o i&@sdZddlmZddlmZmZmZddlmZddl m Z ddl m Z ddl mZddlmZdd lmZeGd d d ejZGd d d eZdS)zEMistral LLM service implementation using OpenAI-compatible interface.) dataclass)ListOptionalSequence)logger)ChatCompletionMessageParam)OpenAILLMInvocationParams)FunctionCallFromLLM)BaseOpenAILLMService)OpenAILLMServicec@seZdZdZdS)MistralLLMSettingszSettings for MistralLLMService.N)__name__ __module__ __qualname____doc__rrP/home/ubuntu/.local/lib/python3.10/site-packages/pipecat/services/mistral/llm.pyr sr c seZdZUdZeZeed<dddddededeed eeffd d Z dfd d Z de e de e fddZ deeffdd ZdedefddZZS)MistralLLMServicezA service for interacting with Mistral's API using the OpenAI-compatible interface. This service extends OpenAILLMService to connect to Mistral's API endpoint while maintaining full compatibility with OpenAI's interface and functionality. _settingszhttps://api.mistral.ai/v1N)base_urlmodelsettingsapi_keyrrrc sV|jdd}|dur|dd||_|dur||tjd|||d|dS)aInitialize the Mistral LLM service. Args: api_key: The API key for accessing Mistral's API. base_url: The base URL for Mistral API. Defaults to "https://api.mistral.ai/v1". model: The model identifier to use. Defaults to "mistral-small-latest". .. deprecated:: 0.0.105 Use ``settings=MistralLLMService.Settings(model=...)`` instead. settings: Runtime-updatable settings. When provided alongside deprecated parameters, ``settings`` values take precedence. **kwargs: Additional keyword arguments passed to OpenAILLMService. zmistral-small-latest)rNr)rrrr)Settings"_warn_init_param_moved_to_settingsr apply_updatesuper__init__)selfrrrrkwargsdefault_settings __class__rrr&s   zMistralLLMService.__init__c s&td|tj||fi|S)aCreate OpenAI-compatible client for Mistral API endpoint. Args: api_key: The API key for authentication. If None, uses instance key. base_url: The base URL for the API. If None, uses instance URL. **kwargs: Additional arguments passed to the client constructor. Returns: An OpenAI-compatible client configured for Mistral API. z!Creating Mistral client with api )rdebugr create_client)rrrrr!rrr$Ms zMistralLLMService.create_clientmessagesreturnc Cs|s|Sdd|D}g}t|D]%\}}|ddkr6|t|dks/||dddkr6||dqt|D] }||dddq;td d t|Dt|}t|D]\}}|dd krl||krld |d<qY|d }|ddkrd|vrd|d<|S)a-Apply fixups to messages to meet Mistral-specific requirements. 1. A "tool"-role message must be followed by an assistant message. 2. "system"-role messages must only appear at the start of a conversation. 3. Assistant messages must have prefix=True when they are the final message in a conversation (but at no other point). Args: messages: The original list of messages. Returns: Messages with Mistral prefix requirement applied to final assistant message. cSsg|]}t|qSr)dict).0msgrrr rsz;MistralLLMService._apply_mistral_fixups..roletool assistant r+contentcss&|]\}}|ddkr|VqdS)r+systemN)get)r(ir)rrr s$z:MistralLLMService._apply_mistral_fixups..r2userprefixT) enumerater3lenappendreversedinsertnext) rr%fixed_messagesassistant_insert_indicesr4r)idxfirst_non_system_idx last_messagerrr_apply_mistral_fixups[s.& z'MistralLLMService._apply_mistral_fixupsfunction_callscs|sdSg}|r|djng}t}|D]}|ddkr-|dr-||dq|D]}|j|vr=||q0td|j d|jq0|rXt |IdHdSdS)aExecute function calls, filtering out already-completed ones. Mistral and OpenAI have different function call detection patterns: OpenAI (Stream-based detection): - Detects function calls only from streaming chunks as the LLM generates them - Second LLM completion doesn't re-detect existing tool_calls in message history - Function calls execute exactly once Mistral (Message-based detection): - Detects function calls from the complete message history on each completion - Second LLM completion with the response re-detects the same tool_calls from previous messages - Without filtering, function calls would execute twice This method prevents duplicate execution by: 1. Checking message history for existing tool result messages 2. Filtering out function calls that already have corresponding results 3. Only executing function calls that haven't been completed yet Note: This filtering prevents duplicate function execution, but the on_function_calls_started event may still fire twice due to the detection pattern difference. This is expected behavior. Args: function_calls: The function calls to potentially execute. Nrr+r, tool_call_idz)Skipping already-executed function call: :) context get_messagessetr3addrFr;rtrace function_namerrun_function_calls)rrEcalls_to_executer%executed_call_idsr)callr!rrrNs&  z$MistralLLMService.run_function_callsparams_from_contextc Cs||d}|jjd||d|d|jj|jj|jj|jj|jjd }|jjr.|jj|d<| |jj |jj r^| dg}|rR|d dd krRt |d d |jj d g||d<|S) aBuild parameters for Mistral chat completion request. Handles Mistral-specific requirements including: - Assistant message prefix requirement for API compatibility - Parameter mapping (random_seed instead of seed) - Core completion settings r%Ttools tool_choice) rstreamr%rSrTfrequency_penaltypresence_penalty temperaturetop_p max_tokens random_seedrr+r2zc: Both system_instruction and an initial system message in context are set. This may be unintended.r0)rDrrrVrWrXrYrZseedupdateextrasystem_instructionr3rwarning)rrRr?paramsr%rrrbuild_chat_completion_paramss4    z.MistralLLMService.build_chat_completion_params)NN)r rrrr r__annotations__strrrr$rrrDrr rNrr'rb __classcell__rrr!rrs0 ' 6;rN)r dataclassesrtypingrrrlogururopenai.types.chatr)pipecat.adapters.services.open_ai_adapterrpipecat.frames.framesr pipecat.services.openai.base_llmr pipecat.services.openai.llmr rr rrrrrs