Update main.py

main.py

@@ -12,65 +12,21 @@ from pydantic import BaseModel
 from dotenv import load_dotenv
 from datetime import datetime
 
-# ------------------------------ Safe imports for Pylance ------------------------------
-# If your editor/Pylance can't resolve the local package, these stubs prevent "unresolved import"
-# while you fix your workspace settings (see tips below).
-try:
-    # Import shared vocab from KB services
-    from services.kb_creation import ACTION_SYNONYMS, MODULE_VOCAB
-    from services.kb_creation import (
-        collection,
-        ingest_documents,
-        hybrid_search_knowledge_base,
-        get_section_text,
-        get_best_steps_section_text,
-        get_best_errors_section_text,
-        get_escalation_text,  # for escalation heading
-    )
-    from services.kb_creation import bm25_docs
-    from services.login import router as login_router
-    from services.generate_ticket import get_valid_token, create_incident
-except Exception:
-    # Lightweight fallbacks (only to make Pylance happy; you should use real implementations at runtime)
-    ACTION_SYNONYMS: Dict[str, List[str]] = {"create": ["create"], "update": ["update"], "delete": ["delete"]}
-    MODULE_VOCAB: Dict[str, List[str]] = {"appointments": ["appointment", "schedule"]}
-    bm25_docs: List[Dict[str, Any]] = []
-
-    class _DummyColl:
-        def count(self) -> int:
-            return 0
-
-    def collection() -> _DummyColl:
-        return _DummyColl()
-
-    def ingest_documents(folder_path: str) -> None:
-        raise NotImplementedError("ingest_documents stub in editor mode")
-
-    def hybrid_search_knowledge_base(q: str, top_k: int = 10, alpha: float = 0.6, beta: float = 0.4) -> Dict[str, Any]:
-        return {"documents": [], "metadatas": [], "distances": [], "combined_scores": [], "user_intent": "neutral", "best_doc": None, "actions": []}
-
-    def get_section_text(doc: Optional[str], section: Optional[str]) -> str:
-        return ""
-
-    def get_best_steps_section_text(doc: Optional[str]) -> str:
-        return ""
-
-    def get_best_errors_section_text(doc: Optional[str]) -> str:
-        return ""
-
-    def get_escalation_text(doc: Optional[str]) -> str:
-        return ""
-
-    class _DummyRouter:
-        pass
-
-    login_router = _DummyRouter()
-
-    def get_valid_token() -> str:
-        return ""
-
-    def create_incident(short: str, desc: str) -> Dict[str, Any]:
-        return {"error": "ServiceNow not configured"}
+# ------------------------------ Imports ------------------------------
+# Import shared vocab from KB services
+from services.kb_creation import ACTION_SYNONYMS, MODULE_VOCAB
+from services.kb_creation import (
+    collection,
+    ingest_documents,
+    hybrid_search_knowledge_base,
+    get_section_text,
+    get_best_steps_section_text,
+    get_best_errors_section_text,
+    get_escalation_text,  # for escalation heading
+    bm25_docs,
+)
+from services.login import router as login_router
+from services.generate_ticket import get_valid_token, create_incident
 
 # ------------------------------ Config ------------------------------
 VERIFY_SSL = os.getenv("SERVICENOW_SSL_VERIFY", "true").lower() in ("1", "true", "yes")
@@ -103,10 +59,7 @@ async def lifespan(app: FastAPI):
 
 
 app = FastAPI(lifespan=lifespan)
-try:
-    app.include_router(login_router)
-except Exception:
-    pass  # stubbed router in editor-only mode
+app.include_router(login_router)
 
 origins = ["https://chatbotnova-chatbot-frontend.hf.space"]
 app.add_middleware(
@@ -221,6 +174,7 @@ def _detect_error_families(msg: str) -> list:
     return fams
 
 
+# --- Title keywords global selector (robust when action_tag is missing) ---
 def _get_steps_by_title_keywords_global(keywords: List[str], prefer_doc: Optional[str] = None) -> Tuple[Optional[str], Optional[str], Optional[str]]:
     """
     Search ALL SOP docs for a 'steps' section whose *section title* contains any of `keywords`.
@@ -261,6 +215,7 @@ def _get_steps_by_title_keywords_global(keywords: List[str], prefer_doc: Optiona
     _, best_doc_g, best_sec_g, best_text_g = candidates[0]
     return best_doc_g, best_sec_g, best_text_g
 
+
 # --- Action-targeted steps selector (uses existing KB metadata) ---
 def _get_steps_for_action(best_doc: str, actions: list) -> Optional[str]:
     """
@@ -324,6 +279,7 @@ def _get_steps_for_action_global(actions: list, prefer_doc: Optional[str] = None
     _, best_doc_global, best_text = candidates[0]
     return best_doc_global, best_text
 
+
 # --- Default section picker when query doesn't reveal action ---
 def _pick_default_action_section(best_doc: str) -> Optional[str]:
     """
@@ -1334,7 +1290,7 @@ async def chat_with_ai(input_data: ChatInput):
         next_step_applied = False
         next_step_info: Dict[str, Any] = {}
 
-        # ---------------- Steps branch (fixed indentation) ----------------
+        # ---------------- Steps branch ----------------
         if best_doc and detected_intent == "steps":
             context_preformatted = False
             full_steps = None
@@ -1480,7 +1436,7 @@ async def chat_with_ai(input_data: ChatInput):
 ### Output
 Return ONLY the rewritten guidance."""
         headers = {"Content-Type": "application/json"}
-        payload = {"contents": [{"parts": [{"text": enhanced_prompt}]}]}
+        payload = {"contents": [{"parts": [{"text": enhanced_prompt}]}]]}
         bot_text = ""
         http_code = 0
         if use_gemini and GEMINI_API_KEY:
@@ -1577,6 +1533,7 @@ Return ONLY the rewritten guidance."""
     except Exception as e:
         raise HTTPException(status_code=500, detail=safe_str(e))
 
+
 # ------------------------------ Ticket description generation ------------------------------
 @app.post("/generate_ticket_desc")
 async def generate_ticket_desc_ep(input_data: TicketDescInput):
@@ -1591,7 +1548,7 @@ async def generate_ticket_desc_ep(input_data: TicketDescInput):
             "Do not include any extra text, comments, or explanations outside the JSON."
         )
         headers = {"Content-Type": "application/json"}
-        payload = {"contents": [{"parts": [{"text": prompt}]}]}
+        payload = {"contents": [{"parts": [{"text": prompt}]}]]}
         resp = requests.post(GEMINI_URL, headers=headers, json=payload, timeout=25, verify=GEMINI_SSL_VERIFY)
         try:
             data = resp.json()