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-rw-r--r--g4f/Provider/nexra/NexraBing.py93
-rw-r--r--g4f/Provider/nexra/NexraBlackbox.py100
-rw-r--r--g4f/Provider/nexra/NexraChatGPT.py285
-rw-r--r--g4f/Provider/nexra/NexraDallE.py63
-rw-r--r--g4f/Provider/nexra/NexraDallE2.py63
-rw-r--r--g4f/Provider/nexra/NexraEmi.py63
-rw-r--r--g4f/Provider/nexra/NexraFluxPro.py70
-rw-r--r--g4f/Provider/nexra/NexraGeminiPro.py86
-rw-r--r--g4f/Provider/nexra/NexraMidjourney.py63
-rw-r--r--g4f/Provider/nexra/NexraProdiaAI.py151
-rw-r--r--g4f/Provider/nexra/NexraQwen.py86
-rw-r--r--g4f/Provider/nexra/NexraSD15.py72
-rw-r--r--g4f/Provider/nexra/NexraSDLora.py69
-rw-r--r--g4f/Provider/nexra/NexraSDTurbo.py69
-rw-r--r--g4f/Provider/nexra/__init__.py14
15 files changed, 0 insertions, 1347 deletions
diff --git a/g4f/Provider/nexra/NexraBing.py b/g4f/Provider/nexra/NexraBing.py
deleted file mode 100644
index 28f0b117..00000000
--- a/g4f/Provider/nexra/NexraBing.py
+++ /dev/null
@@ -1,93 +0,0 @@
-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
deleted file mode 100644
index be048fdd..00000000
--- a/g4f/Provider/nexra/NexraBlackbox.py
+++ /dev/null
@@ -1,100 +0,0 @@
-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
deleted file mode 100644
index 074a0363..00000000
--- a/g4f/Provider/nexra/NexraChatGPT.py
+++ /dev/null
@@ -1,285 +0,0 @@
-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
deleted file mode 100644
index f605c6d0..00000000
--- a/g4f/Provider/nexra/NexraDallE.py
+++ /dev/null
@@ -1,63 +0,0 @@
-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
deleted file mode 100644
index 2a36b6e6..00000000
--- a/g4f/Provider/nexra/NexraDallE2.py
+++ /dev/null
@@ -1,63 +0,0 @@
-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
deleted file mode 100644
index c26becec..00000000
--- a/g4f/Provider/nexra/NexraEmi.py
+++ /dev/null
@@ -1,63 +0,0 @@
-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
deleted file mode 100644
index cfb26385..00000000
--- a/g4f/Provider/nexra/NexraFluxPro.py
+++ /dev/null
@@ -1,70 +0,0 @@
-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
deleted file mode 100644
index e4e6a8ec..00000000
--- a/g4f/Provider/nexra/NexraGeminiPro.py
+++ /dev/null
@@ -1,86 +0,0 @@
-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
deleted file mode 100644
index c427f8a0..00000000
--- a/g4f/Provider/nexra/NexraMidjourney.py
+++ /dev/null
@@ -1,63 +0,0 @@
-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
deleted file mode 100644
index de997fce..00000000
--- a/g4f/Provider/nexra/NexraProdiaAI.py
+++ /dev/null
@@ -1,151 +0,0 @@
-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
deleted file mode 100644
index 7f944e44..00000000
--- a/g4f/Provider/nexra/NexraQwen.py
+++ /dev/null
@@ -1,86 +0,0 @@
-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
deleted file mode 100644
index 860a132f..00000000
--- a/g4f/Provider/nexra/NexraSD15.py
+++ /dev/null
@@ -1,72 +0,0 @@
-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
deleted file mode 100644
index a12bff1a..00000000
--- a/g4f/Provider/nexra/NexraSDLora.py
+++ /dev/null
@@ -1,69 +0,0 @@
-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
deleted file mode 100644
index 865b4522..00000000
--- a/g4f/Provider/nexra/NexraSDTurbo.py
+++ /dev/null
@@ -1,69 +0,0 @@
-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
deleted file mode 100644
index bebc1fb6..00000000
--- a/g4f/Provider/nexra/__init__.py
+++ /dev/null
@@ -1,14 +0,0 @@
-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
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-22 09:58:17 +0100