Update src/RAGSample.py

src/RAGSample.py

@@ -119,9 +119,9 @@ class SmartFAQRetriever(BaseRetriever):
         return self._k
 
     def get_documents_with_confidence(self, query: str) -> List[dict]:
-    """Return top documents and their confidence (similarity) scores."""
-    results = self._get_relevant_documents_with_scores(query)
-    return [{"document": doc.page_content, "confidence": round(score, 3)} for doc, score in results]
+        """Return top documents and their confidence (similarity) scores."""
+        results = self._get_relevant_documents_with_scores(query)
+        return [{"document": doc.page_content, "confidence": round(score, 3)} for doc, score in results]
 
 
     
@@ -522,38 +522,38 @@ class RAGApplication:
     #         traceback.print_exc()
     #         return f"I apologize, but I encountered an error processing your question: {str(e)}. Please try rephrasing it or ask a different question."
     def run(self, question: str) -> str:
-    try:
-        if not question.strip():
-            return "Please provide a valid question."
-
-        print(f"\nProcessing question: '{question}'")
-
-        if hasattr(self.retriever, "get_documents_with_confidence"):
-            docs_with_scores = self.retriever.get_documents_with_confidence(question)
-            documents = [Document(page_content=d["document"]) for d in docs_with_scores]
-            confidence_info = "\n".join([f"- Score: {d['confidence']}, Snippet: {d['document'][:100]}..." for d in docs_with_scores])
-        else:
-            documents = self.retriever.invoke(question)
-            confidence_info = "Confidence scoring not available."
-
-        print(f"Retrieved {len(documents)} documents")
-        print(confidence_info)
-
-        doc_texts = "\n\n".join([doc.page_content for doc in documents])
-        if len(doc_texts) > 500:
-            doc_texts = doc_texts[:500] + "..."
-
-        answer = self.rag_chain.invoke({"question": question, "documents": doc_texts})
-
-        # Append confidence footer
-        footer = "\n\n(Note: This answer is based on documents with confidence scores. Review full context if critical.)"
-        return answer.strip() + footer
-
-        except Exception as e:
-            print(f"Error in RAG application: {str(e)}")
-            import traceback
-            traceback.print_exc()
-            return f"I apologize, but I encountered an error processing your question: {str(e)}. Please try rephrasing it or ask a different question."
+        try:
+            if not question.strip():
+                return "Please provide a valid question."
+    
+            print(f"\nProcessing question: '{question}'")
+    
+            if hasattr(self.retriever, "get_documents_with_confidence"):
+                docs_with_scores = self.retriever.get_documents_with_confidence(question)
+                documents = [Document(page_content=d["document"]) for d in docs_with_scores]
+                confidence_info = "\n".join([f"- Score: {d['confidence']}, Snippet: {d['document'][:100]}..." for d in docs_with_scores])
+            else:
+                documents = self.retriever.invoke(question)
+                confidence_info = "Confidence scoring not available."
+    
+            print(f"Retrieved {len(documents)} documents")
+            print(confidence_info)
+    
+            doc_texts = "\n\n".join([doc.page_content for doc in documents])
+            if len(doc_texts) > 500:
+                doc_texts = doc_texts[:500] + "..."
+    
+            answer = self.rag_chain.invoke({"question": question, "documents": doc_texts})
+    
+            # Append confidence footer
+            footer = "\n\n(Note: This answer is based on documents with confidence scores. Review full context if critical.)"
+            return answer.strip() + footer
+    
+            except Exception as e:
+                print(f"Error in RAG application: {str(e)}")
+                import traceback
+                traceback.print_exc()
+                return f"I apologize, but I encountered an error processing your question: {str(e)}. Please try rephrasing it or ask a different question."
 
 
 # Main execution block