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* fixing browser * fix syntax * try other container as base * use node 20 * use layers * fix chromium * add chromium sandbox and env vars * add chromium flags * clean up * revert to a previous version of g4f * use client * use asyncio * revert to previous version * switching retry method * use str * change defaults * more changes to default models * improve rotation * improve logic * select model * fix err * fix file path * fix defaults * improve logic * add logging, remove provider * skip if provider models is empty * remove provider
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,39 +1,146 @@ | ||
| from g4f.client import AsyncClient | ||
| import logging | ||
| import asyncio | ||
| import random | ||
| from g4f.Provider import ( | ||
| HuggingChat, | ||
| ChatgptAi, | ||
| DeepInfra, | ||
| ChatBase, | ||
| Liaobots, | ||
| FreeGpt, | ||
| GptGo, | ||
| Gpt6, | ||
| ) | ||
|
|
||
|
|
||
| class Gpt4freeProvider: | ||
| def __init__(self, AI_MODEL: str = "gemini-pro", **kwargs): | ||
| self.requirements = ["g4f"] | ||
| self.AI_MODEL = AI_MODEL if AI_MODEL else "gemini-pro" | ||
| def __init__(self, AI_MODEL: str = "gpt-3.5-turbo", **kwargs): | ||
| self.requirements = ["g4f"] # Breaking changes were made after g4f v0.2.6.2 | ||
| self.AI_MODEL = AI_MODEL if AI_MODEL else "gpt-3.5-turbo" | ||
| self.provider = ChatgptAi | ||
| self.provider_name = "ChatgptAi" | ||
| self.providers = [ | ||
| { | ||
| "name": "HuggingChat", | ||
| "class": HuggingChat, | ||
| "models": [ | ||
| "mistralai/Mixtral-8x7B-Instruct-v0.1", | ||
| "mistralai/Mistral-7B-Instruct-v0.1", | ||
| "openchat/openchat_3.5", | ||
| "meta-llama/Llama-2-70b-chat-hf", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "ChatgptAi", | ||
| "class": ChatgptAi, | ||
| "models": [ | ||
| "gpt-3.5-turbo", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "DeepInfra", | ||
| "class": DeepInfra, | ||
| "models": [ | ||
| "meta-llama/Meta-Llama-3-70B-Instruct", | ||
| "Qwen/Qwen2-72B-Instruct", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "ChatBase", | ||
| "class": ChatBase, | ||
| "models": [ | ||
| "gpt-3.5-turbo", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "Liaobots", | ||
| "class": Liaobots, | ||
| "models": [ | ||
| "gpt-4", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "FreeGpt", | ||
| "class": FreeGpt, | ||
| "models": [ | ||
| "gpt-3.5-turbo", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "GptGo", | ||
| "class": GptGo, | ||
| "models": [ | ||
| "gpt-3.5-turbo", | ||
| ], | ||
| }, | ||
| { | ||
| "name": "Gpt6", | ||
| "class": Gpt6, | ||
| "models": [ | ||
| "gpt-3.5-turbo", | ||
| ], | ||
| }, | ||
| ] | ||
| self.failures = [] | ||
|
|
||
| @staticmethod | ||
| def services(): | ||
| return ["llm"] | ||
|
|
||
| async def inference(self, prompt, tokens: int = 0, images: list = []): | ||
| asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy()) | ||
| client = AsyncClient() | ||
| models = ["gemini-pro", "gpt-4-turbo", "gpt-4", "mixtral-8x7b", "mistral-7b"] | ||
| logging.info( | ||
| f"[Gpt4Free] Using provider: {self.provider_name} with model: {self.AI_MODEL}" | ||
| ) | ||
| try: | ||
| response = await client.chat.completions.create( | ||
| model=self.AI_MODEL, | ||
| messages=[{"role": "user", "content": prompt}], | ||
| stream=False, | ||
| ) | ||
| return str(response.choices[0].message.content) | ||
| except Exception as e: | ||
| logging.warning(f"gpt4free API Error: {e}") | ||
| for model in models: | ||
| try: | ||
| response = await client.chat.completions.create( | ||
| model=model, | ||
| return ( | ||
| await asyncio.gather( | ||
| self.provider.create_async( | ||
| model=self.AI_MODEL, | ||
| messages=[{"role": "user", "content": prompt}], | ||
| stream=False, | ||
| ) | ||
| return str(response.choices[0].message.content) | ||
| except Exception as e: | ||
| logging.warning(f"gpt4free API Error: {e}") | ||
| continue | ||
| return "Unable to retrieve a response from the gpt4free provider." | ||
| ) | ||
| )[0] | ||
| except Exception as e: | ||
| logging.error(f"[Gpt4Free] {e}") | ||
| self.failures.append( | ||
| {"provider": self.provider_name, "model": self.AI_MODEL} | ||
| ) | ||
| if len(self.failures) < len(self.providers): | ||
| available_providers = self.get_available_providers() | ||
| if available_providers: | ||
| provider = random.choice(available_providers) | ||
| self.provider = provider["class"] | ||
| self.provider_name = provider["name"] | ||
| self.AI_MODEL = random.choice(provider["models"]) | ||
| logging.info( | ||
| f"[Gpt4Free] Switching to provider: {self.provider_name} with model: {self.AI_MODEL}" | ||
| ) | ||
| return await self.inference( | ||
| prompt=prompt, tokens=tokens, images=images | ||
| ) | ||
| else: | ||
| return "No available providers. Unable to retrieve response." | ||
| else: | ||
| return "All providers exhausted. Unable to retrieve response." | ||
|
|
||
| def get_available_providers(self): | ||
| available_providers = [] | ||
| for provider in self.providers: | ||
| provider_models = provider["models"] | ||
| if not isinstance(provider_models, list): | ||
| provider_models = [provider_models] | ||
| # Remove any models that have failed | ||
| available_models = [ | ||
| model | ||
| for model in provider_models | ||
| if not any( | ||
| failure["provider"] == provider["name"] | ||
| and failure["model"] == model | ||
| for failure in self.failures | ||
| ) | ||
| ] | ||
| if available_models: | ||
| provider_copy = provider.copy() | ||
| provider_copy["models"] = available_models | ||
| available_providers.append(provider_copy) | ||
| return available_providers |
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