Update app.py

app.py

@@ -1,64 +1,55 @@
 import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
+import openai
 
-# Load the chatbot model
-@st.cache_resource
-def load_model():
-    model_name = "microsoft/DialoGPT-medium"  # Conversational model
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    model = AutoModelForCausalLM.from_pretrained(model_name)
-    return tokenizer, model
+# Set your OpenAI API key
+openai.api_key = "YOUR_OPENAI_API_KEY"  # Replace with your OpenAI API key
 
-# Initialize model and tokenizer
-tokenizer, model = load_model()
-
-# Session state for chat history
+# Initialize chat history
 if "chat_history" not in st.session_state:
-    st.session_state["chat_history"] = []
+    st.session_state["chat_history"] = [
+        {"role": "system", "content": "You are a friendly and knowledgeable assistant. Answer questions accurately and helpfully. Always reply directly and avoid vague or unclear responses."}
+    ]
 
 # 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! 😊")
+st.markdown("Hi! I'm **GM Chatbot**, your friendly assistant. Ask me anything! 😊")
 
 # User input
-user_input = st.text_input("Your Message:", placeholder="Ask me anything or just say hello!")
+user_input = st.text_input("Your Message:", placeholder="Type your question or start a conversation...")
 
-# Chatbot Response Logic
 if user_input:
     # Add user input to chat history
-    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")
-    
-    # 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"]:
-        if message.startswith("GM Chatbot"):
-            st.write(f"🤖 {message}")
-        else:
-            st.write(f"🙂 {message}")
+    st.session_state["chat_history"].append({"role": "user", "content": user_input})
+
+    # Generate response from OpenAI GPT
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4",  # Use "gpt-3.5-turbo" if GPT-4 is unavailable
+            messages=st.session_state["chat_history"],
+            temperature=0.7,
+            max_tokens=150
+        )
+        bot_reply = response['choices'][0]['message']['content']
+        
+        # Add bot reply to chat history
+        st.session_state["chat_history"].append({"role": "assistant", "content": bot_reply})
+
+        # Display chat history
+        for message in st.session_state["chat_history"]:
+            if message["role"] == "assistant":
+                st.write(f"🤖 GM Chatbot: {message['content']}")
+            elif message["role"] == "user":
+                st.write(f"🙂 You: {message['content']}")
+    except Exception as e:
+        st.error(f"Something went wrong: {e}")
 
 # Reset Chat Button
 if st.button("Reset Chat"):
-    st.session_state["chat_history"] = []
+    st.session_state["chat_history"] = [
+        {"role": "system", "content": "You are a friendly and knowledgeable assistant. Answer questions accurately and helpfully. Always reply directly and avoid vague or unclear responses."}
+    ]
     st.write("Chat reset! Let's start fresh. 😊")
 
 # Footer
 st.markdown("---")
-st.caption("Powered by Hugging Face and Streamlit")
+st.caption("Powered by OpenAI GPT and Streamlit")