Update chatbot.py

chatbot.py

@@ -4,16 +4,16 @@ import torch
 from huggingface_hub import login
 import os
 
-# Force authentication
+# ================= AUTHENTICATION =================
+# Ensure this is flush to the left margin
 hf_token = os.getenv("HF_TOKEN")
 if hf_token:
     try:
-        # This confirms your identity to HF
         login(token=hf_token)
     except Exception:
-        # If network is down, we just skip login. 
-        # If the model is public, it will still load.
+        # Silently fail if network is temporarily down
         pass
+
 # ================= CACHE THE MODEL =================
 @st.cache_resource
 def load_model():
@@ -25,7 +25,6 @@ def load_model():
     )
 
     tokenizer = AutoTokenizer.from_pretrained(model_id)
-    # Ensure tokenizer has a chat template, or use a default one
     if tokenizer.chat_template is None:
         tokenizer.chat_template = "{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '</s>\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% endif %}"
 
@@ -37,36 +36,31 @@ def load_model():
         trust_remote_code=True
     )
 
-    return pipeline(
-        "text-generation",
-        model=model,
-        tokenizer=tokenizer
-    )
+    return pipeline("text-generation", model=model, tokenizer=tokenizer)
 
 pipe = load_model()
 
 # ==================== CHAT INTERFACE ====================
-st.title("IPT Chatbot Assistance")
-st.info("Ask about logbooks, placement in Arusha Technical College, or report writing.")
+st.title("Industrial Practical Training Chatbot")
+st.info("Ask about logbooks, placement, or report writing.")
 
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
-# Display chat history
+# Display history
 for message in st.session_state.messages:
     if message["role"] != "system":
         with st.chat_message(message["role"]):
             st.markdown(message["content"])
 
 # User input
-if prompt := st.chat_input("Ask about Industrial Practical Training..."):
+if prompt := st.chat_input("Ask about IPT..."):
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
     with st.chat_message("assistant"):
-        with st.spinner("Thinking..."):
-            # 1. Fixed system_message structure and quotes
+        with st.spinner("Analyzing IPT guidelines..."):
             system_message = {
                 "role": "system",
                 "content": """You are the "IPT Master Assistant," a specialized AI coordinator for engineering and ICT students in Tanzania undergoing Industrial Practical Training (IPT). Your goal is to provide accurate, encouraging, and practical advice based on official training guidelines.
@@ -93,17 +87,15 @@ if prompt := st.chat_input("Ask about Industrial Practical Training..."):
 Academic mentor. Refer to Tanzanian institutions (ATC, DIT, MUST, UDSM)."""
             }
 
-            # 2. Fixed line 102 indentation (ensure 12 spaces)
+            # Standardized indentation for input_messages
             input_messages = [system_message] + st.session_state.messages[-3:]
 
-            # 3. Apply the chat template
             formatted_prompt = pipe.tokenizer.apply_chat_template(
                 input_messages, 
                 tokenize=False, 
                 add_generation_prompt=True
             )
 
-            # 4. Generate response
             outputs = pipe(
                 formatted_prompt,
                 max_new_tokens=300,
@@ -116,9 +108,8 @@ Academic mentor. Refer to Tanzanian institutions (ATC, DIT, MUST, UDSM)."""
             response = outputs[0]["generated_text"].strip()
             st.markdown(response)
 
-    # Save assistant response to history
     st.session_state.messages.append({"role": "assistant", "content": response})
 
-if st.button("Clear Conversation"):
+if st.button("Clear History"):
     st.session_state.messages = []
     st.rerun()