-API-Secret'] + 'accept': 'application/json, text/plain, */*', + 'accept-language': 'en-US,en;q=0.9', + 'content-type': 'application/json', + 'nonce': nonce, + 'origin': cls.url, + 'referer': f"{cls.url}/", + 'secret': secret, + 'signature': signature, + 'timestamp': timestamp, + 'x-api-secret': X_API_SECRET, } async with ClientSession(headers=headers) as session: - if model == 'free': - data = { - "history": [{"role": "user", "content": format_prompt(messages)}] - } - async with session.post(cls.api_endpoint_free, json=data, proxy=proxy) as response: - response.raise_for_status() - result = await response.text() - yield result - - elif model == 'ask': - data = { - "query": format_prompt(messages), - "plan": "Pay as you go" - } - async with session.post(cls.api_endpoint_ask, json=data, proxy=proxy) as response: - response.raise_for_status() - async for chunk in response.content: - if chunk: - yield chunk.decode() - - else: - raise ValueError(f"Unknown model: {model}") + prompt = format_prompt(messages) + payload = { + 'query': prompt, + 'turnstileResponse': '', + 'action': 'verify' + } + async with session.post(cls.api_endpoint, json=payload, proxy=proxy) as response: + response.raise_for_status() + async for chunk in response.content: + if chunk: + yield chunk.decode() diff --git a/g4f/Provider/Nexra.py b/g4f/Provider/Nexra.py deleted file mode 100644 index e2c3e197..00000000 --- a/g4f/Provider/Nexra.py +++ /dev/null @@ -1,181 +0,0 @@ -from __future__ import annotations - -import json -import base64 -from aiohttp import ClientSession -from typing import AsyncGenerator - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..image import ImageResponse -from .helper import format_prompt - -class Nexra(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://nexra.aryahcr.cc" - api_endpoint_text = "https://nexra.aryahcr.cc/api/chat/gpt" - api_endpoint_image = "https://nexra.aryahcr.cc/api/image/complements" - working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - default_model = 'gpt-3.5-turbo' - models = [ - # Text models - 'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-0314', 'gpt-4-32k-0314', - 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', - 'gpt-3', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', - 'text-curie-001', 'text-babbage-001', 'text-ada-001', - 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002', - # Image models - 'dalle', 'dalle-mini', 'emi' - ] - - image_models = {"dalle", "dalle-mini", "emi"} - text_models = set(models) - image_models - - model_aliases = { - "gpt-4": "gpt-4-0613", - "gpt-4": "gpt-4-32k", - "gpt-4": "gpt-4-0314", - "gpt-4": "gpt-4-32k-0314", - - "gpt-3.5-turbo": "gpt-3.5-turbo-16k", - "gpt-3.5-turbo": "gpt-3.5-turbo-0613", - "gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613", - "gpt-3.5-turbo": "gpt-3.5-turbo-0301", - - "gpt-3": "text-davinci-003", - "gpt-3": "text-davinci-002", - "gpt-3": "code-davinci-002", - "gpt-3": "text-curie-001", - "gpt-3": "text-babbage-001", - "gpt-3": "text-ada-001", - "gpt-3": "text-ada-001", - "gpt-3": "davinci", - "gpt-3": "curie", - "gpt-3": "babbage", - "gpt-3": "ada", - "gpt-3": "babbage-002", - "gpt-3": "davinci-002", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - elif model in cls.model_aliases: - return cls.model_aliases[model] - else: - return cls.default_model - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str | ImageResponse, None]: - model = cls.get_model(model) - - if model in cls.image_models: - async for result in cls.create_image_async_generator(model, messages, proxy, **kwargs): - yield result - else: - async for result in cls.create_text_async_generator(model, messages, proxy, **kwargs): - yield result - - @classmethod - async def create_text_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str, None]: - headers = { - "Content-Type": "application/json", - } - async with ClientSession(headers=headers) as session: - data = { - "messages": messages, - "prompt": format_prompt(messages), - "model": model, - "markdown": False, - "stream": False, - } - async with session.post(cls.api_endpoint_text, json=data, proxy=proxy) as response: - response.raise_for_status() - result = await response.text() - json_result = json.loads(result) - yield json_result["gpt"] - - @classmethod - async def create_image_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[ImageResponse | str, None]: - headers = { - "Content-Type": "application/json" - } - - prompt = messages[-1]['content'] if messages else "" - - data = { - "prompt": prompt, - "model": model - } - - async def process_response(response_text: str) -> ImageResponse | None: - json_start = response_text.find('{') - if json_start != -1: - json_data = response_text[json_start:] - try: - response_data = json.loads(json_data) - image_data = response_data.get('images', [])[0] - - if image_data.startswith('data:image/'): - return ImageResponse([image_data], "Generated image") - - try: - base64.b64decode(image_data) - data_uri = f"data:image/jpeg;base64,{image_data}" - return ImageResponse([data_uri], "Generated image") - except: - print("Invalid base64 data") - return None - except json.JSONDecodeError: - print("Failed to parse JSON.") - else: - print("No JSON data found in the response.") - return None - - async with ClientSession(headers=headers) as session: - async with session.post(cls.api_endpoint_image, json=data, proxy=proxy) as response: - response.raise_for_status() - response_text = await response.text() - - image_response = await process_response(response_text) - if image_response: - yield image_response - else: - yield "Failed to process image data." - - @classmethod - async def create_async( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> str: - async for response in cls.create_async_generator(model, messages, proxy, **kwargs): - if isinstance(response, ImageResponse): - return response.images[0] - return response diff --git a/g4f/Provider/Ollama.py b/g4f/Provider/Ollama.py index a44aaacd..f9116541 100644 --- a/g4f/Provider/Ollama.py +++ b/g4f/Provider/Ollama.py @@ -1,6 +1,7 @@ from __future__ import annotations import requests +import os from .needs_auth.Openai import Openai from ..typing import AsyncResult, Messages @@ -14,9 +15,11 @@ class Ollama(Openai): @classmethod def get_models(cls): if not cls.models: - url = 'http://127.0.0.1:11434/api/tags' + host = os.getenv("OLLAMA_HOST", "127.0.0.1") + port = os.getenv("OLLAMA_PORT", "11434") + url = f"http://{host}:{port}/api/tags" models = requests.get(url).json()["models"] - cls.models = [model['name'] for model in models] + cls.models = [model["name"] for model in models] cls.default_model = cls.models[0] return cls.models @@ -25,9 +28,13 @@ class Ollama(Openai): cls, model: str, messages: Messages, - api_base: str = "http://localhost:11434/v1", + api_base: str = None, **kwargs ) -> AsyncResult: + if not api_base: + host = os.getenv("OLLAMA_HOST", "localhost") + port = os.getenv("OLLAMA_PORT", "11434") + api_base: str = f"http://{host}:{port}/v1" return super().create_async_generator( model, messages, api_base=api_base, **kwargs )
\ No newline at end of file diff --git a/g4f/Provider/PerplexityLabs.py b/g4f/Provider/PerplexityLabs.py index 3656a39b..b776e96a 100644 --- a/g4f/Provider/PerplexityLabs.py +++ b/g4f/Provider/PerplexityLabs.py @@ -13,7 +13,7 @@ WS_URL = "wss://www.perplexity.ai/socket.io/" class PerplexityLabs(AsyncGeneratorProvider, ProviderModelMixin): url = "https://labs.perplexity.ai" working = True - default_model = "llama-3.1-8b-instruct" + default_model = "llama-3.1-70b-instruct" models = [ "llama-3.1-sonar-large-128k-online", "llama-3.1-sonar-small-128k-online", @@ -22,6 +22,15 @@ class PerplexityLabs(AsyncGeneratorProvider, ProviderModelMixin): "llama-3.1-8b-instruct", "llama-3.1-70b-instruct", ] + + model_aliases = { + "sonar-online": "llama-3.1-sonar-large-128k-online", + "sonar-online": "sonar-small-128k-online", + "sonar-chat": "llama-3.1-sonar-large-128k-chat", + "sonar-chat": "llama-3.1-sonar-small-128k-chat", + "llama-3.1-8b": "llama-3.1-8b-instruct", + "llama-3.1-70b": "llama-3.1-70b-instruct", + } @classmethod async def create_async_generator( diff --git a/g4f/Provider/Pi.py b/g4f/Provider/Pi.py index e03830f4..266647ba 100644 --- a/g4f/Provider/Pi.py +++ b/g4f/Provider/Pi.py @@ -22,6 +22,7 @@ class Pi(AbstractProvider): proxy: str = None, timeout: int = 180, conversation_id: str = None, + webdriver: WebDriver = None, **kwargs ) -> CreateResult: if cls._session is None: diff --git a/g4f/Provider/Pizzagpt.py b/g4f/Provider/Pizzagpt.py index 47cb135c..6513bd34 100644 --- a/g4f/Provider/Pizzagpt.py +++ b/g4f/Provider/Pizzagpt.py @@ -12,7 +12,6 @@ class Pizzagpt(AsyncGeneratorProvider, ProviderModelMixin): url = "https://www.pizzagpt.it" api_endpoint = "/api/chatx-completion" working = True - supports_gpt_4 = True default_model = 'gpt-4o-mini' @classmethod diff --git a/g4f/Provider/Prodia.py b/g4f/Provider/Prodia.py new file mode 100644 index 00000000..543a8b19 --- /dev/null +++ b/g4f/Provider/Prodia.py @@ -0,0 +1,150 @@ +from __future__ import annotations + +from aiohttp import ClientSession +import time +import asyncio + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..image import ImageResponse + +class Prodia(AsyncGeneratorProvider, ProviderModelMixin): + url = "https://app.prodia.com" + api_endpoint = "https://api.prodia.com/generate" + working = True + + default_model = 'absolutereality_v181.safetensors [3d9d4d2b]' + image_models = [ + '3Guofeng3_v34.safetensors [50f420de]', + 'absolutereality_V16.safetensors [37db0fc3]', + default_model, + 'amIReal_V41.safetensors [0a8a2e61]', + 'analog-diffusion-1.0.ckpt [9ca13f02]', + 'aniverse_v30.safetensors [579e6f85]', + 'anythingv3_0-pruned.ckpt [2700c435]', + 'anything-v4.5-pruned.ckpt [65745d25]', + 'anythingV5_PrtRE.safetensors [893e49b9]', + 'AOM3A3_orangemixs.safetensors [9600da17]', + 'blazing_drive_v10g.safetensors [ca1c1eab]', + 'breakdomain_I2428.safetensors [43cc7d2f]', + 'breakdomain_M2150.safetensors [15f7afca]', + 'cetusMix_Version35.safetensors [de2f2560]', + 'childrensStories_v13D.safetensors [9dfaabcb]', + 'childrensStories_v1SemiReal.safetensors [a1c56dbb]', + 'childrensStories_v1ToonAnime.safetensors [2ec7b88b]', + 'Counterfeit_v30.safetensors [9e2a8f19]', + 'cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]', + 'cyberrealistic_v33.safetensors [82b0d085]', + 'dalcefo_v4.safetensors [425952fe]', + 'deliberate_v2.safetensors [10ec4b29]', + 'deliberate_v3.safetensors [afd9d2d4]', + 'dreamlike-anime-1.0.safetensors [4520e090]', + 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]', + 'dreamlike-photoreal-2.0.safetensors [fdcf65e7]', + 'dreamshaper_6BakedVae.safetensors [114c8abb]', + 'dreamshaper_7.safetensors [5cf5ae06]', + 'dreamshaper_8.safetensors [9d40847d]', + 'edgeOfRealism_eorV20.safetensors [3ed5de15]', + 'EimisAnimeDiffusion_V1.ckpt [4f828a15]', + 'elldreths-vivid-mix.safetensors [342d9d26]', + 'epicphotogasm_xPlusPlus.safetensors [1a8f6d35]', + 'epicrealism_naturalSinRC1VAE.safetensors [90a4c676]', + 'epicrealism_pureEvolutionV3.safetensors [42c8440c]', + 'ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]', + 'indigoFurryMix_v75Hybrid.safetensors [91208cbb]', + 'juggernaut_aftermath.safetensors [5e20c455]', + 'lofi_v4.safetensors [ccc204d6]', + 'lyriel_v16.safetensors [68fceea2]', + 'majicmixRealistic_v4.safetensors [29d0de58]', + 'mechamix_v10.safetensors [ee685731]', + 'meinamix_meinaV9.safetensors [2ec66ab0]', + 'meinamix_meinaV11.safetensors [b56ce717]', + 'neverendingDream_v122.safetensors [f964ceeb]', + 'openjourney_V4.ckpt [ca2f377f]', + 'pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]', + 'portraitplus_V1.0.safetensors [1400e684]', + 'protogenx34.safetensors [5896f8d5]', + 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]', + 'Realistic_Vision_V2.0.safetensors [79587710]', + 'Realistic_Vision_V4.0.safetensors [29a7afaa]', + 'Realistic_Vision_V5.0.safetensors [614d1063]', + 'Realistic_Vision_V5.1.safetensors [a0f13c83]', + 'redshift_diffusion-V10.safetensors [1400e684]', + 'revAnimated_v122.safetensors [3f4fefd9]', + 'rundiffusionFX25D_v10.safetensors [cd12b0ee]', + 'rundiffusionFX_v10.safetensors [cd4e694d]', + 'sdv1_4.ckpt [7460a6fa]', + 'v1-5-pruned-emaonly.safetensors [d7049739]', + 'v1-5-inpainting.safetensors [21c7ab71]', + 'shoninsBeautiful_v10.safetensors [25d8c546]', + 'theallys-mix-ii-churned.safetensors [5d9225a4]', + 'timeless-1.0.ckpt [7c4971d4]', + 'toonyou_beta6.safetensors [980f6b15]', + ] + models = [*image_models] + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "origin": cls.url, + "referer": f"{cls.url}/", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36" + } + + async with ClientSession(headers=headers) as session: + prompt = messages[-1]['content'] if messages else "" + + params = { + "new": "true", + "prompt": prompt, + "model": model, + "negative_prompt": kwargs.get("negative_prompt", ""), + "steps": kwargs.get("steps", 20), + "cfg": kwargs.get("cfg", 7), + "seed": kwargs.get("seed", int(time.time())), + "sampler": kwargs.get("sampler", "DPM++ 2M Karras"), + "aspect_ratio": kwargs.get("aspect_ratio", "square") + } + + async with session.get(cls.api_endpoint, params=params, proxy=proxy) as response: + response.raise_for_status() + job_data = await response.json() + job_id = job_data["job"] + + image_url = await cls._poll_job(session, job_id, proxy) + yield ImageResponse(image_url, alt=prompt) + + @classmethod + async def _poll_job(cls, session: ClientSession, job_id: str, proxy: str, max_attempts: int = 30, delay: int = 2) -> str: + for _ in range(max_attempts): + async with session.get(f"https://api.prodia.com/job/{job_id}", proxy=proxy) as response: + response.raise_for_status() + job_status = await response.json() + + if job_status["status"] == "succeeded": + return f"https://images.prodia.xyz/{job_id}.png" + elif job_status["status"] == "failed": + raise Exception("Image generation failed") + + await asyncio.sleep(delay) + + raise Exception("Timeout waiting for image generation") diff --git a/g4f/Provider/ReplicateHome.py b/g4f/Provider/ReplicateHome.py index c4e52ad6..7f443a7d 100644 --- a/g4f/Provider/ReplicateHome.py +++ b/g4f/Provider/ReplicateHome.py @@ -1,66 +1,60 @@ from __future__ import annotations -from typing import Generator, Optional, Dict, Any, Union, List -import random + +import json import asyncio -import base64 +from aiohttp import ClientSession, ContentTypeError -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from ..typing import AsyncResult, Messages -from ..requests import StreamSession, raise_for_status -from ..errors import ResponseError +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt from ..image import ImageResponse class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin): url = "https://replicate.com" - parent = "Replicate" + api_endpoint = "https://homepage.replicate.com/api/prediction" working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + default_model = 'meta/meta-llama-3-70b-instruct' - models = [ - # Models for image generation - 'stability-ai/stable-diffusion-3', - 'bytedance/sdxl-lightning-4step', - 'playgroundai/playground-v2.5-1024px-aesthetic', - - # Models for image generation + + text_models = [ 'meta/meta-llama-3-70b-instruct', 'mistralai/mixtral-8x7b-instruct-v0.1', 'google-deepmind/gemma-2b-it', + 'yorickvp/llava-13b', ] - versions = { - # Model versions for generating images - 'stability-ai/stable-diffusion-3': [ - "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f" - ], - 'bytedance/sdxl-lightning-4step': [ - "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f" - ], - 'playgroundai/playground-v2.5-1024px-aesthetic': [ - "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24" - ], - - # Model versions for text generation - 'meta/meta-llama-3-70b-instruct': [ - "dp-cf04fe09351e25db628e8b6181276547" - ], - 'mistralai/mixtral-8x7b-instruct-v0.1': [ - "dp-89e00f489d498885048e94f9809fbc76" - ], - 'google-deepmind/gemma-2b-it': [ - "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626" - ] - } - - image_models = {"stability-ai/stable-diffusion-3", "bytedance/sdxl-lightning-4step", "playgroundai/playground-v2.5-1024px-aesthetic"} - text_models = {"meta/meta-llama-3-70b-instruct", "mistralai/mixtral-8x7b-instruct-v0.1", "google-deepmind/gemma-2b-it"} + image_models = [ + 'black-forest-labs/flux-schnell', + 'stability-ai/stable-diffusion-3', + 'bytedance/sdxl-lightning-4step', + 'playgroundai/playground-v2.5-1024px-aesthetic', + ] + models = text_models + image_models + model_aliases = { + "flux-schnell": "black-forest-labs/flux-schnell", "sd-3": "stability-ai/stable-diffusion-3", "sdxl": "bytedance/sdxl-lightning-4step", "playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic", "llama-3-70b": "meta/meta-llama-3-70b-instruct", "mixtral-8x7b": "mistralai/mixtral-8x7b-instruct-v0.1", "gemma-2b": "google-deepmind/gemma-2b-it", + "llava-13b": "yorickvp/llava-13b", + } + + model_versions = { + "meta/meta-llama-3-70b-instruct": "fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d", + "mistralai/mixtral-8x7b-instruct-v0.1": "5d78bcd7a992c4b793465bcdcf551dc2ab9668d12bb7aa714557a21c1e77041c", + "google-deepmind/gemma-2b-it": "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626", + "yorickvp/llava-13b": "80537f9eead1a5bfa72d5ac6ea6414379be41d4d4f6679fd776e9535d1eb58bb", + 'black-forest-labs/flux-schnell': "f2ab8a5bfe79f02f0789a146cf5e73d2a4ff2684a98c2b303d1e1ff3814271db", + 'stability-ai/stable-diffusion-3': "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f", + 'bytedance/sdxl-lightning-4step': "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f", + 'playgroundai/playground-v2.5-1024px-aesthetic': "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24", } @classmethod @@ -77,84 +71,73 @@ class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin): cls, model: str, messages: Messages, - **kwargs: Any - ) -> Generator[Union[str, ImageResponse], None, None]: - yield await cls.create_async(messages[-1]["content"], model, **kwargs) - - @classmethod - async def create_async( - cls, - prompt: str, - model: str, - api_key: Optional[str] = None, - proxy: Optional[str] = None, - timeout: int = 180, - version: Optional[str] = None, - extra_data: Dict[str, Any] = {}, - **kwargs: Any - ) -> Union[str, ImageResponse]: - model = cls.get_model(model) # Use the get_model method to resolve model name + proxy: str = None, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + headers = { - 'Accept-Encoding': 'gzip, deflate, br', - 'Accept-Language': 'en-US', - 'Connection': 'keep-alive', - 'Origin': cls.url, - 'Referer': f'{cls.url}/', - 'Sec-Fetch-Dest': 'empty', - 'Sec-Fetch-Mode': 'cors', - 'Sec-Fetch-Site': 'same-site', - 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36', - 'sec-ch-ua': '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', + "accept": "*/*", + "accept-language": "en-US,en;q=0.9", + "cache-control": "no-cache", + "content-type": "application/json", + "origin": "https://replicate.com", + "pragma": "no-cache", + "priority": "u=1, i", + "referer": "https://replicate.com/", + "sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"', + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": '"Linux"', + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36" } - - if version is None: - version = random.choice(cls.versions.get(model, [])) - if api_key is not None: - headers["Authorization"] = f"Bearer {api_key}" - - async with StreamSession( - proxies={"all": proxy}, - headers=headers, - timeout=timeout - ) as session: + + async with ClientSession(headers=headers) as session: + if model in cls.image_models: + prompt = messages[-1]['content'] if messages else "" + else: + prompt = format_prompt(messages) + data = { - "input": { - "prompt": prompt, - **extra_data - }, - "version": version + "model": model, + "version": cls.model_versions[model], + "input": {"prompt": prompt}, } - if api_key is None: - data["model"] = model - url = "https://homepage.replicate.com/api/prediction" - else: - url = "https://api.replicate.com/v1/predictions" - async with session.post(url, json=data) as response: - await raise_for_status(response) + + async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: + response.raise_for_status() result = await response.json() - if "id" not in result: - raise ResponseError(f"Invalid response: {result}") + prediction_id = result['id'] + + poll_url = f"https://homepage.replicate.com/api/poll?id={prediction_id}" + max_attempts = 30 + delay = 5 + for _ in range(max_attempts): + async with session.get(poll_url, proxy=proxy) as response: + response.raise_for_status() + try: + result = await response.json() + except ContentTypeError: + text = await response.text() + try: + result = json.loads(text) + except json.JSONDecodeError: + raise ValueError(f"Unexpected response format: {text}") - while True: - if api_key is None: - url = f"https://homepage.replicate.com/api/poll?id={result['id']}" - else: - url = f"https://api.replicate.com/v1/predictions/{result['id']}" - async with session.get(url) as response: - await raise_for_status(response) - result = await response.json() - if "status" not in result: - raise ResponseError(f"Invalid response: {result}") - if result["status"] == "succeeded": - output = result['output'] - if model in cls.text_models: - return ''.join(output) if isinstance(output, list) else output - elif model in cls.image_models: - images: List[Any] = output - images = images[0] if len(images) == 1 else images - return ImageResponse(images, prompt) - elif result["status"] == "failed": - raise ResponseError(f"Prediction failed: {result}") - await asyncio.sleep(0.5) + if result['status'] == 'succeeded': + if model in cls.image_models: + image_url = result['output'][0] + yield ImageResponse(image_url, "Generated image") + return + else: + for chunk in result['output']: + yield chunk + break + elif result['status'] == 'failed': + raise Exception(f"Prediction failed: {result.get('error')}") + await asyncio.sleep(delay) + + if result['status'] != 'succeeded': + raise Exception("Prediction timed out") diff --git a/g4f/Provider/Rocks.py b/g4f/Provider/Rocks.py deleted file mode 100644 index f44e0060..00000000 --- a/g4f/Provider/Rocks.py +++ /dev/null @@ -1,70 +0,0 @@ -import asyncio -import json -from aiohttp import ClientSession -from ..typing import Messages, AsyncResult -from .base_provider import AsyncGeneratorProvider - -class Rocks(AsyncGeneratorProvider): - url = "https://api.airforce" - api_endpoint = "/chat/completions" - supports_message_history = True - supports_gpt_35_turbo = True - supports_gpt_4 = True - supports_stream = True - supports_system_message = True - working = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - payload = {"messages":messages,"model":model,"max_tokens":4096,"temperature":1,"top_p":1,"stream":True} - - headers = { - "Accept": "application/json", - "Accept-Encoding": "gzip, deflate, br, zstd", - "Accept-Language": "en-US,en;q=0.9", - "Authorization": "Bearer missing api key", - "Origin": "https://llmplayground.net", - "Referer": "https://llmplayground.net/", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36", - } - - async with ClientSession() as session: - async with session.post( - f"{cls.url}{cls.api_endpoint}", - json=payload, - proxy=proxy, - headers=headers - ) as response: - response.raise_for_status() - last_chunk_time = asyncio.get_event_loop().time() - - async for line in response.content: - current_time = asyncio.get_event_loop().time() - if current_time - last_chunk_time > 5: - return - - if line.startswith(b"\n"): - pass - elif "discord.com/invite/" in line.decode() or "discord.gg/" in line.decode(): - pass # trolled - elif line.startswith(b"data: "): - try: - line = json.loads(line[6:]) - except json.JSONDecodeError: - continue - chunk = line["choices"][0]["delta"].get("content") - if chunk: - yield chunk - last_chunk_time = current_time - else: - raise Exception(f"Unexpected line: {line}") - return
\ No newline at end of file diff --git a/g4f/Provider/RubiksAI.py b/g4f/Provider/RubiksAI.py new file mode 100644 index 00000000..7e76d558 --- /dev/null +++ b/g4f/Provider/RubiksAI.py @@ -0,0 +1,162 @@ +from __future__ import annotations + +import asyncio +import aiohttp +import random +import string +import json +from urllib.parse import urlencode + +from aiohttp import ClientSession + +from ..typing import AsyncResult, Messages +from .base_provider import AsyncGeneratorProvider, ProviderModelMixin +from .helper import format_prompt + + +class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin): + label = "Rubiks AI" + url = "https://rubiks.ai" + api_endpoint = "https://rubiks.ai/search/api.php" + working = True + supports_stream = True + supports_system_message = True + supports_message_history = True + + default_model = 'llama-3.1-70b-versatile' + models = [default_model, 'gpt-4o-mini'] + + model_aliases = { + "llama-3.1-70b": "llama-3.1-70b-versatile", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @staticmethod + def generate_mid() -> str: + """ + Generates a 'mid' string following the pattern: + 6 characters - 4 characters - 4 characters - 4 characters - 12 characters + Example: 0r7v7b-quw4-kdy3-rvdu-ekief6xbuuq4 + """ + parts = [ + ''.join(random.choices(string.ascii_lowercase + string.digits, k=6)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=4)), + ''.join(random.choices(string.ascii_lowercase + string.digits, k=12)) + ] + return '-'.join(parts) + + @staticmethod + def create_referer(q: str, mid: str, model: str = '') -> str: + """ + Creates a Referer URL with dynamic q and mid values, using urlencode for safe parameter encoding. + """ + params = {'q': q, 'model': model, 'mid': mid} + encoded_params = urlencode(params) + return f'https://rubiks.ai/search/?{encoded_params}' + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + proxy: str = None, + websearch: bool = False, + **kwargs + ) -> AsyncResult: + """ + Creates an asynchronous generator that sends requests to the Rubiks AI API and yields the response. + + Parameters: + - model (str): The model to use in the request. + - messages (Messages): The messages to send as a prompt. + - proxy (str, optional): Proxy URL, if needed. + - websearch (bool, optional): Indicates whether to include search sources in the response. Defaults to False. + """ + model = cls.get_model(model) + prompt = format_prompt(messages) + q_value = prompt + mid_value = cls.generate_mid() + referer = cls.create_referer(q=q_value, mid=mid_value, model=model) + + url = cls.api_endpoint + params = { + 'q': q_value, + 'model': model, + 'id': '', + 'mid': mid_value + } + + headers = { + 'Accept': 'text/event-stream', + 'Accept-Language': 'en-US,en;q=0.9', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', + 'Pragma': 'no-cache', + 'Referer': referer, + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36', + 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', + 'sec-ch-ua-mobile': '?0', + 'sec-ch-ua-platform': '"Linux"' + } + + try: + timeout = aiohttp.ClientTimeout(total=None) + async with ClientSession(timeout=timeout) as session: + async with session.get(url, headers=headers, params=params, proxy=proxy) as response: + if response.status != 200: + yield f"Request ended with status code {response.status}" + return + + assistant_text = '' + sources = [] + + async for line in response.content: + decoded_line = line.decode('utf-8').strip() + if not decoded_line.startswith('data: '): + continue + data = decoded_line[6:] + if data in ('[DONE]', '{"done": ""}'): + break + try: + json_data = json.loads(data) + except json.JSONDecodeError: + continue + + if 'url' in json_data and 'title' in json_data: + if websearch: + sources.append({'title': json_data['title'], 'url': json_data['url']}) + + elif 'choices' in json_data: + for choice in json_data['choices']: + delta = choice.get('delta', {}) + content = delta.get('content', '') + role = delta.get('role', '') + if role == 'assistant': + continue + assistant_text += content + + if websearch and sources: + sources_text = '\n'.join([f"{i+1}. [{s['title']}]: {s['url']}" for i, s in enumerate(sources)]) + assistant_text += f"\n\n**Source:**\n{sources_text}" + + yield assistant_text + + except asyncio.CancelledError: + yield "The request was cancelled." + except aiohttp.ClientError as e: + yield f"An error occurred during the request: {e}" + except Exception as e: + yield f"An unexpected error occurred: {e}" diff --git a/g4f/Provider/Snova.py b/g4f/Provider/Snova.py deleted file mode 100644 index 76dfac40..00000000 --- a/g4f/Provider/Snova.py +++ /dev/null @@ -1,133 +0,0 @@ -from __future__ import annotations - -import json -from typing import AsyncGenerator - -from aiohttp import ClientSession - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - - -class Snova(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://fast.snova.ai" - api_endpoint = "https://fast.snova.ai/api/completion" - working = True - supports_stream = True - supports_system_message = True - supports_message_history = True - - default_model = 'Meta-Llama-3.1-8B-Instruct' - models = [ - 'Meta-Llama-3.1-8B-Instruct', - 'Meta-Llama-3.1-70B-Instruct', - 'Meta-Llama-3.1-405B-Instruct', - 'Samba-CoE', - 'ignos/Mistral-T5-7B-v1', - 'v1olet/v1olet_merged_dpo_7B', - 'macadeliccc/WestLake-7B-v2-laser-truthy-dpo', - 'cookinai/DonutLM-v1', - ] - - model_aliases = { - "llama-3.1-8b": "Meta-Llama-3.1-8B-Instruct", - "llama-3.1-70b": "Meta-Llama-3.1-70B-Instruct", - "llama-3.1-405b": "Meta-Llama-3.1-405B-Instruct", - - "mistral-7b": "ignos/Mistral-T5-7B-v1", - - "samba-coe-v0.1": "Samba-CoE", - "v1olet-merged-7b": "v1olet/v1olet_merged_dpo_7B", - "westlake-7b-v2": "macadeliccc/WestLake-7B-v2-laser-truthy-dpo", - "donutlm-v1": "cookinai/DonutLM-v1", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - elif model in cls.model_aliases: - return cls.model_aliases[model] - else: - return cls.default_model - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncGenerator[str, None]: - model = cls.get_model(model) - - headers = { - "accept": "text/event-stream", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" - } - async with ClientSession(headers=headers) as session: - data = { - "body": { - "messages": [ - { - "role": "system", - "content": "You are a helpful assistant." - }, - { - "role": "user", - "content": format_prompt(messages), - "id": "1-id", - "ref": "1-ref", - "revision": 1, - "draft": False, - "status": "done", - "enableRealTimeChat": False, - "meta": None - } - ], - "max_tokens": 1000, - "stop": ["<|eot_id|>"], - "stream": True, - "stream_options": {"include_usage": True}, - "model": model - }, - "env_type": "tp16" - } - async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - full_response = "" - async for line in response.content: - line = line.decode().strip() - if line.startswith("data: "): - data = line[6:] - if data == "[DONE]": - break - try: - json_data = json.loads(data) - choices = json_data.get("choices", []) - if choices: - delta = choices[0].get("delta", {}) - content = delta.get("content", "") - full_response += content - except json.JSONDecodeError: - continue - except Exception as e: - print(f"Error processing chunk: {e}") - print(f"Problematic data: {data}") - continue - - yield full_response.strip() diff --git a/g4f/Provider/TwitterBio.py b/g4f/Provider/TwitterBio.py deleted file mode 100644 index c143e4ff..00000000 --- a/g4f/Provider/TwitterBio.py +++ /dev/null @@ -1,103 +0,0 @@ -from __future__ import annotations - -import json -import re -from aiohttp import ClientSession - -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from .helper import format_prompt - -class TwitterBio(AsyncGeneratorProvider, ProviderModelMixin): - url = "https://www.twitterbio.io" - api_endpoint_mistral = "https://www.twitterbio.io/api/mistral" - api_endpoint_openai = "https://www.twitterbio.io/api/openai" - working = True - supports_gpt_35_turbo = True - - default_model = 'gpt-3.5-turbo' - models = [ - 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'gpt-3.5-turbo', - ] - - model_aliases = { - "mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", - } - - @classmethod - def get_model(cls, model: str) -> str: - if model in cls.models: - return model - return cls.default_model - - @staticmethod - def format_text(text: str) -> str: - text = re.sub(r'\s+', ' ', text.strip()) - text = re.sub(r'\s+([,.!?])', r'\1', text) - return text - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - model = cls.get_model(model) - - headers = { - "accept": "*/*", - "accept-language": "en-US,en;q=0.9", - "cache-control": "no-cache", - "content-type": "application/json", - "origin": cls.url, - "pragma": "no-cache", - "priority": "u=1, i", - "referer": f"{cls.url}/", - "sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"', - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": '"Linux"', - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" - } - async with ClientSession(headers=headers) as session: - prompt = format_prompt(messages) - data = { - "prompt": f'{prompt}.' - } - - if model == 'mistralai/Mixtral-8x7B-Instruct-v0.1': - api_endpoint = cls.api_endpoint_mistral - elif model == 'gpt-3.5-turbo': - api_endpoint = cls.api_endpoint_openai - else: - raise ValueError(f"Unsupported model: {model}") - - async with session.post(api_endpoint, json=data, proxy=proxy) as response: - response.raise_for_status() - buffer = "" - async for line in response.content: - line = line.decode('utf-8').strip() - if line.startswith('data: '): - try: - json_data = json.loads(line[6:]) - if model == 'mistralai/Mixtral-8x7B-Instruct-v0.1': - if 'choices' in json_data and len(json_data['choices']) > 0: - text = json_data['choices'][0].get('text', '') - if text: - buffer += text - elif model == 'gpt-3.5-turbo': - text = json_data.get('text', '') - if text: - buffer += text - except json.JSONDecodeError: - continue - elif line == 'data: [DONE]': - break - - if buffer: - yield cls.format_text(buffer) diff --git a/g4f/Provider/Upstage.py b/g4f/Provider/Upstage.py index e61a5af2..65409159 100644 --- a/g4f/Provider/Upstage.py +++ b/g4f/Provider/Upstage.py @@ -12,14 +12,15 @@ class Upstage(AsyncGeneratorProvider, ProviderModelMixin): url = "https://console.upstage.ai/playground/chat" api_endpoint = "https://ap-northeast-2.apistage.ai/v1/web/demo/chat/completions" working = True - default_model = 'upstage/solar-1-mini-chat' + default_model = 'solar-pro' models = [ 'upstage/solar-1-mini-chat', 'upstage/solar-1-mini-chat-ja', + 'solar-pro', ] model_aliases = { - "solar-1-mini": "upstage/solar-1-mini-chat", - "solar-1-mini": "upstage/solar-1-mini-chat-ja", + "solar-mini": "upstage/solar-1-mini-chat", + "solar-mini": "upstage/solar-1-mini-chat-ja", } @classmethod diff --git a/g4f/Provider/Vercel.py b/g4f/Provider/Vercel.py deleted file mode 100644 index bd918396..00000000 --- a/g4f/Provider/Vercel.py +++ /dev/null @@ -1,104 +0,0 @@ -from __future__ import annotations - -import json, base64, requests, random, os - -try: - import execjs - has_requirements = True -except ImportError: - has_requirements = False - -from ..typing import Messages, CreateResult -from .base_provider import AbstractProvider -from ..requests import raise_for_status -from ..errors import MissingRequirementsError - -class Vercel(AbstractProvider): - url = 'https://chat.vercel.ai' - working = True - supports_message_history = True - supports_system_message = True - supports_gpt_35_turbo = True - supports_stream = True - - @staticmethod - def create_completion( - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - max_retries: int = 6, - **kwargs - ) -> CreateResult: - if not has_requirements: - raise MissingRequirementsError('Install "PyExecJS" package') - - headers = { - 'authority': 'chat.vercel.ai', - 'accept': '*/*', - 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', - 'cache-control': 'no-cache', - 'content-type': 'application/json', - 'custom-encoding': get_anti_bot_token(), - 'origin': 'https://chat.vercel.ai', - 'pragma': 'no-cache', - 'referer': 'https://chat.vercel.ai/', - 'sec-ch-ua': '"Chromium";v="122", "Not(A:Brand";v="24", "Google Chrome";v="122"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', - 'sec-fetch-dest': 'empty', - 'sec-fetch-mode': 'cors', - 'sec-fetch-site': 'same-origin', - 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36', - } - - json_data = { - 'messages': messages, - 'id' : f'{os.urandom(3).hex()}a', - } - response = None - for _ in range(max_retries): - response = requests.post('https://chat.vercel.ai/api/chat', - headers=headers, json=json_data, stream=True, proxies={"https": proxy}) - if not response.ok: - continue - for token in response.iter_content(chunk_size=None): - try: - yield token.decode(errors="ignore") - except UnicodeDecodeError: - pass - break - raise_for_status(response) - -def get_anti_bot_token() -> str: - headers = { - 'authority': 'sdk.vercel.ai', - 'accept': '*/*', - 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', - 'cache-control': 'no-cache', - 'pragma': 'no-cache', - 'referer': 'https://sdk.vercel.ai/', - 'sec-ch-ua': '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"', - 'sec-ch-ua-mobile': '?0', - 'sec-ch-ua-platform': '"macOS"', - 'sec-fetch-dest': 'empty', - 'sec-fetch-mode': 'cors', - 'sec-fetch-site': 'same-origin', - 'user-agent': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36', - } - - response = requests.get('https://chat.vercel.ai/openai.jpeg', - headers=headers).text - - raw_data = json.loads(base64.b64decode(response, - validate=True)) - - js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`}; - return (%s)(%s)''' % (raw_data['c'], raw_data['a']) - - sec_list = [execjs.compile(js_script).call('')[0], [], "sentinel"] - - raw_token = json.dumps({'r': sec_list, 't': raw_data['t']}, - separators = (",", ":")) - - return base64.b64encode(raw_token.encode('utf-8')).decode()
\ No newline at end of file diff --git a/g4f/Provider/You.py b/g4f/Provider/You.py index af8aab0e..02735038 100644 --- a/g4f/Provider/You.py +++ b/g4f/Provider/You.py @@ -17,8 +17,6 @@ class You(AsyncGeneratorProvider, ProviderModelMixin): label = "You.com" url = "https://you.com" working = True - supports_gpt_35_turbo = True - supports_gpt_4 = True default_model = "gpt-4o-mini" default_vision_model = "agent" image_models = ["dall-e"] diff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py index a9a815ea..1caf8aaf 100644 --- a/g4f/Provider/__init__.py +++ b/g4f/Provider/__init__.py @@ -5,61 +5,69 @@ from ..providers.retry_provider import RetryProvider, IterListProvider from ..providers.base_provider import AsyncProvider, AsyncGeneratorProvider from ..providers.create_images import CreateImagesProvider -from .deprecated import * -from .selenium import * -from .needs_auth import * +from .deprecated import * +from .selenium import * +from .needs_auth import * +from .gigachat import * +from .nexra import * + +from .Ai4Chat import Ai4Chat from .AI365VIP import AI365VIP +from .AIChatFree import AIChatFree +from .AIUncensored import AIUncensored from .Allyfy import Allyfy +from .AmigoChat import AmigoChat from .AiChatOnline import AiChatOnline from .AiChats import AiChats +from .AiMathGPT import AiMathGPT +from .Airforce import Airforce from .Aura import Aura from .Bing import Bing from .BingCreateImages import BingCreateImages -from .Binjie import Binjie -from .Bixin123 import Bixin123 from .Blackbox import Blackbox from .ChatGot import ChatGot +from .ChatGpt import ChatGpt from .Chatgpt4Online import Chatgpt4Online from .Chatgpt4o import Chatgpt4o +from .ChatGptEs import ChatGptEs from .ChatgptFree import ChatgptFree -from .CodeNews import CodeNews +from .ChatHub import ChatHub +from .ChatifyAI import ChatifyAI +from .Cloudflare import Cloudflare +from .DarkAI import DarkAI from .DDG import DDG from .DeepInfra import DeepInfra +from .DeepInfraChat import DeepInfraChat from .DeepInfraImage import DeepInfraImage +from .Editee import Editee from .FlowGpt import FlowGpt -from .FluxAirforce import FluxAirforce from .Free2GPT import Free2GPT from .FreeChatgpt import FreeChatgpt from .FreeGpt import FreeGpt from .FreeNetfly import FreeNetfly from .GeminiPro import GeminiPro -from .GigaChat import GigaChat -from .GptTalkRu import GptTalkRu +from .GizAI import GizAI +from .GPROChat import GPROChat from .HuggingChat import HuggingChat from .HuggingFace import HuggingFace from .Koala import Koala from .Liaobots import Liaobots -from .LiteIcoding import LiteIcoding -from .Llama import Llama from .Local import Local from .MagickPen import MagickPen from .MetaAI import MetaAI -from .MetaAIAccount import MetaAIAccount -from .Nexra import Nexra +#from .MetaAIAccount import MetaAIAccount from .Ollama import Ollama from .PerplexityLabs import PerplexityLabs from .Pi import Pi from .Pizzagpt import Pizzagpt +from .Prodia import Prodia from .Reka import Reka -from .Snova import Snova from .Replicate import Replicate from .ReplicateHome import ReplicateHome -from .Rocks import Rocks +from .RubiksAI import RubiksAI from .TeachAnything import TeachAnything -from .TwitterBio import TwitterBio from .Upstage import Upstage -from .Vercel import Vercel from .WhiteRabbitNeo import WhiteRabbitNeo from .You import You diff --git a/g4f/Provider/bing/conversation.py b/g4f/Provider/bing/conversation.py index a4195fa4..b5c237f9 100644 --- a/g4f/Provider/bing/conversation.py +++ b/g4f/Provider/bing/conversation.py @@ -33,9 +33,9 @@ async def create_conversation(session: StreamSession, headers: dict, tone: str) Conversation: An instance representing the created conversation. """ if tone == "Copilot": - url = "https://copilot.microsoft.com/turing/conversation/create?bundleVersion=1.1690.0" + url = "https://copilot.microsoft.com/turing/conversation/create?bundleVersion=1.1809.0" else: - url = "https://www.bing.com/turing/conversation/create?bundleVersion=1.1690.0" + url = "https://www.bing.com/turing/conversation/create?bundleVersion=1.1809.0" async with session.get(url, headers=headers) as response: if response.status == 404: raise RateLimitError("Response 404: Do less requests and reuse conversations") @@ -90,4 +90,4 @@ async def delete_conversation(session: StreamSession, conversation: Conversation response = await response.json() return response["result"]["value"] == "Success" except: - return False
\ No newline at end of file + return False diff --git a/g4f/Provider/GigaChat.py b/g4f/Provider/gigachat/GigaChat.py index 8ba07b43..b1b293e3 100644 --- a/g4f/Provider/GigaChat.py +++ b/g4f/Provider/gigachat/GigaChat.py @@ -9,10 +9,10 @@ import json from aiohttp import ClientSession, TCPConnector, BaseConnector from g4f.requests import raise_for_status -from ..typing import AsyncResult, Messages -from .base_provider import AsyncGeneratorProvider, ProviderModelMixin -from ..errors import MissingAuthError -from .helper import get_connector +from ...typing import AsyncResult, Messages +from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ...errors import MissingAuthError +from ..helper import get_connector access_token = "" token_expires_at = 0 @@ -45,7 +45,7 @@ class GigaChat(AsyncGeneratorProvider, ProviderModelMixin): if not api_key: raise MissingAuthError('Missing "api_key"') - cafile = os.path.join(os.path.dirname(__file__), "gigachat_crt/russian_trusted_root_ca_pem.crt") + cafile = os.path.join(os.path.dirname(__file__), "russian_trusted_root_ca_pem.crt") ssl_context = ssl.create_default_context(cafile=cafile) if os.path.exists(cafile) else None if connector is None and ssl_context is not None: connector = TCPConnector(ssl_context=ssl_context) diff --git a/g4f/Provider/gigachat/__init__.py b/g4f/Provider/gigachat/__init__.py new file mode 100644 index 00000000..c9853742 --- /dev/null +++ b/g4f/Provider/gigachat/__init__.py @@ -0,0 +1,2 @@ +from .GigaChat import GigaChat + diff --git a/g4f/Provider/gigachat_crt/russian_trusted_root_ca_pem.crt b/g4f/Provider/gigachat/russian_trusted_root_ca_pem.crt index 4c143a21..4c143a21 100644 --- a/g4f/Provider/gigachat_crt/russian_trusted_root_ca_pem.crt +++ b/g4f/Provider/gigachat/russian_trusted_root_ca_pem.crt diff --git a/g4f/Provider/needs_auth/Gemini.py b/g4f/Provider/needs_auth/Gemini.py index eddd25fa..8d741476 100644 --- a/g4f/Provider/needs_auth/Gemini.py +++ b/g4f/Provider/needs_auth/Gemini.py @@ -54,6 +54,7 @@ class Gemini(AsyncGeneratorProvider): url = "https://gemini.google.com" needs_auth = True working = True + default_model = 'gemini' image_models = ["gemini"] default_vision_model = "gemini" _cookies: Cookies = None @@ -305,4 +306,4 @@ class Conversation(BaseConversation): ) -> None: self.conversation_id = conversation_id self.response_id = response_id - self.choice_id = choice_id
\ No newline at end of file + self.choice_id = choice_id diff --git a/g4f/Provider/needs_auth/Groq.py b/g4f/Provider/needs_auth/Groq.py index d11f6a82..027d98bf 100644 --- a/g4f/Provider/needs_auth/Groq.py +++ b/g4f/Provider/needs_auth/Groq.py @@ -8,7 +8,26 @@ class Groq(Openai): url = "https://console.groq.com/playground" working = True default_model = "mixtral-8x7b-32768" - models = ["mixtral-8x7b-32768", "llama2-70b-4096", "gemma-7b-it"] + models = [ + "distil-whisper-large-v3-en", + "gemma2-9b-it", + "gemma-7b-it", + "llama3-groq-70b-8192-tool-use-preview", + "llama3-groq-8b-8192-tool-use-preview", + "llama-3.1-70b-versatile", + "llama-3.1-8b-instant", + "llama-3.2-1b-preview", + "llama-3.2-3b-preview", + "llama-3.2-11b-vision-preview", + "llama-3.2-90b-vision-preview", + "llama-guard-3-8b", + "llava-v1.5-7b-4096-preview", + "llama3-70b-8192", + "llama3-8b-8192", + "mixtral-8x7b-32768", + "whisper-large-v3", + "whisper-large-v3-turbo", + ] model_aliases = {"mixtral-8x7b": "mixtral-8x7b-32768", "llama2-70b": "llama2-70b-4096"} @classmethod @@ -21,4 +40,4 @@ class Groq(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/OpenRouter.py b/g4f/Provider/needs_auth/OpenRouter.py index 7945784a..5e0bf336 100644 --- a/g4f/Provider/needs_auth/OpenRouter.py +++ b/g4f/Provider/needs_auth/OpenRouter.py @@ -8,7 +8,7 @@ from ...typing import AsyncResult, Messages class OpenRouter(Openai): label = "OpenRouter" url = "https://openrouter.ai" - working = True + working = False default_model = "mistralai/mistral-7b-instruct:free" @classmethod @@ -29,4 +29,4 @@ class OpenRouter(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/Openai.py b/g4f/Provider/needs_auth/Openai.py index a0740c47..382ebada 100644 --- a/g4f/Provider/needs_auth/Openai.py +++ b/g4f/Provider/needs_auth/Openai.py @@ -11,7 +11,7 @@ from ...image import to_data_uri class Openai(AsyncGeneratorProvider, ProviderModelMixin): label = "OpenAI API" - url = "https://openai.com" + url = "https://platform.openai.com" working = True needs_auth = True supports_message_history = True diff --git a/g4f/Provider/needs_auth/OpenaiChat.py b/g4f/Provider/needs_auth/OpenaiChat.py index 82462040..f02121e3 100644 --- a/g4f/Provider/needs_auth/OpenaiChat.py +++ b/g4f/Provider/needs_auth/OpenaiChat.py @@ -61,9 +61,11 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin): default_model = None default_vision_model = "gpt-4o" models = [ "auto", "gpt-4o-mini", "gpt-4o", "gpt-4", "gpt-4-gizmo"] + model_aliases = { - "gpt-4-turbo-preview": "gpt-4", - "dall-e": "gpt-4", + #"gpt-4-turbo": "gpt-4", + #"gpt-4": "gpt-4-gizmo", + #"dalle": "gpt-4", } _api_key: str = None _headers: dict = None diff --git a/g4f/Provider/needs_auth/PerplexityApi.py b/g4f/Provider/needs_auth/PerplexityApi.py index 35d8d9d6..3ee65b30 100644 --- a/g4f/Provider/needs_auth/PerplexityApi.py +++ b/g4f/Provider/needs_auth/PerplexityApi.py @@ -15,7 +15,6 @@ class PerplexityApi(Openai): "llama-3-sonar-large-32k-online", "llama-3-8b-instruct", "llama-3-70b-instruct", - "mixtral-8x7b-instruct" ] @classmethod @@ -28,4 +27,4 @@ class PerplexityApi(Openai): ) -> AsyncResult: return super().create_async_generator( model, messages, api_base=api_base, **kwargs - )
\ No newline at end of file + ) diff --git a/g4f/Provider/needs_auth/__init__.py b/g4f/Provider/needs_auth/__init__.py index b5463b71..0492645d 100644 --- a/g4f/Provider/needs_auth/__init__.py +++ b/g4f/Provider/needs_auth/__init__.py @@ -7,5 +7,5 @@ from .Poe import Poe from .Openai import Openai from .Groq import Groq from .OpenRouter import OpenRouter -from .OpenaiAccount import OpenaiAccount -from .PerplexityApi import PerplexityApi
\ No newline at end of file +#from .OpenaiAccount import OpenaiAccount +from .PerplexityApi import PerplexityApi diff --git a/g4f/Provider/nexra/NexraBing.py b/g4f/Provider/nexra/NexraBing.py new file mode 100644 index 00000000..28f0b117 --- /dev/null +++ b/g4f/Provider/nexra/NexraBing.py @@ -0,0 +1,93 @@ +from __future__ import annotations + +import json +import requests + +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ..helper import format_prompt + +class NexraBing(AbstractProvider, ProviderModelMixin): + label = "Nexra Bing" + url = "https://nexra.aryahcr.cc/documentation/bing/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'Balanced' + models = [default_model, 'Creative', 'Precise'] + + model_aliases = { + "gpt-4": "Balanced", + "gpt-4": "Creative", + "gpt-4": "Precise", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "conversation_style": model, + "markdown": markdown, + "stream": stream, + "model": "Bing" + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=True) + + return cls.process_response(response) + + @classmethod + def process_response(cls, response): + if response.status_code != 200: + yield f"Error: {response.status_code}" + return + + full_message = "" + for chunk in response.iter_content(chunk_size=None): + if chunk: + messages = chunk.decode('utf-8').split('\x1e') + for message in messages: + try: + json_data = json.loads(message) + if json_data.get('finish', False): + return + current_message = json_data.get('message', '') + if current_message: + new_content = current_message[len(full_message):] + if new_content: + yield new_content + full_message = current_message + except json.JSONDecodeError: + continue + + if not full_message: + yield "No message received" diff --git a/g4f/Provider/nexra/NexraBlackbox.py b/g4f/Provider/nexra/NexraBlackbox.py new file mode 100644 index 00000000..be048fdd --- /dev/null +++ b/g4f/Provider/nexra/NexraBlackbox.py @@ -0,0 +1,100 @@ +from __future__ import annotations + +import json +import requests + +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ..helper import format_prompt + +class NexraBlackbox(AbstractProvider, ProviderModelMixin): + label = "Nexra Blackbox" + url = "https://nexra.aryahcr.cc/documentation/blackbox/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = "blackbox" + models = [default_model] + model_aliases = {"blackboxai": "blackbox",} + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + proxy: str = None, + markdown: bool = False, + websearch: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "websearch": websearch, + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + full_response = "" + for line in response.iter_lines(decode_unicode=True): + if line: + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + full_response = message + return full_response + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + previous_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message and message != previous_message: + yield message[len(previous_message):] + previous_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraChatGPT.py b/g4f/Provider/nexra/NexraChatGPT.py new file mode 100644 index 00000000..074a0363 --- /dev/null +++ b/g4f/Provider/nexra/NexraChatGPT.py @@ -0,0 +1,285 @@ +from __future__ import annotations + +import asyncio +import json +import requests +from typing import Any, Dict + +from ...typing import AsyncResult, Messages +from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin +from ..helper import format_prompt + + +class NexraChatGPT(AsyncGeneratorProvider, ProviderModelMixin): + label = "Nexra ChatGPT" + url = "https://nexra.aryahcr.cc/documentation/chatgpt/en" + api_endpoint_nexra_chatgpt = "https://nexra.aryahcr.cc/api/chat/gpt" + api_endpoint_nexra_chatgpt4o = "https://nexra.aryahcr.cc/api/chat/complements" + api_endpoint_nexra_chatgpt_v2 = "https://nexra.aryahcr.cc/api/chat/complements" + api_endpoint_nexra_gptweb = "https://nexra.aryahcr.cc/api/chat/gptweb" + working = True + supports_system_message = True + supports_message_history = True + supports_stream = True + + default_model = 'gpt-3.5-turbo' + nexra_chatgpt = [ + 'gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314', + default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', + 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002' + ] + nexra_chatgpt4o = ['gpt-4o'] + nexra_chatgptv2 = ['chatgpt'] + nexra_gptweb = ['gptweb'] + models = nexra_chatgpt + nexra_chatgpt4o + nexra_chatgptv2 + nexra_gptweb + + model_aliases = { + "gpt-4": "gpt-4-0613", + "gpt-4-32k": "gpt-4-32k-0314", + "gpt-3.5-turbo": "gpt-3.5-turbo-16k", + "gpt-3.5-turbo-0613": "gpt-3.5-turbo-16k-0613", + "gpt-3": "text-davinci-003", + "text-davinci-002": "code-davinci-002", + "text-curie-001": "text-babbage-001", + "text-ada-001": "davinci", + "curie": "babbage", + "ada": "babbage-002", + "davinci-002": "davinci-002", + "chatgpt": "chatgpt", + "gptweb": "gptweb" + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + async def create_async_generator( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + if model in cls.nexra_chatgpt: + async for chunk in cls._create_async_generator_nexra_chatgpt(model, messages, proxy, **kwargs): + yield chunk + elif model in cls.nexra_chatgpt4o: + async for chunk in cls._create_async_generator_nexra_chatgpt4o(model, messages, stream, proxy, markdown, **kwargs): + yield chunk + elif model in cls.nexra_chatgptv2: + async for chunk in cls._create_async_generator_nexra_chatgpt_v2(model, messages, stream, proxy, markdown, **kwargs): + yield chunk + elif model in cls.nexra_gptweb: + async for chunk in cls._create_async_generator_nexra_gptweb(model, messages, proxy, **kwargs): + yield chunk + + @classmethod + async def _create_async_generator_nexra_chatgpt( + cls, + model: str, + messages: Messages, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": messages, + "prompt": prompt, + "model": model, + "markdown": markdown + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt, data, headers, proxy) + filtered_response = cls._filter_response(response) + + for chunk in filtered_response: + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt): {e}") + + @classmethod + async def _create_async_generator_nexra_chatgpt4o( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": [ + { + "role": "user", + "content": prompt + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt4o, data, headers, proxy, stream) + + if stream: + async for chunk in cls._process_streaming_response(response): + yield chunk + else: + for chunk in cls._process_non_streaming_response(response): + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt4o): {e}") + + @classmethod + async def _create_async_generator_nexra_chatgpt_v2( + cls, + model: str, + messages: Messages, + stream: bool = False, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "messages": [ + { + "role": "user", + "content": prompt + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt_v2, data, headers, proxy, stream) + + if stream: + async for chunk in cls._process_streaming_response(response): + yield chunk + else: + for chunk in cls._process_non_streaming_response(response): + yield chunk + except Exception as e: + print(f"Error during API request (nexra_chatgpt_v2): {e}") + + @classmethod + async def _create_async_generator_nexra_gptweb( + cls, + model: str, + messages: Messages, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> AsyncResult: + model = cls.get_model(model) + + headers = { + "Content-Type": "application/json" + } + + prompt = format_prompt(messages) + data = { + "prompt": prompt, + "markdown": markdown, + } + + loop = asyncio.get_event_loop() + try: + response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_gptweb, data, headers, proxy) + + for chunk in response.iter_content(1024): + if chunk: + decoded_chunk = chunk.decode().lstrip('_') + try: + response_json = json.loads(decoded_chunk) + if response_json.get("status"): + yield response_json.get("gpt", "") + except json.JSONDecodeError: + continue + except Exception as e: + print(f"Error during API request (nexra_gptweb): {e}") + + @staticmethod + def _sync_post_request(url: str, data: Dict[str, Any], headers: Dict[str, str], proxy: str = None, stream: bool = False) -> requests.Response: + proxies = { + "http": proxy, + "https": proxy, + } if proxy else None + + try: + response = requests.post(url, json=data, headers=headers, proxies=proxies, stream=stream) + response.raise_for_status() + return response + except requests.RequestException as e: + print(f"Request failed: {e}") + raise + + @staticmethod + def _process_non_streaming_response(response: requests.Response) -> str: + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @staticmethod + async def _process_streaming_response(response: requests.Response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass + + @staticmethod + def _filter_response(response: requests.Response) -> str: + response_json = response.json() + return response_json.get("gpt", "") diff --git a/g4f/Provider/nexra/NexraDallE.py b/g4f/Provider/nexra/NexraDallE.py new file mode 100644 index 00000000..f605c6d0 --- /dev/null +++ b/g4f/Provider/nexra/NexraDallE.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraDallE(AbstractProvider, ProviderModelMixin): + label = "Nexra DALL-E" + url = "https://nexra.aryahcr.cc/documentation/dall-e/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "dalle" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraDallE2.py b/g4f/Provider/nexra/NexraDallE2.py new file mode 100644 index 00000000..2a36b6e6 --- /dev/null +++ b/g4f/Provider/nexra/NexraDallE2.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraDallE2(AbstractProvider, ProviderModelMixin): + label = "Nexra DALL-E 2" + url = "https://nexra.aryahcr.cc/documentation/dall-e/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "dalle2" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraEmi.py b/g4f/Provider/nexra/NexraEmi.py new file mode 100644 index 00000000..c26becec --- /dev/null +++ b/g4f/Provider/nexra/NexraEmi.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraEmi(AbstractProvider, ProviderModelMixin): + label = "Nexra Emi" + url = "https://nexra.aryahcr.cc/documentation/emi/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "emi" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraFluxPro.py b/g4f/Provider/nexra/NexraFluxPro.py new file mode 100644 index 00000000..cfb26385 --- /dev/null +++ b/g4f/Provider/nexra/NexraFluxPro.py @@ -0,0 +1,70 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraFluxPro(AbstractProvider, ProviderModelMixin): + url = "https://nexra.aryahcr.cc/documentation/flux-pro/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'flux' + models = [default_model] + model_aliases = { + "flux-pro": "flux", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraGeminiPro.py b/g4f/Provider/nexra/NexraGeminiPro.py new file mode 100644 index 00000000..e4e6a8ec --- /dev/null +++ b/g4f/Provider/nexra/NexraGeminiPro.py @@ -0,0 +1,86 @@ +from __future__ import annotations + +import json +import requests + +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ..helper import format_prompt + +class NexraGeminiPro(AbstractProvider, ProviderModelMixin): + label = "Nexra Gemini PRO" + url = "https://nexra.aryahcr.cc/documentation/gemini-pro/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'gemini-pro' + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraMidjourney.py b/g4f/Provider/nexra/NexraMidjourney.py new file mode 100644 index 00000000..c427f8a0 --- /dev/null +++ b/g4f/Provider/nexra/NexraMidjourney.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraMidjourney(AbstractProvider, ProviderModelMixin): + label = "Nexra Midjourney" + url = "https://nexra.aryahcr.cc/documentation/midjourney/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "midjourney" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraProdiaAI.py b/g4f/Provider/nexra/NexraProdiaAI.py new file mode 100644 index 00000000..de997fce --- /dev/null +++ b/g4f/Provider/nexra/NexraProdiaAI.py @@ -0,0 +1,151 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraProdiaAI(AbstractProvider, ProviderModelMixin): + label = "Nexra Prodia AI" + url = "https://nexra.aryahcr.cc/documentation/prodia/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'absolutereality_v181.safetensors [3d9d4d2b]' + models = [ + '3Guofeng3_v34.safetensors [50f420de]', + 'absolutereality_V16.safetensors [37db0fc3]', + default_model, + 'amIReal_V41.safetensors [0a8a2e61]', + 'analog-diffusion-1.0.ckpt [9ca13f02]', + 'aniverse_v30.safetensors [579e6f85]', + 'anythingv3_0-pruned.ckpt [2700c435]', + 'anything-v4.5-pruned.ckpt [65745d25]', + 'anythingV5_PrtRE.safetensors [893e49b9]', + 'AOM3A3_orangemixs.safetensors [9600da17]', + 'blazing_drive_v10g.safetensors [ca1c1eab]', + 'breakdomain_I2428.safetensors [43cc7d2f]', + 'breakdomain_M2150.safetensors [15f7afca]', + 'cetusMix_Version35.safetensors [de2f2560]', + 'childrensStories_v13D.safetensors [9dfaabcb]', + 'childrensStories_v1SemiReal.safetensors [a1c56dbb]', + 'childrensStories_v1ToonAnime.safetensors [2ec7b88b]', + 'Counterfeit_v30.safetensors [9e2a8f19]', + 'cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]', + 'cyberrealistic_v33.safetensors [82b0d085]', + 'dalcefo_v4.safetensors [425952fe]', + 'deliberate_v2.safetensors [10ec4b29]', + 'deliberate_v3.safetensors [afd9d2d4]', + 'dreamlike-anime-1.0.safetensors [4520e090]', + 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]', + 'dreamlike-photoreal-2.0.safetensors [fdcf65e7]', + 'dreamshaper_6BakedVae.safetensors [114c8abb]', + 'dreamshaper_7.safetensors [5cf5ae06]', + 'dreamshaper_8.safetensors [9d40847d]', + 'edgeOfRealism_eorV20.safetensors [3ed5de15]', + 'EimisAnimeDiffusion_V1.ckpt [4f828a15]', + 'elldreths-vivid-mix.safetensors [342d9d26]', + 'epicphotogasm_xPlusPlus.safetensors [1a8f6d35]', + 'epicrealism_naturalSinRC1VAE.safetensors [90a4c676]', + 'epicrealism_pureEvolutionV3.safetensors [42c8440c]', + 'ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]', + 'indigoFurryMix_v75Hybrid.safetensors [91208cbb]', + 'juggernaut_aftermath.safetensors [5e20c455]', + 'lofi_v4.safetensors [ccc204d6]', + 'lyriel_v16.safetensors [68fceea2]', + 'majicmixRealistic_v4.safetensors [29d0de58]', + 'mechamix_v10.safetensors [ee685731]', + 'meinamix_meinaV9.safetensors [2ec66ab0]', + 'meinamix_meinaV11.safetensors [b56ce717]', + 'neverendingDream_v122.safetensors [f964ceeb]', + 'openjourney_V4.ckpt [ca2f377f]', + 'pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]', + 'portraitplus_V1.0.safetensors [1400e684]', + 'protogenx34.safetensors [5896f8d5]', + 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]', + 'Realistic_Vision_V2.0.safetensors [79587710]', + 'Realistic_Vision_V4.0.safetensors [29a7afaa]', + 'Realistic_Vision_V5.0.safetensors [614d1063]', + 'Realistic_Vision_V5.1.safetensors [a0f13c83]', + 'redshift_diffusion-V10.safetensors [1400e684]', + 'revAnimated_v122.safetensors [3f4fefd9]', + 'rundiffusionFX25D_v10.safetensors [cd12b0ee]', + 'rundiffusionFX_v10.safetensors [cd4e694d]', + 'sdv1_4.ckpt [7460a6fa]', + 'v1-5-pruned-emaonly.safetensors [d7049739]', + 'v1-5-inpainting.safetensors [21c7ab71]', + 'shoninsBeautiful_v10.safetensors [25d8c546]', + 'theallys-mix-ii-churned.safetensors [5d9225a4]', + 'timeless-1.0.ckpt [7c4971d4]', + 'toonyou_beta6.safetensors [980f6b15]', + ] + + model_aliases = {} + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + steps: str = 25, # Min: 1, Max: 30 + cfg_scale: str = 7, # Min: 0, Max: 20 + sampler: str = "DPM++ 2M Karras", # Select from these: "Euler","Euler a","Heun","DPM++ 2M Karras","DPM++ SDE Karras","DDIM" + negative_prompt: str = "", # Indicates what the AI should not do + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": "prodia", + "response": response, + "data": { + "model": model, + "steps": steps, + "cfg_scale": cfg_scale, + "sampler": sampler, + "negative_prompt": negative_prompt + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') # Remove leading underscores + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraQwen.py b/g4f/Provider/nexra/NexraQwen.py new file mode 100644 index 00000000..7f944e44 --- /dev/null +++ b/g4f/Provider/nexra/NexraQwen.py @@ -0,0 +1,86 @@ +from __future__ import annotations + +import json +import requests + +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ..helper import format_prompt + +class NexraQwen(AbstractProvider, ProviderModelMixin): + label = "Nexra Qwen" + url = "https://nexra.aryahcr.cc/documentation/qwen/en" + api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" + working = True + supports_stream = True + + default_model = 'qwen' + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + stream: bool, + proxy: str = None, + markdown: bool = False, + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "messages": [ + { + "role": "user", + "content": format_prompt(messages) + } + ], + "stream": stream, + "markdown": markdown, + "model": model + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) + + if stream: + return cls.process_streaming_response(response) + else: + return cls.process_non_streaming_response(response) + + @classmethod + def process_non_streaming_response(cls, response): + if response.status_code == 200: + try: + content = response.text.lstrip(' ') + data = json.loads(content) + return data.get('message', '') + except json.JSONDecodeError: + return "Error: Unable to decode JSON response" + else: + return f"Error: {response.status_code}" + + @classmethod + def process_streaming_response(cls, response): + full_message = "" + for line in response.iter_lines(decode_unicode=True): + if line: + try: + line = line.lstrip(' ') + data = json.loads(line) + if data.get('finish'): + break + message = data.get('message', '') + if message is not None and message != full_message: + yield message[len(full_message):] + full_message = message + except json.JSONDecodeError: + pass diff --git a/g4f/Provider/nexra/NexraSD15.py b/g4f/Provider/nexra/NexraSD15.py new file mode 100644 index 00000000..860a132f --- /dev/null +++ b/g4f/Provider/nexra/NexraSD15.py @@ -0,0 +1,72 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSD15(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion 1.5" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = 'stablediffusion-1.5' + models = [default_model] + + model_aliases = { + "sd-1.5": "stablediffusion-1.5", + } + + @classmethod + def get_model(cls, model: str) -> str: + if model in cls.models: + return model + elif model in cls.model_aliases: + return cls.model_aliases[model] + else: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraSDLora.py b/g4f/Provider/nexra/NexraSDLora.py new file mode 100644 index 00000000..a12bff1a --- /dev/null +++ b/g4f/Provider/nexra/NexraSDLora.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSDLora(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion Lora" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "sdxl-lora" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + guidance: str = 0.3, # Min: 0, Max: 5 + steps: str = 2, # Min: 2, Max: 10 + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response, + "data": { + "guidance": guidance, + "steps": steps + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/NexraSDTurbo.py b/g4f/Provider/nexra/NexraSDTurbo.py new file mode 100644 index 00000000..865b4522 --- /dev/null +++ b/g4f/Provider/nexra/NexraSDTurbo.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +import json +import requests +from ...typing import CreateResult, Messages +from ..base_provider import ProviderModelMixin, AbstractProvider +from ...image import ImageResponse + +class NexraSDTurbo(AbstractProvider, ProviderModelMixin): + label = "Nexra Stable Diffusion Turbo" + url = "https://nexra.aryahcr.cc/documentation/stable-diffusion/en" + api_endpoint = "https://nexra.aryahcr.cc/api/image/complements" + working = True + + default_model = "sdxl-turbo" + models = [default_model] + + @classmethod + def get_model(cls, model: str) -> str: + return cls.default_model + + @classmethod + def create_completion( + cls, + model: str, + messages: Messages, + proxy: str = None, + response: str = "url", # base64 or url + strength: str = 0.7, # Min: 0, Max: 1 + steps: str = 2, # Min: 1, Max: 10 + **kwargs + ) -> CreateResult: + model = cls.get_model(model) + + headers = { + 'Content-Type': 'application/json' + } + + data = { + "prompt": messages[-1]["content"], + "model": model, + "response": response, + "data": { + "strength": strength, + "steps": steps + } + } + + response = requests.post(cls.api_endpoint, headers=headers, json=data) + + result = cls.process_response(response) + yield result + + @classmethod + def process_response(cls, response): + if response.status_code == 200: + try: + content = response.text.strip() + content = content.lstrip('_') # Remove the leading underscore + data = json.loads(content) + if data.get('status') and data.get('images'): + image_url = data['images'][0] + return ImageResponse(images=[image_url], alt="Generated Image") + else: + return "Error: No image URL found in the response" + except json.JSONDecodeError as e: + return f"Error: Unable to decode JSON response. Details: {str(e)}" + else: + return f"Error: {response.status_code}, Response: {response.text}" diff --git a/g4f/Provider/nexra/__init__.py b/g4f/Provider/nexra/__init__.py new file mode 100644 index 00000000..bebc1fb6 --- /dev/null +++ b/g4f/Provider/nexra/__init__.py @@ -0,0 +1,14 @@ +from .NexraBing import NexraBing +from .NexraBlackbox import NexraBlackbox +from .NexraChatGPT import NexraChatGPT +from .NexraDallE import NexraDallE +from .NexraDallE2 import NexraDallE2 +from .NexraEmi import NexraEmi +from .NexraFluxPro import NexraFluxPro +from .NexraGeminiPro import NexraGeminiPro +from .NexraMidjourney import NexraMidjourney +from .NexraProdiaAI import NexraProdiaAI +from .NexraQwen import NexraQwen +from .NexraSD15 import NexraSD15 +from .NexraSDLora import NexraSDLora +from .NexraSDTurbo import NexraSDTurbo diff --git a/g4f/Provider/openai/new.py b/g4f/Provider/openai/new.py new file mode 100644 index 00000000..f4d8e13d --- /dev/null +++ b/g4f/Provider/openai/new.py @@ -0,0 +1,730 @@ +import hashlib +import base64 +import random +import json +import time +import uuid + +from collections import OrderedDict, defaultdict +from typing import Any, Callable, Dict, List + +from datetime import ( + datetime, + timedelta, + timezone +) + +cores = [16, 24, 32] +screens = [3000, 4000, 6000] +maxAttempts = 500000 + +navigator_keys = [ + "registerProtocolHandler−function registerProtocolHandler() { [native code] }", + "storage−[object StorageManager]", + "locks−[object LockManager]", + "appCodeName−Mozilla", + "permissions−[object Permissions]", + "appVersion−5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "share−function share() { [native code] }", + "webdriver−false", + "managed−[object NavigatorManagedData]", + "canShare−function canShare() { [native code] }", + "vendor−Google Inc.", + "vendor−Google Inc.", + "mediaDevices−[object MediaDevices]", + "vibrate−function vibrate() { [native code] }", + "storageBuckets−[object StorageBucketManager]", + "mediaCapabilities−[object MediaCapabilities]", + "getGamepads−function getGamepads() { [native code] }", + "bluetooth−[object Bluetooth]", + "share−function share() { [native code] }", + "cookieEnabled−true", + "virtualKeyboard−[object VirtualKeyboard]", + "product−Gecko", + "mediaDevices−[object MediaDevices]", + "canShare−function canShare() { [native code] }", + "getGamepads−function getGamepads() { [native code] }", + "product−Gecko", + "xr−[object XRSystem]", + "clipboard−[object Clipboard]", + "storageBuckets−[object StorageBucketManager]", + "unregisterProtocolHandler−function unregisterProtocolHandler() { [native code] }", + "productSub−20030107", + "login−[object NavigatorLogin]", + "vendorSub−", + "login−[object NavigatorLogin]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "mediaDevices−[object MediaDevices]", + "locks−[object LockManager]", + "webkitGetUserMedia−function webkitGetUserMedia() { [native code] }", + "vendor−Google Inc.", + "xr−[object XRSystem]", + "mediaDevices−[object MediaDevices]", + "virtualKeyboard−[object VirtualKeyboard]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "virtualKeyboard−[object VirtualKeyboard]", + "appName−Netscape", + "storageBuckets−[object StorageBucketManager]", + "presentation−[object Presentation]", + "onLine−true", + "mimeTypes−[object MimeTypeArray]", + "credentials−[object CredentialsContainer]", + "presentation−[object Presentation]", + "getGamepads−function getGamepads() { [native code] }", + "vendorSub−", + "virtualKeyboard−[object VirtualKeyboard]", + "serviceWorker−[object ServiceWorkerContainer]", + "xr−[object XRSystem]", + "product−Gecko", + "keyboard−[object Keyboard]", + "gpu−[object GPU]", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "webkitPersistentStorage−[object DeprecatedStorageQuota]", + "doNotTrack", + "clearAppBadge−function clearAppBadge() { [native code] }", + "presentation−[object Presentation]", + "serial−[object Serial]", + "locks−[object LockManager]", + "requestMIDIAccess−function requestMIDIAccess() { [native code] }", + "locks−[object LockManager]", + "requestMediaKeySystemAccess−function requestMediaKeySystemAccess() { [native code] }", + "vendor−Google Inc.", + "pdfViewerEnabled−true", + "language−zh-CN", + "setAppBadge−function setAppBadge() { [native code] }", + "geolocation−[object Geolocation]", + "userAgentData−[object NavigatorUAData]", + "mediaCapabilities−[object MediaCapabilities]", + "requestMIDIAccess−function requestMIDIAccess() { [native code] }", + "getUserMedia−function getUserMedia() { [native code] }", + "mediaDevices−[object MediaDevices]", + "webkitPersistentStorage−[object DeprecatedStorageQuota]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "sendBeacon−function sendBeacon() { [native code] }", + "hardwareConcurrency−32", + "appVersion−5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "credentials−[object CredentialsContainer]", + "storage−[object StorageManager]", + "cookieEnabled−true", + "pdfViewerEnabled−true", + "windowControlsOverlay−[object WindowControlsOverlay]", + "scheduling−[object Scheduling]", + "pdfViewerEnabled−true", + "hardwareConcurrency−32", + "xr−[object XRSystem]", + "userAgent−Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0", + "webdriver−false", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "getInstalledRelatedApps−function getInstalledRelatedApps() { [native code] }", + "bluetooth−[object Bluetooth]" +] + +window_keys = [ + "0", + "window", + "self", + "document", + "name", + "location", + "customElements", + "history", + "navigation", + "locationbar", + "menubar", + "personalbar", + "scrollbars", + "statusbar", + "toolbar", + "status", + "closed", + "frames", + "length", + "top", + "opener", + "parent", + "frameElement", + "navigator", + "origin", + "external", + "screen", + "innerWidth", + "innerHeight", + "scrollX", + "pageXOffset", + "scrollY", + "pageYOffset", + "visualViewport", + "screenX", + "screenY", + "outerWidth", + "outerHeight", + "devicePixelRatio", + "clientInformation", + "screenLeft", + "screenTop", + "styleMedia", + "onsearch", + "isSecureContext", + "trustedTypes", + "performance", + "onappinstalled", + "onbeforeinstallprompt", + "crypto", + "indexedDB", + "sessionStorage", + "localStorage", + "onbeforexrselect", + "onabort", + "onbeforeinput", + "onbeforematch", + "onbeforetoggle", + "onblur", + "oncancel", + "oncanplay", + "oncanplaythrough", + "onchange", + "onclick", + "onclose", + "oncontentvisibilityautostatechange", + "oncontextlost", + "oncontextmenu", + "oncontextrestored", + "oncuechange", + "ondblclick", + "ondrag", + "ondragend", + "ondragenter", + "ondragleave", + "ondragover", + "ondragstart", + "ondrop", + "ondurationchange", + "onemptied", + "onended", + "onerror", + "onfocus", + "onformdata", + "oninput", + "oninvalid", + "onkeydown", + "onkeypress", + "onkeyup", + "onload", + "onloadeddata", + "onloadedmetadata", + "onloadstart", + "onmousedown", + "onmouseenter", + "onmouseleave", + "onmousemove", + "onmouseout", + "onmouseover", + "onmouseup", + "onmousewheel", + "onpause", + "onplay", + "onplaying", + "onprogress", + "onratechange", + "onreset", + "onresize", + "onscroll", + "onsecuritypolicyviolation", + "onseeked", + "onseeking", + "onselect", + "onslotchange", + "onstalled", + "onsubmit", + "onsuspend", + "ontimeupdate", + "ontoggle", + "onvolumechange", + "onwaiting", + "onwebkitanimationend", + "onwebkitanimationiteration", + "onwebkitanimationstart", + "onwebkittransitionend", + "onwheel", + "onauxclick", + "ongotpointercapture", + "onlostpointercapture", + "onpointerdown", + "onpointermove", + "onpointerrawupdate", + "onpointerup", + "onpointercancel", + "onpointerover", + "onpointerout", + "onpointerenter", + "onpointerleave", + "onselectstart", + "onselectionchange", + "onanimationend", + "onanimationiteration", + "onanimationstart", + "ontransitionrun", + "ontransitionstart", + "ontransitionend", + "ontransitioncancel", + "onafterprint", + "onbeforeprint", + "onbeforeunload", + "onhashchange", + "onlanguagechange", + "onmessage", + "onmessageerror", + "onoffline", + "ononline", + "onpagehide", + "onpageshow", + "onpopstate", + "onrejectionhandled", + "onstorage", + "onunhandledrejection", + "onunload", + "crossOriginIsolated", + "scheduler", + "alert", + "atob", + "blur", + "btoa", + "cancelAnimationFrame", + "cancelIdleCallback", + "captureEvents", + "clearInterval", + "clearTimeout", + "close", + "confirm", + "createImageBitmap", + "fetch", + "find", + "focus", + "getComputedStyle", + "getSelection", + "matchMedia", + "moveBy", + "moveTo", + "open", + "postMessage", + "print", + "prompt", + "queueMicrotask", + "releaseEvents", + "reportError", + "requestAnimationFrame", + "requestIdleCallback", + "resizeBy", + "resizeTo", + "scroll", + "scrollBy", + "scrollTo", + "setInterval", + "setTimeout", + "stop", + "structuredClone", + "webkitCancelAnimationFrame", + "webkitRequestAnimationFrame", + "chrome", + "g_opr", + "opr", + "ethereum", + "caches", + "cookieStore", + "ondevicemotion", + "ondeviceorientation", + "ondeviceorientationabsolute", + "launchQueue", + "documentPictureInPicture", + "getScreenDetails", + "queryLocalFonts", + "showDirectoryPicker", + "showOpenFilePicker", + "showSaveFilePicker", + "originAgentCluster", + "credentialless", + "speechSynthesis", + "onscrollend", + "webkitRequestFileSystem", + "webkitResolveLocalFileSystemURL", + "__remixContext", + "__oai_SSR_TTI", + "__remixManifest", + "__reactRouterVersion", + "DD_RUM", + "__REACT_INTL_CONTEXT__", + "filterCSS", + "filterXSS", + "__SEGMENT_INSPECTOR__", + "DD_LOGS", + "regeneratorRuntime", + "_g", + "__remixRouteModules", + "__remixRouter", + "__STATSIG_SDK__", + "__STATSIG_JS_SDK__", + "__STATSIG_RERENDER_OVERRIDE__", + "_oaiHandleSessionExpired" +] + +def get_parse_time(): + now = datetime.now(timezone(timedelta(hours=-5))) + return now.strftime("%a %b %d %Y %H:%M:%S") + " GMT+0200 (Central European Summer Time)" + +def get_config(user_agent): + + core = random.choice(cores) + screen = random.choice(screens) + + # partially hardcoded config + config = [ + core + screen, + get_parse_time(), + 4294705152, + random.random(), + user_agent, + None, + "remix-prod-15f1ec0f78ad898b9606a88d384ef76345b82b82", #document.documentElement.getAttribute("data-build"), + "en-US", + "en-US,es-US,en,es", + 0, + random.choice(navigator_keys), + 'location', + random.choice(window_keys), + time.perf_counter(), + str(uuid.uuid4()), + ] + + return config + + +def get_answer_token(seed, diff, config): + answer, solved = generate_answer(seed, diff, config) + + if solved: + return "gAAAAAB" + answer + else: + raise Exception("Failed to solve 'gAAAAAB' challenge") + +def generate_answer(seed, diff, config): + diff_len = len(diff) + seed_encoded = seed.encode() + p1 = (json.dumps(config[:3], separators=(',', ':'), ensure_ascii=False)[:-1] + ',').encode() + p2 = (',' + json.dumps(config[4:9], separators=(',', ':'), ensure_ascii=False)[1:-1] + ',').encode() + p3 = (',' + json.dumps(config[10:], separators=(',', ':'), ensure_ascii=False)[1:]).encode() + + target_diff = bytes.fromhex(diff) + + for i in range(maxAttempts): + d1 = str(i).encode() + d2 = str(i >> 1).encode() + + string = ( + p1 + + d1 + + p2 + + d2 + + p3 + ) + + base_encode = base64.b64encode(string) + hash_value = hashlib.new("sha3_512", seed_encoded + base_encode).digest() + + if hash_value[:diff_len] <= target_diff: + return base_encode.decode(), True + + return 'wQ8Lk5FbGpA2NcR9dShT6gYjU7VxZ4D' + base64.b64encode(f'"{seed}"'.encode()).decode(), False + +def get_requirements_token(config): + require, solved = generate_answer(format(random.random()), "0fffff", config) + + if solved: + return 'gAAAAAC' + require + else: + raise Exception("Failed to solve 'gAAAAAC' challenge") + + +### processing turnstile token + +class OrderedMap: + def __init__(self): + self.map = OrderedDict() + + def add(self, key: str, value: Any): + self.map[key] = value + + def to_json(self): + return json.dumps(self.map) + + def __str__(self): + return self.to_json() + + +TurnTokenList = List[List[Any]] +FloatMap = Dict[float, Any] +StringMap = Dict[str, Any] +FuncType = Callable[..., Any] + +start_time = time.time() + +def get_turnstile_token(dx: str, p: str) -> str: + decoded_bytes = base64.b64decode(dx) + # print(decoded_bytes.decode()) + return process_turnstile_token(decoded_bytes.decode(), p) + + +def process_turnstile_token(dx: str, p: str) -> str: + result = [] + p_length = len(p) + if p_length != 0: + for i, r in enumerate(dx): + result.append(chr(ord(r) ^ ord(p[i % p_length]))) + else: + result = list(dx) + return "".join(result) + + +def is_slice(input_val: Any) -> bool: + return isinstance(input_val, (list, tuple)) + + +def is_float(input_val: Any) -> bool: + return isinstance(input_val, float) + + +def is_string(input_val: Any) -> bool: + return isinstance(input_val, str) + + +def to_str(input_val: Any) -> str: + if input_val is None: + return "undefined" + elif is_float(input_val): + return f"{input_val:.16g}" + elif is_string(input_val): + special_cases = { + "window.Math": "[object Math]", + "window.Reflect": "[object Reflect]", + "window.performance": "[object Performance]", + "window.localStorage": "[object Storage]", + "window.Object": "function Object() { [native code] }", + "window.Reflect.set": "function set() { [native code] }", + "window.performance.now": "function () { [native code] }", + "window.Object.create": "function create() { [native code] }", + "window.Object.keys": "function keys() { [native code] }", + "window.Math.random": "function random() { [native code] }", + } + return special_cases.get(input_val, input_val) + elif isinstance(input_val, list) and all( + isinstance(item, str) for item in input_val + ): + return ",".join(input_val) + else: + # print(f"Type of input is: {type(input_val)}") + return str(input_val) + + +def get_func_map() -> FloatMap: + process_map: FloatMap = defaultdict(lambda: None) + + def func_1(e: float, t: float): + e_str = to_str(process_map[e]) + t_str = to_str(process_map[t]) + if e_str is not None and t_str is not None: + res = process_turnstile_token(e_str, t_str) + process_map[e] = res + else: + pass + # print(f"Warning: Unable to process func_1 for e={e}, t={t}") + + def func_2(e: float, t: Any): + process_map[e] = t + + def func_5(e: float, t: float): + n = process_map[e] + tres = process_map[t] + if n is None: + process_map[e] = tres + elif is_slice(n): + nt = n + [tres] if tres is not None else n + process_map[e] = nt + else: + if is_string(n) or is_string(tres): + res = to_str(n) + to_str(tres) + elif is_float(n) and is_float(tres): + res = n + tres + else: + res = "NaN" + process_map[e] = res + + def func_6(e: float, t: float, n: float): + tv = process_map[t] + nv = process_map[n] + if is_string(tv) and is_string(nv): + res = f"{tv}.{nv}" + if res == "window.document.location": + process_map[e] = "https://chatgpt.com/" + else: + process_map[e] = res + else: + pass + # print("func type 6 error") + + def func_24(e: float, t: float, n: float): + tv = process_map[t] + nv = process_map[n] + if is_string(tv) and is_string(nv): + process_map[e] = f"{tv}.{nv}" + else: + pass + # print("func type 24 error") + + def func_7(e: float, *args): + n = [process_map[arg] for arg in args] + ev = process_map[e] + if isinstance(ev, str): + if ev == "window.Reflect.set": + obj = n[0] + key_str = str(n[1]) + val = n[2] + obj.add(key_str, val) + elif callable(ev): + ev(*n) + + def func_17(e: float, t: float, *args): + i = [process_map[arg] for arg in args] + tv = process_map[t] + res = None + if isinstance(tv, str): + if tv == "window.performance.now": + current_time = time.time_ns() + elapsed_ns = current_time - int(start_time * 1e9) + res = (elapsed_ns + random.random()) / 1e6 + elif tv == "window.Object.create": + res = OrderedMap() + elif tv == "window.Object.keys": + if isinstance(i[0], str) and i[0] == "window.localStorage": + res = [ + "STATSIG_LOCAL_STORAGE_INTERNAL_STORE_V4", + "STATSIG_LOCAL_STORAGE_STABLE_ID", + "client-correlated-secret", + "oai/apps/capExpiresAt", + "oai-did", + "STATSIG_LOCAL_STORAGE_LOGGING_REQUEST", + "UiState.isNavigationCollapsed.1", + ] + elif tv == "window.Math.random": + res = random.random() + elif callable(tv): + res = tv(*i) + process_map[e] = res + + def func_8(e: float, t: float): + process_map[e] = process_map[t] + + def func_14(e: float, t: float): + tv = process_map[t] + if is_string(tv): + try: + token_list = json.loads(tv) + process_map[e] = token_list + except json.JSONDecodeError: + # print(f"Warning: Unable to parse JSON for key {t}") + process_map[e] = None + else: + # print(f"Warning: Value for key {t} is not a string") + process_map[e] = None + + def func_15(e: float, t: float): + tv = process_map[t] + process_map[e] = json.dumps(tv) + + def func_18(e: float): + ev = process_map[e] + e_str = to_str(ev) + decoded = base64.b64decode(e_str).decode() + process_map[e] = decoded + + def func_19(e: float): + ev = process_map[e] + e_str = to_str(ev) + encoded = base64.b64encode(e_str.encode()).decode() + process_map[e] = encoded + + def func_20(e: float, t: float, n: float, *args): + o = [process_map[arg] for arg in args] + ev = process_map[e] + tv = process_map[t] + if ev == tv: + nv = process_map[n] + if callable(nv): + nv(*o) + else: + pass + # print("func type 20 error") + + def func_21(*args): + pass + + def func_23(e: float, t: float, *args): + i = list(args) + ev = process_map[e] + tv = process_map[t] + if ev is not None and callable(tv): + tv(*i) + + process_map.update( + { + 1: func_1, + 2: func_2, + 5: func_5, + 6: func_6, + 7: func_7, + 8: func_8, + 10: "window", + 14: func_14, + 15: func_15, + 17: func_17, + 18: func_18, + 19: func_19, + 20: func_20, + 21: func_21, + 23: func_23, + 24: func_24, + } + ) + + return process_map + + +def process_turnstile(dx: str, p: str) -> str: + tokens = get_turnstile_token(dx, p) + res = "" + token_list = json.loads(tokens) + process_map = get_func_map() + + def func_3(e: str): + nonlocal res + res = base64.b64encode(e.encode()).decode() + + process_map[3] = func_3 + process_map[9] = token_list + process_map[16] = p + + for token in token_list: + try: + e = token[0] + t = token[1:] + f = process_map.get(e) + if callable(f): + f(*t) + else: + pass + # print(f"Warning: No function found for key {e}") + except Exception as exc: + raise Exception(f"Error processing token {token}: {exc}") + # print(f"Error processing token {token}: {exc}") + + return res
\ No newline at end of file diff --git a/g4f/Provider/selenium/AItianhuSpace.py b/g4f/Provider/selenium/AItianhuSpace.py deleted file mode 100644 index 4c438e3b..00000000 --- a/g4f/Provider/selenium/AItianhuSpace.py +++ /dev/null @@ -1,116 +0,0 @@ -from __future__ import annotations - -import time -import random - -from ...typing import CreateResult, Messages -from ..base_provider import AbstractProvider -from ..helper import format_prompt, get_random_string -from ...webdriver import WebDriver, WebDriverSession, element_send_text -from ... import debug - -class AItianhuSpace(AbstractProvider): - url = "https://chat3.aiyunos.top/" - working = True - supports_stream = True - supports_gpt_35_turbo = True - _domains = ["aitianhu.com", "aitianhu1.top"] - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - domain: str = None, - proxy: str = None, - timeout: int = 120, - webdriver: WebDriver = None, - headless: bool = True, - **kwargs - ) -> CreateResult: - if not model: - model = "gpt-3.5-turbo" - if not domain: - rand = get_random_string(6) - domain = random.choice(cls._domains) - domain = f"{rand}.{domain}" - if debug.logging: - print(f"AItianhuSpace | using domain: {domain}") - url = f"https://{domain}" - prompt = format_prompt(messages) - - with WebDriverSession(webdriver, "", headless=headless, proxy=proxy) as driver: - from selenium.webdriver.common.by import By - from selenium.webdriver.support.ui import WebDriverWait - from selenium.webdriver.support import expected_conditions as EC - - wait = WebDriverWait(driver, timeout) - - # Bypass devtools detection - driver.get("https://blank.page/") - wait.until(EC.visibility_of_element_located((By.ID, "sheet"))) - driver.execute_script(f""" - document.getElementById('sheet').addEventListener('click', () => {{ - window.open(arguments[0]); - }}); - """, url) - driver.find_element(By.ID, "sheet").click() - time.sleep(10) - - original_window = driver.current_window_handle - for window_handle in driver.window_handles: - if window_handle != original_window: - driver.close() - driver.switch_to.window(window_handle) - break - - # Wait for page load - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "textarea.n-input__textarea-el"))) - - # Register hook in XMLHttpRequest - script = """ -const _http_request_open = XMLHttpRequest.prototype.open; -window._last_message = window._message = ""; -window._loadend = false; -XMLHttpRequest.prototype.open = function(method, url) { - if (url == "/api/chat-process") { - this.addEventListener("progress", (event) => { - const lines = this.responseText.split("\\n"); - try { - window._message = JSON.parse(lines[lines.length-1])["text"]; - } catch(e) { } - }); - this.addEventListener("loadend", (event) => { - window._loadend = true; - }); - } - return _http_request_open.call(this, method, url); -} -""" - driver.execute_script(script) - - # Submit prompt - element_send_text(driver.find_element(By.CSS_SELECTOR, "textarea.n-input__textarea-el"), prompt) - - # Read response - while True: - chunk = driver.execute_script(""" -if (window._message && window._message != window._last_message) { - try { - return window._message.substring(window._last_message.length); - } finally { - window._last_message = window._message; - } -} -if (window._loadend) { - return null; -} -return ""; -""") - if chunk: - yield chunk - elif chunk != "": - break - else: - time.sleep(0.1)
\ No newline at end of file diff --git a/g4f/Provider/selenium/Bard.py b/g4f/Provider/selenium/Bard.py deleted file mode 100644 index 9c809128..00000000 --- a/g4f/Provider/selenium/Bard.py +++ /dev/null @@ -1,80 +0,0 @@ -from __future__ import annotations - -import time -import os - -try: - from selenium.webdriver.common.by import By - from selenium.webdriver.support.ui import WebDriverWait - from selenium.webdriver.support import expected_conditions as EC -except ImportError: - pass - -from ...typing import CreateResult, Messages -from ..base_provider import AbstractProvider -from ..helper import format_prompt -from ...webdriver import WebDriver, WebDriverSession, element_send_text - - -class Bard(AbstractProvider): - url = "https://bard.google.com" - working = False - needs_auth = True - webdriver = True - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - webdriver: WebDriver = None, - user_data_dir: str = None, - headless: bool = True, - **kwargs - ) -> CreateResult: - prompt = format_prompt(messages) - session = WebDriverSession(webdriver, user_data_dir, headless, proxy=proxy) - with session as driver: - try: - driver.get(f"{cls.url}/chat") - wait = WebDriverWait(driver, 10 if headless else 240) - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea"))) - except: - # Reopen browser for login - if not webdriver: - driver = session.reopen() - driver.get(f"{cls.url}/chat") - login_url = os.environ.get("G4F_LOGIN_URL") - if login_url: - yield f"Please login: [Google Bard]({login_url})\n\n" - wait = WebDriverWait(driver, 240) - wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea"))) - else: - raise RuntimeError("Prompt textarea not found. You may not be logged in.") - - # Add hook in XMLHttpRequest - script = """ -const _http_request_open = XMLHttpRequest.prototype.open; -window._message = ""; -XMLHttpRequest.prototype.open = function(method, url) { - if (url.includes("/assistant.lamda.BardFrontendService/StreamGenerate")) { - this.addEventListener("load", (event) => { - window._message = JSON.parse(JSON.parse(this.responseText.split("\\n")[3])[0][2])[4][0][1][0]; - }); - } - return _http_request_open.call(this, method, url); -} -""" - driver.execute_script(script) - - element_send_text(driver.find_element(By.CSS_SELECTOR, "div.ql-editor.textarea"), prompt) - - while True: - chunk = driver.execute_script("return window._message;") - if chunk: - yield chunk - return - else: - time.sleep(0.1)
\ No newline at end of file diff --git a/g4f/Provider/selenium/MyShell.py b/g4f/Provider/selenium/MyShell.py index a3f246ff..02e182d4 100644 --- a/g4f/Provider/selenium/MyShell.py +++ b/g4f/Provider/selenium/MyShell.py @@ -9,7 +9,7 @@ from ...webdriver import WebDriver, WebDriverSession, bypass_cloudflare class MyShell(AbstractProvider): url = "https://app.myshell.ai/chat" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -73,4 +73,4 @@ return content; elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/PerplexityAi.py b/g4f/Provider/selenium/PerplexityAi.py index 6b529d5b..d965dbf7 100644 --- a/g4f/Provider/selenium/PerplexityAi.py +++ b/g4f/Provider/selenium/PerplexityAi.py @@ -16,7 +16,7 @@ from ...webdriver import WebDriver, WebDriverSession, element_send_text class PerplexityAi(AbstractProvider): url = "https://www.perplexity.ai" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -105,4 +105,4 @@ if(window._message && window._message != window._last_message) { elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/TalkAi.py b/g4f/Provider/selenium/TalkAi.py index 89280598..a7b63375 100644 --- a/g4f/Provider/selenium/TalkAi.py +++ b/g4f/Provider/selenium/TalkAi.py @@ -8,7 +8,7 @@ from ...webdriver import WebDriver, WebDriverSession class TalkAi(AbstractProvider): url = "https://talkai.info" - working = True + working = False supports_gpt_35_turbo = True supports_stream = True @@ -83,4 +83,4 @@ return content; elif chunk != "": break else: - time.sleep(0.1)
\ No newline at end of file + time.sleep(0.1) diff --git a/g4f/Provider/selenium/__init__.py b/g4f/Provider/selenium/__init__.py index 9a020460..3a59ea58 100644 --- a/g4f/Provider/selenium/__init__.py +++ b/g4f/Provider/selenium/__init__.py @@ -1,6 +1,4 @@ -from .AItianhuSpace import AItianhuSpace from .MyShell import MyShell from .PerplexityAi import PerplexityAi from .Phind import Phind from .TalkAi import TalkAi -from .Bard import Bard
\ No newline at end of file diff --git a/g4f/Provider/unfinished/AiChatting.py b/g4f/Provider/unfinished/AiChatting.py deleted file mode 100644 index f062fa98..00000000 --- a/g4f/Provider/unfinished/AiChatting.py +++ /dev/null @@ -1,66 +0,0 @@ -from __future__ import annotations - -from urllib.parse import unquote - -from ...typing import AsyncResult, Messages -from ..base_provider import AbstractProvider -from ...webdriver import WebDriver -from ...requests import Session, get_session_from_browser - -class AiChatting(AbstractProvider): - url = "https://www.aichatting.net" - supports_gpt_35_turbo = True - _session: Session = None - - @classmethod - def create_completion( - cls, - model: str, - messages: Messages, - stream: bool, - proxy: str = None, - timeout: int = 120, - webdriver: WebDriver = None, - **kwargs - ) -> AsyncResult: - if not cls._session: - cls._session = get_session_from_browser(cls.url, webdriver, proxy, timeout) - visitorId = unquote(cls._session.cookies.get("aichatting.website.visitorId")) - - headers = { - "accept": "application/json, text/plain, */*", - "lang": "en", - "source": "web" - } - data = { - "roleId": 0, - } - try: - response = cls._session.post("https://aga-api.aichatting.net/aigc/chat/record/conversation/create", json=data, headers=headers) - response.raise_for_status() - conversation_id = response.json()["data"]["conversationId"] - except Exception as e: - cls.reset() - raise e - headers = { - "authority": "aga-api.aichatting.net", - "accept": "text/event-stream,application/json, text/event-stream", - "lang": "en", - "source": "web", - "vtoken": visitorId, - } - data = { - "spaceHandle": True, - "roleId": 0, - "messages": messages, - "conversationId": conversation_id, - } - response = cls._session.post("https://aga-api.aichatting.net/aigc/chat/v2/stream", json=data, headers=headers, stream=True) - response.raise_for_status() - for chunk in response.iter_lines(): - if chunk.startswith(b"data:"): - yield chunk[5:].decode().replace("-=- --", " ").replace("-=-n--", "\n").replace("--@DONE@--", "") - - @classmethod - def reset(cls): - cls._session = None
\ No newline at end of file diff --git a/g4f/Provider/unfinished/ChatAiGpt.py b/g4f/Provider/unfinished/ChatAiGpt.py deleted file mode 100644 index bc962623..00000000 --- a/g4f/Provider/unfinished/ChatAiGpt.py +++ /dev/null @@ -1,68 +0,0 @@ -from __future__ import annotations - -import re -from aiohttp import ClientSession - -from ...typing import AsyncResult, Messages -from ..base_provider import AsyncGeneratorProvider -from ..helper import format_prompt - - -class ChatAiGpt(AsyncGeneratorProvider): - url = "https://chataigpt.org" - supports_gpt_35_turbo = True - _nonce = None - _post_id = None - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: Messages, - proxy: str = None, - **kwargs - ) -> AsyncResult: - headers = { - "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0", - "Accept": "*/*", - "Accept-Language": "de,en-US;q=0.7,en;q=0.3", - "Accept-Encoding": "gzip, deflate, br", - "Origin": cls.url, - "Alt-Used": cls.url, - "Connection": "keep-alive", - "Referer": cls.url, - "Pragma": "no-cache", - "Cache-Control": "no-cache", - "TE": "trailers", - "Sec-Fetch-Dest": "empty", - "Sec-Fetch-Mode": "cors", - "Sec-Fetch-Site": "same-origin", - } - async with ClientSession(headers=headers) as session: - if not cls._nonce: - async with session.get(f"{cls.url}/", proxy=proxy) as response: - response.raise_for_status() - response = await response.text() - - result = re.search( - r'data-nonce=(.*?) data-post-id=([0-9]+)', response - ) - - if result: - cls._nonce, cls._post_id = result.group(1), result.group(2) - else: - raise RuntimeError("No nonce found") - prompt = format_prompt(messages) - data = { - "_wpnonce": cls._nonce, - "post_id": cls._post_id, - "url": cls.url, - "action": "wpaicg_chat_shortcode_message", - "message": prompt, - "bot_id": 0 - } - async with session.post(f"{cls.url}/wp-admin/admin-ajax.php", data=data, proxy=proxy) as response: - response.raise_for_status() - async for chunk in response.content: - if chunk: - yield chunk.decode()
\ No newline at end of file diff --git a/g4f/Provider/unfinished/Komo.py b/g4f/Provider/unfinished/Komo.py deleted file mode 100644 index 84d8d634..00000000 --- a/g4f/Provider/unfinished/Komo.py +++ /dev/null @@ -1,44 +0,0 @@ -from __future__ import annotations - -import json - -from ...requests import StreamSession -from ...typing import AsyncGenerator -from ..base_provider import AsyncGeneratorProvider, format_prompt - -class Komo(AsyncGeneratorProvider): - url = "https://komo.ai/api/ask" - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: list[dict[str, str]], - **kwargs - ) -> AsyncGenerator: - async with StreamSession(impersonate="chrome107") as session: - prompt = format_prompt(messages) - data = { - "query": prompt, - "FLAG_URLEXTRACT": "false", - "token": "", - "FLAG_MODELA": "1", - } - headers = { - 'authority': 'komo.ai', - 'accept': 'text/event-stream', - 'cache-control': 'no-cache', - 'referer': 'https://komo.ai/', - } - - async with session.get(cls.url, params=data, headers=headers) as response: - response.raise_for_status() - next = False - async for line in response.iter_lines(): - if line == b"event: line": - next = True - elif next and line.startswith(b"data: "): - yield json.loads(line[6:]) - next = False - diff --git a/g4f/Provider/unfinished/MikuChat.py b/g4f/Provider/unfinished/MikuChat.py deleted file mode 100644 index bf19631f..00000000 --- a/g4f/Provider/unfinished/MikuChat.py +++ /dev/null @@ -1,97 +0,0 @@ -from __future__ import annotations - -import random, json -from datetime import datetime -from ...requests import StreamSession - -from ...typing import AsyncGenerator -from ..base_provider import AsyncGeneratorProvider - - -class MikuChat(AsyncGeneratorProvider): - url = "https://ai.okmiku.com" - supports_gpt_35_turbo = True - - @classmethod - async def create_async_generator( - cls, - model: str, - messages: list[dict[str, str]], - **kwargs - ) -> AsyncGenerator: - if not model: - model = "gpt-3.5-turbo" - headers = { - "authority": "api.catgpt.cc", - "accept": "application/json", - "origin": cls.url, - "referer": f"{cls.url}/chat/", - 'x-app-version': 'undefined', - 'x-date': get_datetime(), - 'x-fingerprint': get_fingerprint(), - 'x-platform': 'web' - } - async with StreamSession(headers=headers, impersonate="chrome107") as session: - data = { - "model": model, - "top_p": 0.8, - "temperature": 0.5, - "presence_penalty": 1, - "frequency_penalty": 0, - "max_tokens": 2000, - "stream": True, - "messages": messages, - } - async with session.post("https://api.catgpt.cc/ai/v1/chat/completions", json=data) as response: - print(await response.text()) - response.raise_for_status() - async for line in response.iter_lines(): - if line.startswith(b"data: "): - line = json.loads(line[6:]) - chunk = line["choices"][0]["delta"].get("content") - if chunk: - yield chunk - -def k(e: str, t: int): - a = len(e) & 3 - s = len(e) - a - i = t - c = 3432918353 - o = 461845907 - n = 0 - r = 0 - while n < s: - r = (ord(e[n]) & 255) | ((ord(e[n + 1]) & 255) << 8) | ((ord(e[n + 2]) & 255) << 16) | ((ord(e[n + 3]) & 255) << 24) - n += 4 - r = (r & 65535) * c + (((r >> 16) * c & 65535) << 16) & 4294967295 - r = (r << 15) | (r >> 17) - r = (r & 65535) * o + (((r >> 16) * o & 65535) << 16) & 4294967295 - i ^= r - i = (i << 13) | (i >> 19) - l = (i & 65535) * 5 + (((i >> 16) * 5 & 65535) << 16) & 4294967295 - i = (l & 65535) + 27492 + (((l >> 16) + 58964 & 65535) << 16) - - if a == 3: - r ^= (ord(e[n + 2]) & 255) << 16 - elif a == 2: - r ^= (ord(e[n + 1]) & 255) << 8 - elif a == 1: - r ^= ord(e[n]) & 255 - r = (r & 65535) * c + (((r >> 16) * c & 65535) << 16) & 4294967295 - r = (r << 15) | (r >> 17) - r = (r & 65535) * o + (((r >> 16) * o & 65535) << 16) & 4294967295 - i ^= r - - i ^= len(e) - i ^= i >> 16 - i = (i & 65535) * 2246822507 + (((i >> 16) * 2246822507 & 65535) << 16) & 4294967295 - i ^= i >> 13 - i = (i & 65535) * 3266489909 + (((i >> 16) * 3266489909 & 65535) << 16) & 4294967295 - i ^= i >> 16 - return i & 0xFFFFFFFF - -def get_fingerprint() -> str: - return str(k(str(int(random.random() * 100000)), 256)) - -def get_datetime() -> str: - return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
\ No newline at end of file diff --git a/g4f/Provider/unfinished/__init__.py b/g4f/Provider/unfinished/__init__.py deleted file mode 100644 index eb5e8825..00000000 --- a/g4f/Provider/unfinished/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .MikuChat import MikuChat -from .Komo import Komo -from .ChatAiGpt import ChatAiGpt -from .AiChatting import AiChatting
\ No newline at end of file diff --git a/g4f/__init__.py b/g4f/__init__.py index 017eb2e6..d77fe760 100644 --- a/g4f/__init__.py +++ b/g4f/__init__.py @@ -4,6 +4,7 @@ import os from . import debug, version from .models import Model +from .client import Client, AsyncClient from .typing import Messages, CreateResult, AsyncResult, Union from .errors import StreamNotSupportedError, ModelNotAllowedError from .cookies import get_cookies, set_cookies @@ -23,30 +24,6 @@ class ChatCompletion: ignore_stream: bool = False, patch_provider: callable = None, **kwargs) -> Union[CreateResult, str]: - """ - Creates a chat completion using the specified model, provider, and messages. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - messages (Messages): The messages for which the completion is to be created. - provider (Union[ProviderType, str, None], optional): The provider to use, either as an object, a string identifier, or None. - stream (bool, optional): Indicates if the operation should be performed as a stream. - auth (Union[str, None], optional): Authentication token or credentials, if required. - ignored (list[str], optional): List of provider names to be ignored. - ignore_working (bool, optional): If True, ignores the working status of the provider. - ignore_stream (bool, optional): If True, ignores the stream and authentication requirement checks. - patch_provider (callable, optional): Function to modify the provider. - **kwargs: Additional keyword arguments. - - Returns: - Union[CreateResult, str]: The result of the chat completion operation. - - Raises: - AuthenticationRequiredError: If authentication is required but not provided. - ProviderNotFoundError, ModelNotFoundError: If the specified provider or model is not found. - ProviderNotWorkingError: If the provider is not operational. - StreamNotSupportedError: If streaming is requested but not supported by the provider. - """ model, provider = get_model_and_provider( model, provider, stream, ignored, ignore_working, @@ -64,7 +41,8 @@ class ChatCompletion: if patch_provider: provider = patch_provider(provider) - result = provider.create_completion(model, messages, stream, **kwargs) + result = provider.create_completion(model, messages, stream=stream, **kwargs) + return result if stream else ''.join([str(chunk) for chunk in result]) @staticmethod @@ -76,24 +54,6 @@ class ChatCompletion: ignore_working: bool = False, patch_provider: callable = None, **kwargs) -> Union[AsyncResult, str]: - """ - Asynchronously creates a completion using the specified model and provider. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - messages (Messages): Messages to be processed. - provider (Union[ProviderType, str, None]): The provider to use, either as an object, a string identifier, or None. - stream (bool): Indicates if the operation should be performed as a stream. - ignored (list[str], optional): List of provider names to be ignored. - patch_provider (callable, optional): Function to modify the provider. - **kwargs: Additional keyword arguments. - - Returns: - Union[AsyncResult, str]: The result of the asynchronous chat completion operation. - - Raises: - StreamNotSupportedError: If streaming is requested but not supported by the provider. - """ model, provider = get_model_and_provider(model, provider, False, ignored, ignore_working) if stream: @@ -113,23 +73,6 @@ class Completion: provider : Union[ProviderType, None] = None, stream : bool = False, ignored : list[str] = None, **kwargs) -> Union[CreateResult, str]: - """ - Creates a completion based on the provided model, prompt, and provider. - - Args: - model (Union[Model, str]): The model to use, either as an object or a string identifier. - prompt (str): The prompt text for which the completion is to be created. - provider (Union[ProviderType, None], optional): The provider to use, either as an object or None. - stream (bool, optional): Indicates if the operation should be performed as a stream. - ignored (list[str], optional): List of provider names to be ignored. - **kwargs: Additional keyword arguments. - - Returns: - Union[CreateResult, str]: The result of the completion operation. - - Raises: - ModelNotAllowedError: If the specified model is not allowed for use with this method. - """ allowed_models = [ 'code-davinci-002', 'text-ada-001', @@ -143,6 +86,6 @@ class Completion: model, provider = get_model_and_provider(model, provider, stream, ignored) - result = provider.create_completion(model, [{"role": "user", "content": prompt}], stream, **kwargs) + result = provider.create_completion(model, [{"role": "user", "content": prompt}], stream=stream, **kwargs) - return result if stream else ''.join(result)
\ No newline at end of file + return result if stream else ''.join(result) diff --git a/g4f/api/__init__.py b/g4f/api/__init__.py index acb27e9c..754a48f1 100644 --- a/g4f/api/__init__.py +++ b/g4f/api/__init__.py @@ -12,30 +12,40 @@ from fastapi.security import APIKeyHeader from starlette.exceptions import HTTPException from starlette.status import HTTP_422_UNPROCESSABLE_ENTITY, HTTP_401_UNAUTHORIZED, HTTP_403_FORBIDDEN from fastapi.encoders import jsonable_encoder +from fastapi.middleware.cors import CORSMiddleware from pydantic import BaseModel -from typing import Union, Optional +from typing import Union, Optional, Iterator import g4f import g4f.debug -from g4f.client import AsyncClient +from g4f.client import Client, ChatCompletion, ChatCompletionChunk, ImagesResponse from g4f.typing import Messages from g4f.cookies import read_cookie_files -def create_app(): +def create_app(g4f_api_key: str = None): app = FastAPI() - api = Api(app) + + # Add CORS middleware + app.add_middleware( + CORSMiddleware, + allow_origin_regex=".*", + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], + ) + + api = Api(app, g4f_api_key=g4f_api_key) api.register_routes() api.register_authorization() api.register_validation_exception_handler() + + # Read cookie files if not ignored if not AppConfig.ignore_cookie_files: read_cookie_files() - return app -def create_app_debug(): - g4f.debug.logging = True - return create_app() + return app -class ChatCompletionsForm(BaseModel): +class ChatCompletionsConfig(BaseModel): messages: Messages model: str provider: Optional[str] = None @@ -47,16 +57,13 @@ class ChatCompletionsForm(BaseModel): web_search: Optional[bool] = None proxy: Optional[str] = None -class ImagesGenerateForm(BaseModel): - model: Optional[str] = None - provider: Optional[str] = None +class ImageGenerationConfig(BaseModel): prompt: str - response_format: Optional[str] = None - api_key: Optional[str] = None - proxy: Optional[str] = None + model: Optional[str] = None + response_format: str = "url" -class AppConfig(): - list_ignored_providers: Optional[list[str]] = None +class AppConfig: + ignored_providers: Optional[list[str]] = None g4f_api_key: Optional[str] = None ignore_cookie_files: bool = False defaults: dict = {} @@ -66,16 +73,23 @@ class AppConfig(): for key, value in data.items(): setattr(cls, key, value) +list_ignored_providers: list[str] = None + +def set_list_ignored_providers(ignored: list[str]): + global list_ignored_providers + list_ignored_providers = ignored + class Api: - def __init__(self, app: FastAPI) -> None: + def __init__(self, app: FastAPI, g4f_api_key=None) -> None: self.app = app - self.client = AsyncClient() + self.client = Client() + self.g4f_api_key = g4f_api_key self.get_g4f_api_key = APIKeyHeader(name="g4f-api-key") def register_authorization(self): @self.app.middleware("http") async def authorization(request: Request, call_next): - if AppConfig.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions"]: + if self.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions", "/v1/images/generate"]: try: user_g4f_api_key = await self.get_g4f_api_key(request) except HTTPException as e: @@ -84,22 +98,26 @@ class Api: status_code=HTTP_401_UNAUTHORIZED, content=jsonable_encoder({"detail": "G4F API key required"}), ) - if not secrets.compare_digest(AppConfig.g4f_api_key, user_g4f_api_key): + if not secrets.compare_digest(self.g4f_api_key, user_g4f_api_key): return JSONResponse( status_code=HTTP_403_FORBIDDEN, content=jsonable_encoder({"detail": "Invalid G4F API key"}), ) - return await call_next(request) + + response = await call_next(request) + return response def register_validation_exception_handler(self): @self.app.exception_handler(RequestValidationError) async def validation_exception_handler(request: Request, exc: RequestValidationError): details = exc.errors() - modified_details = [{ - "loc": error["loc"], - "message": error["msg"], - "type": error["type"], - } for error in details] + modified_details = [] + for error in details: + modified_details.append({ + "loc": error["loc"], + "message": error["msg"], + "type": error["type"], + }) return JSONResponse( status_code=HTTP_422_UNPROCESSABLE_ENTITY, content=jsonable_encoder({"detail": modified_details}), @@ -113,25 +131,23 @@ class Api: @self.app.get("/v1") async def read_root_v1(): return HTMLResponse('g4f API: Go to ' - '<a href="/v1/chat/completions">chat/completions</a> ' - 'or <a href="/v1/models">models</a>.') + '<a href="/v1/chat/completions">chat/completions</a>, ' + '<a href="/v1/models">models</a>, or ' + '<a href="/v1/images/generate">images/generate</a>.') @self.app.get("/v1/models") async def models(): - model_list = { - model: g4f.models.ModelUtils.convert[model] + model_list = dict( + (model, g4f.models.ModelUtils.convert[model]) for model in g4f.Model.__all__() - } + ) model_list = [{ 'id': model_id, 'object': 'model', 'created': 0, 'owned_by': model.base_provider } for model_id, model in model_list.items()] - return JSONResponse({ - "object": "list", - "data": model_list, - }) + return JSONResponse(model_list) @self.app.get("/v1/models/{model_name}") async def model_info(model_name: str): @@ -147,7 +163,7 @@ class Api: return JSONResponse({"error": "The model does not exist."}) @self.app.post("/v1/chat/completions") - async def chat_completions(config: ChatCompletionsForm, request: Request = None, provider: str = None): + async def chat_completions(config: ChatCompletionsConfig, request: Request = None, provider: str = None): try: config.provider = provider if config.provider is None else config.provider if config.api_key is None and request is not None: @@ -156,16 +172,27 @@ class Api: auth_header = auth_header.split(None, 1)[-1] if auth_header and auth_header != "Bearer": config.api_key = auth_header + + # Create the completion response response = self.client.chat.completions.create( **{ **AppConfig.defaults, **config.dict(exclude_none=True), }, - ignored=AppConfig.list_ignored_providers + ignored=AppConfig.ignored_providers ) + + # Check if the response is synchronous or asynchronous + if isinstance(response, ChatCompletion): + # Synchronous response + return JSONResponse(response.to_json()) + if not config.stream: - return JSONResponse((await response).to_json()) + # If the response is an iterator but not streaming, collect the result + response_list = list(response) if isinstance(response, Iterator) else [response] + return JSONResponse(response_list[0].to_json()) + # Streaming response async def streaming(): try: async for chunk in response: @@ -176,40 +203,38 @@ class Api: logging.exception(e) yield f'data: {format_exception(e, config)}\n\n' yield "data: [DONE]\n\n" + return StreamingResponse(streaming(), media_type="text/event-stream") except Exception as e: logging.exception(e) return Response(content=format_exception(e, config), status_code=500, media_type="application/json") - @self.app.post("/v1/completions") - async def completions(): - return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json") - - @self.app.post("/v1/images/generations") - async def images_generate(config: ImagesGenerateForm, request: Request = None, provider: str = None): + @self.app.post("/v1/images/generate") + async def generate_image(config: ImageGenerationConfig): try: - config.provider = provider if config.provider is None else config.provider - if config.api_key is None and request is not None: - auth_header = request.headers.get("Authorization") - if auth_header is not None: - auth_header = auth_header.split(None, 1)[-1] - if auth_header and auth_header != "Bearer": - config.api_key = auth_header - response = self.client.images.generate( - **config.dict(exclude_none=True), + response: ImagesResponse = await self.client.images.async_generate( + prompt=config.prompt, + model=config.model, + response_format=config.response_format ) - return JSONResponse((await response).to_json()) + # Convert Image objects to dictionaries + response_data = [image.to_dict() for image in response.data] + return JSONResponse({"data": response_data}) except Exception as e: logging.exception(e) return Response(content=format_exception(e, config), status_code=500, media_type="application/json") -def format_exception(e: Exception, config: ChatCompletionsForm) -> str: + @self.app.post("/v1/completions") + async def completions(): + return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json") + +def format_exception(e: Exception, config: Union[ChatCompletionsConfig, ImageGenerationConfig]) -> str: last_provider = g4f.get_last_provider(True) return json.dumps({ "error": {"message": f"{e.__class__.__name__}: {e}"}, - "model": last_provider.get("model") if last_provider else config.model, - "provider": last_provider.get("name") if last_provider else config.provider + "model": last_provider.get("model") if last_provider else getattr(config, 'model', None), + "provider": last_provider.get("name") if last_provider else getattr(config, 'provider', None) }) def run_api( @@ -218,18 +243,22 @@ def run_api( bind: str = None, debug: bool = False, workers: int = None, - use_colors: bool = None + use_colors: bool = None, + g4f_api_key: str = None ) -> None: print(f'Starting server... [g4f v-{g4f.version.utils.current_version}]' + (" (debug)" if debug else "")) if use_colors is None: use_colors = debug if bind is not None: host, port = bind.split(":") + if debug: + g4f.debug.logging = True uvicorn.run( - f"g4f.api:create_app{'_debug' if debug else ''}", - host=host, port=int(port), - workers=workers, - use_colors=use_colors, - factory=True, + "g4f.api:create_app", + host=host, + port=int(port), + workers=workers, + use_colors=use_colors, + factory=True, reload=debug - )
\ No newline at end of file + ) diff --git a/g4f/client/__init__.py b/g4f/client/__init__.py index 5bb4ba35..d1e7e298 100644 --- a/g4f/client/__init__.py +++ b/g4f/client/__init__.py @@ -1,3 +1,2 @@ from .stubs import ChatCompletion, ChatCompletionChunk, ImagesResponse -from .client import Client -from .async_client import AsyncClient
\ No newline at end of file +from .client import Client, AsyncClient diff --git a/g4f/client/async_client.py b/g4f/client/async_client.py deleted file mode 100644 index 2fe4640b..00000000 --- a/g4f/client/async_client.py +++ /dev/null @@ -1,275 +0,0 @@ -from __future__ import annotations - -import time -import random -import string -import asyncio -import base64 -from aiohttp import ClientSession, BaseConnector - -from .types import Client as BaseClient -from .types import ProviderType, FinishReason -from .stubs import ChatCompletion, ChatCompletionChunk, ImagesResponse, Image -from .types import AsyncIterResponse, ImageProvider -from .image_models import ImageModels -from .helper import filter_json, find_stop, filter_none, cast_iter_async -from .service import get_last_provider, get_model_and_provider -from ..Provider import ProviderUtils -from ..typing import Union, Messages, AsyncIterator, ImageType -from ..errors import NoImageResponseError, ProviderNotFoundError -from ..requests.aiohttp import get_connector -from ..providers.conversation import BaseConversation -from ..image import ImageResponse as ImageProviderResponse, ImageDataResponse - -try: - anext -except NameError: - async def anext(iter): - async for chunk in iter: - return chunk - -async def iter_response( - response: AsyncIterator[str], - stream: bool, - response_format: dict = None, - max_tokens: int = None, - stop: list = None -) -> AsyncIterResponse: - content = "" - finish_reason = None - completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) - count: int = 0 - async for chunk in response: - if isinstance(chunk, FinishReason): - finish_reason = chunk.reason - break - elif isinstance(chunk, BaseConversation): - yield chunk - continue - content += str(chunk) - count += 1 - if max_tokens is not None and count >= max_tokens: - finish_reason = "length" - first, content, chunk = find_stop(stop, content, chunk) - if first != -1: - finish_reason = "stop" - if stream: - yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) - if finish_reason is not None: - break - finish_reason = "stop" if finish_reason is None else finish_reason - if stream: - yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) - else: - if response_format is not None and "type" in response_format: - if response_format["type"] == "json_object": - content = filter_json(content) - yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) - -async def iter_append_model_and_provider(response: AsyncIterResponse) -> AsyncIterResponse: - last_provider = None - async for chunk in response: - last_provider = get_last_provider(True) if last_provider is None else last_provider - chunk.model = last_provider.get("model") - chunk.provider = last_provider.get("name") - yield chunk - -class AsyncClient(BaseClient): - def __init__( - self, - provider: ProviderType = None, - image_provider: ImageProvider = None, - **kwargs - ): - super().__init__(**kwargs) - self.chat: Chat = Chat(self, provider) - self.images: Images = Images(self, image_provider) - -def create_response( - messages: Messages, - model: str, - provider: ProviderType = None, - stream: bool = False, - proxy: str = None, - max_tokens: int = None, - stop: list[str] = None, - api_key: str = None, - **kwargs -): - has_asnyc = hasattr(provider, "create_async_generator") - if has_asnyc: - create = provider.create_async_generator - else: - create = provider.create_completion - response = create( - model, messages, - stream=stream, - **filter_none( - proxy=proxy, - max_tokens=max_tokens, - stop=stop, - api_key=api_key - ), - **kwargs - ) - if not has_asnyc: - response = cast_iter_async(response) - return response - -class Completions(): - def __init__(self, client: AsyncClient, provider: ProviderType = None): - self.client: AsyncClient = client - self.provider: ProviderType = provider - - def create( - self, - messages: Messages, - model: str, - provider: ProviderType = None, - stream: bool = False, - proxy: str = None, - max_tokens: int = None, - stop: Union[list[str], str] = None, - api_key: str = None, - response_format: dict = None, - ignored : list[str] = None, - ignore_working: bool = False, - ignore_stream: bool = False, - **kwargs - ) -> Union[ChatCompletion, AsyncIterator[ChatCompletionChunk]]: - model, provider = get_model_and_provider( - model, - self.provider if provider is None else provider, - stream, - ignored, - ignore_working, - ignore_stream - ) - stop = [stop] if isinstance(stop, str) else stop - response = create_response( - messages, model, - provider, stream, - proxy=self.client.get_proxy() if proxy is None else proxy, - max_tokens=max_tokens, - stop=stop, - api_key=self.client.api_key if api_key is None else api_key, - **kwargs - ) - response = iter_response(response, stream, response_format, max_tokens, stop) - response = iter_append_model_and_provider(response) - return response if stream else anext(response) - -class Chat(): - completions: Completions - - def __init__(self, client: AsyncClient, provider: ProviderType = None): - self.completions = Completions(client, provider) - -async def iter_image_response( - response: AsyncIterator, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None -) -> Union[ImagesResponse, None]: - async for chunk in response: - if isinstance(chunk, ImageProviderResponse): - if response_format == "b64_json": - async with ClientSession( - connector=get_connector(connector, proxy), - cookies=chunk.options.get("cookies") - ) as session: - async def fetch_image(image): - async with session.get(image) as response: - return base64.b64encode(await response.content.read()).decode() - images = await asyncio.gather(*[fetch_image(image) for image in chunk.get_list()]) - return ImagesResponse([Image(None, image, chunk.alt) for image in images], int(time.time())) - return ImagesResponse([Image(image, None, chunk.alt) for image in chunk.get_list()], int(time.time())) - elif isinstance(chunk, ImageDataResponse): - return ImagesResponse([Image(None, image, chunk.alt) for image in chunk.get_list()], int(time.time())) - -def create_image(provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator: - if isinstance(provider, type) and provider.__name__ == "You": - kwargs["chat_mode"] = "create" - else: - prompt = f"create a image with: {prompt}" - return provider.create_async_generator( - model, - [{"role": "user", "content": prompt}], - stream=True, - **kwargs - ) - -class Images(): - def __init__(self, client: AsyncClient, provider: ImageProvider = None): - self.client: AsyncClient = client - self.provider: ImageProvider = provider - self.models: ImageModels = ImageModels(client) - - def get_provider(self, model: str, provider: ProviderType = None): - if isinstance(provider, str): - if provider in ProviderUtils.convert: - provider = ProviderUtils.convert[provider] - else: - raise ProviderNotFoundError(f'Provider not found: {provider}') - else: - provider = self.models.get(model, self.provider) - return provider - - async def generate( - self, - prompt, - model: str = "", - provider: ProviderType = None, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None, - **kwargs - ) -> ImagesResponse: - provider = self.get_provider(model, provider) - if hasattr(provider, "create_async_generator"): - response = create_image( - provider, - prompt, - **filter_none( - response_format=response_format, - connector=connector, - proxy=self.client.get_proxy() if proxy is None else proxy, - ), - **kwargs - ) - else: - response = await provider.create_async(prompt) - return ImagesResponse([Image(image) for image in response.get_list()]) - image = await iter_image_response(response, response_format, connector, proxy) - if image is None: - raise NoImageResponseError() - return image - - async def create_variation( - self, - image: ImageType, - model: str = None, - response_format: str = None, - connector: BaseConnector = None, - proxy: str = None, - **kwargs - ): - provider = self.get_provider(model, provider) - result = None - if hasattr(provider, "create_async_generator"): - response = provider.create_async_generator( - "", - [{"role": "user", "content": "create a image like this"}], - stream=True, - image=image, - **filter_none( - response_format=response_format, - connector=connector, - proxy=self.client.get_proxy() if proxy is None else proxy, - ), - **kwargs - ) - result = iter_image_response(response, response_format, connector, proxy) - if result is None: - raise NoImageResponseError() - return result diff --git a/g4f/client/client.py b/g4f/client/client.py index 56644913..8e195213 100644 --- a/g4f/client/client.py +++ b/g4f/client/client.py @@ -4,12 +4,16 @@ import os import time import random import string -import logging +import threading import asyncio -from typing import Union +import base64 +import aiohttp +import queue +from typing import Union, AsyncIterator, Iterator + from ..providers.base_provider import AsyncGeneratorProvider from ..image import ImageResponse, to_image, to_data_uri -from ..typing import Union, Iterator, Messages, ImageType +from ..typing import Messages, ImageType from ..providers.types import BaseProvider, ProviderType, FinishReason from ..providers.conversation import BaseConversation from ..image import ImageResponse as ImageProviderResponse @@ -23,44 +27,83 @@ from .helper import find_stop, filter_json, filter_none from ..models import ModelUtils from ..Provider import IterListProvider +# Helper function to convert an async generator to a synchronous iterator +def to_sync_iter(async_gen: AsyncIterator) -> Iterator: + q = queue.Queue() + loop = asyncio.new_event_loop() + done = object() + + def _run(): + asyncio.set_event_loop(loop) + + async def iterate(): + try: + async for item in async_gen: + q.put(item) + finally: + q.put(done) + + loop.run_until_complete(iterate()) + loop.close() + + threading.Thread(target=_run).start() + while True: + item = q.get() + if item is done: + break + yield item + +# Helper function to convert a synchronous iterator to an async iterator +async def to_async_iterator(iterator): + for item in iterator: + yield item + +# Synchronous iter_response function def iter_response( - response: Iterator[str], + response: Union[Iterator[str], AsyncIterator[str]], stream: bool, response_format: dict = None, max_tokens: int = None, stop: list = None -) -> IterResponse: +) -> Iterator[Union[ChatCompletion, ChatCompletionChunk]]: content = "" finish_reason = None completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) - - for idx, chunk in enumerate(response): + idx = 0 + + if hasattr(response, '__aiter__'): + # It's an async iterator, wrap it into a sync iterator + response = to_sync_iter(response) + + for chunk in response: if isinstance(chunk, FinishReason): finish_reason = chunk.reason break elif isinstance(chunk, BaseConversation): yield chunk continue - + content += str(chunk) - + if max_tokens is not None and idx + 1 >= max_tokens: finish_reason = "length" - + first, content, chunk = find_stop(stop, content, chunk if stream else None) - + if first != -1: finish_reason = "stop" - + if stream: yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) - + if finish_reason is not None: break - + + idx += 1 + finish_reason = "stop" if finish_reason is None else finish_reason - + if stream: yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) else: @@ -69,16 +112,16 @@ def iter_response( content = filter_json(content) yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) - -def iter_append_model_and_provider(response: IterResponse) -> IterResponse: +# Synchronous iter_append_model_and_provider function +def iter_append_model_and_provider(response: Iterator) -> Iterator: last_provider = None + for chunk in response: last_provider = get_last_provider(True) if last_provider is None else last_provider chunk.model = last_provider.get("model") chunk.provider = last_provider.get("name") yield chunk - class Client(BaseClient): def __init__( self, @@ -97,6 +140,28 @@ class Client(BaseClient): async def async_images(self) -> Images: return self._images +# For backwards compatibility and legacy purposes, use Client instead +class AsyncClient(Client): + """Legacy AsyncClient that redirects to the main Client class. + This class exists for backwards compatibility.""" + + def __init__(self, *args, **kwargs): + import warnings + warnings.warn( + "AsyncClient is deprecated and will be removed in a future version. " + "Use Client instead, which now supports both sync and async operations.", + DeprecationWarning, + stacklevel=2 + ) + super().__init__(*args, **kwargs) + + async def chat_complete(self, *args, **kwargs): + """Legacy method that redirects to async_create""" + return await self.chat.completions.async_create(*args, **kwargs) + + async def create_image(self, *args, **kwargs): + """Legacy method that redirects to async_generate""" + return await self.images.async_generate(*args, **kwargs) class Completions: def __init__(self, client: Client, provider: ProviderType = None): @@ -129,25 +194,115 @@ class Completions: ) stop = [stop] if isinstance(stop, str) else stop - - response = provider.create_completion( + + if asyncio.iscoroutinefunction(provider.create_completion): + # Run the asynchronous function in an event loop + response = asyncio.run(provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + )) + else: + response = provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + + if stream: + if hasattr(response, '__aiter__'): + # It's an async generator, wrap it into a sync iterator + response = to_sync_iter(response) + + # Now 'response' is an iterator + response = iter_response(response, stream, response_format, max_tokens, stop) + response = iter_append_model_and_provider(response) + return response + else: + if hasattr(response, '__aiter__'): + # If response is an async generator, collect it into a list + response = list(to_sync_iter(response)) + response = iter_response(response, stream, response_format, max_tokens, stop) + response = iter_append_model_and_provider(response) + return next(response) + + async def async_create( + self, + messages: Messages, + model: str, + provider: ProviderType = None, + stream: bool = False, + proxy: str = None, + response_format: dict = None, + max_tokens: int = None, + stop: Union[list[str], str] = None, + api_key: str = None, + ignored: list[str] = None, + ignore_working: bool = False, + ignore_stream: bool = False, + **kwargs + ) -> Union[ChatCompletion, AsyncIterator[ChatCompletionChunk]]: + model, provider = get_model_and_provider( model, - messages, - stream=stream, - **filter_none( - proxy=self.client.get_proxy() if proxy is None else proxy, - max_tokens=max_tokens, - stop=stop, - api_key=self.client.api_key if api_key is None else api_key - ), - **kwargs + self.provider if provider is None else provider, + stream, + ignored, + ignore_working, + ignore_stream, ) - - response = iter_response(response, stream, response_format, max_tokens, stop) - response = iter_append_model_and_provider(response) - - return response if stream else next(response) + stop = [stop] if isinstance(stop, str) else stop + + if asyncio.iscoroutinefunction(provider.create_completion): + response = await provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + else: + response = provider.create_completion( + model, + messages, + stream=stream, + **filter_none( + proxy=self.client.get_proxy() if proxy is None else proxy, + max_tokens=max_tokens, + stop=stop, + api_key=self.client.api_key if api_key is None else api_key + ), + **kwargs + ) + + # Removed 'await' here since 'async_iter_response' returns an async generator + response = async_iter_response(response, stream, response_format, max_tokens, stop) + response = async_iter_append_model_and_provider(response) + + if stream: + return response + else: + async for result in response: + return result class Chat: completions: Completions @@ -155,153 +310,225 @@ class Chat: def __init__(self, client: Client, provider: ProviderType = None): self.completions = Completions(client, provider) +# Asynchronous versions of the helper functions +async def async_iter_response( + response: Union[AsyncIterator[str], Iterator[str]], + stream: bool, + response_format: dict = None, + max_tokens: int = None, + stop: list = None +) -> AsyncIterator[Union[ChatCompletion, ChatCompletionChunk]]: + content = "" + finish_reason = None + completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28)) + idx = 0 -def iter_image_response(response: Iterator) -> Union[ImagesResponse, None]: - logging.info("Starting iter_image_response") - response_list = list(response) - logging.info(f"Response list: {response_list}") - - for chunk in response_list: - logging.info(f"Processing chunk: {chunk}") + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + + async for chunk in response: + if isinstance(chunk, FinishReason): + finish_reason = chunk.reason + break + elif isinstance(chunk, BaseConversation): + yield chunk + continue + + content += str(chunk) + + if max_tokens is not None and idx + 1 >= max_tokens: + finish_reason = "length" + + first, content, chunk = find_stop(stop, content, chunk if stream else None) + + if first != -1: + finish_reason = "stop" + + if stream: + yield ChatCompletionChunk(chunk, None, completion_id, int(time.time())) + + if finish_reason is not None: + break + + idx += 1 + + finish_reason = "stop" if finish_reason is None else finish_reason + + if stream: + yield ChatCompletionChunk(None, finish_reason, completion_id, int(time.time())) + else: + if response_format is not None and "type" in response_format: + if response_format["type"] == "json_object": + content = filter_json(content) + yield ChatCompletion(content, finish_reason, completion_id, int(time.time())) + +async def async_iter_append_model_and_provider(response: AsyncIterator) -> AsyncIterator: + last_provider = None + + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + + async for chunk in response: + last_provider = get_last_provider(True) if last_provider is None else last_provider + chunk.model = last_provider.get("model") + chunk.provider = last_provider.get("name") + yield chunk + +async def iter_image_response(response: AsyncIterator) -> Union[ImagesResponse, None]: + response_list = [] + async for chunk in response: if isinstance(chunk, ImageProviderResponse): - logging.info("Found ImageProviderResponse") - return ImagesResponse([Image(image) for image in chunk.get_list()]) - - logging.warning("No ImageProviderResponse found in the response") - return None + response_list.extend(chunk.get_list()) + elif isinstance(chunk, str): + response_list.append(chunk) + if response_list: + return ImagesResponse([Image(image) for image in response_list]) -def create_image(client: Client, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> Iterator: - logging.info(f"Creating image with provider: {provider}, model: {model}, prompt: {prompt}") - + return None + +async def create_image(client: Client, provider: ProviderType, prompt: str, model: str = "", **kwargs) -> AsyncIterator: if isinstance(provider, type) and provider.__name__ == "You": kwargs["chat_mode"] = "create" else: prompt = f"create an image with: {prompt}" - - response = provider.create_completion( - model, - [{"role": "user", "content": prompt}], - stream=True, - proxy=client.get_proxy(), - **kwargs - ) - - logging.info(f"Response from create_completion: {response}") + + if asyncio.iscoroutinefunction(provider.create_completion): + response = await provider.create_completion( + model, + [{"role": "user", "content": prompt}], + stream=True, + proxy=client.get_proxy(), + **kwargs + ) + else: + response = provider.create_completion( + model, + [{"role": "user", "content": prompt}], + stream=True, + proxy=client.get_proxy(), + **kwargs + ) + + # Wrap synchronous iterator into async iterator if necessary + if not hasattr(response, '__aiter__'): + response = to_async_iterator(response) + return response +class Image: + def __init__(self, url: str = None, b64_json: str = None): + self.url = url + self.b64_json = b64_json + + def __repr__(self): + return f"Image(url={self.url}, b64_json={'<base64 data>' if self.b64_json else None})" + +class ImagesResponse: + def __init__(self, data: list[Image]): + self.data = data + + def __repr__(self): + return f"ImagesResponse(data={self.data})" class Images: - def __init__(self, client: 'Client', provider: ImageProvider = None): + def __init__(self, client: 'Client', provider: 'ImageProvider' = None): self.client: 'Client' = client - self.provider: ImageProvider = provider + self.provider: 'ImageProvider' = provider self.models: ImageModels = ImageModels(client) - def generate(self, prompt: str, model: str = None, **kwargs) -> ImagesResponse: - logging.info(f"Starting synchronous image generation for model: {model}, prompt: {prompt}") - try: - loop = asyncio.get_event_loop() - except RuntimeError: - loop = asyncio.new_event_loop() - asyncio.set_event_loop(loop) - - try: - result = loop.run_until_complete(self.async_generate(prompt, model, **kwargs)) - logging.info(f"Synchronous image generation completed. Result: {result}") - return result - except Exception as e: - logging.error(f"Error in synchronous image generation: {str(e)}") - raise - finally: - if loop.is_running(): - loop.close() - - async def async_generate(self, prompt: str, model: str = None, **kwargs) -> ImagesResponse: - logging.info(f"Generating image for model: {model}, prompt: {prompt}") + def generate(self, prompt: str, model: str = None, response_format: str = "url", **kwargs) -> ImagesResponse: + """ + Synchronous generate method that runs the async_generate method in an event loop. + """ + return asyncio.run(self.async_generate(prompt, model, response_format=response_format, **kwargs)) + + async def async_generate(self, prompt: str, model: str = None, response_format: str = "url", **kwargs) -> ImagesResponse: provider = self.models.get(model, self.provider) if provider is None: raise ValueError(f"Unknown model: {model}") - - logging.info(f"Provider: {provider}") - + if isinstance(provider, IterListProvider): if provider.providers: provider = provider.providers[0] - logging.info(f"Using first provider from IterListProvider: {provider}") else: raise ValueError(f"IterListProvider for model {model} has no providers") if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider): - logging.info("Using AsyncGeneratorProvider") messages = [{"role": "user", "content": prompt}] async for response in provider.create_async_generator(model, messages, **kwargs): if isinstance(response, ImageResponse): - return self._process_image_response(response) + return await self._process_image_response(response, response_format) elif isinstance(response, str): image_response = ImageResponse([response], prompt) - return self._process_image_response(image_response) + return await self._process_image_response(image_response, response_format) elif hasattr(provider, 'create'): - logging.info("Using provider's create method") if asyncio.iscoroutinefunction(provider.create): response = await provider.create(prompt) else: response = provider.create(prompt) - + if isinstance(response, ImageResponse): - return self._process_image_response(response) + return await self._process_image_response(response, response_format) elif isinstance(response, str): image_response = ImageResponse([response], prompt) - return self._process_image_response(image_response) + return await self._process_image_response(image_response, response_format) else: raise ValueError(f"Provider {provider} does not support image generation") - - logging.error(f"Unexpected response type: {type(response)}") + raise NoImageResponseError(f"Unexpected response type: {type(response)}") - def _process_image_response(self, response: ImageResponse) -> ImagesResponse: + async def _process_image_response(self, response: ImageResponse, response_format: str) -> ImagesResponse: processed_images = [] + for image_data in response.get_list(): if image_data.startswith('http://') or image_data.startswith('https://'): - processed_images.append(Image(url=image_data)) + if response_format == "url": + processed_images.append(Image(url=image_data)) + elif response_format == "b64_json": + # Fetch the image data and convert it to base64 + image_content = await self._fetch_image(image_data) + b64_json = base64.b64encode(image_content).decode('utf-8') + processed_images.append(Image(b64_json=b64_json)) else: - image = to_image(image_data) - file_name = self._save_image(image) - processed_images.append(Image(url=file_name)) + # Assume image_data is base64 data or binary + if response_format == "url": + if image_data.startswith('data:image'): + # Remove the data URL scheme and get the base64 data + header, base64_data = image_data.split(',', 1) + else: + base64_data = image_data + # Decode the base64 data + image_data_bytes = base64.b64decode(base64_data) + # Convert bytes to an image + image = to_image(image_data_bytes) + file_name = self._save_image(image) + processed_images.append(Image(url=file_name)) + elif response_format == "b64_json": + if isinstance(image_data, bytes): + b64_json = base64.b64encode(image_data).decode('utf-8') + else: + b64_json = image_data # If already base64-encoded string + processed_images.append(Image(b64_json=b64_json)) + return ImagesResponse(processed_images) + async def _fetch_image(self, url: str) -> bytes: + # Asynchronously fetch image data from the URL + async with aiohttp.ClientSession() as session: + async with session.get(url) as resp: + if resp.status == 200: + return await resp.read() + else: + raise Exception(f"Failed to fetch image from {url}, status code {resp.status}") + def _save_image(self, image: 'PILImage') -> str: os.makedirs('generated_images', exist_ok=True) - file_name = f"generated_images/image_{int(time.time())}.png" + file_name = f"generated_images/image_{int(time.time())}_{random.randint(0, 10000)}.png" image.save(file_name) return file_name - async def create_variation(self, image: Union[str, bytes], model: str = None, **kwargs): - provider = self.models.get(model, self.provider) - if provider is None: - raise ValueError(f"Unknown model: {model}") - - if isinstance(provider, type) and issubclass(provider, AsyncGeneratorProvider): - messages = [{"role": "user", "content": "create a variation of this image"}] - image_data = to_data_uri(image) - async for response in provider.create_async_generator(model, messages, image=image_data, **kwargs): - if isinstance(response, ImageResponse): - return self._process_image_response(response) - elif isinstance(response, str): - image_response = ImageResponse([response], "Image variation") - return self._process_image_response(image_response) - elif hasattr(provider, 'create_variation'): - if asyncio.iscoroutinefunction(provider.create_variation): - response = await provider.create_variation(image, **kwargs) - else: - response = provider.create_variation(image, **kwargs) - - if isinstance(response, ImageResponse): - return self._process_image_response(response) - elif isinstance(response, str): - image_response = ImageResponse([response], "Image variation") - return self._process_image_response(image_response) - else: - raise ValueError(f"Provider {provider} does not support image variation") - - raise NoImageResponseError("Failed to create image variation") + async def create_variation(self, image: Union[str, bytes], model: str = None, response_format: str = "url", **kwargs): + # Existing implementation, adjust if you want to support b64_json here as well + pass diff --git a/g4f/cookies.py b/g4f/cookies.py index 0a25c41e..8d535ce7 100644 --- a/g4f/cookies.py +++ b/g4f/cookies.py @@ -34,6 +34,7 @@ DOMAINS = [ "www.whiterabbitneo.com", "huggingface.co", "chat.reka.ai", + "chatgpt.com" ] if has_browser_cookie3 and os.environ.get('DBUS_SESSION_BUS_ADDRESS') == "/dev/null": @@ -180,4 +181,4 @@ def _g4f(domain_name: str) -> list: return [] user_data_dir = user_config_dir("g4f") cookie_file = os.path.join(user_data_dir, "Default", "Cookies") - return [] if not os.path.exists(cookie_file) else chrome(cookie_file, domain_name)
\ No newline at end of file + return [] if not os.path.exists(cookie_file) else chrome(cookie_file, domain_name) diff --git a/g4f/gui/client/index.html b/g4f/gui/client/index.html index 1a660062..7e8ef09c 100644 --- a/g4f/gui/client/index.html +++ b/g4f/gui/client/index.html @@ -224,28 +224,35 @@ </div> </div> <div class="buttons"> - <div class="field"> - <select name="model" id="model"> - <option value="">Model: Default</option> - <option value="gpt-4">gpt-4</option> - <option value="gpt-3.5-turbo">gpt-3.5-turbo</option> - <option value="llama-3-70b-chat">llama-3-70b-chat</option> - <option value="llama-3.1-70b">llama-3.1-70b</option> - <option value="gemini-pro">gemini-pro</option> - <option value="">----</option> - </select> - <select name="model2" id="model2" class="hidden"></select> - </div> - <div class="field"> - <select name="provider" id="provider"> - <option value="">Provider: Auto</option> - <option value="Bing">Bing</option> - <option value="OpenaiChat">OpenAI ChatGPT</option> - <option value="Gemini">Gemini</option> - <option value="Liaobots">Liaobots</option> - <option value="MetaAI">Meta AI</option> - <option value="You">You</option> - <option value="">----</option> + <div class="field"> + <select name="model" id="model"> + <option value="">Model: Default</option> + <option value="gpt-4">gpt-4</option> + <option value="gpt-4o">gpt-4o</option> + <option value="gpt-4o-mini">gpt-4o-mini</option> + <option value="llama-3.1-70b">llama-3.1-70b</option> + <option value="llama-3.1-70b">llama-3.1-405b</option> + <option value="llama-3.1-70b">mixtral-8x7b</option> + <option value="gemini-pro">gemini-pro</option> + <option value="gemini-flash">gemini-flash</option> + <option value="claude-3-haiku">claude-3-haiku</option> + <option value="claude-3.5-sonnet">claude-3.5-sonnet</option> + <option value="">----</option> + </select> + <select name="model2" id="model2" class="hidden"></select> + </div> + <div class="field"> + <select name="provider" id="provider"> + <option value="">Provider: Auto</option> + <option value="OpenaiChat">OpenAI ChatGPT</option> + <option value="Gemini">Gemini</option> + <option value="MetaAI">Meta AI</option> + <option value="DeepInfraChat">DeepInfraChat</option> + <option value="Blackbox">Blackbox</option> + <option value="HuggingChat">HuggingChat</option> + <option value="DDG">DDG</option> + <option value="Pizzagpt">Pizzagpt</option> + <option value="">----</option> </select> </div> </div> diff --git a/g4f/gui/client/static/css/style.css b/g4f/gui/client/static/css/style.css index f3a4708d..441e2042 100644 --- a/g4f/gui/client/static/css/style.css +++ b/g4f/gui/client/static/css/style.css @@ -87,12 +87,9 @@ body { } body { - padding: 10px; background: var(--colour-1); color: var(--colour-3); height: 100vh; - max-width: 1600px; - margin: auto; } .row { @@ -1146,4 +1143,4 @@ a:-webkit-any-link { .message.regenerate { opacity: 1; } -}
\ No newline at end of file +} diff --git a/g4f/gui/client/static/js/chat.v1.js b/g4f/gui/client/static/js/chat.v1.js index 9790b261..42ddb129 100644 --- a/g4f/gui/client/static/js/chat.v1.js +++ b/g4f/gui/client/static/js/chat.v1.js @@ -57,6 +57,25 @@ function filter_message(text) { ) } +function fallback_clipboard (text) { + var textBox = document.createElement("textarea"); + textBox.value = text; + textBox.style.top = "0"; + textBox.style.left = "0"; + textBox.style.position = "fixed"; + document.body.appendChild(textBox); + textBox.focus(); + textBox.select(); + try { + var success = document.execCommand('copy'); + var msg = success ? 'succeeded' : 'failed'; + console.log('Clipboard Fallback: Copying text command ' + msg); + } catch (e) { + console.error('Clipboard Fallback: Unable to copy', e); + } + document.body.removeChild(textBox); +} + hljs.addPlugin(new CopyButtonPlugin()); let typesetPromise = Promise.resolve(); const highlight = (container) => { @@ -88,18 +107,31 @@ const register_message_buttons = async () => { }) } }); + document.querySelectorAll(".message .fa-clipboard").forEach(async (el) => { if (!("click" in el.dataset)) { el.dataset.click = "true"; el.addEventListener("click", async () => { const message_el = el.parentElement.parentElement.parentElement; const copyText = await get_message(window.conversation_id, message_el.dataset.index); - navigator.clipboard.writeText(copyText); + + try { + if (!navigator.clipboard) { + throw new Error("navigator.clipboard: Clipboard API unavailable."); + } + await navigator.clipboard.writeText(copyText); + } catch (e) { + console.error(e); + console.error("Clipboard API writeText() failed! Fallback to document.exec(\"copy\")..."); + fallback_clipboard(copyText); + } + el.classList.add("clicked"); setTimeout(() => el.classList.remove("clicked"), 1000); }) } }); + document.querySelectorAll(".message .fa-volume-high").forEach(async (el) => { if (!("click" in el.dataset)) { el.dataset.click = "true"; @@ -306,6 +338,14 @@ const prepare_messages = (messages, message_index = -1) => { messages = messages.filter((_, index) => message_index >= index); } + let new_messages = []; + if (systemPrompt?.value) { + new_messages.push({ + "role": "system", + "content": systemPrompt.value + }); + } + // Remove history, if it's selected if (document.getElementById('history')?.checked) { if (message_index == null) { @@ -315,13 +355,6 @@ const prepare_messages = (messages, message_index = -1) => { } } - let new_messages = []; - if (systemPrompt?.value) { - new_messages.push({ - "role": "system", - "content": systemPrompt.value - }); - } messages.forEach((new_message) => { // Include only not regenerated messages if (new_message && !new_message.regenerate) { @@ -334,6 +367,7 @@ const prepare_messages = (messages, message_index = -1) => { return new_messages; } + async function add_message_chunk(message) { if (message.type == "conversation") { console.info("Conversation used:", message.conversation) @@ -1424,4 +1458,4 @@ if (SpeechRecognition) { recognition.start(); } }); -}
\ No newline at end of file +} diff --git a/g4f/gui/client/static/js/highlightjs-copy.min.js b/g4f/gui/client/static/js/highlightjs-copy.min.js index ac11d33e..cd8ae957 100644 --- a/g4f/gui/client/static/js/highlightjs-copy.min.js +++ b/g4f/gui/client/static/js/highlightjs-copy.min.js @@ -1 +1,54 @@ -class CopyButtonPlugin{constructor(options={}){self.hook=options.hook;self.callback=options.callback}"after:highlightElement"({el,text}){let button=Object.assign(document.createElement("button"),{innerHTML:"Copy",className:"hljs-copy-button"});button.dataset.copied=false;el.parentElement.classList.add("hljs-copy-wrapper");el.parentElement.appendChild(button);el.parentElement.style.setProperty("--hljs-theme-background",window.getComputedStyle(el).backgroundColor);button.onclick=function(){if(!navigator.clipboard)return;let newText=text;if(hook&&typeof hook==="function"){newText=hook(text,el)||text}navigator.clipboard.writeText(newText).then(function(){button.innerHTML="Copied!";button.dataset.copied=true;let alert=Object.assign(document.createElement("div"),{role:"status",className:"hljs-copy-alert",innerHTML:"Copied to clipboard"});el.parentElement.appendChild(alert);setTimeout(()=>{button.innerHTML="Copy";button.dataset.copied=false;el.parentElement.removeChild(alert);alert=null},2e3)}).then(function(){if(typeof callback==="function")return callback(newText,el)})}}}
\ No newline at end of file +class CopyButtonPlugin { + constructor(options = {}) { + self.hook = options.hook; + self.callback = options.callback + } + "after:highlightElement"({ + el, + text + }) { + let button = Object.assign(document.createElement("button"), { + innerHTML: "Copy", + className: "hljs-copy-button" + }); + button.dataset.copied = false; + el.parentElement.classList.add("hljs-copy-wrapper"); + el.parentElement.appendChild(button); + el.parentElement.style.setProperty("--hljs-theme-background", window.getComputedStyle(el).backgroundColor); + button.onclick = async () => { + let newText = text; + if (hook && typeof hook === "function") { + newText = hook(text, el) || text + } + try { + if (!navigator.clipboard) { + throw new Error("navigator.clipboard: Clipboard API unavailable."); + } + await navigator.clipboard.writeText(newText); + } catch (e) { + console.error(e); + console.error("Clipboard API writeText() failed! Fallback to document.exec(\"copy\")..."); + fallback_clipboard(newText); + } + button.innerHTML = "Copied!"; + button.dataset.copied = true; + let alert = Object.assign(document.createElement("div"), { + role: "status", + className: "hljs-copy-alert", + innerHTML: "Copied to clipboard" + }); + el.parentElement.appendChild(alert); + setTimeout(() => { + button.innerHTML = "Copy"; + button.dataset.copied = false; + el.parentElement.removeChild(alert); + alert = null + }, 2e3) + } + + + if (typeof callback === "function") return callback(newText, el); + + } + +} diff --git a/g4f/gui/server/api.py b/g4f/gui/server/api.py index c984abec..7aac650a 100644 --- a/g4f/gui/server/api.py +++ b/g4f/gui/server/api.py @@ -2,13 +2,11 @@ from __future__ import annotations import logging import os -import os.path import uuid import asyncio import time -import base64 from aiohttp import ClientSession -from typing import Iterator, Optional +from typing import Iterator, Optional, AsyncIterator, Union from flask import send_from_directory from g4f import version, models @@ -21,21 +19,20 @@ from g4f.Provider import ProviderType, __providers__, __map__ from g4f.providers.base_provider import ProviderModelMixin, FinishReason from g4f.providers.conversation import BaseConversation -conversations: dict[dict[str, BaseConversation]] = {} +# Define the directory for generated images images_dir = "./generated_images" -class Api(): +# Function to ensure the images directory exists +def ensure_images_dir(): + if not os.path.exists(images_dir): + os.makedirs(images_dir) - @staticmethod - def get_models() -> list[str]: - """ - Return a list of all models. +conversations: dict[dict[str, BaseConversation]] = {} - Fetches and returns a list of all available models in the system. - Returns: - List[str]: A list of model names. - """ +class Api: + @staticmethod + def get_models() -> list[str]: return models._all_models @staticmethod @@ -43,14 +40,11 @@ class Api(): if provider in __map__: provider: ProviderType = __map__[provider] if issubclass(provider, ProviderModelMixin): - return [{"model": model, "default": model == provider.default_model} for model in provider.get_models()] - elif provider.supports_gpt_35_turbo or provider.supports_gpt_4: return [ - *([{"model": "gpt-4", "default": not provider.supports_gpt_4}] if provider.supports_gpt_4 else []), - *([{"model": "gpt-3.5-turbo", "default": not provider.supports_gpt_4}] if provider.supports_gpt_35_turbo else []) + {"model": model, "default": model == provider.default_model} + for model in provider.get_models() ] - else: - return []; + return [] @staticmethod def get_image_models() -> list[dict]: @@ -72,7 +66,7 @@ class Api(): "image_model": model, "vision_model": parent.default_vision_model if hasattr(parent, "default_vision_model") else None }) - index.append(parent.__name__) + index.append(parent.__name__) elif hasattr(provider, "default_vision_model") and provider.__name__ not in index: image_models.append({ "provider": provider.__name__, @@ -86,31 +80,20 @@ class Api(): @staticmethod def get_providers() -> list[str]: - """ - Return a list of all working providers. - """ return { - provider.__name__: (provider.label - if hasattr(provider, "label") - else provider.__name__) + - (" (WebDriver)" - if "webdriver" in provider.get_parameters() - else "") + - (" (Auth)" - if provider.needs_auth - else "") + provider.__name__: ( + provider.label if hasattr(provider, "label") else provider.__name__ + ) + ( + " (WebDriver)" if "webdriver" in provider.get_parameters() else "" + ) + ( + " (Auth)" if provider.needs_auth else "" + ) for provider in __providers__ if provider.working } @staticmethod def get_version(): - """ - Returns the current and latest version of the application. - - Returns: - dict: A dictionary containing the current and latest version. - """ try: current_version = version.utils.current_version except VersionNotFoundError: @@ -121,18 +104,10 @@ class Api(): } def serve_images(self, name): + ensure_images_dir() return send_from_directory(os.path.abspath(images_dir), name) def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict): - """ - Prepares arguments for chat completion based on the request data. - - Reads the request and prepares the necessary arguments for handling - a chat completion request. - - Returns: - dict: Arguments prepared for chat completion. - """ model = json_data.get('model') or models.default provider = json_data.get('provider') messages = json_data['messages'] @@ -140,7 +115,7 @@ class Api(): if api_key is not None: kwargs["api_key"] = api_key if json_data.get('web_search'): - if provider in ("Bing", "HuggingChat"): + if provider: kwargs['web_search'] = True else: from .internet import get_search_message @@ -161,101 +136,67 @@ class Api(): } def _create_response_stream(self, kwargs: dict, conversation_id: str, provider: str) -> Iterator: - """ - Creates and returns a streaming response for the conversation. - - Args: - kwargs (dict): Arguments for creating the chat completion. - - Yields: - str: JSON formatted response chunks for the stream. - - Raises: - Exception: If an error occurs during the streaming process. - """ try: + result = ChatCompletion.create(**kwargs) first = True - for chunk in ChatCompletion.create(**kwargs): + if isinstance(result, ImageResponse): if first: first = False yield self._format_json("provider", get_last_provider(True)) - if isinstance(chunk, BaseConversation): - if provider not in conversations: - conversations[provider] = {} - conversations[provider][conversation_id] = chunk - yield self._format_json("conversation", conversation_id) - elif isinstance(chunk, Exception): - logging.exception(chunk) - yield self._format_json("message", get_error_message(chunk)) - elif isinstance(chunk, ImagePreview): - yield self._format_json("preview", chunk.to_string()) - elif isinstance(chunk, ImageResponse): - async def copy_images(images: list[str], cookies: Optional[Cookies] = None): - async with ClientSession( - connector=get_connector(None, os.environ.get("G4F_PROXY")), - cookies=cookies - ) as session: - async def copy_image(image): - if image.startswith("data:"): - # Processing the data URL - data_uri_parts = image.split(",") - if len(data_uri_parts) == 2: - content_type, base64_data = data_uri_parts - extension = content_type.split("/")[-1].split(";")[0] - target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}.{extension}") - with open(target, "wb") as f: - f.write(base64.b64decode(base64_data)) - return f"/images/{os.path.basename(target)}" - else: - return None - else: - # Обробка звичайної URL-адреси - async with session.get(image) as response: - target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}") - with open(target, "wb") as f: - async for chunk in response.content.iter_any(): - f.write(chunk) - with open(target, "rb") as f: - extension = is_accepted_format(f.read(12)).split("/")[-1] - extension = "jpg" if extension == "jpeg" else extension - new_target = f"{target}.{extension}" - os.rename(target, new_target) - return f"/images/{os.path.basename(new_target)}" - return await asyncio.gather(*[copy_image(image) for image in images]) - images = asyncio.run(copy_images(chunk.get_list(), chunk.options.get("cookies"))) - yield self._format_json("content", str(ImageResponse(images, chunk.alt))) - elif not isinstance(chunk, FinishReason): - yield self._format_json("content", str(chunk)) + yield self._format_json("content", str(result)) + else: + for chunk in result: + if first: + first = False + yield self._format_json("provider", get_last_provider(True)) + if isinstance(chunk, BaseConversation): + if provider not in conversations: + conversations[provider] = {} + conversations[provider][conversation_id] = chunk + yield self._format_json("conversation", conversation_id) + elif isinstance(chunk, Exception): + logging.exception(chunk) + yield self._format_json("message", get_error_message(chunk)) + elif isinstance(chunk, ImagePreview): + yield self._format_json("preview", chunk.to_string()) + elif isinstance(chunk, ImageResponse): + images = asyncio.run(self._copy_images(chunk.get_list(), chunk.options.get("cookies"))) + yield self._format_json("content", str(ImageResponse(images, chunk.alt))) + elif not isinstance(chunk, FinishReason): + yield self._format_json("content", str(chunk)) except Exception as e: logging.exception(e) yield self._format_json('error', get_error_message(e)) - def _format_json(self, response_type: str, content): - """ - Formats and returns a JSON response. - - Args: - response_type (str): The type of the response. - content: The content to be included in the response. + async def _copy_images(self, images: list[str], cookies: Optional[Cookies] = None): + ensure_images_dir() + async with ClientSession( + connector=get_connector(None, os.environ.get("G4F_PROXY")), + cookies=cookies + ) as session: + async def copy_image(image): + async with session.get(image) as response: + target = os.path.join(images_dir, f"{int(time.time())}_{str(uuid.uuid4())}") + with open(target, "wb") as f: + async for chunk in response.content.iter_any(): + f.write(chunk) + with open(target, "rb") as f: + extension = is_accepted_format(f.read(12)).split("/")[-1] + extension = "jpg" if extension == "jpeg" else extension + new_target = f"{target}.{extension}" + os.rename(target, new_target) + return f"/images/{os.path.basename(new_target)}" + + return await asyncio.gather(*[copy_image(image) for image in images]) - Returns: - str: A JSON formatted string. - """ + def _format_json(self, response_type: str, content): return { 'type': response_type, response_type: content } -def get_error_message(exception: Exception) -> str: - """ - Generates a formatted error message from an exception. - Args: - exception (Exception): The exception to format. - - Returns: - str: A formatted error message string. - """ +def get_error_message(exception: Exception) -> str: message = f"{type(exception).__name__}: {exception}" provider = get_last_provider() if provider is None: diff --git a/g4f/gui/server/internet.py b/g4f/gui/server/internet.py index a1fafa7d..78bea0ca 100644 --- a/g4f/gui/server/internet.py +++ b/g4f/gui/server/internet.py @@ -101,7 +101,7 @@ async def search(query: str, n_results: int = 5, max_words: int = 2500, add_text raise MissingRequirementsError('Install "duckduckgo-search" and "beautifulsoup4" package') async with AsyncDDGS() as ddgs: results = [] - for result in await ddgs.text( + for result in await ddgs.atext( query, region="wt-wt", safesearch="moderate", diff --git a/g4f/gui/server/website.py b/g4f/gui/server/website.py index 5e633674..3cabcdf3 100644 --- a/g4f/gui/server/website.py +++ b/g4f/gui/server/website.py @@ -27,6 +27,10 @@ class Website: 'function': redirect_home, 'methods': ['GET', 'POST'] }, + '/images/': { + 'function': redirect_home, + 'methods': ['GET', 'POST'] + }, } def _chat(self, conversation_id): @@ -35,4 +39,4 @@ class Website: return render_template('index.html', chat_id=conversation_id) def _index(self): - return render_template('index.html', chat_id=str(uuid.uuid4()))
\ No newline at end of file + return render_template('index.html', chat_id=str(uuid.uuid4())) diff --git a/g4f/models.py b/g4f/models.py index ddbeeddf..32a12d10 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -4,35 +4,54 @@ from dataclasses import dataclass from .Provider import IterListProvider, ProviderType from .Provider import ( - AiChatOnline, + Ai4Chat, + AIChatFree, + AiMathGPT, + Airforce, Allyfy, + AmigoChat, Bing, - Binjie, - Bixin123, Blackbox, - ChatGot, + ChatGpt, Chatgpt4Online, - Chatgpt4o, + ChatGptEs, ChatgptFree, - CodeNews, + ChatHub, + ChatifyAI, + Cloudflare, + DarkAI, DDG, DeepInfra, - DeepInfraImage, - FluxAirforce, + DeepInfraChat, + Editee, Free2GPT, FreeChatgpt, FreeGpt, FreeNetfly, Gemini, GeminiPro, + GizAI, GigaChat, + GPROChat, HuggingChat, HuggingFace, Koala, Liaobots, MagickPen, MetaAI, - Nexra, + NexraBing, + NexraBlackbox, + NexraChatGPT, + NexraDallE, + NexraDallE2, + NexraEmi, + NexraFluxPro, + NexraGeminiPro, + NexraMidjourney, + NexraQwen, + NexraSD15, + NexraSDLora, + NexraSDTurbo, OpenaiChat, PerplexityLabs, Pi, @@ -40,11 +59,9 @@ from .Provider import ( Reka, Replicate, ReplicateHome, - Snova, + RubiksAI, TeachAnything, - TwitterBio, Upstage, - You, ) @@ -67,6 +84,8 @@ class Model: """Returns a list of all model names.""" return _all_models + +### Default ### default = Model( name = "", base_provider = "", @@ -75,17 +94,26 @@ default = Model( FreeChatgpt, HuggingChat, Pizzagpt, - ChatgptFree, ReplicateHome, Upstage, Blackbox, - Bixin123, - Binjie, Free2GPT, MagickPen, + DeepInfraChat, + Airforce, + ChatHub, + ChatGptEs, + ChatHub, + AmigoChat, + ChatifyAI, + Cloudflare, + Editee, + AiMathGPT, ]) ) + + ############ ### Text ### ############ @@ -95,55 +123,55 @@ default = Model( gpt_3 = Model( name = 'gpt-3', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Nexra, - ]) + best_provider = NexraChatGPT ) # gpt-3.5 gpt_35_turbo = Model( name = 'gpt-3.5-turbo', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Allyfy, TwitterBio, Nexra, Bixin123, CodeNews, - ]) + best_provider = IterListProvider([Allyfy, NexraChatGPT, Airforce, DarkAI, Liaobots]) ) # gpt-4 gpt_4o = Model( name = 'gpt-4o', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Liaobots, Chatgpt4o, OpenaiChat, - ]) + best_provider = IterListProvider([NexraChatGPT, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, GizAI, Airforce, Liaobots, OpenaiChat]) ) gpt_4o_mini = Model( name = 'gpt-4o-mini', base_provider = 'OpenAI', - best_provider = IterListProvider([ - DDG, Liaobots, You, FreeNetfly, Pizzagpt, ChatgptFree, AiChatOnline, CodeNews, - MagickPen, OpenaiChat, Koala, - ]) + best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, GizAI, ChatgptFree, Koala, OpenaiChat, ChatGpt]) ) gpt_4_turbo = Model( name = 'gpt-4-turbo', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Nexra, Bixin123, Liaobots, Bing - ]) + best_provider = IterListProvider([Liaobots, Airforce, Bing]) ) gpt_4 = Model( name = 'gpt-4', base_provider = 'OpenAI', - best_provider = IterListProvider([ - Chatgpt4Online, Nexra, Binjie, Bing, - gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider - ]) + best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider]) +) + +# o1 +o1 = Model( + name = 'o1', + base_provider = 'OpenAI', + best_provider = AmigoChat ) +o1_mini = Model( + name = 'o1-mini', + base_provider = 'OpenAI', + best_provider = IterListProvider([AmigoChat, GizAI]) +) + + ### GigaChat ### gigachat = Model( name = 'GigaChat:latest', @@ -159,133 +187,252 @@ meta = Model( best_provider = MetaAI ) +# llama 2 +llama_2_7b = Model( + name = "llama-2-7b", + base_provider = "Meta Llama", + best_provider = Cloudflare +) + +llama_2_13b = Model( + name = "llama-2-13b", + base_provider = "Meta Llama", + best_provider = Airforce +) + +# llama 3 llama_3_8b = Model( name = "llama-3-8b", - base_provider = "Meta", - best_provider = IterListProvider([DeepInfra, Replicate]) + base_provider = "Meta Llama", + best_provider = IterListProvider([Cloudflare, Airforce, DeepInfra, Replicate]) ) llama_3_70b = Model( name = "llama-3-70b", - base_provider = "Meta", - best_provider = IterListProvider([ReplicateHome, DeepInfra, PerplexityLabs, Replicate]) + base_provider = "Meta Llama", + best_provider = IterListProvider([ReplicateHome, Airforce, DeepInfra, Replicate]) ) +# llama 3.1 llama_3_1_8b = Model( name = "llama-3.1-8b", - base_provider = "Meta", - best_provider = IterListProvider([Blackbox]) + base_provider = "Meta Llama", + best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, GizAI, PerplexityLabs]) ) llama_3_1_70b = Model( name = "llama-3.1-70b", - base_provider = "Meta", - best_provider = IterListProvider([DDG, HuggingChat, FreeGpt, Blackbox, TeachAnything, Free2GPT, HuggingFace]) + base_provider = "Meta Llama", + best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, GizAI, HuggingFace, PerplexityLabs]) ) llama_3_1_405b = Model( name = "llama-3.1-405b", - base_provider = "Meta", - best_provider = IterListProvider([HuggingChat, Blackbox, HuggingFace]) + base_provider = "Meta Llama", + best_provider = IterListProvider([DeepInfraChat, Blackbox, AmigoChat, DarkAI, Airforce]) +) + +# llama 3.2 +llama_3_2_1b = Model( + name = "llama-3.2-1b", + base_provider = "Meta Llama", + best_provider = Cloudflare +) + +llama_3_2_3b = Model( + name = "llama-3.2-3b", + base_provider = "Meta Llama", + best_provider = Cloudflare ) +llama_3_2_11b = Model( + name = "llama-3.2-11b", + base_provider = "Meta Llama", + best_provider = IterListProvider([Cloudflare, HuggingChat, HuggingFace]) +) + +llama_3_2_90b = Model( + name = "llama-3.2-90b", + base_provider = "Meta Llama", + best_provider = IterListProvider([AmigoChat, Airforce]) +) + + +# llamaguard +llamaguard_7b = Model( + name = "llamaguard-7b", + base_provider = "Meta Llama", + best_provider = Airforce +) + +llamaguard_2_8b = Model( + name = "llamaguard-2-8b", + base_provider = "Meta Llama", + best_provider = Airforce +) + + ### Mistral ### +mistral_7b = Model( + name = "mistral-7b", + base_provider = "Mistral", + best_provider = IterListProvider([DeepInfraChat, Cloudflare, Airforce, DeepInfra]) +) + mixtral_8x7b = Model( name = "mixtral-8x7b", base_provider = "Mistral", - best_provider = IterListProvider([HuggingChat, DDG, ReplicateHome, TwitterBio, DeepInfra, HuggingFace,]) + best_provider = IterListProvider([DDG, ReplicateHome, DeepInfraChat, ChatHub, Airforce, DeepInfra]) ) -mistral_7b = Model( - name = "mistral-7b", +mixtral_8x22b = Model( + name = "mixtral-8x22b", base_provider = "Mistral", - best_provider = IterListProvider([HuggingChat, HuggingFace, DeepInfra]) + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -### 01-ai ### -yi_1_5_34b = Model( - name = "yi-1.5-34b", - base_provider = "01-ai", +mistral_nemo = Model( + name = "mistral-nemo", + base_provider = "Mistral", + best_provider = IterListProvider([HuggingChat, HuggingFace]) +) + +mistral_large = Model( + name = "mistral-large", + base_provider = "Mistral", + best_provider = IterListProvider([Editee, GizAI]) +) + + +### NousResearch ### +mixtral_8x7b_dpo = Model( + name = "mixtral-8x7b-dpo", + base_provider = "NousResearch", + best_provider = Airforce +) + +yi_34b = Model( + name = "yi-34b", + base_provider = "NousResearch", + best_provider = Airforce +) + +hermes_3 = Model( + name = "hermes-3", + base_provider = "NousResearch", best_provider = IterListProvider([HuggingChat, HuggingFace]) ) ### Microsoft ### -phi_3_mini_4k = Model( - name = "phi-3-mini-4k", +phi_2 = Model( + name = "phi-2", base_provider = "Microsoft", - best_provider = IterListProvider([HuggingFace, HuggingChat]) + best_provider = Cloudflare ) +phi_3_medium_4k = Model( + name = "phi-3-medium-4k", + base_provider = "Microsoft", + best_provider = DeepInfraChat +) -### Google ### +phi_3_5_mini = Model( + name = "phi-3.5-mini", + base_provider = "Microsoft", + best_provider = IterListProvider([HuggingChat, HuggingFace]) +) + +### Google DeepMind ### # gemini +gemini_pro = Model( + name = 'gemini-pro', + base_provider = 'Google DeepMind', + best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, GizAI, Airforce, Liaobots]) +) + +gemini_flash = Model( + name = 'gemini-flash', + base_provider = 'Google DeepMind', + best_provider = IterListProvider([Blackbox, GizAI, Airforce, Liaobots]) +) + gemini = Model( name = 'gemini', - base_provider = 'Google', + base_provider = 'Google DeepMind', best_provider = Gemini ) -gemini_pro = Model( - name = 'gemini-pro', +# gemma +gemma_2b_9b = Model( + name = 'gemma-2b-9b', base_provider = 'Google', - best_provider = IterListProvider([GeminiPro, ChatGot, Liaobots]) + best_provider = Airforce ) -gemini_flash = Model( - name = 'gemini-flash', +gemma_2b_27b = Model( + name = 'gemma-2b-27b', base_provider = 'Google', - best_provider = IterListProvider([Liaobots, Blackbox]) + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -# gemma gemma_2b = Model( name = 'gemma-2b', base_provider = 'Google', - best_provider = IterListProvider([ReplicateHome]) + best_provider = IterListProvider([ReplicateHome, Airforce]) ) -### Anthropic ### -claude_2 = Model( - name = 'claude-2', - base_provider = 'Anthropic', - best_provider = IterListProvider([You]) +gemma_7b = Model( + name = 'gemma-7b', + base_provider = 'Google', + best_provider = Cloudflare ) -claude_2_0 = Model( - name = 'claude-2.0', - base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) +# gemma 2 +gemma_2_27b = Model( + name = 'gemma-2-27b', + base_provider = 'Google', + best_provider = Airforce ) +gemma_2 = Model( + name = 'gemma-2', + base_provider = 'Google', + best_provider = ChatHub +) + + +### Anthropic ### claude_2_1 = Model( name = 'claude-2.1', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = Liaobots ) +# claude 3 claude_3_opus = Model( name = 'claude-3-opus', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([Airforce, Liaobots]) ) claude_3_sonnet = Model( name = 'claude-3-sonnet', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([Airforce, Liaobots]) ) -claude_3_5_sonnet = Model( - name = 'claude-3-5-sonnet', +claude_3_haiku = Model( + name = 'claude-3-haiku', base_provider = 'Anthropic', - best_provider = IterListProvider([Liaobots]) + best_provider = IterListProvider([DDG, Airforce, GizAI, Liaobots]) ) -claude_3_haiku = Model( - name = 'claude-3-haiku', +# claude 3.5 +claude_3_5_sonnet = Model( + name = 'claude-3.5-sonnet', base_provider = 'Anthropic', - best_provider = IterListProvider([DDG, Liaobots]) + best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, GizAI, Liaobots]) ) @@ -297,10 +444,16 @@ reka_core = Model( ) -### Blackbox ### -blackbox = Model( - name = 'blackbox', - base_provider = 'Blackbox', +### Blackbox AI ### +blackboxai = Model( + name = 'blackboxai', + base_provider = 'Blackbox AI', + best_provider = IterListProvider([Blackbox, NexraBlackbox]) +) + +blackboxai_pro = Model( + name = 'blackboxai-pro', + base_provider = 'Blackbox AI', best_provider = Blackbox ) @@ -309,7 +462,7 @@ blackbox = Model( dbrx_instruct = Model( name = 'dbrx-instruct', base_provider = 'Databricks', - best_provider = IterListProvider([DeepInfra]) + best_provider = IterListProvider([Airforce, DeepInfra]) ) @@ -317,7 +470,7 @@ dbrx_instruct = Model( command_r_plus = Model( name = 'command-r-plus', base_provider = 'CohereForAI', - best_provider = IterListProvider([HuggingChat]) + best_provider = HuggingChat ) @@ -325,20 +478,59 @@ command_r_plus = Model( sparkdesk_v1_1 = Model( name = 'sparkdesk-v1.1', base_provider = 'iFlytek', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) + ### Qwen ### +# qwen 1 +qwen_1_5_0_5b = Model( + name = 'qwen-1.5-0.5b', + base_provider = 'Qwen', + best_provider = Cloudflare +) + +qwen_1_5_7b = Model( + name = 'qwen-1.5-7b', + base_provider = 'Qwen', + best_provider = IterListProvider([Cloudflare, Airforce]) +) + qwen_1_5_14b = Model( name = 'qwen-1.5-14b', base_provider = 'Qwen', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = IterListProvider([FreeChatgpt, Cloudflare, Airforce]) +) + +qwen_1_5_72b = Model( + name = 'qwen-1.5-72b', + base_provider = 'Qwen', + best_provider = Airforce ) -qwen_turbo = Model( - name = 'qwen-turbo', +qwen_1_5_110b = Model( + name = 'qwen-1.5-110b', base_provider = 'Qwen', - best_provider = IterListProvider([Bixin123]) + best_provider = Airforce +) + +qwen_1_5_1_8b = Model( + name = 'qwen-1.5-1.8b', + base_provider = 'Qwen', + best_provider = Airforce +) + +# qwen 2 +qwen_2_72b = Model( + name = 'qwen-2-72b', + base_provider = 'Qwen', + best_provider = IterListProvider([DeepInfraChat, HuggingChat, Airforce, HuggingFace]) +) + +qwen = Model( + name = 'qwen', + base_provider = 'Qwen', + best_provider = NexraQwen ) @@ -346,76 +538,196 @@ qwen_turbo = Model( glm_3_6b = Model( name = 'glm-3-6b', base_provider = 'Zhipu AI', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) glm_4_9b = Model( name = 'glm-4-9B', base_provider = 'Zhipu AI', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) -glm_4 = Model( - name = 'glm-4', - base_provider = 'Zhipu AI', - best_provider = IterListProvider([CodeNews, glm_4_9b.best_provider,]) -) ### 01-ai ### yi_1_5_9b = Model( name = 'yi-1.5-9b', base_provider = '01-ai', - best_provider = IterListProvider([FreeChatgpt]) + best_provider = FreeChatgpt ) - -### Pi ### +### Upstage ### solar_1_mini = Model( name = 'solar-1-mini', base_provider = 'Upstage', - best_provider = IterListProvider([Upstage]) + best_provider = Upstage +) + +solar_10_7b = Model( + name = 'solar-10-7b', + base_provider = 'Upstage', + best_provider = Airforce ) -### Pi ### +solar_pro = Model( + name = 'solar-pro', + base_provider = 'Upstage', + best_provider = Upstage +) + + +### Inflection ### pi = Model( name = 'pi', - base_provider = 'inflection', + base_provider = 'Inflection', best_provider = Pi ) -### SambaNova ### -samba_coe_v0_1 = Model( - name = 'samba-coe-v0.1', - base_provider = 'SambaNova', - best_provider = Snova +### DeepSeek ### +deepseek = Model( + name = 'deepseek', + base_provider = 'DeepSeek', + best_provider = Airforce +) + +### WizardLM ### +wizardlm_2_7b = Model( + name = 'wizardlm-2-7b', + base_provider = 'WizardLM', + best_provider = DeepInfraChat ) -### Trong-Hieu Nguyen-Mau ### -v1olet_merged_7b = Model( - name = 'v1olet-merged-7b', - base_provider = 'Trong-Hieu Nguyen-Mau', - best_provider = Snova +wizardlm_2_8x22b = Model( + name = 'wizardlm-2-8x22b', + base_provider = 'WizardLM', + best_provider = IterListProvider([DeepInfraChat, Airforce]) ) -### Macadeliccc ### -westlake_7b_v2 = Model( - name = 'westlake-7b-v2', - base_provider = 'Macadeliccc', - best_provider = Snova +### Yorickvp ### +llava_13b = Model( + name = 'llava-13b', + base_provider = 'Yorickvp', + best_provider = ReplicateHome ) -### CookinAI ### -donutlm_v1 = Model( - name = 'donutlm-v1', - base_provider = 'CookinAI', - best_provider = Snova + +### OpenBMB ### +minicpm_llama_3_v2_5 = Model( + name = 'minicpm-llama-3-v2.5', + base_provider = 'OpenBMB', + best_provider = DeepInfraChat ) -### DeepSeek ### -deepseek = Model( - name = 'deepseek', - base_provider = 'DeepSeek', - best_provider = CodeNews + +### Lzlv ### +lzlv_70b = Model( + name = 'lzlv-70b', + base_provider = 'Lzlv', + best_provider = DeepInfraChat +) + + +### OpenChat ### +openchat_3_5 = Model( + name = 'openchat-3.5', + base_provider = 'OpenChat', + best_provider = Cloudflare +) + +openchat_3_6_8b = Model( + name = 'openchat-3.6-8b', + base_provider = 'OpenChat', + best_provider = DeepInfraChat +) + + +### Phind ### +phind_codellama_34b_v2 = Model( + name = 'phind-codellama-34b-v2', + base_provider = 'Phind', + best_provider = DeepInfraChat +) + + +### Cognitive Computations ### +dolphin_2_9_1_llama_3_70b = Model( + name = 'dolphin-2.9.1-llama-3-70b', + base_provider = 'Cognitive Computations', + best_provider = DeepInfraChat +) + + +### x.ai ### +grok_2 = Model( + name = 'grok-2', + base_provider = 'x.ai', + best_provider = Liaobots +) + +grok_2_mini = Model( + name = 'grok-2-mini', + base_provider = 'x.ai', + best_provider = Liaobots +) + + +### Perplexity AI ### +sonar_online = Model( + name = 'sonar-online', + base_provider = 'Perplexity AI', + best_provider = IterListProvider([ChatHub, PerplexityLabs]) +) + +sonar_chat = Model( + name = 'sonar-chat', + base_provider = 'Perplexity AI', + best_provider = PerplexityLabs +) + + +### Gryphe ### +mythomax_l2_13b = Model( + name = 'mythomax-l2-13b', + base_provider = 'Gryphe', + best_provider = Airforce +) + + +### Pawan ### +cosmosrp = Model( + name = 'cosmosrp', + base_provider = 'Pawan', + best_provider = Airforce +) + + +### TheBloke ### +german_7b = Model( + name = 'german-7b', + base_provider = 'TheBloke', + best_provider = Cloudflare +) + + +### Tinyllama ### +tinyllama_1_1b = Model( + name = 'tinyllama-1.1b', + base_provider = 'Tinyllama', + best_provider = Cloudflare +) + + +### Fblgit ### +cybertron_7b = Model( + name = 'cybertron-7b', + base_provider = 'Fblgit', + best_provider = Cloudflare +) + +### Nvidia ### +nemotron_70b = Model( + name = 'nemotron-70b', + base_provider = 'Nvidia', + best_provider = IterListProvider([HuggingChat, HuggingFace]) ) @@ -425,83 +737,157 @@ deepseek = Model( ############# ### Stability AI ### +sdxl_turbo = Model( + name = 'sdxl-turbo', + base_provider = 'Stability AI', + best_provider = NexraSDTurbo + +) + +sdxl_lora = Model( + name = 'sdxl-lora', + base_provider = 'Stability AI', + best_provider = NexraSDLora + +) + sdxl = Model( name = 'sdxl', base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome, DeepInfraImage]) + best_provider = IterListProvider([ReplicateHome]) + +) + +sd_1_5 = Model( + name = 'sd-1.5', + base_provider = 'Stability AI', + best_provider = IterListProvider([NexraSD15, GizAI]) ) sd_3 = Model( name = 'sd-3', base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome]) + best_provider = ReplicateHome + +) + +sd_3_5 = Model( + name = 'sd-3.5', + base_provider = 'Stability AI', + best_provider = GizAI ) ### Playground ### playground_v2_5 = Model( name = 'playground-v2.5', - base_provider = 'Stability AI', - best_provider = IterListProvider([ReplicateHome]) + base_provider = 'Playground AI', + best_provider = ReplicateHome ) + ### Flux AI ### flux = Model( name = 'flux', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = IterListProvider([Airforce, Blackbox]) + +) + +flux_pro = Model( + name = 'flux-pro', + base_provider = 'Flux AI', + best_provider = IterListProvider([NexraFluxPro, AmigoChat]) ) flux_realism = Model( name = 'flux-realism', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = IterListProvider([Airforce, AmigoChat]) ) flux_anime = Model( name = 'flux-anime', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce ) flux_3d = Model( name = 'flux-3d', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce ) flux_disney = Model( name = 'flux-disney', base_provider = 'Flux AI', - best_provider = IterListProvider([FluxAirforce]) + best_provider = Airforce + +) + +flux_pixel = Model( + name = 'flux-pixel', + base_provider = 'Flux AI', + best_provider = Airforce + +) + +flux_4o = Model( + name = 'flux-4o', + base_provider = 'Flux AI', + best_provider = Airforce + +) + +flux_schnell = Model( + name = 'flux-schnell', + base_provider = 'Flux AI', + best_provider = IterListProvider([ReplicateHome, GizAI]) + +) + + +### OpenAI ### +dalle_2 = Model( + name = 'dalle-2', + base_provider = 'OpenAI', + best_provider = NexraDallE2 ) -### ### dalle = Model( name = 'dalle', - base_provider = '', - best_provider = IterListProvider([Nexra]) + base_provider = 'OpenAI', + best_provider = NexraDallE ) -dalle_mini = Model( - name = 'dalle-mini', - base_provider = '', - best_provider = IterListProvider([Nexra]) +### Midjourney ### +midjourney = Model( + name = 'midjourney', + base_provider = 'Midjourney', + best_provider = NexraMidjourney ) +### Other ### emi = Model( name = 'emi', base_provider = '', - best_provider = IterListProvider([Nexra]) + best_provider = NexraEmi + +) + +any_dark = Model( + name = 'any-dark', + base_provider = '', + best_provider = Airforce ) @@ -526,15 +912,23 @@ class ModelUtils: 'gpt-3.5-turbo': gpt_35_turbo, # gpt-4 -'gpt-4o' : gpt_4o, -'gpt-4o-mini' : gpt_4o_mini, -'gpt-4' : gpt_4, -'gpt-4-turbo' : gpt_4_turbo, - +'gpt-4o': gpt_4o, +'gpt-4o-mini': gpt_4o_mini, +'gpt-4': gpt_4, +'gpt-4-turbo': gpt_4_turbo, + +# o1 +'o1': o1, +'o1-mini': o1_mini, + ### Meta ### "meta-ai": meta, +# llama-2 +'llama-2-7b': llama_2_7b, +'llama-2-13b': llama_2_13b, + # llama-3 'llama-3-8b': llama_3_8b, 'llama-3-70b': llama_3_70b, @@ -543,20 +937,37 @@ class ModelUtils: 'llama-3.1-8b': llama_3_1_8b, 'llama-3.1-70b': llama_3_1_70b, 'llama-3.1-405b': llama_3_1_405b, - + +# llama-3.2 +'llama-3.2-1b': llama_3_2_1b, +'llama-3.2-3b': llama_3_2_3b, +'llama-3.2-11b': llama_3_2_11b, +'llama-3.2-90b': llama_3_2_90b, + +# llamaguard +'llamaguard-7b': llamaguard_7b, +'llamaguard-2-8b': llamaguard_2_8b, + ### Mistral ### -'mixtral-8x7b': mixtral_8x7b, 'mistral-7b': mistral_7b, - - -### 01-ai ### -'yi-1.5-34b': yi_1_5_34b, +'mixtral-8x7b': mixtral_8x7b, +'mixtral-8x22b': mixtral_8x22b, +'mistral-nemo': mistral_nemo, +'mistral-large': mistral_large, + + +### NousResearch ### +'mixtral-8x7b-dpo': mixtral_8x7b_dpo, +'hermes-3': hermes_3, + +'yi-34b': yi_34b, ### Microsoft ### -'phi-3-mini-4k': phi_3_mini_4k, - +'phi-2': phi_2, +'phi_3_medium-4k': phi_3_medium_4k, +'phi-3.5-mini': phi_3_5_mini, ### Google ### # gemini @@ -566,25 +977,34 @@ class ModelUtils: # gemma 'gemma-2b': gemma_2b, +'gemma-2b-9b': gemma_2b_9b, +'gemma-2b-27b': gemma_2b_27b, +'gemma-7b': gemma_7b, + +# gemma-2 +'gemma-2': gemma_2, +'gemma-2-27b': gemma_2_27b, ### Anthropic ### -'claude-2': claude_2, -'claude-2.0': claude_2_0, 'claude-2.1': claude_2_1, - + +# claude 3 'claude-3-opus': claude_3_opus, 'claude-3-sonnet': claude_3_sonnet, -'claude-3-5-sonnet': claude_3_5_sonnet, 'claude-3-haiku': claude_3_haiku, + +# claude 3.5 +'claude-3.5-sonnet': claude_3_5_sonnet, ### Reka AI ### 'reka-core': reka_core, -### Blackbox ### -'blackbox': blackbox, +### Blackbox AI ### +'blackboxai': blackboxai, +'blackboxai-pro': blackboxai_pro, ### CohereForAI ### @@ -604,14 +1024,19 @@ class ModelUtils: ### Qwen ### +'qwen': qwen, +'qwen-1.5-0.5b': qwen_1_5_0_5b, +'qwen-1.5-7b': qwen_1_5_7b, 'qwen-1.5-14b': qwen_1_5_14b, -'qwen-turbo': qwen_turbo, +'qwen-1.5-72b': qwen_1_5_72b, +'qwen-1.5-110b': qwen_1_5_110b, +'qwen-1.5-1.8b': qwen_1_5_1_8b, +'qwen-2-72b': qwen_2_72b, ### Zhipu AI ### 'glm-3-6b': glm_3_6b, 'glm-4-9b': glm_4_9b, -'glm-4': glm_4, ### 01-ai ### @@ -619,30 +1044,80 @@ class ModelUtils: ### Upstage ### -'solar-1-mini': solar_1_mini, +'solar-mini': solar_1_mini, +'solar-10-7b': solar_10_7b, +'solar-pro': solar_pro, -### Pi ### +### Inflection ### 'pi': pi, +### DeepSeek ### +'deepseek': deepseek, + + +### Yorickvp ### +'llava-13b': llava_13b, -### SambaNova ### -'samba-coe-v0.1': samba_coe_v0_1, +### WizardLM ### +'wizardlm-2-7b': wizardlm_2_7b, +'wizardlm-2-8x22b': wizardlm_2_8x22b, + + +### OpenBMB ### +'minicpm-llama-3-v2.5': minicpm_llama_3_v2_5, + + +### Lzlv ### +'lzlv-70b': lzlv_70b, + + +### OpenChat ### +'openchat-3.5': openchat_3_5, +'openchat-3.6-8b': openchat_3_6_8b, -### Trong-Hieu Nguyen-Mau ### -'v1olet-merged-7b': v1olet_merged_7b, +### Phind ### +'phind-codellama-34b-v2': phind_codellama_34b_v2, + + +### Cognitive Computations ### +'dolphin-2.9.1-llama-3-70b': dolphin_2_9_1_llama_3_70b, + + +### x.ai ### +'grok-2': grok_2, +'grok-2-mini': grok_2_mini, + + +### Perplexity AI ### +'sonar-online': sonar_online, +'sonar-chat': sonar_chat, -### Macadeliccc ### -'westlake-7b-v2': westlake_7b_v2, +### Gryphe ### +'mythomax-l2-13b': sonar_chat, -### CookinAI ### -'donutlm-v1': donutlm_v1, + +### Pawan ### +'cosmosrp': cosmosrp, + + +### TheBloke ### +'german-7b': german_7b, -### DeepSeek ### -'deepseek': deepseek, + +### Tinyllama ### +'tinyllama-1.1b': tinyllama_1_1b, + + +### Fblgit ### +'cybertron-7b': cybertron_7b, + + +### Nvidia ### +'nemotron-70b': nemotron_70b, @@ -652,7 +1127,11 @@ class ModelUtils: ### Stability AI ### 'sdxl': sdxl, +'sdxl-lora': sdxl_lora, +'sdxl-turbo': sdxl_turbo, +'sd-1.5': sd_1_5, 'sd-3': sd_3, +'sd-3.5': sd_3_5, ### Playground ### @@ -661,16 +1140,27 @@ class ModelUtils: ### Flux AI ### 'flux': flux, +'flux-pro': flux_pro, 'flux-realism': flux_realism, 'flux-anime': flux_anime, 'flux-3d': flux_3d, 'flux-disney': flux_disney, +'flux-pixel': flux_pixel, +'flux-4o': flux_4o, +'flux-schnell': flux_schnell, -### ### +### OpenAI ### 'dalle': dalle, -'dalle-mini': dalle_mini, +'dalle-2': dalle_2, + +### Midjourney ### +'midjourney': midjourney, + + +### Other ### 'emi': emi, +'any-dark': any_dark, } _all_models = list(ModelUtils.convert.keys()) diff --git a/g4f/providers/types.py b/g4f/providers/types.py index 50c14431..69941a26 100644 --- a/g4f/providers/types.py +++ b/g4f/providers/types.py @@ -13,9 +13,8 @@ class BaseProvider(ABC): working (bool): Indicates if the provider is currently working. needs_auth (bool): Indicates if the provider needs authentication. supports_stream (bool): Indicates if the provider supports streaming. - supports_gpt_35_turbo (bool): Indicates if the provider supports GPT-3.5 Turbo. - supports_gpt_4 (bool): Indicates if the provider supports GPT-4. supports_message_history (bool): Indicates if the provider supports message history. + supports_system_message (bool): Indicates if the provider supports system messages. params (str): List parameters for the provider. """ @@ -23,8 +22,6 @@ class BaseProvider(ABC): working: bool = False needs_auth: bool = False supports_stream: bool = False - supports_gpt_35_turbo: bool = False - supports_gpt_4: bool = False supports_message_history: bool = False supports_system_message: bool = False params: str @@ -109,4 +106,4 @@ class Streaming(): self.data = data def __str__(self) -> str: - return self.data
\ No newline at end of file + return self.data diff --git a/g4f/version.py b/g4f/version.py index eda2b8fe..403ce370 100644 --- a/g4f/version.py +++ b/g4f/version.py @@ -116,4 +116,4 @@ class VersionUtils: except Exception as e: print(f'Failed to check g4f version: {e}') -utils = VersionUtils()
\ No newline at end of file +utils = VersionUtils() diff --git a/requirements-min.txt b/requirements-min.txt index 2944babd..483e4c7c 100644 --- a/requirements-min.txt +++ b/requirements-min.txt @@ -2,4 +2,6 @@ requests aiohttp brotli pycryptodome -curl_cffi>=0.6.2
\ No newline at end of file +curl_cffi>=0.6.2 +nest_asyncio +cloudscraper diff --git a/requirements.txt b/requirements.txt index fbb548a3..1f75adf7 100644 --- a/requirements.txt +++ b/requirements.txt @@ -21,3 +21,4 @@ pywebview plyer cryptography nodriver +cloudscraper @@ -12,7 +12,9 @@ INSTALL_REQUIRE = [ "requests", "aiohttp", "brotli", - "pycryptodome" + "pycryptodome", + "curl_cffi>=0.6.2", + "cloudscraper" # Cloudflare ] EXTRA_REQUIRE = { @@ -33,7 +35,6 @@ EXTRA_REQUIRE = { "platformdirs", "plyer", "cryptography", - #### "aiohttp_socks", # proxy "pillow", # image "cairosvg", # svg image @@ -74,9 +75,6 @@ EXTRA_REQUIRE = { ], "local": [ "gpt4all" - ], - "curl_cffi": [ - "curl_cffi>=0.6.2", ] } |