Update app.py

app.py

@@ -5,14 +5,16 @@ import numpy as np
 import os
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
-import speech_recognition as sr
-from pydub import AudioSegment
+from transformers import pipeline, set_seed
 import google.generativeai as genai
 
 # ---------------------------
-# CONFIGURE GEMINI API
+# Load environment variables
 # ---------------------------
-GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"  # 🔐 Keep this secure
+GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"
+  # Add your actual API key here
+
+# Configure Gemini API
 genai.configure(api_key=GOOGLE_API_KEY)
 gemini_model = genai.GenerativeModel("models/gemini-1.5-pro")
 
@@ -38,26 +40,15 @@ def predict_crop(N, P, K, temperature, humidity, ph, rainfall):
     return f"🌾 Recommended Crop: *{crop_name}*"
 
 # ---------------------------
-# VOICE TO TEXT FUNCTION
+# CHATBOT SETUP
 # ---------------------------
-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}"
+chatbot = pipeline("conversational", model="microsoft/DialoGPT-medium")
+set_seed(42)
+
+def chat_with_bot(user_input):
+    conversation = chatbot(user_input)
+    return conversation[0]['generated_text']
 
-# ---------------------------
-# GEMINI CHATBOT FUNCTION
-# ---------------------------
 def chat_with_gemini(prompt):
     try:
         response = gemini_model.generate_content(prompt)
@@ -65,12 +56,11 @@ 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)
+def smart_chat(user_input, model_choice):
+    if model_choice == "Gemini":
+        return chat_with_gemini(user_input)
+    else:
+        return chat_with_bot(user_input)
 
 # ---------------------------
 # GRADIO APP UI
@@ -100,7 +90,7 @@ with gr.Blocks() as demo:
                 outputs=output_crop
             )
 
-        # TAB 2: CROP DISEASE (Placeholder)
+        # TAB 2: CROP DISEASE PREDICTION (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")
@@ -109,21 +99,19 @@ with gr.Blocks() as demo:
 
         # TAB 3: SMART CHATBOT
         with gr.TabItem("💬 Farmer's Chatbot"):
-            gr.Markdown("### Ask your question in Punjabi by text or voice 🎙️")
+            gr.Markdown("### Ask any question related to farming 👨‍🌾")
 
             with gr.Row():
-                user_input = gr.Textbox(label="Type Your Question")
-                audio_input = gr.Audio(source="microphone", type="filepath", label="🎤 Speak Your Question")
+                user_input = gr.Textbox(label="Your Question")
+                model_selector = gr.Dropdown(["Gemini", "DialoGPT"], value="Gemini", label="Select Model")
+
+            # Audio input from microphone
+            audio_input = gr.Audio(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")
 
-            chatbot_btn.click(
-                fn=handle_query,
-                inputs=[user_input, audio_input, model_selector],
-                outputs=chatbot_output
-            )
+            chatbot_btn.click(fn=smart_chat, inputs=[user_input, model_selector], outputs=chatbot_output)
 
 # Launch the app
 demo.launch()