from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from pydantic import BaseModel
from fastapi.responses import JSONResponse
import requests
import json


class Text(BaseModel):
    content: str = ""


app = FastAPI()

headers = {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer ' + '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'
}


@app.get("/")
def home():
    html_content = open('index.html').read()
    return HTMLResponse(content=html_content, status_code=200)


@app.post("/qa_maker")
def sentiment_analysis_ep(content: Text = None):
    url = 'https://api.openai.com/v1/chat/completions'
    prompt = '根据下面的文章，生成的“问题和回答”QA对，大于5个，以一行一个json格式（{“question”:"xxx","answer":"xxx"}）生成：\n'
    print("content = \n", prompt + content.content)
    messages = [{"role": "user", "content": prompt + content.content}]
    data = {
        "model": "gpt-3.5-turbo",
        "messages": messages
    }
    result = requests.post(url=url,
                           data=json.dumps(data),
                           headers=headers
                           )
    res = str(result.json()['choices'][0]['message']['content']).strip()
    print('res:', res)
    res = {'content': res}
    return JSONResponse(content=res)


@app.post("/embeddings")
def embeddings(content: Text = None):
    url = 'https://api.openai.com/v1/embeddings'
    data = {
        "model": "text-embedding-ada-002",
        "input": content.content
    }
    result = requests.post(url=url,
                           data=json.dumps(data),
                           headers=headers
                           )
    return JSONResponse(content=result.json())