Update pages/machine_learning.py

pages/machine_learning.py

@@ -3,31 +3,22 @@ import os
 from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
 from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
 
-
-
+# Set Hugging Face tokens
 hf = os.getenv('Data_science')
 os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
 os.environ['HF_TOKEN'] = hf
+
 # --- Config ---
-st.set_page_config(page_title="AI Mentor Chat", layout="centered")
-st.title("🤖 AI Mentor Chat")
+st.set_page_config(page_title="ML Mentor Chat", layout="centered")
+st.title("🤖 Machine Learning Mentor Chat")
 
 # --- Sidebar for selections ---
 st.sidebar.title("Mentor Preferences")
-
-exp1 = ['<1', '1', '2', '3', '4', '5', '5+']
-exp = st.sidebar.selectbox("Select experience:", exp1)
-
-# Map experience to label
-experience_map = {
-    '<1': 'New bie mentor',
-    '1': '1', '2': '2', '3': '3', '4': '4', '5': '5',
-    '5+': 'Professional'
-}
-experience_label = experience_map[exp]
+exp_options = ['Beginner', 'Intermediate', 'Experienced']
+exp = st.sidebar.selectbox("Select your experience level:", exp_options)
 
 # --- Initialize Chat Model ---
-deep_seek_skeleton = HuggingFaceEndpoint(
+ml_model_skeleton = HuggingFaceEndpoint(
     repo_id='Qwen/Qwen3-14B',
     provider='nebius',
     temperature=0.7,
@@ -35,8 +26,8 @@ deep_seek_skeleton = HuggingFaceEndpoint(
     task='conversational'
 )
 
-deep_seek = ChatHuggingFace(
-    llm=deep_seek_skeleton,
+ml_mentor = ChatHuggingFace(
+    llm=ml_model_skeleton,
     repo_id='Qwen/Qwen3-14B',
     provider='nebius',
     temperature=0.7,
@@ -45,8 +36,8 @@ deep_seek = ChatHuggingFace(
 )
 
 # --- Session State ---
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
+if "chat_history_ml" not in st.session_state:
+    st.session_state.chat_history_ml = []
 
 # --- Chat Form ---
 with st.form(key="chat_form"):
@@ -56,20 +47,19 @@ with st.form(key="chat_form"):
 # --- Chat Logic ---
 if submit and user_input:
     # Add system context
-    system_prompt = f"Act as a machine learning mentor who has {experience_label} years of experience who teaches in a very friendly manner and also tells everything in within 150 words. If any question is asked other than machine learning tell politely that this is out of the topic question"
+    system_prompt = (
+        f"You are a machine learning mentor with {exp.lower()} experience level. "
+        f"Answer only machine learning-related questions in a friendly tone and under 150 words. "
+        f"If the question is out of topic, politely say it's out of scope."
+    )
 
-    # Create message list
     messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
-
-    # Get model response
-    result = deep_seek.invoke(messages)
-
-    # Append to history
-    st.session_state.chat_history.append((user_input, result.content))
+    result = ml_mentor.invoke(messages)
+    st.session_state.chat_history_ml.append((user_input, result.content))
 
 # --- Display Chat History ---
 st.subheader("🗨️ Chat History")
-for i, (user, bot) in enumerate(st.session_state.chat_history):
+for user, bot in st.session_state.chat_history_ml:
     st.markdown(f"**You:** {user}")
     st.markdown(f"**Mentor:** {bot}")
-    st.markdown("---")
+    st.markdown("---")