import os
import time
import json
import random
#import requests
#from gevent import pywsgi
import g4f
from fastapi import FastAPI, Request, Response
from fastapi.responses import JSONResponse, StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
import logging
import uvicorn

from g4f import ChatCompletion
#from contextlib import closing

# Importa el módulo nest_asyncio
import nest_asyncio
g4f.debug.logging = True

nest_asyncio.apply()

app = FastAPI()
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)
LOG = logging.getLogger(__name__)

@app.post("/chat/completions")
@app.post("/v1/chat/completions")
@app.post("/")
async def chat_completions(request: Request):
    data = await request.json()
    streaming = data.get('stream', False)
    model = data.get('model', 'gpt-4-32k')
    messages = data.get('messages')

    response = ChatCompletion.create(model=model, stream=streaming,
                                     messages=messages, provider=g4f.Provider.Bing)

    if not streaming:
        while 'curl_cffi.requests.errors.RequestsError' in response:
            response = ChatCompletion.create(model=model, stream=streaming,
                                             messages=messages, provider=g4f.Provider.Bing)

        completion_timestamp = int(time.time())
        completion_id = ''.join(random.choices(
            'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789', k=28))

        return JSONResponse({
            'id': 'chatcmpl-%s' % completion_id,
            'object': 'chat.completion',
            'created': completion_timestamp,
            'model': model,
            'usage': {
                'prompt_tokens': 0,
                'completion_tokens': 0,
                'total_tokens': 0
            },
            'choices': [{
                'message': {
                    'role': 'assistant',
                    'content': response
                },
                'finish_reason': 'stop',
                'index': 0
            }]
        })

    def stream():
        completion_data = {
            'id': '',
            'object': 'chat.completion.chunk',
            'created': 0,
            'model': 'gpt-4-32k',
            'choices': [
                {
                    'delta': {
                        'content': ""
                    },
                    'index': 0,
                    'finish_reason': None
                }
            ]
        }

        for token in response:
            completion_id = ''.join(
                random.choices('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789', k=28))
            completion_timestamp = int(time.time())
            completion_data['id'] = f'chatcmpl-{completion_id}'
            completion_data['created'] = completion_timestamp
            completion_data['choices'][0]['delta']['content'] = token
            if token.startswith("an error occured"):
                completion_data['choices'][0]['delta']['content'] = "Server Response Error, please try again.\n"
                completion_data['choices'][0]['delta']['stop'] = "error"
                yield 'data: %s\n\ndata: [DONE]\n\n' % json.dumps(completion_data, separators=(',' ':'))
                return
            yield 'data: %s\n\n' % json.dumps(completion_data, separators=(',' ':'))
            time.sleep(0)

        completion_data['choices'][0]['finish_reason'] = "stop"
        completion_data['choices'][0]['delta']['content'] = ""
        yield 'data: %s\n\n' % json.dumps(completion_data, separators=(',' ':'))
        yield 'data: [DONE]\n\n'

    return StreamingResponse(stream(), media_type='text/event-stream')



# if __name__ == '__main__':
#     uvicorn.run("app:app", host=site_config['host'], port=site_config['port'])