Update app.py

app.py

@@ -143,7 +143,7 @@ class SQLiteVectorRetriever(BaseRetriever):
     def _get_relevant_documents(self, query, run_manager=None, **kwargs):
         return query_vector_db(query, self.top_k)
 
-# --- FINETUNED SYSTEM PROMPT FOR DIRECT ANSWERS ---
+# --- SYSTEM PROMPT & CORRECT PROMPT FORMAT ---
 system_prompt = (
     "You are a JSON data assistant. Always give a direct, concise answer based only on the context provided. "
     "If you do not see the answer in the context, reply: 'I don’t have that information.' "
@@ -152,10 +152,10 @@ system_prompt = (
 
 prompt = ChatPromptTemplate.from_messages([
     ("system", system_prompt),
-    ("human", "{question}")
+    ("human", "Context:\n{context}\n\nQuestion: {question}")
 ])
 
-llm = ChatOpenAI(model="gpt-4.1", openai_api_key=OPENAI_API_KEY, temperature=0)
+llm = ChatOpenAI(model="gpt-4o", openai_api_key=OPENAI_API_KEY, temperature=0)
 
 retriever = SQLiteVectorRetriever(top_k=5)
 qa_chain = RetrievalQA.from_chain_type(
@@ -176,7 +176,6 @@ for msg in st.session_state.messages:
         st.markdown(f"<details><summary><b>Function Output:</b></summary><pre>{msg['content']}</pre></details>", unsafe_allow_html=True)
 
 def show_json_links_and_modal():
-    # Look for last function message (top results) and display view buttons
     for msg in reversed(st.session_state.messages):
         if msg.get("role") == "function" and msg.get("content"):
             try:
@@ -205,7 +204,7 @@ def send_message():
         return
     st.session_state.messages.append({"role": "user", "content": user_input})
     with st.spinner("Thinking..."):
-        # Use the chain with { "question": ... } to match prompt format
+        # Use the chain with {"question": ...} to match prompt format
         result = qa_chain({"question": user_input})
         answer = result['result']
         st.session_state.messages.append({"role": "assistant", "content": answer})