welcome agent logging

Author: Dharshan2004

backend/agents/onboarding/agent.py

@@ -39,7 +39,11 @@ def _llm(prompt: str) -> str:
 def execute(payload: Dict[str, Any]) -> Tuple[Dict, Dict]:
     q = payload.get("input",{}).get("question","").strip()
     t0 = time.time()
+    
+    print(f"🤖 Onboarding Agent - Question: '{q}'")
+    
     docs = retrieve(q, k=8)
+    print(f"🔍 Retrieved {len(docs)} documents before filtering")
 
     # Filter for relevant sources
     allowed_paths = ["policies/", "handbook.md"]
@@ -53,15 +57,28 @@ def execute(payload: Dict[str, Any]) -> Tuple[Dict, Dict]:
 
     if not docs:
         ans = "I don't know from current context. Please check HR."
+        print(f"❌ No relevant documents found - returning default response")
+        print(f"📝 Agent Response: {ans}")
         return ({"answer": ans, "citations": ""}, {"latency_ms": int((time.time()-t0)*1000)})
 
     context = "\n\n---\n\n".join(d.page_content for d in docs[:4])
+    print(f"📚 Context length: {len(context)} characters")
+    print(f"📚 Context preview: {context[:200]}...")
+    
     prompt = f"CONTEXT:\n{context}\n\nQUESTION:\n{q}\n\nANSWER:"
+    print(f"🤖 Sending prompt to LLM (length: {len(prompt)} chars)")
+    
     answer = _llm(prompt)
+    print(f"🤖 LLM Response: {answer}")
 
     if "Sources:" not in answer:
         answer = answer.strip() + "\n\nSources:\n" + build_citations(docs[:4])
+        print(f"📝 Added sources to response")
 
     answer = redact(answer)
+    print(f"📝 Final Agent Response: {answer}")
+    
     meta = {"citations": build_citations(docs[:4]), "latency_ms": int((time.time()-t0)*1000)}
+    print(f"⏱️  Response time: {meta['latency_ms']}ms")
+    
     return ({"answer": answer, "citations": meta["citations"]}, meta)

backend/app.py

@@ -253,7 +253,11 @@ def stream_response(text: str):
 @app.post("/agents/welcome/stream")
 def welcome_stream(req: StreamReq):
     """Streaming endpoint for Welcome Agent - matches frontend expectations"""
+    print(f"🌐 Welcome Stream Request - Message: '{req.msg}'")
+    print(f"🌐 Request details - org_id: {req.org_id}, user_id: {req.user_id}, consent: {req.consent}")
+    
     if not req.consent:
+        print("❌ Consent not provided - returning error")
         def error_stream():
             yield "Consent required to proceed."
         return StreamingResponse(error_stream(), media_type="text/plain")
@@ -267,11 +271,16 @@ def error_stream():
     }
 
     try:
+        print("🔄 Calling onboarding agent...")
         output, meta = execute_agent("onboarding", payload)
         answer = output.get("answer", "I couldn't generate a response.")
+        print(f"✅ Onboarding agent response received (length: {len(answer)} chars)")
+        print(f"📝 Final answer preview: {answer[:200]}...")
+        
         return StreamingResponse(stream_response(answer), media_type="text/plain")
     except Exception as e:
-        error_msg = str(e)  # Capture the error message
+        error_msg = str(e)
+        print(f"❌ Error in welcome stream: {error_msg}")
         def error_stream():
             yield f"Error: {error_msg}"
         return StreamingResponse(error_stream(), media_type="text/plain")

backend/rag.py

@@ -104,6 +104,8 @@ def retrieve(query: str, k: int = None):
     if k is None:
         k = int(os.getenv("RETRIEVAL_K", "4"))
 
+    print(f"🔍 RAG Retrieve - Query: '{query}', k={k}")
+    
     vs = get_vectorstore()
     if vs is None:
         print(f"⚠️  Vector store not available - returning empty results for query: '{query[:50]}...'")
@@ -122,22 +124,22 @@ def retrieve(query: str, k: int = None):
         try:
             retriever = vs.as_retriever(search_kwargs={"k": k})
             results = retriever.get_relevant_documents(query)
-            print(f"🔍 Retrieved {len(results)} documents using retriever for query: '{query[:50]}...'")
+            print(f"✅ Retrieved {len(results)} documents using retriever")
         except Exception as retriever_error:
             print(f"⚠️  Retriever failed: {retriever_error}, trying similarity_search")
             results = vs.similarity_search(query, k=k)
-            print(f"🔍 Retrieved {len(results)} documents using similarity_search for query: '{query[:50]}...'")
+            print(f"✅ Retrieved {len(results)} documents using similarity_search")
 
         # Debug: Print source paths for debugging
         for i, doc in enumerate(results):
             source = doc.metadata.get("source", "unknown")
-            print(f"  Doc {i+1}: {source}")
+            content_preview = doc.page_content[:100].replace('\n', ' ')
+            print(f"  📄 Doc {i+1}: {source}")
+            print(f"      Content: {content_preview}...")
 
         return results
     except Exception as e:
         print(f"❌ Vector store retrieval failed for query: '{query[:50]}...' - {e}")
-        import traceback
-        traceback.print_exc()
         return []
 
 def get_document_count():