Update app.py

app.py

@@ -1,41 +1,51 @@
-# app.py
-
-import gradio as gr
-from transformers import pipeline, Conversation
-
-# 1) Create a conversational pipeline with Decryptu/distilgpt2
-chat_pipeline = pipeline("conversational", model="Decryptu/distilgpt2")
-
-def respond(user_message, chat_history):
-    """
-    Receives a user message and a running conversation history,
-    then uses the pipeline to generate a response.
-    """
-    # Create a new Conversation object for the user's message
-    conversation = Conversation(user_message)
-    
-    # Generate a response using the pipeline
-    conversation = chat_pipeline(conversation)
-    bot_response = conversation.generated_responses[-1]
-    
-    # Append user input and model response to chat history
-    chat_history.append((user_message, bot_response))
-    
-    # Return empty input box and updated chat history
-    return "", chat_history
-
-# 2) Build the Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## DistilGPT2 Chatbot")
-    chatbot = gr.Chatbot(label="Chat Window")
-    user_input = gr.Textbox(placeholder="Ask a question or start a conversation...")
-    clear_btn = gr.Button("Clear Chat")
-    
-    # Whenever the user submits text, call the respond function
-    user_input.submit(fn=respond, inputs=[user_input, chatbot], outputs=[user_input, chatbot])
-    
-    # Clear the conversation history when the user clicks 'Clear Chat'
-    clear_btn.click(lambda: [], None, chatbot, queue=False)
-
-# 3) Launch the Gradio interface
-demo.launch()
+import streamlit as st
+from transformers import pipeline
+
+# Create a text-generation pipeline (no Conversation class needed)
+model_name = "Decryptu/distilgpt2"
+generator = pipeline("text-generation", model=model_name)
+
+# Store chat history in session_state
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+st.title("Chat with DistilGPT2")
+st.write("A simple chat-like interface using a text-generation pipeline.")
+
+# User input
+user_input = st.text_input("Type your message here:")
+
+# On 'Send' button click
+if st.button("Send"):
+    if user_input.strip():
+        # 1) Append user's message to the history
+        st.session_state.history.append(("User", user_input))
+        
+        # 2) Build a prompt from the entire conversation
+        prompt = ""
+        for speaker, text in st.session_state.history:
+            prompt += f"{speaker}: {text}\n"
+        prompt += "Bot: "
+
+        # 3) Generate text from the model
+        output = generator(
+            prompt, 
+            max_length=100, 
+            do_sample=True, 
+            temperature=0.7
+        )
+        
+        # The model output includes the prompt plus new text
+        bot_text = output[0]["generated_text"].split("Bot:", 1)[-1].strip()
+        
+        # 4) Append the bot's response to the history
+        st.session_state.history.append(("Bot", bot_text))
+
+# Display the conversation
+st.write("### Conversation")
+for speaker, text in st.session_state.history:
+    st.write(f"**{speaker}:** {text}")
+
+# Add a 'Clear Chat' button (optional)
+if st.button("Clear Chat"):
+    st.session_state.history = []