Update main.py

main.py

@@ -44,8 +44,7 @@ GEMINI_URL = (
 os.environ["POSTHOG_DISABLED"] = "true"
 
 # ---------------------------------------------------------------------
-# Minimal server-side cache to remember last issue text shown to user
-# (Used when user says "issue resolved" but frontend doesn't send last_issue)
+# Minimal server-side cache (used to populate short description if frontend didn’t pass last_issue)
 # ---------------------------------------------------------------------
 LAST_ISSUE_HINT: str = ""
 
@@ -188,7 +187,6 @@ def _normalize_lines(text: str) -> List[str]:
         return [raw.strip()] if raw.strip() else []
 
 
-# ---------------- Action filters for steps (create/update/delete) ----------------
 def _filter_numbered_steps_by_actions(numbered_text: str, wanted: set[str], exclude: set[str]) -> str:
     ACTION_SYNONYMS = {
         "create": ("create", "creation", "add", "new", "generate"),
@@ -217,7 +215,6 @@ def _filter_numbered_steps_by_actions(numbered_text: str, wanted: set[str], excl
     return "\n".join(out_lines).strip() or (numbered_text or "").strip()
 
 
-# ---------------- Small utilities used by next-step & filtering ----------------
 def _dedupe_lines(text: str) -> str:
     seen, out = set(), []
     for ln in (text or "").splitlines():
@@ -233,7 +230,6 @@ def _split_sentences(block: str) -> list:
     return parts if parts else ([block.strip()] if (block or "").strip() else [])
 
 
-# ------------- Numbering + text normalization used elsewhere ----------
 def _ensure_numbering(text: str) -> str:
     text = re.sub(r"[\u2060\u200B]", "", text or "")
     lines = [ln.strip() for ln in (text or "").splitlines() if ln and ln.strip()]
@@ -242,7 +238,6 @@ def _ensure_numbering(text: str) -> str:
     para = " ".join(lines).strip()
     if not para:
         return ""
-    # Hard breaks at step boundaries
     para_clean = re.sub(r"(?:\b\d+\s*[.\)])\s+", "\n\n\n", para)          # 1. / 1)
     para_clean = re.sub(r"(?:[\u2460-\u2473]\s+)", "\n\n\n", para_clean)  # circled digits
     para_clean = re.sub(r"(?i)\bstep\s*\d+\s*:\s*", "\n\n\n", para_clean) # Step 1:
@@ -307,7 +302,6 @@ def _split_sop_into_steps(numbered_text: str) -> list:
 
 
 def _format_steps_as_numbered(steps: list) -> str:
-    """Render a list of steps with circled numbers for visual continuity."""
     circled = {
         1: "\u2460", 2: "\u2461", 3: "\u2462", 4: "\u2463", 5: "\u2464",
         6: "\u2465", 7: "\u2466", 8: "\u2467", 9: "\u2468", 10: "\u2469",
@@ -320,7 +314,6 @@ def _format_steps_as_numbered(steps: list) -> str:
     return "\n".join(out)
 
 
-# ---------------- Similarity for anchor-based next steps ----------------
 def _similarity(a: str, b: str) -> float:
     a_norm, b_norm = _norm_text(a), _norm_text(b)
     ta, tb = set(a_norm.split()), set(b_norm.split())
@@ -340,9 +333,6 @@ def _similarity(a: str, b: str) -> float:
 
 
 def _extract_anchor_from_query(msg: str) -> dict:
-    """
-    Pull the anchor clause out of the user's sentence and note if a follow-up cue exists.
-    """
     raw = (msg or "").strip()
     low = _norm_text(raw)
     FOLLOWUP_CUES = ("what next", "what is next", "what to do", "then", "after that", "next")
@@ -363,10 +353,6 @@ def _extract_anchor_from_query(msg: str) -> dict:
 
 
 def _anchor_next_steps(user_message: str, numbered_text: str, max_next: int = 8) -> list | None:
-    """
-    Locate the best-matching line (or sentence inside it) for the user's anchor,
-    then return ONLY subsequent steps. Returns None if no strong anchor is found.
-    """
     steps = _split_sop_into_steps(numbered_text)
     if not steps:
         return None
@@ -413,7 +399,6 @@ def _anchor_next_steps(user_message: str, numbered_text: str, max_next: int = 8)
     return [ln for ln in _dedupe_lines("\n".join(next_steps)).splitlines() if ln.strip()]
 
 
-# ---------------- Context filtering (neutral/errors rendering) ----------------
 def _filter_context_for_query(context: str, query: str) -> Tuple[str, Dict[str, Any]]:
     STRICT_OVERLAP = 3
     MAX_SENTENCES_STRICT = 4
@@ -549,10 +534,8 @@ def _build_tracking_descriptions(issue_text: str, resolved_text: str) -> Tuple[s
     issue = (issue_text or "").strip()
     resolved = (resolved_text or "").strip()
 
-    # Strict: only the original issue/query goes into ShortDescription
-    short_desc = issue[:100]  # If empty, stays empty—backend now tries to fill from cache
+    short_desc = issue[:100]  # If empty, stays empty; backend will try to fill from cache
 
-    # DetailedDescription documents both the original issue and the user's resolution confirmation
     long_desc = (
         f'User reported: "{issue}". '
         f'User confirmation: "{resolved}". '
@@ -635,6 +618,7 @@ async def health_check():
 # ---------------------------------------------------------------------
 @app.post("/chat")
 async def chat_with_ai(input_data: ChatInput):
+    global LAST_ISSUE_HINT  # <-- ensure global declared before any assignment/use
     assist_followup: Optional[str] = None
     try:
         msg_norm = (input_data.user_message or "").lower().strip()
@@ -664,13 +648,10 @@ async def chat_with_ai(input_data: ChatInput):
             is_llm_resolved = False
         if (not _has_negation_resolved(msg_norm)) and (_is_resolution_ack_heuristic(msg_norm) or is_llm_resolved):
             try:
-                # Prefer server-side cached hint if frontend didn't pass last_issue
+                # Prefer cached issue hint if frontend didn't pass last_issue
                 issue_hint = (input_data.last_issue or "").strip()
                 if not issue_hint:
-                    try:
-                        issue_hint = LAST_ISSUE_HINT.strip()
-                    except Exception:
-                        issue_hint = ""
+                    issue_hint = LAST_ISSUE_HINT.strip()
 
                 short_desc, long_desc = _build_tracking_descriptions(issue_hint, input_data.user_message)
                 result = create_incident(short_desc, long_desc)
@@ -915,7 +896,6 @@ async def chat_with_ai(input_data: ChatInput):
         steps_override_applied = False  # for Gemini paraphrase gating
 
         if best_doc and detected_intent == "steps":
-            # prefer exact section of the top hit; fallback to all steps
             sec = (top_meta or {}).get("section")
             if sec:
                 full_steps = get_section_text(best_doc, sec)
@@ -925,11 +905,9 @@ async def chat_with_ai(input_data: ChatInput):
             if full_steps:
                 numbered_full = _ensure_numbering(full_steps)
 
-                # --- Section-aware action filtering (avoid over-trimming "update" sections) ---
                 raw_actions = set((kb_results.get("actions") or []))
                 msg_low2 = (input_data.user_message or "").lower()
 
-                # infer action from user text if extractor missed it
                 if not raw_actions and ("creation" in msg_low2 or "create" in msg_low2 or "set up" in msg_low2 or "setup" in msg_low2):
                     raw_actions = {"create"}
                 elif not raw_actions and ("update" in msg_low2 or "modify" in msg_low2 or "edit" in msg_low2 or "change" in msg_low2):
@@ -960,11 +938,9 @@ async def chat_with_ai(input_data: ChatInput):
                 if (wanted or exclude) and not skip_action_filter:
                     before = numbered_full
                     numbered_full = _filter_numbered_steps_by_actions(numbered_full, wanted=wanted, exclude=exclude)
-                    # safety: if over-trimmed to <=1 line, revert
                     if len([ln for ln in numbered_full.splitlines() if ln.strip()]) <= 1:
                         numbered_full = before
 
-                # --- Keyword-free anchor-based next-step resolver ---
                 next_only = _anchor_next_steps(input_data.user_message, numbered_full, max_next=6)
 
                 if next_only is not None:
@@ -983,12 +959,10 @@ async def chat_with_ai(input_data: ChatInput):
                     context = numbered_full
                     context_preformatted = True
 
-                # clear filter info for debug clarity
                 filt_info = {'mode': None, 'matched_count': None, 'all_sentences': None}
                 context_found = True
 
         elif best_doc and detected_intent == "errors":
-            # --- Detect explicit "not resolved" phrases ---
             said_not_resolved = (
                 _has_negation_resolved(msg_norm) or
                 bool(re.search(
@@ -999,9 +973,8 @@ async def chat_with_ai(input_data: ChatInput):
             )
 
             if said_not_resolved:
-                # Keep only the card; avoid duplicate text or dots in bubble.
                 return {
-                    "bot_response": "Select an option below.",  # short, non-duplicated helper line
+                    "bot_response": "Select an option below.",  # concise helper; avoids duplicate long sentence/dot
                     "status": "OK",
                     "context_found": False,
                     "ask_resolved": False,
@@ -1017,17 +990,13 @@ async def chat_with_ai(input_data: ChatInput):
                     },
                 }
 
-            # Build errors context
             full_errors = get_best_errors_section_text(best_doc)
             if full_errors:
                 ctx_err = _extract_errors_only(full_errors, max_lines=30)
 
-                # If it's a permissions query, trim to permission lines
                 if is_perm_query:
                     context = _filter_permission_lines(ctx_err, max_lines=6)
                 else:
-                    # Treat domain-only messages (e.g., "putaway error") as specific queries
-                    # so we filter errors to the most relevant lines instead of dumping entire heading.
                     DOMAIN_TERMS = (
                         "trailer", "shipment", "order", "load", "wave",
                         "inventory", "putaway", "receiving", "appointment",
@@ -1038,9 +1007,7 @@ async def chat_with_ai(input_data: ChatInput):
 
                     is_specific_error = (len(_detect_error_families(msg_low)) > 0) or mentions_domain_local
                     if is_specific_error:
-                        # Keep only the top overlapping sentences/bullets with the user's query
                         context = _filter_context_for_query(ctx_err, input_data.user_message)[0]
-                        # If filtering produced too little, keep a small focused set
                         if not context.strip():
                             all_lines = _normalize_lines(ctx_err)
                             error_bullets = [
@@ -1049,7 +1016,6 @@ async def chat_with_ai(input_data: ChatInput):
                             ]
                             context = "\n".join(error_bullets[:6]).strip()
                     else:
-                        # Generic fallback — a compact list
                         all_lines = _normalize_lines(ctx_err)
                         error_bullets = [
                             ln for ln in all_lines
@@ -1063,10 +1029,8 @@ async def chat_with_ai(input_data: ChatInput):
                 )
                 escalation_line = _extract_escalation_line(full_errors)
 
-                # --- Domain-aware next-step override from SOP steps (for messages like "getting putaway error")
-                # If we can anchor into steps, show only the subsequent steps for clear guidance.
                 try:
-                    if mentions_domain:  # computed earlier in the function
+                    if mentions_domain:  # computed earlier
                         steps_src = get_best_steps_section_text(best_doc)
                         if steps_src:
                             numbered_steps = _ensure_numbering(steps_src)
@@ -1079,7 +1043,6 @@ async def chat_with_ai(input_data: ChatInput):
                                 next_step_info = {"count": len(next_only), "source": "errors_domain_override"}
                                 steps_override_applied = True
                 except Exception:
-                    # Non-fatal; keep errors context
                     pass
 
         elif best_doc and detected_intent == "prereqs":
@@ -1167,9 +1130,7 @@ Return ONLY the rewritten guidance."""
 
         # ----- Cache last issue hint (used if user later says "issue resolved thanks")
         try:
-            global LAST_ISSUE_HINT
             if detected_intent == "steps":
-                # Prefer section heading if present; else user's query
                 section_heading = ((top_meta or {}).get("section") or "").strip()
                 LAST_ISSUE_HINT = (section_heading or input_data.user_message or "").strip()[:100]
             elif detected_intent == "errors":
@@ -1310,7 +1271,7 @@ def _classify_resolution_llm(user_message: str) -> bool:
 Return only 'true' or 'false'.
 Message: {user_message}"""
     headers = {"Content-Type": "application/json"}
-    payload = {"contents": [{"parts": [{"text": prompt}]}]}  # noqa: E501
+    payload = {"contents": [{"parts": [{"text": prompt}]}]}
     try:
         resp = requests.post(GEMINI_URL, headers=headers, json=payload, timeout=12, verify=GEMINI_SSL_VERIFY)
         data = resp.json()
@@ -1388,7 +1349,7 @@ def _set_incident_resolved(sys_id: str) -> bool:
         notes_field = os.getenv("SERVICENOW_RESOLUTION_NOTES_FIELD", "close_notes")
         payload_C = clean({
             "state": "6",
-            code_field: close_notes_val,  # adjust if custom fields are mapped differently
+            code_field: close_notes_val,
             notes_field: close_notes_val,
             "caller_id": caller_sysid,
             "resolved_at": datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S"),