main.py

from fastapi import FastAPI, Request
from fastapi.responses import PlainTextResponse
from pydantic import BaseModel
from typing import List, Optional, Literal
from gradio_client import Client
import uvicorn
import time
import uuid
import logging

# === Настройка логгера ===
logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
logger = logging.getLogger(__name__)

# === Задаём модель (используется глобально) ===
AI_MODEL = "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO"

# === Подключаемся к Gradio Space по URL ===
try:
    gr_client = Client("Nymbo/Serverless-TextGen-Hub")
    logger.info("✅ Успешно подключено к Gradio Space")
except Exception as e:
    logger.error(f"❌ Ошибка подключения к Gradio Client: {e}")
    gr_client = None

# === Функция вызова модели ===
def ask(user_prompt, system_prompt):
    if not gr_client:
        return "[Ошибка: Gradio Client не инициализирован]"

    try:
        result = gr_client.predict(
            history=[[user_prompt, None]],
            system_msg=system_prompt,
            max_tokens=512,
            temperature=0.7,
            top_p=0.95,
            freq_penalty=0,
            seed=-1,
            custom_model=AI_MODEL,
            search_term="",
            selected_model=AI_MODEL,
            api_name="/bot"
        )
        return result
    except Exception as e:
        logger.error(f"❌ Ошибка при вызове модели: {e}")
        return f"[Ошибка: {str(e)}]"

# === FastAPI приложение ===
app = FastAPI()

# === Модели запроса ===
class Message(BaseModel):
    role: Literal["user", "assistant", "system"]
    content: str

class ChatRequest(BaseModel):
    model: str  # Заглушка — не используется
    messages: List[Message]
    temperature: Optional[float] = 0.7
    top_p: Optional[float] = 0.95
    max_tokens: Optional[int] = 512

# === Корневой маршрут "/" ===
@app.get("/", response_class=PlainTextResponse)
async def root():
    return "Proxy free test"

# === Основной маршрут OpenAI-совместимый ===
@app.post("/v1/chat/completions")
async def chat_completion(request: Request):
    headers = dict(request.headers)
    body = await request.body()

    logger.info("📥 Запрос получен")
    logger.info(f"🔸 Заголовки: {headers}")
    logger.info(f"🔸 Тело: {body.decode('utf-8')}")

    try:
        data = await request.json()
        chat_request = ChatRequest(**data)
    except Exception as e:
        logger.error(f"❌ Ошибка разбора JSON: {e}")
        return {"error": "Некорректный JSON"}

    # Игнорируем model из запроса и используем глобальный AI_MODEL
    user_msg = next((m.content for m in reversed(chat_request.messages) if m.role == "user"), None)
    system_msg = next((m.content for m in chat_request.messages if m.role == "system"), "You are a helpful AI assistant.")

    if not user_msg:
        return {"error": "User message not found."}

    assistant_reply = ask(user_msg, system_msg)

    response = {
        "id": f"chatcmpl-{uuid.uuid4().hex[:12]}",
        "object": "chat.completion",
        "created": int(time.time()),
        "model": AI_MODEL,
        "choices": [
            {
                "index": 0,
                "message": {
                    "role": "assistant",
                    "content": assistant_reply
                },
                "finish_reason": "stop"
            }
        ],
        "usage": {
            "prompt_tokens": 0,
            "completion_tokens": 0,
            "total_tokens": 0
        }
    }

    return response

# === Запуск сервера ===
if __name__ == "__main__":
    uvicorn.run("local_openai_server:app", host="0.0.0.0", port=7860, reload=True)