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@@ -100,72 +100,43 @@ or set the api base in your client to: [http://localhost:1337/v1](http://localho ##### Install using pypi: -Install all supported tools / all used packages: ``` pip install -U g4f[all] ``` -Or use: [Partially Requirements](/docs/requirements.md) +Or use partial requirements. +See: [/docs/requirements](/docs/requirements.md) ##### Install from source: -1. Clone the GitHub repository: +See: [/docs/git](/docs/git.md) -``` -git clone https://github.com/xtekky/gpt4free.git -``` - -2. Navigate to the project directory: - -``` -cd gpt4free -``` -3. (Recommended) Create a Python virtual environment: -You can follow the [Python official documentation](https://docs.python.org/3/tutorial/venv.html) for virtual environments. - - -``` -python3 -m venv venv -``` +##### Install using Docker -4. Activate the virtual environment: - - On Windows: - ``` - .\venv\Scripts\activate - ``` - - On macOS and Linux: - ``` - source venv/bin/activate - ``` -5. Install minimum requirements: + See: [/docs/docker](/docs/docker.md) -``` -pip install -r requirements-min.txt -``` -6. Or install all used Python packages from `requirements.txt`: +## 💡 Usage -``` -pip install -r requirements.txt -``` +#### Text Generation +**with Python** -7. Create a `test.py` file in the root folder and start using the repo, further Instructions are below +```python +from g4f.client import Client -```py -import g4f -... +client = Client() +response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Say this is a test"}], + ... +) +print(response.choices[0].message.content) ``` -##### Install using Docker - - Or use: [Build Docker](/docs/docker.md) - - -## 💡 Usage - #### Image Generation +**with Python** ```python from g4f.client import Client @@ -182,9 +153,7 @@ Result: [](/docs/client.md) -#### Text Generation - -and more: +**See also for Python:** - [Documentation for new Client](/docs/client.md) - [Documentation for leagcy API](/docs/leagcy.md) @@ -192,19 +161,31 @@ and more: #### Web UI -To start the web interface, type the following codes in the command line. +To start the web interface, type the following codes in python: ```python from g4f.gui import run_gui run_gui() ``` +or type in command line: +```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/interference](/docs/interference.md) + +### Configuration ##### Cookies / Access Token -For generating images with Bing and for the OpenAi Chat you need cookies or a token from your browser session. From Bing you need the "_U" cookie and from OpenAI you need the "access_token". You can pass the cookies / the access token in the create function or you use the `set_cookies` setter: +For generating images with Bing and for the OpenAi Chat you need cookies or a token from your browser session. From Bing you need the "_U" cookie and from OpenAI you need the "access_token". You can pass the cookies / the access token in the create function or you use the `set_cookies` setter before you run G4F: ```python -from g4f import set_cookies +from g4f.cookies import set_cookies set_cookies(".bing.com", { "_U": "cookie value" @@ -212,124 +193,30 @@ set_cookies(".bing.com", { set_cookies("chat.openai.com", { "access_token": "token value" }) +set_cookies(".google.com", { + "__Secure-1PSID": "cookie value" +}) -from g4f.gui import run_gui -run_gui() -``` - -Alternatively, g4f reads the cookies with “browser_cookie3” from your browser -or it starts a browser instance with selenium "webdriver" for logging in. -If you use the pip package, you have to install “browser_cookie3” or "webdriver" by yourself. - -```bash -pip install browser_cookie3 -pip install g4f[webdriver] +... ``` -##### Proxy and Timeout Support +Alternatively, G4F reads the cookies with `browser_cookie3` from your browser +or it starts a browser instance with selenium `webdriver` for logging in. -All providers support specifying a proxy and increasing timeout in the create functions. +##### Using Proxy -```python -import g4f +If you want to hide or change your IP address for the providers, you can set a proxy globally via an environment variable: -response = g4f.ChatCompletion.create( - model=g4f.models.default, - messages=[{"role": "user", "content": "Hello"}], - proxy="http://host:port", - # or socks5://user:pass@host:port - timeout=120, # in secs -) - -print(f"Result:", response) -``` - -You can also set a proxy globally via an environment variable: - -```sh +- On macOS and Linux: +```bash export G4F_PROXY="http://host:port" ``` -### Interference openai-proxy API (Use with openai python package) - -#### Run interference API from PyPi package - -```python -from g4f.api import run_api - -run_api() -``` - -#### Run interference API from repo - -If you want to use the embedding function, you need to get a Hugging Face token. You can get one at [Hugging Face Tokens](https://huggingface.co/settings/tokens). Make sure your role is set to write. If you have your token, just use it instead of the OpenAI api-key. - -Run server: - -```sh -g4f api -``` - -or - -```sh -python -m g4f.api.run -``` - -```python -from openai import OpenAI - -client = OpenAI( - # Set your Hugging Face token as the API key if you use embeddings - api_key="YOUR_HUGGING_FACE_TOKEN", - - # Set the API base URL if needed, e.g., for a local development environment - base_url="http://localhost:1337/v1" -) - - -def main(): - chat_completion = client.chat.completions.create( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "write a poem about a tree"}], - stream=True, - ) - - if isinstance(chat_completion, dict): - # Not streaming - print(chat_completion.choices[0].message.content) - else: - # Streaming - for token in chat_completion: - content = token.choices[0].delta.content - if content is not None: - print(content, end="", flush=True) - - -if __name__ == "__main__": - main() -``` - -## API usage (POST) -#### Chat completions -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', '')) +- On Windows: +```bash +set G4F_PROXY=http://host:port ``` - ## 🚀 Providers and Models ### GPT-4 |