Update app.py

app.py

@@ -1,64 +1,93 @@
-import streamlit as st
+import os
+import gradio as gr
+import whisper
+from gtts import gTTS
+import io
 import requests
 from groq import Groq
+import time
 
-# Set up API keys and URLs
-# Use your OpenWeatherMap API key
-openweather_api_key = "aa4db8152e46c2f3fb19fad5d58a0ed8ddssd"
-openweather_api_url = "https://api.openweathermap.org/data/2.5/weather"
+# 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"
 
-# Set up Groq API
-groq_api_key = "gsk_loI5Z6fHhtPZo25YmryjWGdyb3FYdfrw1oxGVCfZkwXRE79BAgHCO7c"
-client = Groq(api_key=groq_api_key)
+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.")
 
-# Streamlit UI
-st.title("Real-time Weather App")
+# Initialize the Groq client
+client = Groq(api_key=GROQ_API_KEY)
 
-# City input
-city = st.text_input("Enter city name")
+# Load the Whisper model
+model = whisper.load_model("base") # Ensure this model supports Urdu; otherwise, choose a suitable model
 
-# Weather data display
-if city:
- # OpenWeatherMap API request
- params = {
- "q": city,
- "appid": openweather_api_key,
- "units": "metric" # For temperature in Celsius; use "imperial" for Fahrenheit
- }
- 
+def fetch_weather():
  try:
- response = requests.get(openweather_api_url, params=params)
- response.raise_for_status() # Will raise an HTTPError for bad responses
-
+ 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)
 
- if weather_data.get("cod") != 200:
- st.write(f"Error fetching weather data: {weather_data.get('message', 'Unknown error')}")
+ # 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:
- # Display weather data
- st.write("Current Weather:")
- st.write(f"City: {weather_data['name']}, {weather_data['sys']['country']}")
- st.write(f"Temperature: {weather_data['main']['temp']}°C")
- st.write(f"Weather: {weather_data['weather'][0]['description'].capitalize()}")
- st.write(f"Humidity: {weather_data['main']['humidity']}%")
- st.write(f"Wind Speed: {weather_data['wind']['speed']} m/s")
- 
- except requests.exceptions.RequestException as e:
- st.write(f"Error fetching weather data: {e}")
+ # 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
+)
 
- # Remove Groq API request and response handling
- # try:
- # chat_completion = client.chat.completions.create(
- # messages=[
- # {
- # "role": "user",
- # "content": "Explain the importance of fast language models",
- # }
- # ],
- # model="llama3-8b-8192",
- # )
- # st.write("Groq AI Response:")
- # st.write(chat_completion.choices[0].message.content)
- 
- # except Exception as e:
- # st.write(f"Error fetching Groq data: {e}")
+iface.launch()