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| import os | |
| from huggingface_hub import hf_hub_download, login | |
| from llama_cpp import Llama | |
| from fastapi import FastAPI | |
| import uvicorn | |
| import time | |
| from concurrent.futures import ThreadPoolExecutor | |
| # === Авторизация === | |
| token = os.getenv("TOKEN_FACE_GRAINED") | |
| if token: | |
| login(token=token) | |
| # === Загрузка модели === | |
| print("Скачивание модели...") | |
| model_path = hf_hub_download( | |
| repo_id="Sanya2025/Proxima_B-instruct-Q5_0-GGUF", | |
| filename="proxima_b-instruct-q5_0.gguf", | |
| token=token, | |
| local_dir="/tmp/model", | |
| local_dir_use_symlinks=False | |
| ) | |
| print(f"Модель: {model_path}") | |
| print("Инициализация llama.cpp...") | |
| llm = Llama( | |
| model_path=model_path, | |
| n_ctx=4096, | |
| n_threads=4, | |
| verbose=False | |
| ) | |
| print("Модель готова!") | |
| # === ThreadPool для неблокирующей генерации === | |
| executor = ThreadPoolExecutor(max_workers=1) | |
| app = FastAPI() | |
| def health(): | |
| return {"status": "ok", "model": "proxima-b-instruct-q5_0"} | |
| # !!! СИНХРОННЫЙ endpoint (не async) !!! | |
| def chat(request: dict): | |
| print(f"[{time.strftime('%H:%M:%S')}] Запрос: {str(request)[:200]}") | |
| messages = request.get("messages", []) | |
| max_tokens = request.get("max_tokens", 128) | |
| print(f"Генерация начата (max_tokens={max_tokens})...") | |
| start = time.time() | |
| try: | |
| response = llm.create_chat_completion( | |
| messages=messages, | |
| max_tokens=max_tokens, | |
| temperature=request.get("temperature", 0.7), | |
| stop=request.get("stop", []), | |
| stream=False | |
| ) | |
| print(f"Генерация завершена за {time.time()-start:.1f} сек") | |
| return response | |
| except Exception as e: | |
| print(f"ОШИБКА генерации: {e}") | |
| return {"error": str(e)} | |
| if __name__ == "__main__": | |
| uvicorn.run(app, host="0.0.0.0", port=7860) |