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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())
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