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from fastapi import FastAPI, HTTPException
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
import requests
import json
from typing import AsyncIterator
app = FastAPI()
# Define the request model
class ChatRequest(BaseModel):
messages: list = [{"role": "user", "content": "Lol full form"}]
model: str = "gemini-1.5-pro-latest"
temperature: float = 1.0
top_p: float = 0.8
max_tokens: int = 4000
# Define the URL and headers
url = "https://chat.typegpt.net/api/openai/v1/chat/completions"
headers = {
"Accept": "application/json, text/event-stream",
"Content-Type": "application/json",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36 Edg/130.0.0.0",
}
@app.post("/chat")
async def chat(request: ChatRequest):
# Define the payload
payload = {
"messages": request.messages,
"stream": True,
"model": request.model,
"temperature": request.temperature,
"top_p": request.top_p,
"max_tokens": request.max_tokens
}
# Make the POST request with streaming
try:
response = requests.post(url, headers=headers, data=json.dumps(payload), stream=True)
# Check if the request was successful
if response.status_code == 200:
async def event_stream() -> AsyncIterator[str]:
# Stream the response line by line
for line in response.iter_lines():
if line:
# Decode the line
decoded_line = line.decode('utf-8')
# Check if the line starts with "data: "
if decoded_line.startswith("data: "):
try:
data = json.loads(line[len('data: '):])
content = data.get("choices", [{}])[0].get("delta", {}).get("content", '')
if content:
yield f"{json.dumps({'response': content})}\n\n"
except json.JSONDecodeError:
continue
return StreamingResponse(event_stream(), media_type="text/event-stream")
else:
raise HTTPException(status_code=response.status_code, detail=response.text)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8083) |