Public Access
100 lines
4.4 KiB
Python
100 lines
4.4 KiB
Python
import os
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import requests
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import time
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import concurrent.futures
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import base64
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from modules.logger import log_event
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def generer_image_cloudflare(prompt: str) -> bytes:
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"""Appel à l'API Cloudflare Workers AI avec décodage Base64"""
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account_id = os.getenv("CLOUDFLARE_ACCOUNT_ID")
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api_token = os.getenv("CLOUDFLARE_API_TOKEN")
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if not account_id or not api_token: return None
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url = f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/@cf/stabilityai/stable-diffusion-xl-base-1.0"
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headers = {"Authorization": f"Bearer {api_token}"}
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try:
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resp = requests.post(url, headers=headers, json={"prompt": prompt}, timeout=120)
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if resp.status_code == 200:
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if "application/json" in resp.headers.get("Content-Type", ""):
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data = resp.json()
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if data.get("success") and "result" in data:
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return base64.b64decode(data["result"])
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else:
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return resp.content
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except Exception as e:
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log_event("WARNING", "MEDIA", f"Échec Cloudflare : {e}")
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return None
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def generer_image_huggingface(prompt: str) -> bytes:
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"""Appel à l'API HuggingFace"""
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api_key = os.getenv("HUGGINGFACE_API_KEY")
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if not api_key: return None
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url = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
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headers = {"Authorization": f"Bearer {api_key}"}
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try:
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resp = requests.post(url, headers=headers, json={"inputs": prompt}, timeout=120)
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if resp.status_code == 200: return resp.content
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except Exception as e:
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log_event("WARNING", "MEDIA", f"Échec HF : {e}")
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return None
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def generer_les_deux_images(prompt: str, fichiers: list) -> tuple:
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trace = []
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if fichiers:
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trace.append("🟢 Mode Image-to-Image (Désactivé en multi-fournisseur)")
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return f"*(BETA)* Le mode Image-to-Image nécessite une API spécifique. \n\nFichiers : {', '.join(fichiers)}", "#ff9800", "Système", "En dev", trace
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trace.append("🟢 Lancement Text-to-Image (HuggingFace + Cloudflare)")
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# Exécution des deux API en parallèle pour gagner du temps
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with concurrent.futures.ThreadPoolExecutor() as executor:
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future_hf = executor.submit(generer_image_huggingface, prompt)
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future_cf = executor.submit(generer_image_cloudflare, prompt)
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img_hf = future_hf.result()
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img_cf = future_cf.result()
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dossier_media = "/DATA/AppData/MULTI-IA-AETHAS38/RAG/Media"
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os.makedirs(dossier_media, exist_ok=True)
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reponse_md = f"**Prompt analysé :** {prompt}\n\n"
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fournisseurs_actifs = []
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# Traitement Cloudflare
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if img_cf:
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nom_cf = f"img_cf_{int(time.time())}.png"
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with open(os.path.join(dossier_media, nom_cf), 'wb') as f: f.write(img_cf)
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reponse_md += f"### ☁️ Cloudflare Workers AI (SDXL)\n\n\n"
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reponse_md += f"**[📥 Cliquez ici pour télécharger l'image](/Media/{nom_cf})**\n\n---\n\n"
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fournisseurs_actifs.append("Cloudflare")
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trace.append("🟢 Cloudflare : Succès")
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else:
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trace.append("🔴 Cloudflare : Échec")
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# Traitement HuggingFace
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if img_hf:
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nom_hf = f"img_hf_{int(time.time())}.png"
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with open(os.path.join(dossier_media, nom_hf), 'wb') as f: f.write(img_hf)
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reponse_md += f"### 🤗 HuggingFace (SDXL)\n\n\n"
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reponse_md += f"**[📥 Cliquez ici pour télécharger l'image](/Media/{nom_hf})**\n\n"
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fournisseurs_actifs.append("HuggingFace")
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trace.append("🟢 HF : Succès")
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else:
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trace.append("🔴 HF : Échec")
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# Si les deux ont échoué
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if not img_hf and not img_cf:
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return "*Échec critique : HuggingFace et Cloudflare ont échoué.*", "#ff4444", "Système", "Erreur", trace
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return reponse_md, "#00e5ff", " + ".join(fournisseurs_actifs), "Stable Diffusion XL", trace
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def router_media(prompt: str, type_media: str, premium: bool, fichiers: list) -> tuple:
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trace = [f"🟢 Routage Média : {type_media.upper()}"]
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if type_media == "image":
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return generer_les_deux_images(prompt, fichiers)
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elif type_media == "video":
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return "*La génération vidéo nécessite une API payante (Luma, Kling).* \n\nPrompt : " + prompt, "#ff4444", "Système", "En attente API", trace
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return "Type de média non reconnu.", "#333", "Erreur", "Aucun", trace |