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import os |
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from typing import Any, Dict, List, Optional, Type, Union |
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from openai import AsyncStream, Stream |
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from pydantic import BaseModel |
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from camel.configs import OPENROUTER_API_PARAMS, OpenRouterConfig |
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from camel.messages import OpenAIMessage |
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from camel.models._utils import try_modify_message_with_format |
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from camel.models.openai_compatible_model_v2 import OpenAICompatibleModelV2 |
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from camel.types import ( |
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ChatCompletion, |
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ChatCompletionChunk, |
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ModelType, |
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) |
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from camel.utils import ( |
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BaseTokenCounter, |
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api_keys_required, |
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) |
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class OpenRouterModel(OpenAICompatibleModelV2): |
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r"""LLM API served by OpenRouter in a unified OpenAICompatibleModel |
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interface. |
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Args: |
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model_type (Union[ModelType, str]): Model for which a backend is |
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created. |
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model_config_dict (Optional[Dict[str, Any]], optional): A dictionary |
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that will be fed into:obj:`openai.ChatCompletion.create()`. |
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If:obj:`None`, :obj:`GroqConfig().as_dict()` will be used. |
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(default: :obj:`None`) |
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api_key (Optional[str], optional): The API key for authenticating |
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with the OpenRouter service. (default: :obj:`None`). |
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url (Optional[str], optional): The url to the OpenRouter service. |
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(default: :obj:`None`) |
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token_counter (Optional[BaseTokenCounter], optional): Token counter to |
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use for the model. If not provided, :obj:`OpenAITokenCounter( |
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ModelType.GPT_4O_MINI)` will be used. |
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(default: :obj:`None`) |
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timeout (Optional[float], optional): The timeout value in seconds for |
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API calls. If not provided, will fall back to the MODEL_TIMEOUT |
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environment variable or default to 180 seconds. |
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(default: :obj:`None`) |
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""" |
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@api_keys_required([("api_key", "OPENROUTER_API_KEY")]) |
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def __init__( |
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self, |
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model_type: Union[ModelType, str], |
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model_config_dict: Optional[Dict[str, Any]] = None, |
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api_key: Optional[str] = None, |
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url: Optional[str] = None, |
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token_counter: Optional[BaseTokenCounter] = None, |
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timeout: Optional[float] = None, |
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) -> None: |
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if model_config_dict is None: |
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model_config_dict = OpenRouterConfig().as_dict() |
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api_key = api_key or os.environ.get("OPENROUTER_API_KEY") |
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url = url or os.environ.get( |
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"OPENROUTER_API_BASE_URL", "https://openrouter.ai/api/v1" |
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) |
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timeout = timeout or float(os.environ.get("MODEL_TIMEOUT", 180)) |
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super().__init__( |
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model_type=model_type, |
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model_config_dict=model_config_dict, |
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api_key=api_key, |
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url=url, |
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token_counter=token_counter, |
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timeout=timeout, |
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) |
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def _prepare_request( |
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self, |
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messages: List[OpenAIMessage], |
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response_format: Optional[Type[BaseModel]] = None, |
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tools: Optional[List[Dict[str, Any]]] = None, |
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) -> Dict[str, Any]: |
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request_config = self.model_config_dict.copy() |
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if tools: |
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request_config["tools"] = tools |
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elif response_format: |
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try_modify_message_with_format(messages[-1], response_format) |
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request_config["response_format"] = {"type": "json_object"} |
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return request_config |
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def _run( |
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self, |
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messages: List[OpenAIMessage], |
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response_format: Optional[type[BaseModel]] = None, |
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tools: Optional[List[Dict[str, Any]]] = None, |
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) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]: |
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r"""Runs inference of OpenAI chat completion. |
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Args: |
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messages (List[OpenAIMessage]): Message list with the chat history |
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in OpenAI API format. |
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response_format (Optional[Type[BaseModel]]): The format of the |
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response. |
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tools (Optional[List[Dict[str, Any]]]): The schema of the tools to |
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use for the request. |
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Returns: |
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Union[ChatCompletion, Stream[ChatCompletionChunk]]: |
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`ChatCompletion` in the non-stream mode, or |
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`Stream[ChatCompletionChunk]` in the stream mode. |
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""" |
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request_config = self._prepare_request( |
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messages, response_format, tools |
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) |
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response = self._client.chat.completions.create( |
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messages=messages, |
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model=self.model_type, |
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) |
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return response |
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async def _arun( |
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self, |
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messages: List[OpenAIMessage], |
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response_format: Optional[type[BaseModel]] = None, |
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tools: Optional[List[Dict[str, Any]]] = None, |
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) -> Union[ChatCompletion, AsyncStream[ChatCompletionChunk]]: |
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r"""Runs inference of OpenRouter chat completion asynchronously. |
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Args: |
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messages (List[OpenAIMessage]): Message list with the chat history |
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in OpenAI API format. |
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response_format (Optional[Type[BaseModel]]): The format of the |
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response. |
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tools (Optional[List[Dict[str, Any]]]): The schema of the tools to |
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use for the request. |
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Returns: |
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Union[ChatCompletion, AsyncStream[ChatCompletionChunk]]: |
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`ChatCompletion` in the non-stream mode, or |
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`AsyncStream[ChatCompletionChunk]` in the stream mode. |
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""" |
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request_config = self._prepare_request( |
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messages, response_format, tools |
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) |
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response = await self._async_client.chat.completions.create( |
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messages=messages, |
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model=self.model_type, |
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**request_config, |
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) |
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return response |
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def run( |
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self, |
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messages: List[OpenAIMessage], |
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response_format: Optional[type[BaseModel]] = None, |
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tools: Optional[List[Dict[str, Any]]] = None, |
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) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]: |
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""" |
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Public synchronous entrypoint, required by the abstract base. |
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""" |
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return self._run(messages, response_format=response_format, tools=tools) |
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async def arun( |
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self, |
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messages: List[OpenAIMessage], |
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response_format: Optional[type[BaseModel]] = None, |
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tools: Optional[List[Dict[str, Any]]] = None, |
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) -> Union[ChatCompletion, AsyncStream[ChatCompletionChunk]]: |
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""" |
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Public async entrypoint, required by the abstract base. |
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""" |
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return await self._arun(messages, response_format=response_format, tools=tools) |
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def check_model_config(self): |
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r"""Check whether the model configuration contains any unexpected |
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arguments to OpenRouter API. But OpenRouter API does not have any |
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additional arguments to check. |
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Raises: |
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ValueError: If the model configuration dictionary contains any |
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unexpected arguments to OpenRouter API. |
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""" |
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for param in self.model_config_dict: |
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if param not in OPENROUTER_API_PARAMS: |
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raise ValueError( |
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f"Unexpected argument `{param}` is " |
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"input into OpenRouter model backend." |
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) |
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