From 134312ebffb80598dfaefa25a7f253e9ed15e8cc Mon Sep 17 00:00:00 2001 From: Xavier Date: Thu, 8 Oct 2026 17:12:39 +0200 Subject: [PATCH] feat maj fonctionnement --- backend/main.py | 92 +++++++++++++++-- backend/orchestrator.py | 34 ++++++- backend/schemas.py | 8 +- frontend/dashboard.html | 215 ++++++++++++++++++++++++++++++++-------- 4 files changed, 290 insertions(+), 59 deletions(-) diff --git a/backend/main.py b/backend/main.py index 4e2b8d2..4a782df 100644 --- a/backend/main.py +++ b/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"}) \ No newline at end of file + 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"} + ) \ No newline at end of file diff --git a/backend/orchestrator.py b/backend/orchestrator.py index b4910ec..b8d1280 100644 --- a/backend/orchestrator.py +++ b/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. " @@ -285,9 +306,12 @@ 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 \ No newline at end of file diff --git a/backend/schemas.py b/backend/schemas.py index 5b9339b..e0e6a82 100644 --- a/backend/schemas.py +++ b/backend/schemas.py @@ -64,4 +64,10 @@ class MessageResponse(MessageBase): class PasswordChange(BaseModel): old_password: str - new_password: str \ No newline at end of file + new_password: str + +class ModelReplacementRequest(BaseModel): + missing_model: str + +class LogRequest(BaseModel): + message: str \ No newline at end of file diff --git a/frontend/dashboard.html b/frontend/dashboard.html index 4446af1..88976fc 100644 --- a/frontend/dashboard.html +++ b/frontend/dashboard.html @@ -91,8 +91,20 @@ + +
+
+
SYSTEM LOGS
+
+
+
+
{{ log }}
+
En attente d'activité serveur...
+
+
+ -
+
{{ fin.provider }} @@ -101,7 +113,7 @@
-
+
{{ user.username.charAt(0).toUpperCase() }}
@@ -178,7 +190,7 @@

Outils Administrateur

- Exporter DB Modèles (JSON) + Exporter DB Modèles (ZIP CSV/MD)
@@ -215,6 +227,10 @@
+