app.py

import os
import gradio as gr
import whisper
from gtts import gTTS
import io
import requests
from groq import Groq
import time

# Ensure GROQ_API_KEY and OpenWeather API key are defined
GROQ_API_KEY = "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"
OPENWEATHER_API_KEY = "aa4db8152e46c2f3fb19fad5d58a0ed8"
OPENWEATHER_URL = "https://api.openweathermap.org/data/2.5/weather"

if not GROQ_API_KEY:
 raise ValueError("GROQ_API_KEY is not set in environment variables.")
if not OPENWEATHER_API_KEY:
 raise ValueError("OPENWEATHER_API_KEY is not set in environment variables.")

# Initialize the Groq client
client = Groq(api_key=GROQ_API_KEY)

# Load the Whisper model
model = whisper.load_model("base") # Ensure this model supports Urdu; otherwise, choose a suitable model

def fetch_weather():
 try:
 response = requests.get(
 OPENWEATHER_URL,
 params={
 'q': 'London', # Change to dynamic city name as needed
 'appid': OPENWEATHER_API_KEY,
 'units': 'metric'
 }
 )
 response.raise_for_status()
 weather_data = response.json()
 temp = weather_data['main']['temp']
 weather_description = weather_data['weather'][0]['description']
 return f"Current temperature is {temp}°C with {weather_description}."
 except Exception as e:
 return f"Unable to fetch weather data: {e}"

def process_audio(file_path):
 try:
 # Load the audio file
 audio = whisper.load_audio(file_path)

 # Transcribe the audio using Whisper (specify language if needed)
 result = model.transcribe(audio, language="ur") # Specify 'ur' for Urdu
 text = result["text"]

 # Check if the text contains any weather-related keywords
 weather_keywords = ['weather', 'temperature', 'climate', 'forecast']
 if any(keyword in text.lower() for keyword in weather_keywords):
 weather_info = fetch_weather()
 response_message = f"The weather update: {weather_info}"
 else:
 # Generate a response in Urdu using Groq
 chat_completion = client.chat.completions.create(
 messages=[{"role": "user", "content": text}],
 model="gemma2-9b-it", # Ensure this model can handle Urdu
 )
 # Access the response using dot notation
 response_message = chat_completion.choices[0].message.content.strip()

 # Convert the response text to Urdu speech
 tts = gTTS(response_message, lang='ur') # Specify language 'ur' for Urdu
 response_audio_io = io.BytesIO()
 tts.write_to_fp(response_audio_io) # Save the audio to the BytesIO object
 response_audio_io.seek(0)

 # Generate a unique filename
 response_audio_path = "response_" + str(int(time.time())) + ".mp3"
 
 # Save audio to a file
 with open(response_audio_path, "wb") as audio_file:
 audio_file.write(response_audio_io.getvalue())

 # Return the response text and the path to the saved audio file
 return response_message, response_audio_path

 except Exception as e:
 return f"An error occurred: {e}", None

iface = gr.Interface(
 fn=process_audio,
 inputs=gr.Audio(type="filepath"), # Use type="filepath"
 outputs=[gr.Textbox(label="Response Text (Urdu)"), gr.Audio(label="Response Audio (Urdu)")],
 live=True # Set to False if you do not need real-time updates
)

iface.launch()