google_ai_studio/analyze_video.py

import uvicorn
from fastapi import FastAPI
from pydantic import BaseModel
from loguru import logger
from google_ai.generativeai_video import main

app = FastAPI()


class VideoRequest(BaseModel):
    api_key: str
    video_path: str
    prompt: str
    mark: str
    sample_data: str


@app.post("/process_video/")
async def process_video(request: VideoRequest):
    """处理视频请求"""
    api_key = request.api_key
    video_path = request.video_path
    prompt = request.prompt
    mark = request.mark
    sample_data = request.sample_data
    try:
        logger.info(f"来一个请求，使用 API key: {api_key}")
        result = await main(video_path, api_key, prompt, sample_data)
        return {
            "code": 0,
            "message": "视频处理成功",
            "result": result,
            "mark": str(mark)
        }
    except Exception as e:
        logger.error(f"处理失败: {str(e)}")
        return {
            "code": 1,
            "message": f"处理失败: {e}",
            "result": f"处理失败: {e}",
            "mark": f"处理失败: {e}"
        }


if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8080)