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from fastapi import FastAPI, HTTPException,UploadFile,File
from pydantic import BaseModel
from deep_translator import GoogleTranslator
from fastapi.responses import JSONResponse
import os
from main import process,audio_process
from dotenv import load_dotenv
load_dotenv()
# Create the FastAPI app instance
os.makedirs("/tmp/huggingface_cache", exist_ok=True)
os.environ["HF_HOME"] = "/tmp/huggingface_cache"
app = FastAPI()
# Root endpoint
@app.get("/")
async def home():
return {"message": "Testing_api"}
import os
from fastapi import FastAPI, HTTPException, UploadFile, File
from deep_translator import GoogleTranslator
app = FastAPI()
# Token verification function
def verify_token(token: str):
if token != os.getenv("TOKEN"):
raise HTTPException(status_code=401, detail="Token not matched")
# Translate endpoint that accepts a query parameter 'text'
@app.get("/translate")
async def translate(text: str = "", token: str = ""):
if not text or not token:
raise HTTPException(status_code=400, detail="No text or token provided")
verify_token(token)
translator = GoogleTranslator(source="auto", target="mr")
result = translator.translate(text)
return {"result": result}
@app.get("/chatbot")
async def chatbot(text: str = "", token: str = ""):
if not text or not token:
raise HTTPException(status_code=400, detail="No text provided")
verify_token(token)
result = process(user_query=text)
return {"result": result}
@app.post("/audio_chat")
async def audio_chat(audio: UploadFile = File(...), token: str = ""):
if not audio or not token:
raise HTTPException(status_code=400, detail="No audio file provided")
verify_token(token)
try:
result = audio_process(audio.file) # Replace with actual audio processing logic
return {"result": result}
except Exception as e:
raise HTTPException(status_code=500, detail=f"An error occurred: {str(e)}")
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