Update app.py

app.py

@@ -1,61 +1,64 @@
 import streamlit as st
 from transformers import AutoModelForCausalLM, AutoTokenizer
-from serpapi import GoogleSearch
+import torch
 
 # Load the chatbot model
 @st.cache_resource
 def load_model():
-    model_name = "microsoft/DialoGPT-medium"
+    model_name = "microsoft/DialoGPT-medium"  # Conversational model
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForCausalLM.from_pretrained(model_name)
     return tokenizer, model
 
+# Initialize model and tokenizer
 tokenizer, model = load_model()
 
-# SerpAPI Setup
-def google_search(query):
-    params = {
-        "q": query,
-        "api_key": "YOUR_SERPAPI_KEY",  # Replace with your SerpAPI key
-    }
-    search = GoogleSearch(params)
-    results = search.get_dict()
-    return results.get("organic_results", [])
-
-# Chat history
+# Session state for chat history
 if "chat_history" not in st.session_state:
     st.session_state["chat_history"] = []
 
-# Streamlit UI
-st.title("🤖 Friendly Chatbot with Google Search")
-st.write("Hi! I'm here to chat with you and fetch Google results if needed. 😊")
+# Streamlit App Layout
+st.title("🤗 GM Chatbot")
+st.markdown("Hi there! I'm **GM Chatbot**. I can answer your questions, chat with you, and keep the conversation friendly! 😊")
 
-user_input = st.text_input("You:", placeholder="Type your message here...")
+# User input
+user_input = st.text_input("Your Message:", placeholder="Ask me anything or just say hello!")
 
+# Chatbot Response Logic
 if user_input:
     # Add user input to chat history
-    st.session_state["chat_history"].append(f"User: {user_input}")
-    
-    if "search" in user_input.lower():
-        # Fetch Google Search results
-        search_results = google_search(user_input)
-        if search_results:
-            bot_reply = f"Here are the top Google results for your query:\n\n"
-            for idx, result in enumerate(search_results[:5], 1):
-                bot_reply += f"{idx}. [{result['title']}]({result['link']})\n"
-        else:
-            bot_reply = "Sorry, I couldn't find anything for your query."
-    else:
-        # Generate chatbot response
-        inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt")
-        response = model.generate(inputs, max_length=500, pad_token_id=tokenizer.eos_token_id)
-        bot_reply = tokenizer.decode(response[:, inputs.shape[-1]:][0], skip_special_tokens=True)
+    st.session_state["chat_history"].append(f"You: {user_input}")
+
+    # Prepare input for the model
+    chat_history_str = "\n".join(st.session_state["chat_history"])
+    inputs = tokenizer.encode(chat_history_str + tokenizer.eos_token, return_tensors="pt")
     
-    st.session_state["chat_history"].append(f"Bot: {bot_reply}")
+    # Generate chatbot response
+    response = model.generate(
+        inputs,
+        max_length=100,
+        pad_token_id=tokenizer.eos_token_id,
+        temperature=0.7,
+        top_p=0.9,
+        do_sample=True
+    )
+    bot_reply = tokenizer.decode(response[:, inputs.shape[-1]:][0], skip_special_tokens=True)
+
+    # Add bot reply to chat history
+    st.session_state["chat_history"].append(f"GM Chatbot: {bot_reply}")
+
+    # Display chat history
     for message in st.session_state["chat_history"]:
-        st.write(message)
+        if message.startswith("GM Chatbot"):
+            st.write(f"🤖 {message}")
+        else:
+            st.write(f"🙂 {message}")
 
-# Reset button
+# Reset Chat Button
 if st.button("Reset Chat"):
     st.session_state["chat_history"] = []
     st.write("Chat reset! Let's start fresh. 😊")
+
+# Footer
+st.markdown("---")
+st.caption("Powered by Hugging Face and Streamlit")