Next set of feature improvements

features_to_add.txt

@@ -17,4 +17,10 @@ Compare mode — a dedicated side-by-side view for "How does Book A vs Book B ad
 Hallucination guardrail — run a separate verification pass checking every claim in the answer maps back to a retrieved chunk; flag or remove unsupported claims
 Out-of-scope detection — classify queries before retrieval; politely decline non-spiritual questions (e.g. "Write me code") with a prompt-level or classifier-level guard
 Rate limiting — add per-IP request throttling in FastAPI to prevent API key exhaustion
-API key security — move to server-side key storage properly; never expose NVIDIA_API_KEY or GEMINI_API_KEY in frontend calls
+API key security — move to server-side key storage properly; never expose NVIDIA_API_KEY or GEMINI_API_KEY in frontend calls
+
+
+Need to debug -
+1. General questions not citing verses
+2. For exact verses cache threshold score is returning same for chapter 2 verse 4 and chapter 1 verse 10
+3. 

frontend/index.html

@@ -778,7 +778,7 @@
         const reader = res.body.getReader();
         const decoder = new TextDecoder();
         let fullAnswer = "";
-        let sourcesData = [];
+        let buffer = "";
 
         // Prepare the assistant UI bubble immediately
         loadingEl.innerHTML = `
@@ -796,8 +796,14 @@
           const { done, value } = await reader.read();
           if (done) break;
 
-          const chunk = decoder.decode(value, { stream: true });
-          const lines = chunk.split("\n");
+          // Append new data to the buffer
+          buffer += decoder.decode(value, { stream: true });
+
+          // Split by newline
+          const lines = buffer.split("\n");
+
+          buffer = lines.pop();
+          
 
           for (const line of lines) {
             if (!line.trim()) continue;
@@ -826,7 +832,7 @@
                 scrollToBottom();
               }
             } catch (e) {
-              console.error("Error parsing NDJSON line:", e);
+              console.error("Stream parsing error", e);
             }
           }
         }

rag_chain.py

@@ -335,6 +335,10 @@ def query_sacred_texts(question: str):
         if display_name not in seen_sources:
             seen_sources.add(display_name)
             sources.append({"book": display_name, "page": cite_val, "snippet": snippet})
+    # Print book and page of each retrieved source for debugging
+    print("\n📚 Retrieved sources:")
+    for s in sources:
+        print(f"  - {s['book']} ({s['page']})")    
     # Step 2: Format context grouped by book
     context = format_docs(source_docs)
     full_answer =""
@@ -362,6 +366,7 @@ def query_sacred_texts(question: str):
         "sources": display_sources,
     }
     
+    
     cache_coll.add(
         documents=[question],
         metadatas=[{"response_json": json.dumps(result)}],