Update app.py

app.py

@@ -2,22 +2,18 @@ import gradio as gr
 import pandas as pd
 import lightgbm as lgb
 import numpy as np
-import os
+import google.generativeai as genai
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
-from transformers import pipeline, Conversation, set_seed
-from dotenv import load_dotenv
-import google.generativeai as genai
 
 # ---------------------------
-# Load environment variables
+# HARDCODED GEMINI API KEY
 # ---------------------------
-# load_dotenv()
-GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"
-
-# Configure Gemini API
+GOOGLE_API_KEY = "AIzaSyAju28ijKpMNxr1kh4Ml5GPNmI7reBN7FE"  # Replace with your actual Gemini API key
 genai.configure(api_key=GOOGLE_API_KEY)
-gemini_model = genai.GenerativeModel("gemini-pro")
+
+# Load Gemini model
+gemini_model = genai.GenerativeModel(model_name="models/gemini-pro")
 
 # ---------------------------
 # CROP RECOMMENDATION SETUP
@@ -41,16 +37,8 @@ def predict_crop(N, P, K, temperature, humidity, ph, rainfall):
     return f"🌾 Recommended Crop: *{crop_name}*"
 
 # ---------------------------
-# CHATBOT SETUP
+# CHATBOT FUNCTION (GEMINI ONLY)
 # ---------------------------
-chatbot = pipeline("conversational", model="microsoft/DialoGPT-medium")
-set_seed(42)
-
-def chat_with_bot(user_input):
-    conversation = Conversation(user_input)
-    conversation = chatbot(conversation)
-    return conversation.generated_responses[-1]
-
 def chat_with_gemini(prompt):
     try:
         response = gemini_model.generate_content(prompt)
@@ -58,12 +46,6 @@ def chat_with_gemini(prompt):
     except Exception as e:
         return f"❌ Error from Gemini: {str(e)}"
 
-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
 # ---------------------------
@@ -99,16 +81,13 @@ with gr.Blocks() as demo:
             gr.Button("Predict Disease (Coming Soon)")
             gr.Textbox(label="Prediction Output", placeholder="Model response will appear here...")
 
-        # TAB 3: SMART CHATBOT
+        # TAB 3: SMART CHATBOT (Gemini Only)
         with gr.TabItem("💬 Farmer's Chatbot"):
             gr.Markdown("### Ask any question related to farming 👨‍🌾")
-
-            with gr.Row():
-                user_input = gr.Textbox(label="Your Question")
-                model_selector = gr.Dropdown(["Gemini", "DialoGPT"], value="Gemini", label="Select Model")
+            user_input = gr.Textbox(label="Your Question")
             chatbot_output = gr.Textbox(label="AgroVision Bot Response")
-            chatbot_btn = gr.Button("Ask")
-            chatbot_btn.click(fn=smart_chat, inputs=[user_input, model_selector], outputs=chatbot_output)
+            chatbot_btn = gr.Button("Ask Gemini")
+            chatbot_btn.click(fn=chat_with_gemini, inputs=user_input, outputs=chatbot_output)
 
-# Launch the app
+# Run the app
 demo.launch()