Update app.py

app.py

@@ -1,52 +1,21 @@
-import os
 import streamlit as st
 from transformers import pipeline
 
-# Set the Hugging Face API key in the environment (if required)
-HUGGINGFACE_API_KEY = st.secrets["huggingface_api_key"]
-os.environ["HF_HOME"] = HUGGINGFACE_API_KEY  # Set the Hugging Face API key
+# Configure the Hugging Face API key
+HF_API_KEY = st.secrets['huggingface_api_key']
 
-# Initialize the text generation pipeline (without passing api_key)
-chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+# Initialize the Hugging Face model
+generator = pipeline('text-generation', model='gpt-2', tokenizer='gpt-2', api_key=HF_API_KEY)
 
-# Initialize the conversation history
-if "history" not in st.session_state:
-    st.session_state["history"] = []
-
-# Function to get response from the model
+# Function to get response from the Hugging Face model
 def get_chatbot_response(user_input):
     try:
-        # Prepare the conversation history for the model
-        conversation_history = ""
-        for user_input, response in st.session_state["history"][-5:]:  # Limit history to last 5 exchanges
-            conversation_history += f"User: {user_input}\nBot: {response}\n"
-        
-        # Add the current user input to the conversation
-        conversation_history += f"User: {user_input}\n"
-        
-        # Debug: Print the conversation history
-        print("Conversation History (Trimmed if Necessary):")
-        print(conversation_history)
-        
-        # Generate response from the model
-        response = chatbot(conversation_history, max_length=1000, pad_token_id=50256, num_return_sequences=1)[0]["generated_text"]
-        
-        # Debug: Print the full response generated by the model
-        print("Generated Response (Before Stripping User Input):")
-        print(response)
-        
-        # Remove the user input from the generated response (optional)
-        response = response[len(conversation_history):].strip()
-        
-        # Debug: Print the final response
-        print("Final Response (After Stripping User Input):")
-        print(response)
-        
-        return response
+        response = generator(user_input, max_length=100, num_return_sequences=1)
+        return response[0]['generated_text']
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Streamlit interface setup
+# Streamlit interface
 st.set_page_config(page_title="Smart ChatBot", layout="centered")
 
 # Custom CSS for chat bubbles with full width and emojis
@@ -78,7 +47,7 @@ st.markdown("""
         border-radius: 10px 10px 10px 10px;
     }
     .chat-header {
-        text-align: center;
+        # text-align: center;
         font-size: 35px;
         font-weight: bold;
         margin-bottom: 20px;
@@ -91,8 +60,11 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-st.markdown('<div class="chat-header">Gemini Chatbot-Your AI Companion 💻</div>', unsafe_allow_html=True)
-st.write("Powered by Hugging Face’s DialoGPT model for smart, engaging conversations. 🤖")
+st.markdown('<div class="chat-header">AI Chatbot-Your Companion 💻</div>', unsafe_allow_html=True)
+st.write("Powered by Hugging Face AI for smart, engaging conversations. 🤖")
+
+if "history" not in st.session_state:
+    st.session_state["history"] = []
 
 with st.form(key="chat_form", clear_on_submit=True):
     user_input = st.text_input("Your message here... ✍️", max_chars=2000, label_visibility="collapsed")
@@ -101,10 +73,7 @@ with st.form(key="chat_form", clear_on_submit=True):
     if submit_button:
         if user_input:
             response = get_chatbot_response(user_input)
-            if response:
-                st.session_state.history.append((user_input, response))
-            else:
-                st.warning("Bot returned an empty response.")
+            st.session_state.history.append((user_input, response))
         else:
             st.warning("Please Enter A Prompt 😅")