Update app.py

app.py

@@ -0,0 +1,62 @@
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the pre-trained model and tokenizer
+@st.cache_resource
+def load_model():
+    model_name = "microsoft/DialoGPT-medium"  # Replace with your preferred model
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    return model, tokenizer
+
+model, tokenizer = load_model()
+
+# Chat history
+if "messages" not in st.session_state:
+    st.session_state["messages"] = []
+
+# Sidebar configuration
+st.sidebar.title("Chatbot Settings")
+st.sidebar.write("Customize your chatbot:")
+max_length = st.sidebar.slider("Max Response Length", 10, 200, 50)
+temperature = st.sidebar.slider("Response Creativity (Temperature)", 0.1, 1.0, 0.7)
+
+# App title
+st.title("🤖 Open Source Text-to-Text Chatbot")
+
+# Chat Interface
+st.write("### Chat with the bot:")
+user_input = st.text_input("You:", key="user_input", placeholder="Type your message here...")
+
+if user_input:
+    # Encode the input and add chat history for context
+    inputs = tokenizer.encode(
+        " ".join(st.session_state["messages"] + [user_input]),
+        return_tensors="pt",
+        truncation=True
+    )
+    
+    # Generate response
+    response = model.generate(
+        inputs,
+        max_length=max_length,
+        temperature=temperature,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+    bot_response = tokenizer.decode(response[:, inputs.shape[-1]:][0], skip_special_tokens=True)
+
+    # Append to chat history
+    st.session_state["messages"].append(f"You: {user_input}")
+    st.session_state["messages"].append(f"Bot: {bot_response}")
+
+    # Display the chat
+    for message in st.session_state["messages"]:
+        if message.startswith("You:"):
+            st.markdown(f"**{message}**")
+        else:
+            st.markdown(f"> {message}")
+
+# Clear chat history button
+if st.button("Clear Chat"):
+    st.session_state["messages"] = []
+    st.experimental_rerun()