Update app.py

app.py

@@ -97,16 +97,33 @@ for message in st.session_state.messages:
 if prompt := st.chat_input("Ask me anything about diabetes"):
     with st.chat_message("user"):
         st.markdown(prompt)
+
+    # Append user prompt to session state
     st.session_state.messages.append({"role": "user", "content": prompt})
 
+    # Structured instructions as used in your Colab example
+    instructions = "you are an expert endocrinologist. introduce your name as Dr Adam from the beginning then answer a patient query in a language the patient will understand"
+
+    # Combine structured instructions with user prompt
+    full_prompt = f"<s>[INST] {instructions} [/INST] {prompt}</s>"
+
     with st.chat_message("assistant"):
+        # Generate response using the pipeline with structured prompting
         result = pipeline(
             task="text-generation",
             model=model,
             tokenizer=tokenizer,
             max_length=1024,
             temperature=temp_values
-        )(prompt)
-        response = result[0]['generated_text']
+        )(full_prompt)
+
+        # Extract the answer from the generated text
+        generated_text = result[0]['generated_text']
+        response = generated_text.split("</s>")[-1].strip()
+
+        # Display the response
         st.markdown(response)
+
+    # Append assistant response to session state
     st.session_state.messages.append({"role": "assistant", "content": response})
+