feat: support de 10 fichiers max avec destruction post-envoi, traduction automatique en anglais par le prompteur et traduction en français par le concaténeur en préservant le code

backend/main.py

@@ -144,8 +144,11 @@ def get_messages(project_id: int, db: Session = Depends(get_db), current_user: U
 @app.post("/api/projects/{project_id}/messages", response_model=List[MessageResponse])
 async def create_message(project_id: int, message: MessageCreate, db: Session = Depends(get_db), current_user: User = Depends(get_current_user)):
     final_content = message.content
-    if message.file_content and message.file_name:
-        final_content = f"[Fichier attaché : {message.file_name}]\n```\n{message.file_content}\n```\n\n{message.content}"
+    if message.files:
+        files_text = ""
+        for f in message.files:
+            files_text += f"\n\n[Fichier attaché : {f.name}]\n```\n{f.content}\n```"
+        final_content = message.content + files_text
 
     db.add(Message(role=message.role, content=final_content, project_id=project_id))
     db.commit()

backend/orchestrator.py

@@ -15,9 +15,7 @@ def determine_domain(model_id: str) -> str:
     return "Texte Polyvalent"
 
 async def sync_finances(db: Session, settings: SystemSettings):
-    """Interroge les fournisseurs pour récupérer le solde financier exact."""
     async with httpx.AsyncClient(timeout=30.0) as client:
-        # OpenRouter
         if settings.openrouter_management_key or settings.openrouter_api_key:
             try:
                 key = settings.openrouter_management_key or settings.openrouter_api_key
@@ -38,10 +36,7 @@ async def sync_finances(db: Session, settings: SystemSettings):
                 update_finance_db(db, "OpenRouter", balance, usage)
             except Exception as e: print(f"Erreur Finance OR: {e}")
             
-        # Groq
         if settings.groq_api_key: update_finance_db(db, "Groq", 999.0, 0.0)
-            
-        # DeepSeek
         if settings.deepseek_api_key:
             try:
                 resp = await client.get("https://api.deepseek.com/user/balance", headers={"Authorization": f"Bearer {settings.deepseek_api_key}"})
@@ -49,11 +44,7 @@ async def sync_finances(db: Session, settings: SystemSettings):
                     infos = resp.json().get("balance_infos", [{}])[0]
                     update_finance_db(db, "DeepSeek", float(infos.get("total_balance", 0)), 0.0)
             except Exception: pass
-
-        # Mistral AI
         if settings.mistral_api_key: update_finance_db(db, "Mistral", 0.0, 0.0)
-        
-        # Gemini
         if settings.gemini_api_key: update_finance_db(db, "Gemini", 0.0, 0.0)
 
     try: db.commit()
@@ -70,11 +61,8 @@ def update_finance_db(db, provider, balance, usage):
 
 async def sync_providers_models(db: Session, settings: SystemSettings, sync_type: str = "Automatique"):
     added = 0
-    # On stocke les modèles en mémoire avant de les envoyer en base pour éviter les doublons
     models_to_process = {}
-
     async with httpx.AsyncClient(timeout=90.0) as client:
-        # 1. OpenRouter
         if settings.openrouter_api_key:
             try:
                 resp = await client.get("https://openrouter.ai/api/v1/models")
@@ -84,80 +72,62 @@ async def sync_providers_models(db: Session, settings: SystemSettings, sync_type
                             m_id = item.get("id")
                             if not m_id: continue
                             pricing = item.get("pricing") or {}
-                            try: pp = float(pricing.get("prompt") or 0.0) * 1000000
-                            except: pp = 0.0
-                            try: pc = float(pricing.get("completion") or 0.0) * 1000000
-                            except: pc = 0.0
+                            pp = float(pricing.get("prompt") or 0.0) * 1000000
+                            pc = float(pricing.get("completion") or 0.0) * 1000000
                             is_free = (pp == 0.0 and pc == 0.0)
                             desc = item.get("description", "Modèle OpenRouter.")[:200] + "..."
                             models_to_process[m_id] = {"provider": "openrouter", "name": item.get("name", "Inconnu"), "desc": desc, "domain": determine_domain(m_id), "is_free": is_free, "ctx": item.get("context_length", 0), "pp": pp, "pc": pc}
                         except: pass
             except Exception as e: print(f"Erreur OR Models: {e}")
             
-        # 2. Groq
         if settings.groq_api_key:
             try:
                 resp = await client.get("https://api.groq.com/openai/v1/models", headers={"Authorization": f"Bearer {settings.groq_api_key}"})
                 if resp.status_code == 200:
                     for item in resp.json().get("data", []):
-                        try:
-                            m_id = item["id"]
-                            models_to_process[m_id] = {"provider": "groq", "name": m_id.capitalize(), "desc": "Modèle rapide LPU Groq.", "domain": determine_domain(m_id), "is_free": True, "ctx": 8192, "pp": 0.0, "pc": 0.0}
-                        except: pass
+                        m_id = item["id"]
+                        models_to_process[m_id] = {"provider": "groq", "name": m_id.capitalize(), "desc": "Modèle rapide LPU Groq.", "domain": determine_domain(m_id), "is_free": True, "ctx": 8192, "pp": 0.0, "pc": 0.0}
             except Exception: pass
 
-        # 3. DeepSeek
         if settings.deepseek_api_key:
             try:
                 resp = await client.get("https://api.deepseek.com/models", headers={"Authorization": f"Bearer {settings.deepseek_api_key}"})
                 if resp.status_code == 200:
                     for item in resp.json().get("data", []):
-                        try:
-                            m_id = item["id"]
-                            models_to_process[m_id] = {"provider": "deepseek", "name": m_id.capitalize(), "desc": "Modèle officiel DeepSeek.", "domain": determine_domain(m_id), "is_free": False, "ctx": 64000, "pp": 0.14, "pc": 0.28}
-                        except: pass
+                        m_id = item["id"]
+                        models_to_process[m_id] = {"provider": "deepseek", "name": m_id.capitalize(), "desc": "Modèle officiel DeepSeek.", "domain": determine_domain(m_id), "is_free": False, "ctx": 64000, "pp": 0.14, "pc": 0.28}
             except Exception: pass
 
-        # 4. Mistral
         if settings.mistral_api_key:
             try:
                 resp = await client.get("https://api.mistral.ai/v1/models", headers={"Authorization": f"Bearer {settings.mistral_api_key}"})
                 if resp.status_code == 200:
                     for item in resp.json().get("data", []):
-                        try:
-                            m_id = item["id"]
-                            models_to_process[m_id] = {"provider": "mistral", "name": m_id.capitalize(), "desc": "Modèle officiel Mistral AI.", "domain": determine_domain(m_id), "is_free": False, "ctx": 32000, "pp": 0.2, "pc": 0.6}
-                        except: pass
+                        m_id = item["id"]
+                        models_to_process[m_id] = {"provider": "mistral", "name": m_id.capitalize(), "desc": "Modèle officiel Mistral AI.", "domain": determine_domain(m_id), "is_free": False, "ctx": 32000, "pp": 0.2, "pc": 0.6}
             except Exception: pass
 
-        # 5. Gemini (Google)
         if settings.gemini_api_key:
             try:
                 resp = await client.get(f"https://generativelanguage.googleapis.com/v1beta/models?key={settings.gemini_api_key}")
                 if resp.status_code == 200:
                     for item in resp.json().get("models", []):
-                        try:
-                            m_id = item["name"].replace("models/", "")
-                            desc = item.get("description", "Modèle Google Gemini.")[:200] + "..."
-                            models_to_process[m_id] = {"provider": "gemini", "name": item.get("displayName", m_id), "desc": desc, "domain": determine_domain(m_id), "is_free": True, "ctx": item.get("inputTokenLimit", 32000), "pp": 0.0, "pc": 0.0}
-                        except: pass
+                        m_id = item["name"].replace("models/", "")
+                        desc = item.get("description", "Modèle Google Gemini.")[:200] + "..."
+                        models_to_process[m_id] = {"provider": "gemini", "name": item.get("displayName", m_id), "desc": desc, "domain": determine_domain(m_id), "is_free": True, "ctx": item.get("inputTokenLimit", 32000), "pp": 0.0, "pc": 0.0}
             except Exception: pass
 
-        # 6. Cloudflare
         if settings.cloudflare_account_id and settings.cloudflare_api_token:
             try:
                 url = f"https://api.cloudflare.com/client/v4/accounts/{settings.cloudflare_account_id}/ai/models/search"
                 resp = await client.get(url, headers={"Authorization": f"Bearer {settings.cloudflare_api_token}"})
                 if resp.status_code == 200:
                     for item in resp.json().get("result", []):
-                        try:
-                            m_id = item.get("name")
-                            desc = item.get("description", "Modèle Cloudflare Workers AI.")[:200] + "..."
-                            models_to_process[m_id] = {"provider": "cloudflare", "name": m_id.split("/")[-1], "desc": desc, "domain": determine_domain(m_id), "is_free": True, "ctx": 4096, "pp": 0.0, "pc": 0.0}
-                        except: pass
+                        m_id = item.get("name")
+                        desc = item.get("description", "Modèle Cloudflare Workers AI.")[:200] + "..."
+                        models_to_process[m_id] = {"provider": "cloudflare", "name": m_id.split("/")[-1], "desc": desc, "domain": determine_domain(m_id), "is_free": True, "ctx": 4096, "pp": 0.0, "pc": 0.0}
             except Exception: pass
 
-    # --- Phase d'enregistrement sécurisée ---
     for m_id, data in models_to_process.items():
         try:
             existing = db.query(AIModel).filter(AIModel.model_id == m_id).first()
@@ -166,13 +136,9 @@ async def sync_providers_models(db: Session, settings: SystemSettings, sync_type
             else:
                 db.add(AIModel(provider=data["provider"], model_id=m_id, name=data["name"], description_fr=data["desc"], domain=data["domain"], is_free=data["is_free"], context_length=data["ctx"], pricing_prompt=data["pp"], pricing_completion=data["pc"]))
             added += 1
-            # Commit très fréquent pour éviter les gros blocs qui plantent
-            if added % 50 == 0:
-                db.commit()
-        except IntegrityError:
-            db.rollback() # Si conflit, on annule cette insertion et on continue
-        except Exception:
-            db.rollback()
+            if added % 50 == 0: db.commit()
+        except IntegrityError: db.rollback()
+        except Exception: db.rollback()
 
     try:
         settings.last_sync_date = datetime.now(timezone.utc)
@@ -180,13 +146,11 @@ async def sync_providers_models(db: Session, settings: SystemSettings, sync_type
         db.commit()
     except Exception as e:
         db.rollback()
-        print(f"Erreur DB Commit Sync: {e}")
         
     await sync_finances(db, settings)
     return {"status": "success", "models_processed": added}
 
 def get_client_for_model(db: Session, model_id: str, settings: SystemSettings):
-    """Récupère dynamiquement le bon client OpenAI en fonction du fournisseur du modèle."""
     model_db = db.query(AIModel).filter(AIModel.model_id == model_id).first()
     provider = model_db.provider if model_db else "openrouter"
 
@@ -217,26 +181,39 @@ async def run_orchestrator(db: Session, history: list, settings: SystemSettings,
 
     final_response = ""
     try:
+        # Étape 1 : Le prompteur traduit et optimise la requête en ANGLAIS pour les travailleurs
+        p_mod = config.get("prompter", "gemini-3.5-flash-lite")
+        p_client, p_prov = get_client_for_model(db, p_mod, settings)
+        prompt_system = "You are an expert prompt engineer. Translate and optimize the user request into clear, precise English tailored for AI execution."
+        optimized = await ask_agent(p_client, p_mod, [{"role": "system", "content": prompt_system}, {"role": "user", "content": user_prompt}], p_prov)
+
         if len(workers) == 1:
             w_mod = workers[0]
             client, provider = get_client_for_model(db, w_mod, settings)
-            final_response = await ask_agent(client, w_mod, formatted_history + [{"role": "user", "content": user_prompt}], provider)
+            worker_response = await ask_agent(client, w_mod, formatted_history + [{"role": "user", "content": optimized}], provider)
+            responses = [worker_response]
         else:
-            p_mod = config.get("prompter", "gemini-3.5-flash-lite")
-            p_client, p_prov = get_client_for_model(db, p_mod, settings)
-            optimized = await ask_agent(p_client, p_mod, [{"role": "system", "content": "Optimise cette requête."}, {"role": "user", "content": user_prompt}], p_prov)
-
             w_tasks = []
             for w in workers:
                 w_client, w_prov = get_client_for_model(db, w, settings)
                 w_tasks.append(ask_agent(w_client, w, formatted_history + [{"role": "user", "content": optimized}], w_prov))
-                
             responses = await asyncio.gather(*w_tasks, return_exceptions=True)
 
-            c_mod = config.get("concatenator", "gemini-3.5-flash-lite")
-            c_client, c_prov = get_client_for_model(db, c_mod, settings)
-            synth = f"Requête: {user_prompt}\n\n" + "\n".join([f"--- EXPERT {i+1} ---\n{r}" for i, r in enumerate(responses)]) + "\n\nFais une synthèse finale."
-            final_response = await ask_agent(c_client, c_mod, [{"role": "user", "content": synth}], c_prov)
+        # Étape 2 : Le concaténeur synthétise et traduit le retour en FRANÇAIS (en préservant le code et les commentaires)
+        c_mod = config.get("concatenator", "gemini-3.5-flash-lite")
+        c_client, c_prov = get_client_for_model(db, c_mod, settings)
+        
+        concat_system = (
+            "You are a master lead developer and technical synthesizer. "
+            "Synthesize the provided expert responses into a single cohesive response. "
+            "Translate all explanatory text, descriptions, and user-facing prose into natural French. "
+            "CRITICAL: Do NOT translate code blocks, programming keywords, or source code contents. "
+            "You may translate code comments into French if appropriate, but leave code syntax strictly intact."
+        )
+        
+        synth = f"User Request: {user_prompt}\n\n" + "\n".join([f"--- EXPERT {i+1} ---\n{r}" for i, r in enumerate(responses)])
+        final_response = await ask_agent(c_client, c_mod, [{"role": "system", "content": concat_system}, {"role": "user", "content": synth}], c_prov)
+
     except Exception as e:
         final_response = f"L'IA a rencontré une erreur critique: {str(e)}"
     

backend/schemas.py

@@ -44,14 +44,17 @@ class OrchestratorConfig(BaseModel):
     prompter: Optional[str] = "gemini-3.5-flash-lite"
     concatenator: Optional[str] = "gemini-3.5-flash-lite"
 
+class AttachedFile(BaseModel):
+    name: str
+    content: str
+
 class MessageBase(BaseModel):
     role: str
     content: str
 
 class MessageCreate(MessageBase):
     config: Optional[OrchestratorConfig] = None
-    file_content: Optional[str] = None
-    file_name: Optional[str] = None
+    files: Optional[List[AttachedFile]] = None
 
 class MessageResponse(MessageBase):
     id: int