Update main.py

main.py

@@ -43,6 +43,12 @@ 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)
+# ---------------------------------------------------------------------
+LAST_ISSUE_HINT: str = ""
+
 
 def safe_str(e: Any) -> str:
     try:
@@ -535,9 +541,6 @@ def _build_clarifying_message() -> str:
             "or should I raise a ServiceNow ticket for you?")
 
 
-
-
-
 def _build_tracking_descriptions(issue_text: str, resolved_text: str) -> Tuple[str, str]:
     """
     ShortDescription must always be the original user query / process heading / error text.
@@ -547,7 +550,7 @@ def _build_tracking_descriptions(issue_text: str, resolved_text: str) -> Tuple[s
     resolved = (resolved_text or "").strip()
 
     # Strict: only the original issue/query goes into ShortDescription
-    short_desc = issue[:100]  # If empty, stays empty—frontend should provide last_issue
+    short_desc = issue[:100]  # If empty, stays empty—backend now tries to fill from cache
 
     # DetailedDescription documents both the original issue and the user's resolution confirmation
     long_desc = (
@@ -559,7 +562,6 @@ def _build_tracking_descriptions(issue_text: str, resolved_text: str) -> Tuple[s
     return short_desc, long_desc
 
 
-
 def _is_incident_intent(msg_norm: str) -> bool:
     intent_phrases = [
         "create ticket", "create a ticket", "raise ticket", "raise a ticket", "open ticket", "open a ticket",
@@ -662,7 +664,15 @@ 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:
-                short_desc, long_desc = _build_tracking_descriptions(input_data.last_issue, input_data.user_message)
+                # Prefer server-side cached 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 = ""
+
+                short_desc, long_desc = _build_tracking_descriptions(issue_hint, input_data.user_message)
                 result = create_incident(short_desc, long_desc)
                 if isinstance(result, dict) and not result.get("error"):
                     inc_number = result.get("number", "<unknown>")
@@ -902,6 +912,7 @@ async def chat_with_ai(input_data: ChatInput):
         next_step_applied = False
         next_step_info: Dict[str, Any] = {}
         context_preformatted = False
+        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
@@ -976,10 +987,8 @@ async def chat_with_ai(input_data: ChatInput):
                 filt_info = {'mode': None, 'matched_count': None, 'all_sentences': None}
                 context_found = True
 
-        
-        
         elif best_doc and detected_intent == "errors":
-            # --- NEW: detect explicit "not resolved" phrases ---
+            # --- Detect explicit "not resolved" phrases ---
             said_not_resolved = (
                 _has_negation_resolved(msg_norm) or
                 bool(re.search(
@@ -990,9 +999,9 @@ async def chat_with_ai(input_data: ChatInput):
             )
 
             if said_not_resolved:
-                # Suppress the long error bullets reply; let the frontend card handle this flow.
+                # Keep only the card; avoid duplicate text or dots in bubble.
                 return {
-                    "bot_response": "\u00A0",      # zero-width space → no visible bubble; no "No response text"
+                    "bot_response": "Select an option below.",  # short, non-duplicated helper line
                     "status": "OK",
                     "context_found": False,
                     "ask_resolved": False,
@@ -1005,19 +1014,17 @@ async def chat_with_ai(input_data: ChatInput):
                     "debug": {
                        "intent": "errors_not_resolved",
                        "best_doc": best_doc,
-                           },
+                    },
                 }
 
             # Build errors context
             full_errors = get_best_errors_section_text(best_doc)
-            steps_override_applied = False
             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.
@@ -1075,7 +1082,6 @@ async def chat_with_ai(input_data: ChatInput):
                     # Non-fatal; keep errors context
                     pass
 
-
         elif best_doc and detected_intent == "prereqs":
             full_prereqs = _find_prereq_section_text(best_doc)
             if full_prereqs:
@@ -1159,6 +1165,28 @@ Return ONLY the rewritten guidance."""
 
         options = [{"type": "yesno", "title": "Share details or raise a ticket?"}] if status == "PARTIAL" else []
 
+        # ----- 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":
+                shown_lines = [ln.strip() for ln in (bot_text or "").splitlines() if ln.strip()]
+                top_error_line = ""
+                for ln in shown_lines:
+                    if re.match(r"^\s*[\-\*\u2022]\s*", ln) or ":" in ln:
+                        top_error_line = ln
+                        break
+                base = (input_data.user_message or "").strip()
+                if top_error_line:
+                    LAST_ISSUE_HINT = f"{base} — {top_error_line}".strip()[:100]
+                else:
+                    LAST_ISSUE_HINT = base[:100]
+        except Exception:
+            pass
+
         return {
             "bot_response": bot_text,
             "status": status,
@@ -1282,7 +1310,7 @@ 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}]}]}
+    payload = {"contents": [{"parts": [{"text": prompt}]}]}  # noqa: E501
     try:
         resp = requests.post(GEMINI_URL, headers=headers, json=payload, timeout=12, verify=GEMINI_SSL_VERIFY)
         data = resp.json()