from __future__ import annotations import json 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 DeepInfraChat(AsyncGeneratorProvider, ProviderModelMixin): url = "https://deepinfra.com/chat" api_endpoint = "https://api.deepinfra.com/v1/openai/chat/completions" working = True needs_auth = False supports_stream = True supports_system_message = True supports_message_history = True default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo' models = [ 'meta-llama/Llama-3.3-70B-Instruct', 'meta-llama/Meta-Llama-3.1-8B-Instruct', 'meta-llama/Llama-3.3-70B-Instruct-Turbo', default_model, 'Qwen/QwQ-32B-Preview', 'microsoft/WizardLM-2-8x22B', 'Qwen/Qwen2.5-72B-Instruct', 'Qwen/Qwen2.5-Coder-32B-Instruct', 'nvidia/Llama-3.1-Nemotron-70B-Instruct', ] model_aliases = { "llama-3.3-70b": "meta-llama/Llama-3.3-70B-Instruct", "llama-3.1-8b": "meta-llama/Meta-Llama-3.1-8B-Instruct", "llama-3.3-70b": "meta-llama/Llama-3.3-70B-Instruct-Turbo", "llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", "qwq-32b": "Qwen/QwQ-32B-Preview", "wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B", "qwen-2-72b": "Qwen/Qwen2.5-72B-Instruct", "qwen-2.5-coder-32b": "Qwen/Qwen2.5-Coder-32B-Instruct", "nemotron-70b": "nvidia/Llama-3.1-Nemotron-70B-Instruct", } @classmethod async def create_async_generator( cls, model: str, messages: Messages, proxy: str = None, **kwargs ) -> AsyncResult: model = cls.get_model(model) headers = { 'Accept-Language': 'en-US,en;q=0.9', 'Content-Type': 'application/json', 'Origin': 'https://deepinfra.com', 'Referer': 'https://deepinfra.com/', 'X-Deepinfra-Source': 'web-page', 'accept': 'text/event-stream', } async with ClientSession(headers=headers) as session: data = { "model": model, "messages": messages, "stream": True } async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: await raise_for_status(response) async for chunk in response.content: if chunk: chunk_text = chunk.decode(errors="ignore") try: # Handle streaming response if chunk_text.startswith("data: "): if chunk_text.strip() == "data: [DONE]": continue chunk_data = json.loads(chunk_text[6:]) content = chunk_data["choices"][0]["delta"].get("content") if content: yield content # Handle non-streaming response else: chunk_data = json.loads(chunk_text) content = chunk_data["choices"][0]["message"].get("content") if content: yield content except (json.JSONDecodeError, KeyError): continue