Update main.py

main.py

@@ -13,6 +13,8 @@ from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 from dotenv import load_dotenv
 from datetime import datetime
+
+# Import shared vocab from KB services
 from services.kb_creation import ACTION_SYNONYMS, MODULE_VOCAB
 from services.kb_creation import (
     collection,
@@ -144,6 +146,20 @@ ERROR_FAMILY_SYNS = {
     ),
 }
 
+# ----- local extension so runtime filtering is precise even without re-ingest -----
+# (Does NOT override your KB synonyms—just augments them at runtime.)
+ACTION_SYNONYMS_EXT: Dict[str, List[str]] = {}
+for k, v in ACTION_SYNONYMS.items():
+    ACTION_SYNONYMS_EXT[k] = list(v)  # copy
+
+# Extend with SOP phrasing (appointments often say 'updation', 'deletion', 'reschedule')
+ACTION_SYNONYMS_EXT.setdefault("create", []).extend(["appointment creation", "create appointment"])
+ACTION_SYNONYMS_EXT.setdefault("update", []).extend([
+    "updation", "reschedule", "change time", "change date", "change slot",
+    "update time", "update date", "update slot", "update appointment", "edit appointment"
+])
+ACTION_SYNONYMS_EXT.setdefault("delete", []).extend(["deletion", "delete appointment", "cancel appointment"])
+
 
 def _detect_error_families(msg: str) -> list:
     """Return matching error family names found in the message (generic across SOPs)."""
@@ -936,23 +952,24 @@ async def chat_with_ai(input_data: ChatInput):
             "pre-requirements", "requirements"
         )
         if detected_intent == "neutral" and any(h in sec_title for h in PREREQ_HEADINGS):
-            detected_intent = "prereqs"        
-# Make steps nudges module-aware (appointments, picking, shipping, etc.)
+            detected_intent = "prereqs"
+
+        # --- Module-aware steps nudge (appointments, picking, shipping, etc.) ---
         STEPS_TERMS = ("how to", "procedure", "perform", "steps", "do", "navigate")
-        ACTIONS_PRESENT = any(s in msg_low for syns in ACTION_SYNONYMS.values() for s in syns)
+        ACTIONS_PRESENT = any(s in msg_low for syns in ACTION_SYNONYMS_EXT.values() for s in syns)
         mod_tags = ((top_meta or {}).get("module_tags") or "").lower()
-        sec_title = ((top_meta or {}).get("section") or "").strip().lower()
-  # Flatten vocabulary terms for module detection (appointments, picking, shipping, inventory...)
+
         MODULE_TOKENS = tuple({term for syns in MODULE_VOCAB.values() for term in syns})
         looks_like_module = (
-                 any(t in msg_low for t in MODULE_TOKENS)
-                 or any(m in mod_tags for m in ["appointments", "receiving", "picking", "putaway", "shipping", "inventory", "replenishment"])
-                 or any(m in sec_title for m in ["appointment", "appointments", "schedule", "dock", "door", "picking", "putaway", "shipping", "inventory"])
-)
+            any(t in msg_low for t in MODULE_TOKENS)
+            or any(m in mod_tags for m in ["appointments", "receiving", "picking", "putaway", "shipping", "inventory", "replenishment"])
+            or any(m in sec_title for m in ["appointment", "appointments", "schedule", "dock", "door", "picking", "putaway", "shipping", "inventory"])
+        )
         looks_like_steps_query = any(t in msg_low for t in STEPS_TERMS) or ACTIONS_PRESENT
 
         if detected_intent in ("neutral", "prereqs") and looks_like_steps_query and looks_like_module:
-           detected_intent = "steps"
+            detected_intent = "steps"
+
         # --- Meaning-aware SOP gating ---
         def _contains_any(s: str, keywords: tuple) -> bool:
             low = (s or "").lower()
@@ -984,7 +1001,6 @@ async def chat_with_ai(input_data: ChatInput):
         weak_domain_only = (mentions_domain and not has_any_action_or_error)
         low_context_hit = (matched_count < 2 and filter_mode in ("concise", "exact"))
 
-        # Bypass gate when strong steps signals are present for Receiving module
         strong_steps_bypass = looks_like_steps_query and looks_like_module
         strong_error_signal = len(_detect_error_families(msg_low)) > 0
         if (weak_domain_only or (low_context_hit and not combined_ok)) \
@@ -1023,6 +1039,26 @@ async def chat_with_ai(input_data: ChatInput):
         next_step_applied = False
         next_step_info: Dict[str, Any] = {}
 
+        # Helper: detect asked action from query using extended synonyms
+        def _detect_action_from_query(q: str) -> Optional[str]:
+            qlow = (q or "").lower()
+            for act, syns in ACTION_SYNONYMS_EXT.items():
+                if any(s in qlow for s in syns):
+                    return act
+            return None
+
+        # Helper: filter lines in a steps context to keep only the asked action
+        def _filter_steps_by_action(raw_context: str, asked_act: Optional[str]) -> str:
+            if not asked_act or not raw_context.strip():
+                return raw_context
+            other_terms: List[str] = []
+            for act, syns in ACTION_SYNONYMS_EXT.items():
+                if act != asked_act:
+                    other_terms.extend(syns)
+            lines = _normalize_lines(raw_context)
+            kept = [ln for ln in lines if not any(t in ln.lower() for t in other_terms)]
+            return "\n".join(kept).strip() if kept else raw_context
+
         if best_doc:
             if detected_intent == "steps":
                 full_steps = get_best_steps_section_text(best_doc)
@@ -1032,6 +1068,10 @@ async def chat_with_ai(input_data: ChatInput):
                         full_steps = get_section_text(best_doc, sec)
 
                 if full_steps:
+                    # Apply action-focused filtering FIRST (to avoid mixing create/update/delete)
+                    asked_action = _detect_action_from_query(input_data.user_message)
+                    full_steps = _filter_steps_by_action(full_steps, asked_action)
+
                     # Use numbered form only for matching; keep raw for full output
                     numbered_full = _ensure_numbering(full_steps)
                     next_only = _resolve_next_steps(input_data.user_message, numbered_full, max_next=6, min_score=0.35)
@@ -1049,8 +1089,7 @@ async def chat_with_ai(input_data: ChatInput):
                             next_step_info = {"count": len(next_only)}
                             context_preformatted = True
                     else:
-                        # Normal mode: return the full SOP section (raw),
-                        # and we'll number it below once.
+                        # Normal mode: return the full SOP section (raw), and we'll number it below once.
                         context = full_steps
                         context_preformatted = False
 
@@ -1075,23 +1114,32 @@ async def chat_with_ai(input_data: ChatInput):
                             )
                     escalation_line = _extract_escalation_line(full_errors)
                 else:
-                     # Fallback when Errors section is missing: show steps
-                     full_steps = get_best_steps_section_text(best_doc) or get_section_text(best_doc, sec_title or "")
-                     if full_steps:
+                    # Fallback when Errors section is missing: show steps
+                    full_steps = get_best_steps_section_text(best_doc) or get_section_text(best_doc, sec_title or "")
+                    if full_steps:
+                        # Apply action filter to keep responses tight
+                        asked_action = _detect_action_from_query(input_data.user_message)
+                        full_steps = _filter_steps_by_action(full_steps, asked_action)
+
                         context = full_steps
                         detected_intent = "steps"
                         context_preformatted = False
+
             elif detected_intent == "prereqs":
                 full_prereqs = _find_prereq_section_text(best_doc)
                 if full_prereqs:
                     context = full_prereqs.strip()
                 else:
-        # Fallback when Prereqs section is missing: show steps
+                    # Fallback when Prereqs section is missing: show steps
                     full_steps = get_best_steps_section_text(best_doc) or get_section_text(best_doc, sec_title or "")
                     if full_steps:
-                       context = full_steps
-                       detected_intent = "steps"
-                       context_preformatted = False    
+                        asked_action = _detect_action_from_query(input_data.user_message)
+                        full_steps = _filter_steps_by_action(full_steps, asked_action)
+
+                        context = full_steps
+                        detected_intent = "steps"
+                        context_preformatted = False
+
         language_hint = _detect_language_hint(input_data.user_message)
         lang_line = f"Respond in {language_hint}." if language_hint else "Respond in a clear, polite tone."
         use_gemini = (detected_intent == "errors")