Update app.py

app.py

@@ -2,18 +2,19 @@ import gradio as gr
 import pandas as pd
 import lightgbm as lgb
 import numpy as np
-import google.generativeai as genai
+import os
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
+import speech_recognition as sr
+from pydub import AudioSegment
+import google.generativeai as genai
 
 # ---------------------------
-# HARDCODED GEMINI API KEY
+# CONFIGURE GEMINI API
 # ---------------------------
-GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"  # Replace with your actual Gemini API key
+GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"  # 🔐 Keep this secure
 genai.configure(api_key=GOOGLE_API_KEY)
-
-# Load Gemini model
-gemini_model = genai.GenerativeModel(model_name="models/gemini-1.5-pro")
+gemini_model = genai.GenerativeModel("models/gemini-1.5-pro")
 
 # ---------------------------
 # CROP RECOMMENDATION SETUP
@@ -37,7 +38,25 @@ def predict_crop(N, P, K, temperature, humidity, ph, rainfall):
     return f"🌾 Recommended Crop: *{crop_name}*"
 
 # ---------------------------
-# CHATBOT FUNCTION (GEMINI ONLY)
+# VOICE TO TEXT FUNCTION
+# ---------------------------
+def voice_to_text(audio_path):
+    recognizer = sr.Recognizer()
+    audio = AudioSegment.from_file(audio_path)
+    audio.export("converted.wav", format="wav")
+
+    with sr.AudioFile("converted.wav") as source:
+        audio_data = recognizer.record(source)
+        try:
+            text = recognizer.recognize_google(audio_data, language="pa-IN")  # Punjabi
+            return text
+        except sr.UnknownValueError:
+            return "❌ Unable to understand the audio."
+        except sr.RequestError as e:
+            return f"❌ Request Error: {e}"
+
+# ---------------------------
+# GEMINI CHATBOT FUNCTION
 # ---------------------------
 def chat_with_gemini(prompt):
     try:
@@ -46,6 +65,13 @@ def chat_with_gemini(prompt):
     except Exception as e:
         return f"❌ Error from Gemini: {str(e)}"
 
+def handle_query(text_input, audio_file, model_choice):
+    if not text_input and audio_file:
+        text_input = voice_to_text(audio_file)
+    if not text_input:
+        return "❗ Please speak or type your question."
+    return chat_with_gemini(text_input)
+
 # ---------------------------
 # GRADIO APP UI
 # ---------------------------
@@ -74,20 +100,30 @@ with gr.Blocks() as demo:
                 outputs=output_crop
             )
 
-        # TAB 2: CROP DISEASE PREDICTION (Placeholder)
+        # TAB 2: CROP DISEASE (Placeholder)
         with gr.TabItem("🌿 Crop Disease Detection"):
             gr.Markdown("### Upload an image of a crop leaf to detect disease (Coming Soon)")
             gr.Image(label="Upload Crop Image", type="filepath")
             gr.Button("Predict Disease (Coming Soon)")
             gr.Textbox(label="Prediction Output", placeholder="Model response will appear here...")
 
-        # TAB 3: SMART CHATBOT (Gemini Only)
+        # TAB 3: SMART CHATBOT
         with gr.TabItem("💬 Farmer's Chatbot"):
-            gr.Markdown("### Ask any question related to farming 👨‍🌾")
-            user_input = gr.Textbox(label="Your Question")
+            gr.Markdown("### Ask your question in Punjabi by text or voice 🎙️")
+
+            with gr.Row():
+                user_input = gr.Textbox(label="Type Your Question")
+                audio_input = gr.Audio(source="microphone", type="filepath", label="🎤 Speak Your Question")
+            
+            model_selector = gr.Dropdown(["Gemini"], value="Gemini", label="Select Model (Only Gemini Supported)")
             chatbot_output = gr.Textbox(label="AgroVision Bot Response")
-            chatbot_btn = gr.Button("Ask Gemini")
-            chatbot_btn.click(fn=chat_with_gemini, inputs=user_input, outputs=chatbot_output)
+            chatbot_btn = gr.Button("Ask")
+
+            chatbot_btn.click(
+                fn=handle_query,
+                inputs=[user_input, audio_input, model_selector],
+                outputs=chatbot_output
+            )
 
-# Run the app
+# Launch the app
 demo.launch()