""" Transformation logic from OpenAI /v1/chat/completion format to Mistral's /chat/completion format. Why separate file? Make it easy to see how transformation works Docs - https://docs.mistral.ai/api/ """ from typing import List, Literal, Optional, Tuple, Union from litellm.litellm_core_utils.prompt_templates.common_utils import ( handle_messages_with_content_list_to_str_conversion, strip_none_values_from_message, ) from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig from litellm.secret_managers.main import get_secret_str from litellm.types.llms.mistral import MistralToolCallMessage from litellm.types.llms.openai import AllMessageValues class MistralConfig(OpenAIGPTConfig): """ Reference: https://docs.mistral.ai/api/ The class `MistralConfig` provides configuration for the Mistral's Chat API interface. Below are the parameters: - `temperature` (number or null): Defines the sampling temperature to use, varying between 0 and 2. API Default - 0.7. - `top_p` (number or null): An alternative to sampling with temperature, used for nucleus sampling. API Default - 1. - `max_tokens` (integer or null): This optional parameter helps to set the maximum number of tokens to generate in the chat completion. API Default - null. - `tools` (list or null): A list of available tools for the model. Use this to specify functions for which the model can generate JSON inputs. - `tool_choice` (string - 'auto'/'any'/'none' or null): Specifies if/how functions are called. If set to none the model won't call a function and will generate a message instead. If set to auto the model can choose to either generate a message or call a function. If set to any the model is forced to call a function. Default - 'auto'. - `stop` (string or array of strings): Stop generation if this token is detected. Or if one of these tokens is detected when providing an array - `random_seed` (integer or null): The seed to use for random sampling. If set, different calls will generate deterministic results. - `safe_prompt` (boolean): Whether to inject a safety prompt before all conversations. API Default - 'false'. - `response_format` (object or null): An object specifying the format that the model must output. Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is in JSON. When using JSON mode you MUST also instruct the model to produce JSON yourself with a system or a user message. """ temperature: Optional[int] = None top_p: Optional[int] = None max_tokens: Optional[int] = None tools: Optional[list] = None tool_choice: Optional[Literal["auto", "any", "none"]] = None random_seed: Optional[int] = None safe_prompt: Optional[bool] = None response_format: Optional[dict] = None stop: Optional[Union[str, list]] = None def __init__( self, temperature: Optional[int] = None, top_p: Optional[int] = None, max_tokens: Optional[int] = None, tools: Optional[list] = None, tool_choice: Optional[Literal["auto", "any", "none"]] = None, random_seed: Optional[int] = None, safe_prompt: Optional[bool] = None, response_format: Optional[dict] = None, stop: Optional[Union[str, list]] = None, ) -> None: locals_ = locals().copy() for key, value in locals_.items(): if key != "self" and value is not None: setattr(self.__class__, key, value) @classmethod def get_config(cls): return super().get_config() def get_supported_openai_params(self, model: str) -> List[str]: return [ "stream", "temperature", "top_p", "max_tokens", "tools", "tool_choice", "seed", "stop", "response_format", ] def _map_tool_choice(self, tool_choice: str) -> str: if tool_choice == "auto" or tool_choice == "none": return tool_choice elif tool_choice == "required": return "any" else: # openai 'tool_choice' object param not supported by Mistral API return "any" def map_openai_params( self, non_default_params: dict, optional_params: dict, model: str, drop_params: bool, ) -> dict: for param, value in non_default_params.items(): if param == "max_tokens": optional_params["max_tokens"] = value if param == "tools": optional_params["tools"] = value if param == "stream" and value is True: optional_params["stream"] = value if param == "temperature": optional_params["temperature"] = value if param == "top_p": optional_params["top_p"] = value if param == "stop": optional_params["stop"] = value if param == "tool_choice" and isinstance(value, str): optional_params["tool_choice"] = self._map_tool_choice( tool_choice=value ) if param == "seed": optional_params["extra_body"] = {"random_seed": value} if param == "response_format": optional_params["response_format"] = value return optional_params def _get_openai_compatible_provider_info( self, api_base: Optional[str], api_key: Optional[str] ) -> Tuple[Optional[str], Optional[str]]: # mistral is openai compatible, we just need to set this to custom_openai and have the api_base be https://api.mistral.ai api_base = ( api_base or get_secret_str("MISTRAL_AZURE_API_BASE") # for Azure AI Mistral or "https://api.mistral.ai/v1" ) # type: ignore # if api_base does not end with /v1 we add it if api_base is not None and not api_base.endswith( "/v1" ): # Mistral always needs a /v1 at the end api_base = api_base + "/v1" dynamic_api_key = ( api_key or get_secret_str("MISTRAL_AZURE_API_KEY") # for Azure AI Mistral or get_secret_str("MISTRAL_API_KEY") ) return api_base, dynamic_api_key def _transform_messages( self, messages: List[AllMessageValues], model: str ) -> List[AllMessageValues]: """ - handles scenario where content is list and not string - content list is just text, and no images - if image passed in, then just return as is (user-intended) - if `name` is passed, then drop it for mistral API: https://github.com/BerriAI/litellm/issues/6696 Motivation: mistral api doesn't support content as a list """ ## 1. If 'image_url' in content, then return as is for m in messages: _content_block = m.get("content") if _content_block and isinstance(_content_block, list): for c in _content_block: if c.get("type") == "image_url": return messages ## 2. If content is list, then convert to string messages = handle_messages_with_content_list_to_str_conversion(messages) ## 3. Handle name in message new_messages: List[AllMessageValues] = [] for m in messages: m = MistralConfig._handle_name_in_message(m) m = MistralConfig._handle_tool_call_message(m) m = strip_none_values_from_message(m) # prevents 'extra_forbidden' error new_messages.append(m) return new_messages @classmethod def _handle_name_in_message(cls, message: AllMessageValues) -> AllMessageValues: """ Mistral API only supports `name` in tool messages If role == tool, then we keep `name` Otherwise, we drop `name` """ _name = message.get("name") # type: ignore if _name is not None and message["role"] != "tool": message.pop("name", None) # type: ignore return message @classmethod def _handle_tool_call_message(cls, message: AllMessageValues) -> AllMessageValues: """ Mistral API only supports tool_calls in Messages in `MistralToolCallMessage` spec """ _tool_calls = message.get("tool_calls") mistral_tool_calls: List[MistralToolCallMessage] = [] if _tool_calls is not None and isinstance(_tool_calls, list): for _tool in _tool_calls: _tool_call_message = MistralToolCallMessage( id=_tool.get("id"), type="function", function=_tool.get("function"), # type: ignore ) mistral_tool_calls.append(_tool_call_message) message["tool_calls"] = mistral_tool_calls # type: ignore return message