mo-daq-all/mo-daq-openai/web/route.py

import os
from pathlib import Path

from fastapi import FastAPI, File, UploadFile
from openai import OpenAI

app = FastAPI()

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您没有配置环境变量，请在此处替换您的API-KEY
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填写DashScope服务base_url
)


DEFAULT_USER_MSG = f"""解析文件中的表格内容：要求准确识别金额等小数的位数，去掉金额单位、英文和多余的空格，结果用字典返回；
                   检查所有字段是否完整，确保没有遗漏或错误，可能需要多次校对，以确保生成的字典准确无误。"""


@app.get("/upload-filepath")
async def create_upload_file(filepath: str = None,
                             file_id: str = None,
                             user_msg: str = DEFAULT_USER_MSG):
    # 读取文件内容（可选）
    # contents = await file.read()

    # 这里可以对文件进行进一步处理，比如保存到服务器上
    # with open(f"./{file.filename}", "wb") as f:
    #     f.write(contents)

    if file_id is None:
        file_object = client.files.create(file=Path(filepath), purpose="file-extract")
        file_id = file_object.id

    # 初始化messages列表
    completion = client.chat.completions.create(
        model="qwen-long",
        temperature=0.1,
        presence_penalty=1,
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            {'role': 'system', 'content': f'fileid://{file_id}'},
            {'role': 'user', 'content': user_msg}
        ],
    )

    return {"file_id": file_id, "content": completion.choices[0].message.content}


@app.post("/upload-file")
async def create_upload_file(file: UploadFile = File(...),
                             file_id: str = None,
                             user_msg: str = DEFAULT_USER_MSG):
    if file_id is None:
        # 读取文件内容（可选）
        contents = await file.read()

        # 这里可以对文件进行进一步处理，比如保存到服务器上
        with open(f"./uploads/{file.filename}", "wb") as f:
            f.write(contents)

        file_object = client.files.create(file=Path(f"./uploads/{file.filename}"), purpose="file-extract")
        file_id = file_object.id

    # 初始化messages列表
    completion = client.chat.completions.create(
        model="qwen-long",
        temperature=0.1,
        presence_penalty=1,
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            {'role': 'system', 'content': f'fileid://{file_id}'},
            {'role': 'user', 'content': user_msg}
        ],
    )

    return {"file_id": file_id, "content": completion.choices[0].message.content}