Update app.py

app.py

@@ -1,29 +1,107 @@
 import streamlit as st
 import requests
 
-# Hugging Face API URL
+# -----------------------------------
+# 1. Hugging Face API Configuration
+# -----------------------------------
 API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
 
-# Function to query the Hugging Face API
 def query(payload):
+    """
+    Query the Hugging Face Inference API with the given payload.
+    Keeps the original approach: payload = {"inputs": user_input}.
+    """
     headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}
     response = requests.post(API_URL, headers=headers, json=payload)
     return response.json()
 
-# Streamlit app
-st.title("DeepSeek-R1-Distill-Qwen-32B Chatbot")
 
-# Input text box
-user_input = st.text_input("Enter your message:")
+# -----------------------------------
+# 2. Streamlit Page Settings
+# -----------------------------------
+st.set_page_config(
+    page_title="DeepSeek Chatbot - ruslanmv.com",
+    page_icon="🤖",
+    layout="centered"
+)
 
-if user_input:
-    # Query the Hugging Face API with the user input
-    payload = {"inputs": user_input}
-    output = query(payload)
+# -----------------------------------
+# 3. Session State Initialization
+# -----------------------------------
+# We'll keep a chat history in st.session_state
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# -----------------------------------
+# 4. Sidebar Configuration
+# -----------------------------------
+with st.sidebar:
+    st.header("Configuration")
+    st.markdown("[Get your HuggingFace Token](https://huggingface.co/settings/tokens)")
+
+    # Although these parameters are shown on the sidebar, we won't actually
+    # pass them to the payload in `query()`, to strictly preserve the "original" approach.
+    st.write("**NOTE:** These sliders do not affect the inference in this demo.")
+    system_message = st.text_area(
+        "System Message (display only)",
+        value="You are a friendly Chatbot created by ruslanmv.com",
+        height=100
+    )
+    max_tokens = st.slider("Max Tokens (not used here)", 1, 4000, 512)
+    temperature = st.slider("Temperature (not used here)", 0.1, 4.0, 0.7)
+    top_p = st.slider("Top-p (not used here)", 0.1, 1.0, 0.9)
+
+# -----------------------------------
+# 5. Main Chat Interface
+# -----------------------------------
+st.title("🤖 DeepSeek Chatbot")
+st.caption("Powered by Hugging Face Inference API - Original Inference Approach")
+
+# Display the chat history, message by message
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# -----------------------------------
+# 6. Capture User Input
+# -----------------------------------
+if user_input := st.chat_input("Type your message..."):
+    # 6.1 Append user message to chat history
+    st.session_state.messages.append({"role": "user", "content": user_input})
     
-    # Display the output
-    if isinstance(output, list) and len(output) > 0 and 'generated_text' in output[0]:
-        st.write("Response:")
-        st.write(output[0]['generated_text'])
-    else:
-        st.write("Error: Unable to generate a response. Please try again.")
+    # Display user's message
+    with st.chat_message("user"):
+        st.markdown(user_input)
+
+    # -----------------------------------
+    # 7. Query the Model
+    # -----------------------------------
+    try:
+        with st.spinner("Generating response..."):
+            # Prepare payload with the original approach
+            payload = {"inputs": user_input}
+            output = query(payload)
+
+            # Check if the output is valid
+            if (
+                isinstance(output, list) 
+                and len(output) > 0 
+                and "generated_text" in output[0]
+            ):
+                assistant_response = output[0]["generated_text"]
+            else:
+                assistant_response = (
+                    "Error: Unable to generate a response. Please try again."
+                )
+
+        # Display the assistant's response
+        with st.chat_message("assistant"):
+            st.markdown(assistant_response)
+
+        # Store assistant's response in chat history
+        st.session_state.messages.append(
+            {"role": "assistant", "content": assistant_response}
+        )
+
+    except Exception as e:
+        st.error(f"Application Error: {str(e)}")