Update app.py

app.py

@@ -208,17 +208,18 @@ class EnhancedLangChainRAGSystem:
             user = st.session_state.get('current_user')
             if user:
                 user_context = f"""
-            User Profile Context:
-            - Name: {user.display_name}
-            - Experience Level: {user.expertise_level}
-            - Preferred Languages: {', '.join(user.preferred_languages) if user.preferred_languages else 'None specified'}
-            - Learning Goals: {user.learning_goals or 'None specified'}
-            
-            Please tailor your response to match the user's experience level and preferences.
-            """
+                User Profile Context:
+                - Name: {user.display_name}
+                - Experience Level: {user.expertise_level}
+                - Preferred Languages: {', '.join(user.preferred_languages) if user.preferred_languages else 'None specified'}
+                - Learning Goals: {user.learning_goals or 'None specified'}
+                
+                Please tailor your response to match the user's experience level and preferences.
+                """
             else:
                 user_context = "User profile not available. Provide general guidance."
-                        return f"""You are an expert assistant for iCodeGuru, a programming education platform. 
+            
+            return f"""You are an expert assistant for iCodeGuru, a programming education platform. 
             {user_context}
             
             Use the following context to answer the user's question comprehensively and accurately.
@@ -229,30 +230,28 @@ class EnhancedLangChainRAGSystem:
             Chat History: {{chat_history}}
             Human: {{question}}"""
 
-            # Part 2 of Enhanced App - RAG System Implementation and Features
-
-            PROMPT = PromptTemplate(
-                template=get_personalized_prompt(),
-                input_variables=["context", "chat_history", "question"]
+        PROMPT = PromptTemplate(
+        template=get_personalized_prompt(),
+        input_variables=["context", "chat_history", "question"]
+    )
+    
+        try:
+            retriever = self.vectorstore.as_retriever(
+                search_type="similarity",
+                search_kwargs={"k": 4}
             )
             
-            try:
-                retriever = self.vectorstore.as_retriever(
-                    search_type="similarity",
-                    search_kwargs={"k": 4}
-                )
-                
-                self.retrieval_chain = ConversationalRetrievalChain.from_llm(
-                    llm=self.llm,
-                    retriever=retriever,
-                    memory=self.memory,
-                    combine_docs_chain_kwargs={"prompt": PROMPT},
-                    return_source_documents=True,
-                    verbose=False
-                )
-                
-            except Exception as e:
-                self.retrieval_chain = None
+            self.retrieval_chain = ConversationalRetrievalChain.from_llm(
+                llm=self.llm,
+                retriever=retriever,
+                memory=self.memory,
+                combine_docs_chain_kwargs={"prompt": PROMPT},
+                return_source_documents=True,
+                verbose=False
+            )
+            
+        except Exception as e:
+            self.retrieval_chain = None
     
     def load_and_process_documents(self) -> List[Document]:
         """Load and process JSON documents from the docs directory."""