fixed the RAg in test pipeline issue

app/routers/chat.py

@@ -2,7 +2,7 @@ import time
 from collections import defaultdict
 
 from fastapi import APIRouter, HTTPException, Depends, Request
-from app.models import ChatMessage, ChatResponse, ConversationResponse, MessageResponse, FeedbackCreate
+from app.models import ChatMessage, ChatResponse, ConversationResponse, MessageResponse, FeedbackCreate, TestChatRequest, TestChatResult
 from app.database import get_supabase
 from app.dependencies import get_current_user, get_optional_user
 from app.services.rag import rag_engine
@@ -15,6 +15,8 @@ import logging
 logger = logging.getLogger(__name__)
 router = APIRouter(tags=["Chat"])
 
+CONFIDENCE_THRESHOLD = 0.55
+
 # ── Simple in-memory rate limiter ────────────────────────────────────────────
 _rate_store: dict = defaultdict(list)
 _RATE_LIMIT = 30   # max requests
@@ -166,29 +168,27 @@ async def chat(
         language=message.language,
     )
 
-    # Compute confidence score
-    confidence_score = max((s.score for s in result.get("sources", [])), default=0.0)
+    confidence_score = result.get("confidence_score", 0.0)
 
     # Check handoff
     is_handoff = False
+    low_confidence = confidence_score < CONFIDENCE_THRESHOLD
     if chatbot.get("handoff_enabled"):
         handoff_keywords = chatbot.get("handoff_keywords", [])
         msg_lower = message.message.lower()
-        if any(kw.lower() in msg_lower for kw in handoff_keywords):
+        keyword_triggered = any(kw.lower() in msg_lower for kw in handoff_keywords)
+        if keyword_triggered or low_confidence:
             is_handoff = True
-            # Fire n8n notification (async, non-blocking)
             try:
-                from app.services.n8n_service import send_handoff_notification
-                from app.config import settings as _settings
-                company_data_for_handoff = chatbot.get("companies", {}) or {}
-                await send_handoff_notification(
+                from app.services.notification_service import send_handoff_alert
+                await send_handoff_alert(
+                    chatbot_id=chatbot_id,
                     chatbot_name=chatbot.get("name", ""),
-                    owner_email=chatbot.get("handoff_email") or "",
                     conversation_history=history,
                     trigger_message=message.message,
-                    chatbot_id=chatbot_id,
                     conversation_id=conversation["id"],
-                    webhook_url=_settings.n8n_handoff_webhook_url,
+                    low_confidence=low_confidence,
+                    supabase=supabase,
                 )
             except Exception:
                 pass  # never block chat on handoff failure
@@ -228,6 +228,7 @@ async def chat(
         tokens_used=result.get("tokens_used", 0),
         needs_lead_capture=needs_lead_capture,
         handoff=is_handoff,
+        low_confidence=low_confidence,
     )
 
 
@@ -289,6 +290,56 @@ async def submit_feedback(chatbot_id: str, data: FeedbackCreate):
     return {"success": True}
 
 
+@router.post("/chat/{chatbot_id}/test", response_model=List[TestChatResult])
+async def test_chat(
+    chatbot_id: str,
+    body: TestChatRequest,
+    user=Depends(get_current_user),
+):
+    """Run test questions against a chatbot without saving to conversation history. Owner only."""
+    supabase = get_supabase()
+    chatbot = _get_public_chatbot(chatbot_id, supabase)
+
+    company = supabase.table("companies").select("id").eq("owner_id", user.id).execute()
+    if not company.data or company.data[0]["id"] != chatbot.get("company_id"):
+        raise HTTPException(status_code=403, detail="Access denied")
+
+    collection_name = chatbot.get("qdrant_collection_name")
+    if not collection_name:
+        raise HTTPException(status_code=400, detail="Chatbot has no knowledge base configured")
+
+    company_data = chatbot.get("companies", {}) or {}
+    chatbot_config = {**chatbot, "company_name": company_data.get("name", "")}
+
+    results = []
+    for question in body.questions:
+        try:
+            result = await rag_engine.process_query(
+                query=question,
+                collection_name=collection_name,
+                chatbot_config=chatbot_config,
+                conversation_history=[],
+                language="auto",
+                bypass_cache=True,
+            )
+            results.append(TestChatResult(
+                question=question,
+                response=result["response"],
+                confidence_score=result.get("confidence_score", 0.0),
+                sources=result.get("sources", []),
+                model_used=result.get("model", ""),
+            ))
+        except Exception as e:
+            results.append(TestChatResult(
+                question=question,
+                response=f"Error: {e}",
+                confidence_score=0.0,
+                sources=[],
+                model_used="",
+            ))
+    return results
+
+
 # ── OLD analytics endpoint REMOVED ───────────────────────────────────────────
 # The /analytics/{chatbot_id} endpoint that was here has been replaced by
 # the dedicated analytics router (app/routers/analytics.py) which provides: