updating the app

app.py

@@ -58,31 +58,31 @@ retriever = vectorstore.as_retriever(search_kwargs={"k": 20})  # k=20
 # System prompt template for long, detailed answers
 def build_system(context: str) -> dict:
     """
-    Build the system prompt that instructs the model to:
+    Build a comprehensive system prompt:
     - Act as an expert medical assistant and attentive listener.
-    - Leverage all retrieved context to craft detailed, accurate, and empathetic responses.
-    - Ask clarifying follow-up questions if the user’s query is ambiguous.
-    - Structure answers clearly, using headings, bullet points, and step-by-step explanations.
+    - Leverage retrieved context to craft detailed, accurate, and empathetic responses.
+    - Ask clarifying follow-up questions if the user's query is ambiguous.
+    - Structure answers clearly with headings, bullet points, and step-by-step explanations.
     - Cite relevant context sections when appropriate.
-    - Maintain conversational memory so follow-up queries build upon prior discussion.
+    - Maintain conversational memory for follow-up continuity.
     """
-    prompt = (
-        "You are a world-class medical assistant and conversational partner. "
-        "Listen carefully to the user’s questions, reference the context below, and provide a thorough, evidence-based response. "
-        "If any part of the question is unclear, ask a clarifying question before proceeding. "
-        "Organize your answer with clear headings or bullet points, and refer back to specific context snippets as needed. "
-        "Always be empathetic, concise, and precise in your medical explanations. "
-        "Retain memory of previous user messages to support follow-up interactions.
-
-"
-        "=== Retrieved Context Start ===
-" 
-        + context +
-        "
-=== Retrieved Context End ==="
-    )
+    prompt = f"""
+You are a world-class medical assistant and conversational partner.
+
+Listen carefully to the user’s questions, reference the context below, and provide a thorough, evidence-based response.
+If any part of the question is unclear, ask a clarifying question before proceeding.
+Organize your answer with clear headings or bullet points, and refer back to specific context snippets as needed.
+Always be empathetic, concise, and precise in your medical explanations.
+Retain memory of previous user messages to support follow-up interactions.
+
+=== Retrieved Context Start ===
+{context}
+=== Retrieved Context End ===
+"""
     return {"role": "system", "content": prompt}
 
+ {"role": "system", "content": prompt}
+
 st.title("🩺 DocChatter RAG (Streaming & Memory)")
 
 # Initialize chat history