import io
from fastapi import FastAPI, File, UploadFile
import subprocess
import os
import requests
import random
from datetime import datetime
from datetime import date
import json
from pydantic import BaseModel
from typing import Annotated
import random
from fastapi import FastAPI, Response
import string
import time
from huggingface_hub import InferenceClient

from fastapi import Form

class Query(BaseModel):
    text: str
    
    
class Query2(BaseModel):
    text: str
  
   
class QueryM(BaseModel):
    text: str
    tokens:int
    temp:float
    topp:float
    topk:float



from fastapi import FastAPI, Request, Depends, UploadFile, File
from fastapi.exceptions import HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse


app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=['*'],
    allow_credentials=True,
    allow_methods=['*'],
    allow_headers=['*'],
)


# cred = credentials.Certificate('key.json')
# app1 = firebase_admin.initialize_app(cred)
# db = firestore.client()
# data_frame = pd.read_csv('data.csv')



@app.on_event("startup")
async def startup_event():
    print("on startup")
    # requests.get("https://audiospace-1-u9912847.deta.app/sendcode")

audio_space="https://audiospace-1-u9912847.deta.app/uphoto"

import threading
from huggingface_hub.inference_api import InferenceApi
client = InferenceClient()


@app.post("/image")
async def get_answer(q: Query ):
    text = q.text
    try:
        global client
        imagei = client.text_to_image(text)
        byte_array = io.BytesIO()
        imagei.save(byte_array, format='JPEG')
        response = Response(content=byte_array.getvalue(), media_type="image/png")
        return response
    
    except:
        return JSONResponse({"status":False})
    
    
@app.post("/mistral")
async def get_answer(q: QueryM ):
    text = q.text
    try:
        client = InferenceClient()
        generate_kwargs = dict(
        max_new_tokens= int(q.tokens),
        do_sample=True,
        top_p= q.topp,
        top_k=int(q.topk),
        temperature=q.temp,
        )
        inputs= text
        response = client.post(json={"inputs": inputs, "parameters": generate_kwargs}, model="mistralai/Mistral-7B-Instruct-v0.1")
        json_string = response.decode('utf-8')
        list_of_dicts = json.loads(json_string)
        result_dict = list_of_dicts[0]
        x=(result_dict['generated_text'])
        x=x.replace(inputs,'')
        return JSONResponse({"result":x,"status":True})    
    except Exception as e:
        print(e)
        return JSONResponse({"status":False})
    
    


@app.post("/zephyr")
async def get_answer(q: QueryM ):
    text = q.text
    try:
        client = InferenceClient()
        generate_kwargs = dict(
        max_new_tokens= int(q.tokens),
        repetition_penalty=1.0,
        top_p= q.topp,
        top_k=int(q.topk),
        temperature=q.temp,
        stop= ["</s>", "<|>"]
        )
        inputs= text
        response = client.post(json={"inputs": inputs, "parameters": generate_kwargs}, model="mistralai/Mistral-7B-Instruct-v0.1")
        json_string = response.decode('utf-8')
        list_of_dicts = json.loads(json_string)
        result_dict = list_of_dicts[0]
        x=(result_dict['generated_text'])
        x=x.replace(inputs,'')
        return JSONResponse({"result":x,"status":True})    
    except Exception as e:
        print(e)
        return JSONResponse({"status":False})


@app.post("/openchat35")
async def get_answer(q: QueryM ):
    text = q.text
    try:
        client = InferenceClient()
        generate_kwargs = dict(
        max_new_tokens= int(q.tokens),
        repetition_penalty=1.0,
        top_p= q.topp,
        top_k=int(q.topk),
        temperature=q.temp,
        stop= ["<|end_of_turn|>", "<??|>"]
        )
        inputs= text
        response = client.post(json={"inputs": inputs, "parameters": generate_kwargs},model="openchat/openchat_3.5")
        json_string = response.decode('utf-8')
        list_of_dicts = json.loads(json_string)
        result_dict = list_of_dicts[0]
        x=(result_dict['generated_text'])
        x=x.replace(inputs,'')
        return JSONResponse({"result":x,"status":True})    
    except Exception as e:
        print(e)
        return JSONResponse({"status":False})




@app.post("/image_new")
async def get_answer(q: Query ):
    text = q.text
    try:
        global client
        imagei = client.text_to_image(text, model ='openskyml/dalle-3-xl')
        byte_array = io.BytesIO()
        imagei.save(byte_array, format='JPEG')
        response = Response(content=byte_array.getvalue(), media_type="image/png")
        return response
    
    except:
        return JSONResponse({"status":False})