"""Adaptateur LLM — Mistral AI (Mistral Large, Pixtral).""" from __future__ import annotations import os from typing import Optional from picarones.llm.base import BaseLLMAdapter class MistralAdapter(BaseLLMAdapter): """Adaptateur pour les modèles Mistral AI. Clé API via la variable d'environnement ``MISTRAL_API_KEY``. Modes supportés : text_only (tous modèles), text_and_image et zero_shot avec les modèles multimodaux (pixtral-12b, pixtral-large). """ @property def name(self) -> str: return "mistral" @property def default_model(self) -> str: return "mistral-large-latest" def __init__( self, model: Optional[str] = None, config: Optional[dict] = None, ) -> None: super().__init__(model, config) self._api_key = os.environ.get("MISTRAL_API_KEY") def _call(self, prompt: str, image_b64: Optional[str] = None) -> str: if not self._api_key: raise RuntimeError( "Clé API Mistral manquante — définissez la variable d'environnement MISTRAL_API_KEY" ) try: from mistralai import Mistral except ImportError as exc: raise RuntimeError( "Le package 'mistralai' n'est pas installé. Lancez : pip install mistralai" ) from exc client = Mistral(api_key=self._api_key) temperature = float(self.config.get("temperature", 0.0)) max_tokens = int(self.config.get("max_tokens", 4096)) if image_b64: content: list | str = [ {"type": "text", "text": prompt}, { "type": "image_url", "image_url": f"data:image/png;base64,{image_b64}", }, ] else: content = prompt response = client.chat.complete( model=self.model, messages=[{"role": "user", "content": content}], temperature=temperature, max_tokens=max_tokens, ) return response.choices[0].message.content or ""