133 lines
7.7 KiB
Python
133 lines
7.7 KiB
Python
import asyncio
|
|
import httpx
|
|
from openai import AsyncOpenAI
|
|
from fastapi import HTTPException
|
|
from sqlalchemy.orm import Session
|
|
from .models import SystemSettings, AIModel, FinancialLog
|
|
from datetime import datetime, timezone
|
|
|
|
def determine_domain(model_id: str) -> str:
|
|
mid = model_id.lower()
|
|
if "vision" in mid or "vl" in mid: return "Vision & Texte"
|
|
if "coder" in mid or "code" in mid or "math" in mid: return "Code & Logique"
|
|
if "audio" in mid or "whisper" in mid: return "Audio"
|
|
return "Texte Polyvalent"
|
|
|
|
async def sync_finances(db: Session, settings: SystemSettings):
|
|
"""Interroge les fournisseurs pour récupérer le solde financier exact."""
|
|
async with httpx.AsyncClient() as client:
|
|
if settings.openrouter_management_key or settings.openrouter_api_key:
|
|
try:
|
|
key = settings.openrouter_management_key or settings.openrouter_api_key
|
|
# Test de l'endpoint des crédits prépayés en priorité
|
|
cred_resp = await client.get("https://openrouter.ai/api/v1/credits", headers={"Authorization": f"Bearer {key}"})
|
|
balance = 0.0
|
|
usage = 0.0
|
|
|
|
if cred_resp.status_code == 200 and cred_resp.json().get("data"):
|
|
data = cred_resp.json().get("data", {})
|
|
balance = float(data.get("total_credits") or 0.0) - float(data.get("total_usage") or 0.0)
|
|
usage = float(data.get("total_usage") or 0.0)
|
|
else:
|
|
# Fallback sur l'usage de la clé si pas de crédits prépayés
|
|
key_resp = await client.get("https://openrouter.ai/api/v1/auth/key", headers={"Authorization": f"Bearer {key}"})
|
|
if key_resp.status_code == 200:
|
|
data = key_resp.json().get("data", {})
|
|
limit = data.get("limit")
|
|
usage = float(data.get("usage") or 0.0)
|
|
balance = (float(limit) - usage) if limit is not None else -usage
|
|
|
|
update_finance_db(db, "OpenRouter", balance, usage)
|
|
except Exception as e: print(f"Erreur Finance OR: {e}")
|
|
|
|
if settings.groq_api_key: update_finance_db(db, "Groq", 999.0, 0.0) # Gratuit en Beta
|
|
|
|
if settings.deepseek_api_key:
|
|
try:
|
|
resp = await client.get("https://api.deepseek.com/user/balance", headers={"Authorization": f"Bearer {settings.deepseek_api_key}"})
|
|
if resp.status_code == 200:
|
|
infos = resp.json().get("balance_infos", [{}])[0]
|
|
update_finance_db(db, "DeepSeek", float(infos.get("total_balance", 0)), 0.0)
|
|
except Exception: pass
|
|
db.commit()
|
|
|
|
def update_finance_db(db, provider, balance, usage):
|
|
log = db.query(FinancialLog).filter(FinancialLog.provider == provider).first()
|
|
if log:
|
|
log.balance = balance; log.total_usage = usage; log.checked_at = datetime.now(timezone.utc)
|
|
else:
|
|
db.add(FinancialLog(provider=provider, balance=balance, total_usage=usage))
|
|
|
|
async def sync_providers_models(db: Session, settings: SystemSettings, sync_type: str = "Automatique"):
|
|
added = 0
|
|
async with httpx.AsyncClient() as client:
|
|
if settings.openrouter_api_key:
|
|
try:
|
|
resp = await client.get("https://openrouter.ai/api/v1/models")
|
|
if resp.status_code == 200:
|
|
for item in resp.json().get("data", []):
|
|
pricing = item.get("pricing") or {}
|
|
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 IA générique.")[:200] + "..."
|
|
process_model(db, "openrouter", item["id"], item["name"], desc, determine_domain(item["id"]), is_free, item.get("context_length", 0), pp, pc)
|
|
added += 1
|
|
except Exception as e: print(f"Erreur Modèles OR: {e}")
|
|
|
|
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", []):
|
|
process_model(db, "groq", item["id"], item["id"].capitalize(), "Modèle ultra-rapide exécuté sur LPU Groq.", determine_domain(item["id"]), True, 8192, 0.0, 0.0)
|
|
added += 1
|
|
except Exception: pass
|
|
|
|
settings.last_sync_date = datetime.now(timezone.utc)
|
|
settings.last_sync_type = sync_type
|
|
db.commit()
|
|
await sync_finances(db, settings)
|
|
return {"status": "success", "models_processed": added}
|
|
|
|
def process_model(db, provider, mod_id, name, desc, domain, is_free, ctx, pp, pc):
|
|
existing = db.query(AIModel).filter(AIModel.model_id == mod_id).first()
|
|
if existing:
|
|
existing.pricing_prompt = pp; existing.pricing_completion = pc; existing.is_free = is_free; existing.last_updated = datetime.now(timezone.utc)
|
|
else:
|
|
db.add(AIModel(provider=provider, model_id=mod_id, name=name, description_fr=desc, domain=domain, is_free=is_free, context_length=ctx, pricing_prompt=pp, pricing_completion=pc))
|
|
|
|
def get_client_for_model(model_id: str, settings: SystemSettings):
|
|
if "gemini" in model_id.lower() and settings.gemini_api_key: return AsyncOpenAI(base_url="https://generativelanguage.googleapis.com/v1beta/openai/", api_key=settings.gemini_api_key)
|
|
elif "groq" in model_id.lower() or "llama" in model_id.lower(): return AsyncOpenAI(base_url="https://api.groq.com/openai/v1", api_key=settings.groq_api_key)
|
|
return AsyncOpenAI(base_url="https://openrouter.ai/api/v1", api_key=settings.openrouter_api_key)
|
|
|
|
async def ask_agent(client, model_id, messages, is_openrouter=False):
|
|
kwargs = {"model": model_id, "messages": messages}
|
|
if is_openrouter: kwargs["extra_headers"] = {"HTTP-Referer": "https://aethas38.duckdns.org", "X-Title": "AETHAS38 Orchestrator"}
|
|
resp = await client.chat.completions.create(**kwargs)
|
|
return resp.choices[0].message.content
|
|
|
|
async def run_orchestrator(db: Session, history: list, settings: SystemSettings, config: dict) -> str:
|
|
workers = config.get("workers", ["gemini-3.5-flash-lite"])
|
|
user_prompt = history[-1].content
|
|
formatted_history = [{"role": msg.role, "content": msg.content} for msg in history[:-1]]
|
|
|
|
final_response = ""
|
|
if len(workers) == 1:
|
|
w_mod = workers[0]
|
|
final_response = await ask_agent(get_client_for_model(w_mod, settings), w_mod, formatted_history + [{"role": "user", "content": user_prompt}], "openrouter" in w_mod.lower())
|
|
else:
|
|
p_mod = config.get("prompter", "gemini-3.5-flash-lite")
|
|
optimized = await ask_agent(get_client_for_model(p_mod, settings), p_mod, [{"role": "system", "content": "Optimise cette requête."}, {"role": "user", "content": user_prompt}])
|
|
|
|
w_tasks = [ask_agent(get_client_for_model(w, settings), w, formatted_history + [{"role": "user", "content": optimized}], "openrouter" in w.lower()) for w in workers]
|
|
responses = await asyncio.gather(*w_tasks, return_exceptions=True)
|
|
|
|
c_mod = config.get("concatenator", "gemini-3.5-flash-lite")
|
|
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(get_client_for_model(c_mod, settings), c_mod, [{"role": "user", "content": synth}])
|
|
|
|
# MAJ Financière après requête
|
|
await sync_finances(db, settings)
|
|
return final_response |