Files
aethas-free/modules/ai_openrouter.py
T
2026-08-24 19:25:05 +02:00

121 lines
5.3 KiB
Python

import os
import time
import json
from dotenv import load_dotenv
from openai import OpenAI
from modules.logger import log_event
load_dotenv()
api_key_openrouter = os.getenv("OPENROUTER_API_KEY") or "sk-or-v1-cle-non-definie"
client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=api_key_openrouter)
CATALOGUE_FILE = "/DATA/AppData/MULTI-IA-AETHAS38/catalogue_dynamique.json"
def verifier_cle_api():
cle = os.getenv("OPENROUTER_API_KEY")
if not cle or cle == "sk-or-v1-cle-non-definie":
raise Exception("Clé OPENROUTER_API_KEY absente dans le fichier .env.")
return cle
def obtenir_modele_dynamique(premium: bool, prompt: str = ""):
"""Charge le catalogue dynamiquement et adapte le modèle si la règle Éducation est détectée."""
est_education = "RÈGLE ÉDUCATION NATIONALE" in prompt
try:
if os.path.exists(CATALOGUE_FILE):
with open(CATALOGUE_FILE, "r", encoding="utf-8") as f:
data = json.load(f)
if premium:
paid_models = data.get("paid_models", [])
claude = [m for m in paid_models if "claude-3.5-sonnet" in m.lower()]
return claude[0] if claude else (paid_models[0] if paid_models else "anthropic/claude-3.5-sonnet")
else:
# En mode gratuit + Education, Mistral est le plus pointu en syntaxe française
if est_education:
return "mistralai/mistral-small-24b-instruct-2501:free"
free_models = data.get("free_models", [])
priorites = [m for m in free_models if "gemma" in m.lower() or "nemotron" in m.lower()]
return priorites[0] if priorites else (free_models[0] if free_models else "google/gemma-2-9b-it:free")
except Exception:
pass
if premium: return "anthropic/claude-3.5-sonnet"
return "mistralai/mistral-small-24b-instruct-2501:free" if est_education else "google/gemma-2-9b-it:free"
def interroger_openrouter(prompt: str, type_modele: str = "openrouter_chat", premium: bool = False, max_retries: int = 2, chat_id: str = None):
verifier_cle_api()
nom_modele_api = obtenir_modele_dynamique(premium, prompt) # On passe le prompt pour détecter le marqueur
nom_affichage = f"OpenRouter ({nom_modele_api.split('/')[-1]})"
couleur = "#d97757" if premium else "#4a90e2"
extra_body_data = {"session_id": chat_id} if chat_id else {}
for tentative in range(max_retries):
try:
response = client.chat.completions.create(
model=nom_modele_api,
messages=[{"role": "user", "content": prompt}],
extra_headers={"HTTP-Referer": "https://aethas38.duckdns.org", "X-Title": "Aethas38 Multi-IA"},
extra_body=extra_body_data,
timeout=90.0
)
texte = response.choices[0].message.content
usage = response.usage
tokens_in = usage.prompt_tokens if usage else 0
tokens_out = usage.completion_tokens if usage else 0
return texte, couleur, "OpenRouter", nom_affichage, tokens_in, tokens_out
except Exception as e:
log_event("WARNING", "OPENROUTER", f"Tentative {tentative + 1} échouée pour {nom_modele_api} : {e}")
if tentative == max_retries - 1:
try:
from modules.model_updater import trigger_update_now
trigger_update_now()
except Exception:
pass
raise e
time.sleep(1)
return None, None, None, None, 0, 0
def interroger_openrouter_multi(prompt: str, type_modele: str = "openrouter_code", premium: bool = False, chat_id: str = None) -> list:
verifier_cle_api()
extra_body_data = {"session_id": chat_id} if chat_id else {}
# --- LA LISTE BLANCHE DES 5 MEILLEURS MODÈLES ---
if premium:
modeles = [
"anthropic/claude-3.5-sonnet", # Le meilleur en code/logique
"openai/gpt-4o", # Ultra polyvalent
"google/gemini-1.5-pro", # Excellent contexte
"mistralai/mistral-large-2407", # Top pour le français
"meta-llama/llama-3.1-405b-instruct" # Le titan OpenSource
]
else:
modeles = [
"google/gemma-2-9b-it:free",
"meta-llama/llama-3.1-8b-instruct:free",
"microsoft/phi-3-mini-128k-instruct:free",
"mistralai/mistral-nemo:free",
"qwen/qwen-2-7b-instruct:free"
]
reponses = []
for modele in modeles:
try:
res = client.chat.completions.create(
model=modele,
messages=[{"role": "user", "content": prompt}],
extra_headers={"HTTP-Referer": "https://aethas38.duckdns.org", "X-Title": "Aethas38 Multi-IA"},
extra_body=extra_body_data,
timeout=90.0
)
contenu = res.choices[0].message.content
if contenu:
reponses.append({"modele": modele, "texte": contenu})
except Exception as e:
log_event("WARNING", "OPENROUTER_MULTI", f"Échec rapide pour {modele} : {e}")
continue
return reponses