feat maj fonctionnement

backend/main.py

@@ -3,15 +3,15 @@ from fastapi.responses import RedirectResponse, FileResponse
 from fastapi.staticfiles import StaticFiles
 from sqlalchemy.orm import Session
 from typing import List
-import os, json, asyncio, shutil, base64, io
+import os, json, asyncio, shutil, base64, io, csv, zipfile
 from datetime import datetime
 import pytz
 
 from .database import engine, Base, get_db, SessionLocal
 from .auth import get_password_hash, generate_totp_secret, get_totp_uri, verify_password, verify_totp, create_access_token, verify_token
-from .schemas import AdminCreate, LoginRequest, ProjectCreate, ProjectResponse, ProjectRename, MessageCreate, MessageResponse, PasswordChange
+from .schemas import AdminCreate, LoginRequest, ProjectCreate, ProjectResponse, ProjectRename, MessageCreate, MessageResponse, PasswordChange, ModelReplacementRequest, LogRequest
 from .models import User, Project, Message, SystemSettings, AIModel, FinancialLog
-from .orchestrator import run_orchestrator, sync_providers_models, sync_finances
+from .orchestrator import run_orchestrator, sync_providers_models, sync_finances, activity_logs, log_activity
 
 Base.metadata.create_all(bind=engine)
 app = FastAPI(title="AETHAS38")
@@ -73,7 +73,6 @@ def login(login_data: LoginRequest, response: Response, db: Session = Depends(ge
     user = db.query(User).filter(User.username == login_data.username).first()
     if not user or not verify_password(login_data.password, user.hashed_password): raise HTTPException(status_code=401, detail="Identifiants incorrects.")
     if not verify_totp(user.totp_secret, login_data.totp_code): raise HTTPException(status_code=401, detail="2FA invalide.")
-    # Correction : Extension de la durée de session à 7 jours (604800 secondes) pour éviter les erreurs 401 intempestives
     response.set_cookie(key="session_token", value=create_access_token(data={"sub": user.username}), httponly=True, max_age=604800, samesite="lax")
     return {"message": "Connexion réussie"}
 
@@ -83,6 +82,52 @@ def dashboard(request: Request):
     if not token or not verify_token(token): return RedirectResponse(url="/login")
     return FileResponse(os.path.join(os.getcwd(), "frontend", "dashboard.html"))
 
+@app.get("/api/logs")
+def get_logs():
+    return {"logs": activity_logs}
+
+@app.post("/api/logs")
+def add_frontend_log(req: LogRequest):
+    log_activity(f"[Système UI] {req.message}")
+    return {"status": "ok"}
+
+@app.post("/api/models/suggest_replacement")
+async def suggest_replacement(req: ModelReplacementRequest, db: Session = Depends(get_db)):
+    log_activity(f"⚠️ Modèle indisponible: {req.missing_model}. Demande de suggestion à Gemini...")
+    settings = db.query(SystemSettings).first()
+    if not settings or not settings.gemini_api_key:
+        log_activity("Clé Gemini non trouvée. Fallback forcé sur gemini-3.5-flash-lite.")
+        return {"suggestion": "gemini-3.5-flash-lite", "reason": "Clé API Gemini non configurée dans le système."}
+
+    models = db.query(AIModel).all()
+    available = [m.model_id for m in models]
+    
+    prompt = f"Le modèle IA '{req.missing_model}' n'est plus disponible. Voici les modèles disponibles : {', '.join(available)}. Trouve le modèle le plus proche techniquement. Réponds UNIQUEMENT avec ce format strict : ID_DU_MODELE | Brève explication en français de 10 mots max. Si aucun ne correspond, renvoie gemini-3.5-flash-lite | Par défaut."
+    
+    try:
+        from openai import AsyncOpenAI
+        client = AsyncOpenAI(base_url="https://generativelanguage.googleapis.com/v1beta/openai/", api_key=settings.gemini_api_key)
+        resp = await client.chat.completions.create(model="gemini-3.5-flash-lite", messages=[{"role": "user", "content": prompt}], max_tokens=50)
+        res = resp.choices[0].message.content.strip()
+        
+        if "|" in res:
+            parts = res.split("|")
+            sugg = parts[0].strip()
+            reason = parts[1].strip()
+        else:
+            sugg = res.strip()
+            reason = "Sélectionné par Gemini."
+            
+        if sugg not in available and sugg != "gemini-3.5-flash-lite":
+            sugg = "gemini-3.5-flash-lite"
+            reason = "Gemini a suggéré un modèle invalide. Fallback par défaut."
+
+        log_activity(f"✅ Remplacement trouvé : {req.missing_model} -> {sugg}")
+        return {"suggestion": sugg, "reason": reason}
+    except Exception as e:
+        log_activity(f"Erreur d'interrogation Gemini: {str(e)}. Fallback par défaut.")
+        return {"suggestion": "gemini-3.5-flash-lite", "reason": f"Erreur API."}
+
 @app.get("/api/users/me")
 def get_me(current_user: User = Depends(get_current_user)):
     return {"username": current_user.username, "is_admin": current_user.is_admin, "is_superadmin": current_user.is_superadmin, "avatar_path": current_user.avatar_path}
@@ -202,7 +247,6 @@ async def create_message(project_id: int, message: MessageCreate, db: Session =
             else:
                 extracted_files_data.append({"name": f.name, "content": content})
 
-    # On ne stocke plus le contenu brut des fichiers en DB pour éviter d'exploser le contexte des requêtes suivantes
     db_content = message.content
     if files_names:
         db_content += f"\n\n[Fichiers joints pour analyse : {', '.join(files_names)}]"
@@ -214,7 +258,6 @@ async def create_message(project_id: int, message: MessageCreate, db: Session =
     settings = db.query(SystemSettings).first()
     conf = message.config.dict() if message.config else {"workers": ["gemini-3.5-flash-lite"]} 
     
-    # Transmission des données de fichiers en mémoire vive à l'orchestrateur (Map-Reduce)
     ai_resp = await run_orchestrator(db, history, settings, conf, extracted_files_data)
     
     db.add(Message(role="assistant", content=ai_resp, project_id=project_id))
@@ -245,6 +288,37 @@ async def trigger_model_sync(db: Session = Depends(get_db), current_user: User =
 @app.get("/api/models/export")
 def export_models(db: Session = Depends(get_db), current_user: User = Depends(get_current_user)):
     if not current_user.is_admin: raise HTTPException(status_code=403, detail="Accès admin requis.")
-    models = db.query(AIModel).all()
-    data = [{"provider": m.provider, "model_id": m.model_id, "name": m.name, "description_fr": m.description_fr, "domain": m.domain, "is_free": m.is_free, "context_length": m.context_length, "pricing_prompt": m.pricing_prompt, "pricing_completion": m.pricing_completion} for m in models]
-    return Response(content=json.dumps(data), media_type="application/json", headers={"Content-Disposition": "attachment; filename=aethas38_models.json"})
+    models = db.query(AIModel).order_by(AIModel.provider.asc(), AIModel.name.asc()).all()
+
+    csv_io = io.StringIO()
+    writer = csv.writer(csv_io, delimiter=',')
+    writer.writerow(["Provider", "Model ID", "Name", "Domain", "Is Free", "Context Length", "Pricing Prompt", "Pricing Completion", "Description"])
+    for m in models:
+        writer.writerow([m.provider, m.model_id, m.name, m.domain, m.is_free, m.context_length, m.pricing_prompt, m.pricing_completion, m.description_fr])
+    
+    md_content = f"# Extraction des Modèles IA - AETHAS38\n\n**Date d'extraction :** {datetime.now().strftime('%d/%m/%Y à %H:%M:%S')}\n\n"
+    providers = sorted(list(set(m.provider for m in models)))
+    for prov in providers:
+        md_content += f"## Fournisseur : {prov.upper()}\n\n"
+        prov_models = [m for m in models if m.provider == prov]
+        for m in prov_models:
+            price_info = "**GRATUIT**" if m.is_free else f"In: ${m.pricing_prompt:.2f} / Out: ${m.pricing_completion:.2f}"
+            ctx_info = f"{int(m.context_length/1000)}k"
+            desc = m.description_fr.replace('\n', ' ') if m.description_fr else ""
+            md_content += f"- **{m.name or m.model_id}** (`{m.model_id}`)\n"
+            md_content += f"  - *Domaine :* {m.domain}\n"
+            md_content += f"  - *Prix (1M tokens) :* {price_info}\n"
+            md_content += f"  - *Contexte :* {ctx_info}\n"
+            md_content += f"  - *Description :* {desc}\n\n"
+
+    zip_io = io.BytesIO()
+    with zipfile.ZipFile(zip_io, mode='w', compression=zipfile.ZIP_DEFLATED) as zf:
+        zf.writestr("models_export.csv", csv_io.getvalue().encode('utf-8'))
+        zf.writestr(f"{datetime.now().strftime('%Y%m%d')}-extraction-modeles.md", md_content.encode('utf-8'))
+
+    zip_io.seek(0)
+    return Response(
+        content=zip_io.getvalue(), 
+        media_type="application/zip", 
+        headers={"Content-Disposition": f"attachment; filename=aethas38_models_{datetime.now().strftime('%Y%m%d')}.zip"}
+    )

backend/orchestrator.py

@@ -8,6 +8,16 @@ from sqlalchemy.exc import IntegrityError
 from .models import SystemSettings, AIModel, FinancialLog
 from datetime import datetime, timezone
 
+# --- LOGGER GLOBAL POUR LE TERMINAL ---
+activity_logs = []
+
+def log_activity(msg: str):
+    ts = datetime.now(timezone.utc).strftime('%H:%M:%S')
+    activity_logs.append(f"[{ts}] {msg}")
+    if len(activity_logs) > 100:
+        activity_logs.pop(0)
+# --------------------------------------
+
 def determine_domain(model_id: str) -> str:
     mid = model_id.lower()
     if "vision" in mid or "vl" in mid or "omni" in mid: return "Vision & Texte"
@@ -74,6 +84,7 @@ def update_finance_db(db, provider, balance, usage):
     except Exception as e: print(f"Finance DB Error: {e}")
 
 async def sync_providers_models(db: Session, settings: SystemSettings, sync_type: str = "Automatique"):
+    log_activity(f"Lancement de la synchronisation des modèles ({sync_type})...")
     added = 0
     models_to_process = {}
     async with httpx.AsyncClient(timeout=90.0) as client:
@@ -171,6 +182,7 @@ async def sync_providers_models(db: Session, settings: SystemSettings, sync_type
         db.rollback()
         
     await sync_finances(db, settings)
+    log_activity(f"Synchronisation terminée : {added} modèles analysés.")
     return {"status": "success", "models_processed": added}
 
 def get_client_for_model(db: Session, model_id: str, settings: SystemSettings):
@@ -194,7 +206,6 @@ async def ask_agent(client, model_id, messages, provider="openrouter"):
     kwargs = {"model": model_id, "messages": messages}
     if provider == "openrouter": 
         kwargs["extra_headers"] = {"HTTP-Referer": "https://aethas38.duckdns.org", "X-Title": "AETHAS38 Orchestrator"}
-        # Activation du plugin natif de compression d'OpenRouter pour éviter le dépassement de contexte
         kwargs["extra_body"] = {"plugins": [{"id": "context-compression"}]}
         
     resp = await client.chat.completions.create(**kwargs)
@@ -211,70 +222,80 @@ async def run_orchestrator(db: Session, history: list, settings: SystemSettings,
         p_mod = config.get("prompter")
         if not p_mod: p_mod = "gemini-3.5-flash-lite"
         
+        log_activity(f"Démarrage de l'orchestration. Modèle Prompteur: {p_mod}")
         p_client, p_prov = get_client_for_model(db, p_mod, settings)
 
         # --- WORKFLOW MAP-REDUCE : PRÉ-TRAITEMENT SÉQUENTIEL & CHUNKING ---
         files_context = ""
         if extracted_files:
+            log_activity(f"Traitement Map-Reduce de {len(extracted_files)} fichier(s) joint(s).")
             async def process_single_file(f):
                 file_sys = "You are an expert data analyst and senior developer. Extract the most important technical information from the file without losing critical code syntax."
                 content = f['content']
-                chunk_size = 150000  # Environ 35k à 40k tokens par morceau pour rester très large par rapport aux limites
+                chunk_size = 150000 
                 
-                # CHUNKING : Découpage intelligent si le fichier est massif
                 if len(content) > chunk_size:
                     chunks = [content[i:i+chunk_size] for i in range(0, len(content), chunk_size)]
                     chunk_analyses = []
+                    log_activity(f"Fichier lourd ({f['name']}): Chunking en {len(chunks)} morceaux.")
                     for idx, chunk in enumerate(chunks):
                         file_prompt = f"Demande de l'utilisateur : '{original_user_text}'.\n\nPartie {idx+1}/{len(chunks)} du fichier '{f['name']}'. Analysez, extrayez et résumez le code, VBA, SQL ou les données pertinentes.\n\nContenu :\n```\n{chunk}\n```"
                         try:
                             analysis = await ask_agent(p_client, p_mod, [{"role": "system", "content": file_sys}, {"role": "user", "content": file_prompt}], p_prov)
                             chunk_analyses.append(analysis)
+                            log_activity(f"Analyse chunk {idx+1}/{len(chunks)} pour {f['name']} réussie.")
                         except Exception as e:
                             chunk_analyses.append(f"[Erreur sur la partie {idx+1}: {str(e)}]")
+                            log_activity(f"Erreur chunk {idx+1}/{len(chunks)} pour {f['name']}: {str(e)}")
                         
-                        await asyncio.sleep(1.5) # Pause anti-spam (429) entre les morceaux
+                        await asyncio.sleep(1.5) 
                     
                     return f"\n\n--- Extraction du fichier {f['name']} (en {len(chunks)} parties) ---\n" + "\n".join(chunk_analyses)
                 else:
                     file_prompt = f"Demande de l'utilisateur : '{original_user_text}'.\n\nAnalysez le fichier ci-dessous. Extrayez, résumez et conservez méticuleusement tout le code, les macros VBA, les requêtes SQL, ou les données métier pertinentes pour répondre à la demande.\n\nFichier : {f['name']}\nContenu :\n```\n{content}\n```"
                     try:
                         analysis = await ask_agent(p_client, p_mod, [{"role": "system", "content": file_sys}, {"role": "user", "content": file_prompt}], p_prov)
+                        log_activity(f"Analyse intégrale de {f['name']} réussie.")
                         return f"\n\n--- Extraction du fichier {f['name']} ---\n{analysis}"
                     except Exception as e:
+                        log_activity(f"Erreur d'analyse sur {f['name']}: {str(e)}")
                         return f"\n\n--- Erreur sur {f['name']} ---\n{str(e)}"
 
             file_analyses = []
             for f in extracted_files:
                 analysis = await process_single_file(f)
                 file_analyses.append(analysis)
-                # SÉQUENÇAGE : Pause de 1.5 seconde entre les fichiers pour éviter l'erreur 429
                 await asyncio.sleep(1.5)
             
             files_context = "".join(file_analyses)
             user_prompt = f"{original_user_text}\n\nVoici les données pré-traitées des fichiers joints :\n{files_context}"
 
         # --- OPTIMISATION & TRADUCTION ---
+        log_activity(f"Optimisation/Traduction de la requête via Prompteur...")
         prompt_system = "You are an expert prompt engineer. Translate and optimize the user request and any file context into clear, precise English tailored for AI execution. Keep all code blocks intact."
         optimized = await ask_agent(p_client, p_mod, [{"role": "system", "content": prompt_system}, {"role": "user", "content": user_prompt}], p_prov)
 
+        log_activity(f"Lancement de {len(workers)} travailleur(s) en parallèle...")
         if len(workers) == 1:
             w_mod = workers[0]
             client, provider = get_client_for_model(db, w_mod, settings)
             worker_response = await ask_agent(client, w_mod, formatted_history + [{"role": "user", "content": optimized}], provider)
             responses = [worker_response]
+            log_activity(f"Travailleur 1 ({w_mod}) a terminé.")
         else:
             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)
+            log_activity("Tous les travailleurs ont terminé leur analyse.")
 
         c_mod = config.get("concatenator")
         if not c_mod: c_mod = "gemini-3.5-flash-lite"
         
         c_client, c_prov = get_client_for_model(db, c_mod, settings)
         
+        log_activity(f"Synthèse et traduction finale via Concaténeur ({c_mod})...")
         concat_system = (
             "You are a master lead developer and technical synthesizer. "
             "Synthesize the provided expert responses into a single cohesive response. "
@@ -286,8 +307,11 @@ async def run_orchestrator(db: Session, history: list, settings: SystemSettings,
         synth = f"User Request: {original_user_text}\n\n" + "\n".join([f"--- EXPERT {i+1} ---\n{str(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)
         
+        log_activity("Orchestration terminée avec succès.")
+
     except Exception as e:
         final_response = f"L'IA a rencontré une erreur critique: {str(e)}"
+        log_activity(f"ERREUR CRITIQUE: {str(e)}")
     
     await sync_finances(db, settings)
     return final_response

backend/schemas.py

@@ -65,3 +65,9 @@ class MessageResponse(MessageBase):
 class PasswordChange(BaseModel):
     old_password: str
     new_password: str
+
+class ModelReplacementRequest(BaseModel):
+    missing_model: str
+
+class LogRequest(BaseModel):
+    message: str

frontend/dashboard.html

@@ -91,8 +91,20 @@
                 </div>
             </div>
 
+            <!-- TERMINAL SYSTEME -->
+            <div class="h-40 border-t border-gray-700 bg-black flex flex-col font-mono text-[9px] flex-shrink-0 shadow-inner">
+                <div class="p-1.5 bg-gray-900 border-b border-gray-700 text-aethas-cyan font-bold flex items-center justify-between">
+                    <div class="flex items-center gap-1"><i data-lucide="terminal" class="w-3 h-3"></i> SYSTEM LOGS</div>
+                    <div class="w-2 h-2 rounded-full bg-green-500 animate-pulse"></div>
+                </div>
+                <div class="flex-1 overflow-y-auto p-2 custom-scrollbar text-green-400 space-y-1" id="terminal-logs">
+                    <div v-for="(log, i) in systemLogs" :key="i" class="break-words">{{ log }}</div>
+                    <div v-if="systemLogs.length === 0" class="text-gray-600">En attente d'activité serveur...</div>
+                </div>
+            </div>
+
             <!-- ENCART FINANCIER -->
-            <div class="px-4 pb-2 border-b border-gray-700">
+            <div class="px-4 pb-2 pt-2 border-t border-gray-700 bg-aethas-panel flex-shrink-0">
                 <div v-if="financesList.length > 0" class="flex flex-col gap-1.5 mb-2">
                     <div v-for="fin in financesList" :key="fin.provider" class="text-[10px] bg-gray-800/80 border border-gray-600/50 px-2 py-1.5 rounded flex justify-between items-center shadow-inner">
                         <span class="text-gray-400 capitalize">{{ fin.provider }}</span>
@@ -101,7 +113,7 @@
                 </div>
             </div>
             
-            <div class="p-4 flex justify-between items-center cursor-pointer hover:bg-gray-800 transition-colors" @click="openSettings">
+            <div class="p-4 flex justify-between items-center cursor-pointer hover:bg-gray-800 transition-colors border-t border-gray-700 flex-shrink-0" @click="openSettings">
                 <div class="flex items-center gap-2">
                     <img v-if="user.avatar_path" :src="user.avatar_path" class="w-8 h-8 rounded-full object-cover border border-gray-600 bg-gray-900">
                     <div v-else class="w-8 h-8 rounded-full bg-gradient-to-tr from-aethas-cyan to-aethas-purple flex items-center justify-center text-sm font-bold shadow-md">{{ user.username.charAt(0).toUpperCase() }}</div>
@@ -178,7 +190,7 @@
                         <h3 class="text-lg font-semibold text-red-400 mb-4">Outils Administrateur</h3>
                         <div class="flex gap-4">
                             <button @click="activeView = 'models'" class="bg-gray-700 hover:bg-gray-600 text-white px-4 py-2 rounded-lg text-sm border border-gray-600">Ouvrir le panneau Modèles IA</button>
-                            <a href="/api/models/export" target="_blank" class="bg-gray-700 hover:bg-gray-600 text-white px-4 py-2 rounded-lg text-sm border border-gray-600">Exporter DB Modèles (JSON)</a>
+                            <a href="/api/models/export" target="_blank" class="bg-gray-700 hover:bg-gray-600 text-white px-4 py-2 rounded-lg text-sm border border-gray-600">Exporter DB Modèles (ZIP CSV/MD)</a>
                         </div>
                     </div>
                 </div>
@@ -215,6 +227,10 @@
             <div class="bg-aethas-panel border border-gray-700 rounded-xl overflow-hidden flex flex-col">
                 <div class="p-4 bg-gray-800/50 border-b border-gray-700 flex flex-wrap gap-4 items-center">
                     <input v-model="filterSearch" type="text" placeholder="Rechercher..." class="bg-gray-900 border border-gray-600 rounded px-3 py-1.5 text-sm text-gray-200 w-full md:w-64 focus:border-aethas-cyan focus:outline-none">
+                    <select v-model="filterProvider" class="bg-gray-900 border border-gray-600 rounded px-3 py-1.5 text-sm text-gray-200 focus:outline-none">
+                        <option value="">Tous les fournisseurs</option>
+                        <option v-for="p in uniqueProviders" :key="p" :value="p">{{ p.toUpperCase() }}</option>
+                    </select>
                     <select v-model="filterDomain" class="bg-gray-900 border border-gray-600 rounded px-3 py-1.5 text-sm text-gray-200 focus:outline-none">
                         <option value="">Tous les domaines</option>
                         <option value="Texte Polyvalent">Texte Polyvalent</option>
@@ -277,9 +293,10 @@
                             </template>
                         </div>
 
-                        <div v-if="msg.role !== 'user'" class="mt-3 flex items-center gap-3 border-t border-gray-700/50 pt-2 opacity-50 hover:opacity-100 transition-opacity">
+                        <!-- Boutons présents sur toutes les bulles (utilisateur et IA) -->
+                        <div class="mt-3 flex items-center gap-3 border-t border-gray-700/50 pt-2 opacity-50 hover:opacity-100 transition-opacity">
                             <button @click="copyToClipboard(msg.content)" class="text-xs text-gray-400 hover:text-aethas-cyan flex items-center gap-1"><i data-lucide="copy" class="w-3 h-3"></i> Copier</button>
-                            <button @click="downloadMessage(msg.content, msg.created_at)" class="text-xs text-gray-400 hover:text-aethas-cyan flex items-center gap-1"><i data-lucide="file-down" class="w-3 h-3"></i> Extraire</button>
+                            <button @click="downloadMessage(msg.content, msg.created_at || new Date().toISOString())" class="text-xs text-gray-400 hover:text-aethas-cyan flex items-center gap-1"><i data-lucide="file-down" class="w-3 h-3"></i> Extraire</button>
                         </div>
                     </div>
 
@@ -411,7 +428,7 @@
 </div>
 
 <script>
-    const { createApp, ref, reactive, onMounted, nextTick, computed } = Vue;
+    const { createApp, ref, reactive, onMounted, nextTick, computed, watch } = Vue;
 
     createApp({
         setup() {
@@ -440,6 +457,7 @@
             const filterSearch = ref("");
             const filterDomain = ref("");
             const filterPricing = ref("");
+            const filterProvider = ref("");
             
             const colPricing = ref("");
             const colDomain = ref("");
@@ -450,17 +468,25 @@
 
             const attachedFiles = ref([]); 
             
+            const systemLogs = ref([]);
+            let logInterval = null;
+
             const pinnedProjects = computed(() => projects.value.filter(p => p.is_pinned));
             const recentProjects = computed(() => projects.value.filter(p => !p.is_pinned));
             
+            const uniqueProviders = computed(() => {
+                return [...new Set(modelInfo.models.map(m => m.provider))].sort();
+            });
+
             const filteredModels = computed(() => {
                 return modelInfo.models.filter(m => {
                     const matchSearch = (m.model_id.toLowerCase().includes(filterSearch.value.toLowerCase()) || m.provider.toLowerCase().includes(filterSearch.value.toLowerCase()));
                     const matchDomain = filterDomain.value === "" || m.domain === filterDomain.value;
+                    const matchProvider = filterProvider.value === "" || m.provider === filterProvider.value;
                     let matchPrice = true;
                     if (filterPricing.value === 'free') matchPrice = m.is_free;
                     if (filterPricing.value === 'paid') matchPrice = !m.is_free;
-                    return matchSearch && matchDomain && matchPrice;
+                    return matchSearch && matchDomain && matchProvider && matchPrice;
                 });
             });
 
@@ -500,41 +526,90 @@
             const openSettings = () => { isSettingsModalOpen.value = true; nextTick(() => lucide.createIcons()); };
             const closeSettings = () => { isSettingsModalOpen.value = false; };
             
+            const logToTerminal = async (msg) => {
+                try { await fetch('/api/logs', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ message: msg }) }); } catch(e){}
+            };
+
+            const fetchLogs = async () => {
+                try {
+                    const res = await fetch('/api/logs');
+                    if (res.ok) {
+                        const data = await res.json();
+                        if (systemLogs.value.length !== data.logs.length || data.logs[data.logs.length-1] !== systemLogs.value[systemLogs.value.length-1]) {
+                            systemLogs.value = data.logs;
+                            nextTick(() => {
+                                const el = document.getElementById('terminal-logs');
+                                if (el) el.scrollTop = el.scrollHeight;
+                            });
+                        }
+                    }
+                } catch(e){}
+            };
+
+            const validateConfigAndReplace = async () => {
+                if (!modelInfo.models || modelInfo.models.length === 0) return;
+                const availableModels = modelInfo.models.map(m => m.model_id);
+                const replacements = [];
+                
+                const checkAndReplace = async (val, setterCallback, roleName) => {
+                    if (val && val.trim() !== "" && !availableModels.includes(val)) {
+                        logToTerminal(`Le modèle ${val} n'est plus reconnu. Recherche Gemini...`);
+                        try {
+                            const res = await fetch('/api/models/suggest_replacement', {
+                                method: 'POST', headers: {'Content-Type': 'application/json'},
+                                body: JSON.stringify({ missing_model: val })
+                            });
+                            if (res.ok) {
+                                const data = await res.json();
+                                setterCallback(data.suggestion);
+                                replacements.push(`- ${roleName} : ${val} a été remplacé par ${data.suggestion}\n  Raison: ${data.reason}`);
+                            } else {
+                                setterCallback("gemini-3.5-flash-lite");
+                                replacements.push(`- ${roleName} : ${val} remplacé par gemini-3.5-flash-lite (Erreur API)`);
+                            }
+                        } catch(e) {
+                            setterCallback("gemini-3.5-flash-lite");
+                        }
+                    }
+                };
+
+                await checkAndReplace(selectedPrompter.value, (n) => selectedPrompter.value = n, "Prompteur");
+                await checkAndReplace(selectedConcatenator.value, (n) => selectedConcatenator.value = n, "Concaténeur");
+                for(let i=0; i<5; i++) {
+                    await checkAndReplace(workers.value[i], (n) => workers.value[i] = n, `Travailleur ${i+1}`);
+                }
+
+                if (replacements.length > 0) {
+                    alert("⚠️ Mise à jour de la conversation\n\nCertains modèles ne sont plus disponibles. L'IA a trouvé des alternatives :\n\n" + replacements.join("\n\n"));
+                }
+            };
+
+            watch([workers, selectedPrompter, selectedConcatenator], () => {
+                if (activeProject.value) {
+                    const config = {
+                        workers: workers.value,
+                        prompter: selectedPrompter.value,
+                        concatenator: selectedConcatenator.value
+                    };
+                    localStorage.setItem('aethas_config_' + activeProject.value.id, JSON.stringify(config));
+                }
+            }, { deep: true });
+
             const fetchUser = async () => { try { const res = await fetch('/api/users/me'); if(res.ok) user.value = await res.json(); } catch(e){} };
             const fetchModelsInfo = async () => { try { const res = await fetch('/api/models/info'); if(res.ok) { const data = await res.json(); modelInfo.last_sync_date = data.last_sync_date; modelInfo.last_sync_type = data.last_sync_type; modelInfo.models = data.models; } } catch(e){} };
             const fetchFinances = async () => { try { const res = await fetch('/api/finances'); if(res.ok) financesList.value = await res.json(); } catch(e){} };
             
             const syncModels = async () => { 
                 isSyncing.value = true; 
+                logToTerminal("Déclenchement manuel de l'extraction des modèles...");
                 try { 
                     const res = await fetch('/api/models/sync', { method: 'POST' }); 
                     if(res.ok) { 
                         await fetchModelsInfo(); 
                         await fetchFinances();
-                        
-                        let mdContent = `# Extraction des Modèles IA - AETHAS38\n\n`;
-                        const d = new Date();
-                        const dateStr = d.getFullYear() + String(d.getMonth()+1).padStart(2, '0') + String(d.getDate()).padStart(2, '0');
-                        mdContent += `**Date d'extraction :** ${d.toLocaleDateString('fr-FR')} à ${d.toLocaleTimeString('fr-FR')}\n\n`;
-                        
-                        const providers = [...new Set(modelInfo.models.map(m => m.provider))];
-                        providers.forEach(prov => {
-                            mdContent += `## Fournisseur : ${prov.toUpperCase()}\n\n`;
-                            const provModels = modelInfo.models.filter(m => m.provider === prov);
-                            provModels.forEach(m => {
-                                const priceInfo = m.is_free ? "**GRATUIT**" : `In: $${m.pricing_prompt.toFixed(2)} / Out: $${m.pricing_completion.toFixed(2)}`;
-                                const ctxInfo = `${(m.context_length / 1000).toFixed(0)}k`;
-                                mdContent += `- **${m.name || m.model_id}** (\`${m.model_id}\`)\n`;
-                                mdContent += `  - *Domaine :* ${m.domain}\n`;
-                                mdContent += `  - *Prix (1M tokens) :* ${priceInfo}\n`;
-                                mdContent += `  - *Contexte :* ${ctxInfo}\n`;
-                                mdContent += `  - *Description :* ${m.description_fr.replace(/\n/g, ' ')}\n\n`;
-                            });
-                        });
-
-                        const filename = `${dateStr}-extraction-modèles.md`;
-                        downloadFile(mdContent, filename);
-                        alert("Synchronisation réussie ! Le fichier markdown a été généré et téléchargé."); 
+                        alert("Synchronisation réussie !"); 
+                    } else if (res.status === 401) {
+                        alert("Votre session a expiré."); window.location.href = '/login';
                     } else {
                         let errText = await res.text();
                         try { const errObj = JSON.parse(errText); errText = errObj.detail || errText; } catch(e){}
@@ -545,6 +620,7 @@
             };
 
             const downloadTemplate = () => {
+                logToTerminal("Téléchargement du template MD généré.");
                 const templateContent = `# AETHAS38 - Configuration Multi-Agents\n\n**Rappel important :**\n- **Prompteur :** Le système de l'orchestrateur utilisera ce modèle pour traduire et optimiser votre requête initiale en ANGLAIS (langue native des IA).\n- **Concaténeur :** Le système utilisera ce modèle pour regrouper les réponses des travailleurs et traduire la synthèse finale en FRANÇAIS (en préservant le code brut).\n\n## Sélection des Modèles\nRenseignez l'ID exact du modèle (ex: gemini-3.5-flash-lite, mistralai/mistral-large-4-0). Laissez vide si inutilisé.\n\n- Prompteur : \n- Travailleur 1 : \n- Travailleur 2 : \n- Travailleur 3 : \n- Travailleur 4 : \n- Travailleur 5 : \n- Concaténeur : \n`;
                 downloadFile(templateContent, 'aethas38-config-agents.md');
             };
@@ -552,8 +628,9 @@
             const handleConfigImport = (event) => {
                 const file = event.target.files[0];
                 if (!file) return;
+                logToTerminal(`Importation de configuration depuis ${file.name}`);
                 const reader = new FileReader();
-                reader.onload = (e) => {
+                reader.onload = async (e) => {
                     const content = e.target.result;
                     
                     const extractModel = (key) => {
@@ -573,6 +650,7 @@
                     selectedPrompter.value = extractModel('Prompteur');
                     selectedConcatenator.value = extractModel('Concateneur');
 
+                    await validateConfigAndReplace();
                     alert("Configuration IA importée et appliquée avec succès !");
                 };
                 reader.readAsText(file);
@@ -623,6 +701,7 @@
             };
 
             const processFile = (file) => {
+                logToTerminal(`Fichier ${file.name} ajouté en pièce jointe.`);
                 const reader = new FileReader();
                 const textExts = ['.txt', '.md', '.csv', '.json', '.py', '.js', '.html', '.css', '.xml', '.yml', '.yaml', '.sh', '.bat', '.ps1', '.ini', '.cfg', '.conf', '.log'];
                 const isText = textExts.some(ext => file.name.toLowerCase().endsWith(ext)) || file.type.startsWith('text/');
@@ -631,7 +710,6 @@
                     attachedFiles.value.push({ name: file.name, content: e.target.result });
                 };
 
-                // Les fichiers binaires sont lus en Base64.
                 if (isText) {
                     reader.readAsText(file);
                 } else {
@@ -648,8 +726,51 @@
             const parseMessage = (content) => { const regex = /```([\w.-]*)\n([\s\S]*?)```/g; let parts = [], last = 0, m; while ((m = regex.exec(content)) !== null) { if (m.index > last) parts.push({ type: 'text', content: content.slice(last, m.index) }); parts.push({ type: 'code', language: m[1], content: m[2] }); last = m.index + m[0].length; } if (last < content.length) parts.push({ type: 'text', content: content.slice(last) }); return parts.length > 0 ? parts : [{ type: 'text', content: content }]; };
 
             const fetchProjects = async () => { try { const res = await fetch('/api/projects'); if(res.ok) projects.value = await res.json(); nextTick(()=>lucide.createIcons()); } catch(e){} };
-            const selectProject = async (project) => { activeView.value = 'chat'; activeProject.value = project; messages.value = []; try { const res = await fetch(`/api/projects/${project.id}/messages`); if(res.ok) { messages.value = await res.json(); scrollToBottom(); nextTick(()=>lucide.createIcons()); } } catch(e){} };
-            const createNewProject = async () => { activeView.value = 'chat'; isLoading.value = true; try { const res = await fetch('/api/projects', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({title: "Nouvelle discussion"})}); if(res.ok){ const np = await res.json(); projects.value.unshift(np); selectProject(np); } } catch(e){} finally{isLoading.value = false;} };
+            const selectProject = async (project) => { 
+                activeView.value = 'chat'; 
+                activeProject.value = project; 
+                messages.value = []; 
+                logToTerminal(`Chargement du projet: ${project.title}`);
+
+                const saved = localStorage.getItem('aethas_config_' + project.id);
+                if (saved) {
+                    try {
+                        const config = JSON.parse(saved);
+                        workers.value = config.workers || ["", "", "", "", ""];
+                        selectedPrompter.value = config.prompter || "";
+                        selectedConcatenator.value = config.concatenator || "";
+                    } catch(e) {
+                        workers.value = ["", "", "", "", ""];
+                        selectedPrompter.value = "";
+                        selectedConcatenator.value = "";
+                    }
+                } else {
+                    workers.value = ["", "", "", "", ""];
+                    selectedPrompter.value = "";
+                    selectedConcatenator.value = "";
+                }
+
+                try { 
+                    const res = await fetch(`/api/projects/${project.id}/messages`); 
+                    if(res.ok) { 
+                        messages.value = await res.json(); 
+                        scrollToBottom(); 
+                        nextTick(()=>lucide.createIcons()); 
+                    } else if (res.status === 401) {
+                        alert("Votre session a expiré."); window.location.href = '/login';
+                    }
+                } catch(e){} 
+
+                await validateConfigAndReplace();
+            };
+            
+            const createNewProject = async () => { 
+                activeView.value = 'chat'; isLoading.value = true; 
+                try { 
+                    const res = await fetch('/api/projects', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({title: "Nouvelle discussion"})}); 
+                    if(res.ok){ const np = await res.json(); projects.value.unshift(np); selectProject(np); } else if (res.status === 401) { alert("Session expirée."); window.location.href='/login'; }
+                } catch(e){} finally{isLoading.value = false;} 
+            };
 
             const sendMessage = async () => {
                 const activeWorkers = workers.value.filter(w => w && w.trim() !== "");
@@ -667,19 +788,15 @@
                 scrollToBottom();
                 
                 const payloadFiles = [...attachedFiles.value];
-
                 const payload = { 
                     role: 'user', 
                     content: userText || "Analyse ces fichiers joints.", 
-                    config: { 
-                        workers: activeWorkers, 
-                        prompter: selectedPrompter.value, 
-                        concatenator: selectedConcatenator.value 
-                    },
+                    config: { workers: activeWorkers, prompter: selectedPrompter.value, concatenator: selectedConcatenator.value },
                     files: payloadFiles
                 };
 
                 attachedFiles.value = [];
+                logToTerminal("Envoi de la requête à l'orchestrateur...");
 
                 try {
                     const response = await fetch(`/api/projects/${activeProject.value.id}/messages`, { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify(payload) });
@@ -715,17 +832,27 @@
             const togglePin = async (pid) => { try { const res = await fetch(`/api/projects/${pid}/pin`, { method: 'PUT' }); if (res.ok) { const up = await res.json(); const i = projects.value.findIndex(p => p.id === pid); if (i !== -1) projects.value[i] = up; } } catch (e) {} };
             const deleteProject = async (pid) => { if (!confirm("Supprimer ce projet ?")) return; try { const res = await fetch(`/api/projects/${pid}`, { method: 'DELETE' }); if (res.ok) { projects.value = projects.value.filter(p => p.id !== pid); if (activeProject.value && activeProject.value.id === pid) activeProject.value = null; } } catch (e) {} };
 
-            onMounted(() => { lucide.createIcons(); fetchUser(); fetchProjects(); fetchModelsInfo(); fetchFinances(); });
+            onMounted(() => { 
+                lucide.createIcons(); 
+                fetchUser(); 
+                fetchProjects(); 
+                fetchModelsInfo().then(() => {
+                    // Force la validation de la première vue si nécessaire
+                    if(activeProject.value) validateConfigAndReplace();
+                }); 
+                fetchFinances(); 
+                logInterval = setInterval(fetchLogs, 2000);
+            });
 
             return { 
                 user, activeView, settingsTab, isSidebarOpen, toggleSidebar, prompt, autoResize, promptTextarea, 
                 projects, pinnedProjects, recentProjects, activeProject, messages, isAiThinking,
                 createNewProject, selectProject, renameProject, sendMessage, isLoading, togglePin, deleteProject,
                 isSettingsModalOpen, openSettings, closeSettings, passForm, settingsMessage, isSavingSettings, changePassword, uploadAvatar,
-                modelInfo, financesList, filterSearch, filterDomain, filterPricing, filteredModels, getFilteredModelsForCol, formatDate, syncModels, isSyncing,
+                modelInfo, financesList, filterSearch, filterDomain, filterPricing, filterProvider, uniqueProviders, filteredModels, getFilteredModelsForCol, formatDate, syncModels, isSyncing,
                 workers, selectedPrompter, selectedConcatenator, colPricing, colDomain, downloadTemplate, handleConfigImport,
                 attachedFiles, handleFileUpload, handlePaste, removeFile,
-                exportProject, copyToClipboard, downloadFile, downloadMessage, parseMessage
+                exportProject, copyToClipboard, downloadFile, downloadMessage, parseMessage, systemLogs
             };
         }
     }).mount('#app');