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Runtime error
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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
code:str
host:str
class Query2(BaseModel):
text: str
code:str
filename:str
host:str
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"
# @app.post("/code")
# async def get_code(request: Request):
# data = await request.form()
# code = data.get("code")
# global audio_space
# print("code ="+code)
# audio_space= audio_space+code
import threading
@app.post("/")
async def get_answer(q: Query ):
text = q.text
code= q.code
host= q.host
N = 20
res = ''.join(random.choices(string.ascii_uppercase +
string.digits, k=N))
res= res+ str(time.time())
filename= res
t = threading.Thread(target=do_ML, args=(filename,text,code,host))
t.start()
return JSONResponse({"id": filename})
return "hello"
@app.post("/error")
async def get_answer(q: Query2 ):
text = q.text
code= q.code
filename= q.filename
host= q.host
t = threading.Thread(target=do_ML, args=(filename,text,code,host))
t.start()
return JSONResponse({"id": filename})
import requests
import io
import io
from PIL import Image
import json
client = InferenceClient()
# client = InferenceClient(model="SG161222/Realistic_Vision_V1.4")
def do_ML(filename:str,text:str,code:str,host:str):
try:
global client
imagei = client.text_to_image(text)
byte_array = io.BytesIO()
imagei.save(byte_array, format='JPEG')
image_bytes = byte_array.getvalue()
files = {'file': image_bytes}
global audio_space
url = audio_space+code
data = {"filename": filename}
response = requests.post(url, files=files,data= data)
print(response.text)
if response.status_code == 200:
print("File uploaded successfully.")
# Handle the response as needed
else:
print("File upload failed.")
except:
data={"text":text,"filename":filename}
requests.post(host+"texttoimage2handleerror",data=data)
@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})
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