Update app.py

app.py

@@ -1,54 +1,81 @@
+# streamlit_app.py
 import os
 import streamlit as st
 from huggingface_hub import InferenceClient
 from dotenv import load_dotenv
 
-# Load environment variables (for local development)
+# Load environment variables for local development
 load_dotenv()
 
-# Initialize InferenceClient
-token = os.environ.get("HUGGINGFACEHUB_API_TOKEN")
-client = InferenceClient(provider="auto", api_key=token)
+# Initialize the Hugging Face Inference client
+hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+client = InferenceClient(provider="auto", api_key=hf_token)
+
+# Streamlit configuration
+st.set_page_config(
+    page_title="Interview Prep Bot",
+    page_icon="🧠",
+    layout="centered"
+)
 
-st.set_page_config(page_title="Interview Prep Bot", layout="wide")
 st.title("🎓 Interview Preparation Chatbot")
 
-# Initialize history
+# Session state for conversation history and selected topic
 if "history" not in st.session_state:
     st.session_state.history = []
+if "topic" not in st.session_state:
+    st.session_state.topic = "Machine Learning"
+
+# Sidebar: Topic selection
+st.sidebar.header("Practice Topic")
+st.session_state.topic = st.sidebar.selectbox(
+    "Select a topic:",
+    [
+        "Machine Learning",
+        "Data Structures",
+        "Python",
+        "Generative AI",
+        "Computer Vision",
+        "Deep Learning",
+    ],
+    index=["Machine Learning","Data Structures","Python","Generative AI","Computer Vision","Deep Learning"].index(st.session_state.topic)
+)
 
-# Render chat history
-for sender, msg in st.session_state.history:
+# Display existing chat history
+for sender, message in st.session_state.history:
     role = "user" if sender == "You" else "assistant"
-    st.chat_message(role).write(msg)
+    st.chat_message(role).write(message)
 
-# Prompt input
-text = st.chat_input("Ask me anything about interview prep…")
-if text:
-    # record user
-    st.session_state.history.append(("You", text))
-    st.chat_message("user").write(text)
+# User input
+user_input = st.chat_input("Ask me anything about " + st.session_state.topic + "…")
 
-    # placeholder
+if user_input:
+    # Append user message
+    st.session_state.history.append(("You", user_input))
+    st.chat_message("user").write(user_input)
+
+    # Placeholder for bot response
     placeholder = st.chat_message("assistant")
     placeholder.write("⏳ Thinking...")
 
-    # build messages for API
+    # Build messages for the API call
     messages = []
-    for s, m in st.session_state.history:
-        role = "user" if s == "You" else "assistant"
-        messages.append({"role": role, "content": m})
+    for role, text in [("user", msg) if s == "You" else ("assistant", msg)
+                       for s, msg in st.session_state.history]:
+        messages.append({"role": role, "content": text})
 
-    # call HF chat completion
+    # Call the Inference API
     try:
-        completion = client.chat.completions.create(
+        response = client.chat.completions.create(
             model="mistralai/Mistral-7B-Instruct-v0.1",
-            messages=messages,
+            messages=messages
         )
-        reply = completion.choices[0].message["content"].strip()
+        bot_reply = response.choices[0].message["content"].strip()
     except Exception as e:
-        reply = f"❌ API Error: {e}"
+        bot_reply = f"❌ API Error: {e}"
+
+    # Display and store bot reply
+    placeholder.write(bot_reply)
+    st.session_state.history.append(("Bot", bot_reply))
 
-    # display and store reply
-    placeholder.write(reply)
-    st.session_state.history.append(("Bot", reply))
+```