Update AI models to use Mistral by default for better performance

Update backend AI agent to support Mistral API alongside OpenAI and Replit integrations. Default filter model changed to 'mistral-small-latest' and synthesis model to 'mistral-large-latest'. Frontend transparency page updated to reflect these changes and new configuration variables.

Replit-Commit-Author: Agent
Replit-Commit-Session-Id: 923ae0e3-a363-4db8-b04a-e8baca2a1330
Replit-Commit-Checkpoint-Type: full_checkpoint
Replit-Commit-Event-Id: ec257d30-4a6a-4c7b-85f5-c18945dba29f
Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/8af7d2ec-2cc3-4ece-8af3-9f071488d072/923ae0e3-a363-4db8-b04a-e8baca2a1330/qrVKaka
Replit-Helium-Checkpoint-Created: true

artifacts/flask-api/ai_agent.py

@@ -1,6 +1,6 @@
 """
 Agent IA pour le filtrage éthique et la synthèse démocratique.
-Utilise les Intégrations IA de Replit (OpenAI proxy).
+Supporte Mistral AI, OpenAI, et les intégrations Replit AI.
 """
 import json
 import os
@@ -10,25 +10,35 @@ from legal_framework import LEGAL_FILTER_PROMPT, SYNTHESIS_PROMPT
 
 logger = logging.getLogger(__name__)
 
+MISTRAL_BASE_URL = "https://api.mistral.ai/v1"
+
 _client: OpenAI | None = None
 
 
 def get_client() -> OpenAI:
     """
-    Supporte deux modes :
-    - Replit AI Integration : AI_INTEGRATIONS_OPENAI_BASE_URL + AI_INTEGRATIONS_OPENAI_API_KEY
-    - Auto-hébergement standard : OPENAI_API_KEY (+ OPENAI_BASE_URL optionnel pour proxy)
+    Supporte trois modes (par ordre de priorité) :
+    1. Replit AI Integration : AI_INTEGRATIONS_OPENAI_BASE_URL + AI_INTEGRATIONS_OPENAI_API_KEY
+    2. Mistral AI            : MISTRAL_API_KEY (+ MISTRAL_BASE_URL optionnel)
+    3. OpenAI standard       : OPENAI_API_KEY (+ OPENAI_BASE_URL optionnel)
     """
     global _client
     if _client is None:
         replit_base = os.environ.get("AI_INTEGRATIONS_OPENAI_BASE_URL")
         replit_key  = os.environ.get("AI_INTEGRATIONS_OPENAI_API_KEY")
+        mistral_key = os.environ.get("MISTRAL_API_KEY")
+        mistral_base = os.environ.get("MISTRAL_BASE_URL", MISTRAL_BASE_URL)
         std_key     = os.environ.get("OPENAI_API_KEY")
         std_base    = os.environ.get("OPENAI_BASE_URL")
 
         if replit_base and replit_key:
+            logger.info("Utilisation de l'intégration Replit AI")
             _client = OpenAI(base_url=replit_base, api_key=replit_key)
+        elif mistral_key:
+            logger.info("Utilisation de l'API Mistral AI (%s)", mistral_base)
+            _client = OpenAI(base_url=mistral_base, api_key=mistral_key)
         elif std_key:
+            logger.info("Utilisation de l'API OpenAI")
             kwargs = {"api_key": std_key}
             if std_base:
                 kwargs["base_url"] = std_base
@@ -36,7 +46,7 @@ def get_client() -> OpenAI:
         else:
             raise RuntimeError(
                 "Aucune clé IA configurée. "
-                "Définissez OPENAI_API_KEY dans le fichier .env "
+                "Définissez MISTRAL_API_KEY ou OPENAI_API_KEY dans le fichier .env, "
                 "ou configurez les intégrations Replit AI."
             )
     return _client
@@ -49,10 +59,10 @@ def filter_idea(content: str) -> dict:
     """
     try:
         client = get_client()
-        filter_model = os.environ.get("OPENAI_FILTER_MODEL", "gpt-4o-mini")
+        filter_model = os.environ.get("FILTER_MODEL", os.environ.get("OPENAI_FILTER_MODEL", "mistral-small-latest"))
         response = client.chat.completions.create(
             model=filter_model,
-            max_completion_tokens=300,
+            max_tokens=300,
             response_format={"type": "json_object"},
             messages=[
                 {"role": "system", "content": LEGAL_FILTER_PROMPT},
@@ -112,11 +122,11 @@ def synthesize_ideas(ideas: list[str]) -> str:
         )
     try:
         client = get_client()
-        synthesis_model = os.environ.get("OPENAI_SYNTHESIS_MODEL", "gpt-4o")
+        synthesis_model = os.environ.get("SYNTHESIS_MODEL", os.environ.get("OPENAI_SYNTHESIS_MODEL", "mistral-large-latest"))
         ideas_text = "\n".join(f"{i + 1}. {idea}" for i, idea in enumerate(ideas))
         response = client.chat.completions.create(
             model=synthesis_model,
-            max_completion_tokens=1200,
+            max_tokens=1200,
             messages=[
                 {"role": "system", "content": SYNTHESIS_PROMPT},
                 {