Update rag_chain.py

rag_chain.py

@@ -4,7 +4,7 @@ from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
 
 def build_rag_chain(vectorstore, groq_api_key):
-    retriever = vectorstore.as_retriever(search_kwargs={"k": 4})
+    retriever = vectorstore.as_retriever(search_kwargs={"k": 2})
 
     llm = ChatGroq(
         api_key=groq_api_key,
@@ -14,19 +14,29 @@ def build_rag_chain(vectorstore, groq_api_key):
 
     prompt = ChatPromptTemplate.from_template(
         """
-        You are an expert software engineer.
-        Answer the question using ONLY the context below.
+        You are a codebase assistant.
+
+        RULES:
+        - Use ONLY the context below.
+        - If information is missing, say:
+          "I cannot find this information in the provided codebase."
+        - Do NOT guess.
 
         Context:
         {context}
 
         Question:
         {question}
+
+        Answer:
         """
     )
 
     def format_docs(docs):
-        return "\n\n".join(d.page_content for d in docs)
+        return "\n\n".join(
+            f"FILE: {d.metadata['file']}\n{d.page_content}"
+            for d in docs
+        )
 
     chain = (
         {