gateway-bot/http_api.py

@@ -4,6 +4,7 @@ Handles incoming webhooks from Telegram, Discord, etc.
 """
 import asyncio
 import base64
+import copy
 import json
 import re
 import logging
@@ -61,6 +62,10 @@ PENDING_STATE_TTL = 1800  # 30 minutes
 USER_LANGUAGE_PREFS: Dict[str, Dict[str, Any]] = {}
 USER_LANGUAGE_PREF_TTL = 30 * 24 * 3600  # 30 days
 
+# Per-user response style cache (agent:chat:user -> {style, ts})
+USER_RESPONSE_STYLE_PREFS: Dict[str, Dict[str, Any]] = {}
+USER_RESPONSE_STYLE_PREF_TTL = 30 * 24 * 3600  # 30 days
+
 # Recent photo context for follow-up questions in chat (agent:chat:user -> {file_id, ts})
 RECENT_PHOTO_CONTEXT: Dict[str, Dict[str, Any]] = {}
 RECENT_PHOTO_TTL = 30 * 60  # 30 minutes
@@ -88,16 +93,120 @@ def _get_recent_photo_file_id(agent_id: str, chat_id: str, user_id: str) -> Opti
     return rec.get("file_id")
 
 
+def _extract_recent_photo_file_id_from_memory(memory_context: Dict[str, Any]) -> Optional[str]:
+    """
+    Extract last seen Telegram photo file_id from memory context.
+    Looks for patterns like: [Photo: <file_id>]
+    """
+    if not memory_context:
+        return None
+
+    pattern = re.compile(r"\[Photo:\s*([^\]\s]+)\]")
+
+    recent_events = memory_context.get("recent_events", []) or []
+    for ev in reversed(recent_events):
+        body = (ev.get("body_text") or "").strip()
+        if not body:
+            continue
+        m = pattern.search(body)
+        if m:
+            return m.group(1)
+
+    local_text = memory_context.get("local_context_text") or ""
+    for line in reversed(local_text.splitlines()):
+        m = pattern.search(line)
+        if m:
+            return m.group(1)
+    return None
+
+
 def _looks_like_photo_followup(text: str) -> bool:
     if not text:
         return False
     t = text.strip().lower()
-    markers = [
+    direct_markers = [
         "що ти бачиш", "що на фото", "що на зображенні", "опиши фото", "подивись фото",
+        "що на цьому фото", "що на цій фотографії", "що на цій світлині",
+        "проаналізуй фото", "аналіз фото", "переглянь фото", "повернись до фото",
+        "яка це рослина", "що це за рослина", "що за рослина", "що за культура",
+        "яка культура", "визнач рослину",
         "what do you see", "what is in the image", "describe the photo",
+        "analyze the photo", "analyze image", "what plant is this",
         "что ты видишь", "что на фото", "опиши фото", "посмотри фото",
+        "проанализируй фото", "какое это растение", "что за растение",
     ]
-    return any(m in t for m in markers)
+    if any(m in t for m in direct_markers):
+        return True
+
+    # If user is correcting previous visual interpretation, route to vision again.
+    correction_markers = [
+        "неправильна відповідь", "не правильна відповідь", "не видумуй", "це не так",
+        "ти помилився", "ти помилилась", "неправильно визначив",
+        "wrong answer", "you are wrong", "that is incorrect",
+        "неправильный ответ", "это не так", "ты ошибся",
+    ]
+    photo_topic_markers = ["фото", "зображ", "рослин", "image", "photo", "plant", "растен"]
+    if any(c in t for c in correction_markers) and any(p in t for p in photo_topic_markers):
+        return True
+
+    # Flexible forms: "що на ... фото/зображенні/світлині"
+    if re.search(r"(що|what|что)\s+на\s+.*(фото|зображ|світлин|image|photo)", t):
+        # Exclude common meta-questions
+        meta_exclude = ["канал", "чат", "бот", "нормально"]
+        if not any(ex in t for ex in meta_exclude):
+            return True
+    return False
+
+
+def _extract_unanswered_user_messages(
+    memory_context: Dict[str, Any],
+    current_user_id: str,
+    max_items: int = 3,
+) -> List[str]:
+    """
+    Extract unresolved user questions from structured memory events.
+    A user message is considered unresolved if no later agent reply exists.
+    """
+    events = memory_context.get("recent_events") or []
+    if not isinstance(events, list) or not current_user_id:
+        return []
+
+    pending: List[str] = []
+    for ev in events:
+        role = str(ev.get("role") or ev.get("type") or "").lower()
+        text = str(ev.get("body_text") or "").strip()
+        if not text:
+            continue
+        if role == "user" and str(ev.get("user_id") or "") == current_user_id:
+            pending.append(text)
+            continue
+        if role in ("assistant", "agent") and pending:
+            # Assume latest agent reply resolved the oldest pending user question.
+            pending.pop(0)
+
+    # Keep the latest unresolved items only.
+    if len(pending) > max_items:
+        pending = pending[-max_items:]
+    return pending
+
+
+def _is_question_like(text: str) -> bool:
+    """
+    Detect user questions without false positives from substring matches
+    (e.g. 'схоже' should not match 'що').
+    """
+    if not text:
+        return False
+    t = text.strip().lower()
+    if "?" in t:
+        return True
+    # Ukrainian / Russian / English interrogatives with word boundaries.
+    return bool(
+        re.search(
+            r"\b(що|як|чому|коли|де|хто|чи|what|why|how|when|where|who|зачем|почему|когда|где|кто|ли)\b",
+            t,
+        )
+    )
 
 
 def _cleanup_user_language_prefs() -> None:
@@ -107,6 +216,13 @@ def _cleanup_user_language_prefs() -> None:
         del USER_LANGUAGE_PREFS[k]
 
 
+def _cleanup_user_response_style_prefs() -> None:
+    now = time.time()
+    expired = [k for k, v in USER_RESPONSE_STYLE_PREFS.items() if now - float(v.get("ts", 0)) > USER_RESPONSE_STYLE_PREF_TTL]
+    for k in expired:
+        del USER_RESPONSE_STYLE_PREFS[k]
+
+
 def _normalize_lang_code(raw: Optional[str]) -> Optional[str]:
     if not raw:
         return None
@@ -855,6 +971,242 @@ def should_force_concise_reply(text: str) -> bool:
     return True
 
 
+def _detect_response_style_signal(text: str) -> Optional[str]:
+    t = (text or "").strip().lower()
+    if not t:
+        return None
+    concise_markers = ["коротко", "коротка відповідь", "лаконічно", "brief", "short answer"]
+    detailed_markers = ["детально", "розгорнуто", "поясни детальніше", "deep dive", "step by step"]
+    if any(m in t for m in detailed_markers):
+        return "detailed"
+    if any(m in t for m in concise_markers):
+        return "concise"
+    return None
+
+
+async def resolve_response_style_preference(
+    agent_id: str,
+    chat_id: str,
+    user_id: str,
+    text: str,
+    team_id: Optional[str],
+) -> str:
+    _cleanup_user_response_style_prefs()
+    cache_key = f"{agent_id}:{chat_id}:{user_id}"
+    signal = _detect_response_style_signal(text)
+    now = time.time()
+    if signal in ("concise", "detailed"):
+        USER_RESPONSE_STYLE_PREFS[cache_key] = {"style": signal, "ts": now}
+        await memory_client.upsert_fact(
+            user_id=f"tg:{user_id}",
+            fact_key=f"communication_profile:{agent_id}",
+            fact_value_json={"response_style": signal, "updated_at": datetime.utcnow().isoformat()},
+            team_id=team_id,
+        )
+        return signal
+
+    cached = USER_RESPONSE_STYLE_PREFS.get(cache_key)
+    if cached:
+        return str(cached.get("style") or "concise")
+
+    fact = await memory_client.get_fact(
+        user_id=f"tg:{user_id}",
+        fact_key=f"communication_profile:{agent_id}",
+        team_id=team_id,
+    )
+    if fact:
+        data = fact.get("fact_value_json") if isinstance(fact, dict) else None
+        if isinstance(data, str):
+            try:
+                data = json.loads(data)
+            except Exception:
+                data = None
+        if isinstance(data, dict):
+            style = str(data.get("response_style") or "").lower()
+            if style in ("concise", "detailed"):
+                USER_RESPONSE_STYLE_PREFS[cache_key] = {"style": style, "ts": now}
+                return style
+    return "concise"
+
+
+def _redact_private_mentions(text: str) -> str:
+    if not text:
+        return ""
+    sanitized = text
+    sanitized = re.sub(r"(?i)(email|e-mail)\s*[:\-]?\s*[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,}", r"\1: [redacted]", sanitized)
+    sanitized = re.sub(r"(?i)\b[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,}\b", "[redacted-email]", sanitized)
+    sanitized = re.sub(r"(?<!\d)(\+?\d[\d\s\-\(\)]{8,}\d)(?!\d)", "[redacted-phone]", sanitized)
+    return sanitized
+
+
+def _is_private_profile_dump_request(user_text: str) -> bool:
+    t = (user_text or "").lower()
+    if not t:
+        return False
+    markers = [
+        "приватн", "контакт ментор", "телефон ментор", "email ментор",
+        "всі контакти", "скинь контакти", "private data", "mentor contacts",
+    ]
+    return any(m in t for m in markers)
+
+
+def _block_private_profile_dump(user_text: str) -> Optional[str]:
+    if not _is_private_profile_dump_request(user_text):
+        return None
+    return (
+        "Не можу надавати приватні дані людей (контакти, особисті профілі). "
+        "Можу дати лише публічну, узагальнену інформацію."
+    )
+
+
+def _is_numeric_question(text: str) -> bool:
+    t = (text or "").lower()
+    if not t:
+        return False
+    markers = ["скільки", "сума", "витрат", "добрив", "грн", "кг", "вартість", "cost", "amount", "total", "spent"]
+    return any(m in t for m in markers)
+
+
+def _has_numeric_answer_contract(answer_text: str) -> bool:
+    a = (answer_text or "").lower()
+    if not a:
+        return False
+    has_value = bool(re.search(r"\d", a))
+    has_unit = any(u in a for u in ("грн", "uah", "usd", "eur", "кг", "kg", "%"))
+    has_source = any(s in a for s in ("рядок", "лист", "sheet", "row", "джерело"))
+    return has_value and has_unit and has_source
+
+
+def _answer_seems_off_intent(user_text: str, answer_text: str) -> bool:
+    u = (user_text or "").lower()
+    a = (answer_text or "").lower()
+    if not u or not a:
+        return False
+
+    if _is_numeric_question(u) and not _has_numeric_answer_contract(answer_text):
+        return True
+
+    if any(k in u for k in ("excel", "xlsx", "таблиц", "файл", "звіт")) and any(
+        k in a for k in ("вступ", "структура", "презентаці", "слайд")
+    ):
+        return True
+    return False
+
+
+def _sanitize_agent_answer(agent_id: str, user_text: str, answer_text: str) -> str:
+    blocked = _block_private_profile_dump(user_text)
+    if blocked:
+        return blocked
+    sanitized = _redact_private_mentions(answer_text or "")
+    return sanitized
+
+
+def _strip_answer_markup_noise(answer_text: str) -> str:
+    if not answer_text:
+        return ""
+    cleaned = answer_text.strip()
+    cleaned = re.sub(r"^\s*\*{1,3}\s*коротка відповідь\s*:?\s*\*{0,3}\s*", "", cleaned, flags=re.IGNORECASE)
+    cleaned = re.sub(r"^\s*\*{1,3}\s*відповідь\s*:?\s*\*{0,3}\s*", "", cleaned, flags=re.IGNORECASE)
+    cleaned = re.sub(r"^\s*#+\s*", "", cleaned)
+    # Remove markdown emphasis noise that leaks into short answers
+    cleaned = cleaned.replace("**", "")
+    cleaned = cleaned.replace("__", "")
+    return cleaned.strip()
+
+
+def _compress_bulleted_answer(answer_text: str, max_items: int = 3) -> str:
+    if not answer_text:
+        return ""
+    lines = [ln.strip() for ln in answer_text.splitlines() if ln.strip()]
+    bullet_lines: List[str] = []
+    for ln in lines:
+        normalized = ln.replace("**", "").replace("__", "").strip()
+        if re.match(r"^(\*?\s*[-*•]|\*?\s*\d+[\.\):])\s*", normalized):
+            item = re.sub(r"^(\*?\s*[-*•]|\*?\s*\d+[\.\):])\s*", "", normalized).strip()
+            item = re.sub(r"\s+", " ", item).strip(" -–—")
+            item = re.sub(r"\.{2,}", ".", item)
+            item = re.sub(r"\s+\.", ".", item)
+            # Keep concise mode truly short: first complete sentence from each bullet.
+            parts = re.split(r"(?<=[.!?…])\s+", item)
+            if parts:
+                item = parts[0].strip()
+            item = item.rstrip(":").strip()
+            if item:
+                bullet_lines.append(item)
+    if not bullet_lines:
+        return answer_text.strip()
+    picked = bullet_lines[:max_items]
+    joined = ". ".join(picked)
+    if joined and not joined.endswith((".", "!", "?")):
+        joined += "."
+    joined = re.sub(r"\s+", " ", joined).strip()
+    return joined or answer_text.strip()
+
+
+def _limit_to_sentences(text: str, max_sentences: int = 3) -> str:
+    if not text:
+        return ""
+    parts = re.split(r"(?<=[.!?…])\s+", text.strip())
+    parts = [p.strip() for p in parts if p.strip()]
+    if len(parts) <= max_sentences:
+        return " ".join(parts).strip()
+    return " ".join(parts[:max_sentences]).strip()
+
+
+def _agromatrix_rewrite_capability_limitations(user_text: str, answer_text: str) -> str:
+    if not answer_text:
+        return answer_text
+    low = answer_text.lower()
+    limitation_markers = (
+        "не можу бачити", "не можу переглядати зображення", "не маю доступу до зображень",
+        "працюю лише з текстом", "працюю виключно з текстом",
+        "cannot view images", "cannot analyze images", "as a text model",
+    )
+    if not any(m in low for m in limitation_markers):
+        return answer_text
+
+    ulow = (user_text or "").lower()
+    photo_markers = ("фото", "зображ", "image", "photo", "картин", "світлин")
+    if any(m in ulow for m in photo_markers):
+        return (
+            "Можу аналізувати фото. Надішли, будь ласка, зображення ще раз одним повідомленням "
+            "з коротким питанням, і я дам точний розбір."
+        )
+
+    return (
+        "Можу працювати природною мовою та з мультимодальністю: фото, голос і документи. "
+        "Сформулюй запит коротко, і я відповім по суті."
+    )
+
+
+def postprocess_agent_answer(
+    agent_id: str,
+    user_text: str,
+    answer_text: str,
+    force_detailed: bool,
+    needs_complex_reasoning: bool,
+) -> str:
+    if not answer_text:
+        return answer_text
+
+    if (agent_id or "").lower() != "agromatrix":
+        return answer_text
+
+    # Keep detailed/complex answers intact.
+    if force_detailed or needs_complex_reasoning:
+        return answer_text
+
+    user_text_len = len((user_text or "").strip())
+    if user_text_len > 280:
+        return _agromatrix_rewrite_capability_limitations(user_text, answer_text)
+
+    cleaned = _strip_answer_markup_noise(answer_text)
+    cleaned = _agromatrix_rewrite_capability_limitations(user_text, cleaned)
+    compact = _compress_bulleted_answer(cleaned, max_items=1)
+    short = _limit_to_sentences(compact, max_sentences=3)
+    return short or answer_text
+
+
 COMPLEX_REASONING_KEYWORDS = [
     "стратег", "roadmap", "алгоритм", "architecture", "архітектур",
     "прогноз", "scenario", "модель", "аналіз", "побудуй", "plan", "дослідж",
@@ -2148,12 +2500,45 @@ async def handle_telegram_webhook(
         text = update.message.get("text", "")
         caption = update.message.get("caption", "")
 
-    # If user asks about a recently sent photo, run vision on cached photo file_id.
+    # Photo/image intent guard:
-    if text and _looks_like_photo_followup(text):
+    # if text references a photo/image, try to resolve latest file_id and route to vision.
+    photo_intent = False
+    if text:
+        tl = text.lower()
+        photo_intent = _looks_like_photo_followup(text) or any(
+            k in tl for k in ("фото", "зображ", "світлин", "image", "photo")
+        )
+        if not photo_intent:
+            # Robust fallback for common formulations like "що на цьому фото?"
+            photo_intent = bool(
+                re.search(r"(що|what|что).{0,24}(цьому|этом|this).{0,24}(фото|зображ|світлин|image|photo)", tl)
+            )
+
+    if photo_intent:
         recent_file_id = _get_recent_photo_file_id(agent_config.agent_id, chat_id, user_id)
+
+        # Fallback: recover latest photo file_id from memory-service context (survives process restarts).
+        if not recent_file_id:
+            try:
+                mc = await memory_client.get_context(
+                    user_id=f"tg:{user_id}",
+                    agent_id=agent_config.agent_id,
+                    team_id=dao_id,
+                    channel_id=chat_id,
+                    limit=80,
+                )
+                recent_file_id = _extract_recent_photo_file_id_from_memory(mc)
+                if recent_file_id:
+                    _set_recent_photo_context(agent_config.agent_id, chat_id, user_id, recent_file_id)
+                    logger.info(
+                        f"{agent_config.name}: Recovered photo file_id from memory context for follow-up: {recent_file_id}"
+                    )
+            except Exception as e:
+                logger.warning(f"{agent_config.name}: failed to recover photo file_id from memory: {e}")
+
         if recent_file_id:
             logger.info(
-                f"{agent_config.name}: Detected follow-up photo question; using cached file_id={recent_file_id}"
+                f"{agent_config.name}: Photo intent detected; using file_id={recent_file_id}"
             )
             followup_result = await process_photo(
                 agent_config=agent_config,
@@ -2168,6 +2553,16 @@ async def handle_telegram_webhook(
             )
             return followup_result
 
+        # Hard guard: don't send photo-related requests to text LLM path when image context is missing.
+        is_question_like = ("?" in text) or any(k in tl for k in ("що", "опиши", "проанал", "what", "describe", "analy", "что"))
+        if is_question_like:
+            await send_telegram_message(
+                chat_id,
+                "Бачу питання про фото, але не знайшов зображення в історії сесії. Надішли фото ще раз з коротким питанням, і я одразу проаналізую.",
+                telegram_token,
+            )
+            return {"ok": True, "handled": True, "reason": "photo_followup_without_image_context"}
+        
         if not text and not caption:
             # Check for unsupported message types and silently ignore
             unsupported_types = ["sticker", "animation", "video_note", "contact", "location", 
@@ -2218,32 +2613,52 @@ async def handle_telegram_webhook(
     
     # If there's a doc_id and the message looks like a question about the document
     if doc_context and doc_context.doc_id:
-        # Check if it's a question (simple heuristic: contains question words or ends with ?)
+        is_question = _is_question_like(text)
-        is_question = (
-            "?" in text or
-            any(word in text.lower() for word in ["що", "як", "чому", "коли", "де", "хто", "чи"])
-        )
         
         if is_question:
             logger.info(f"{agent_config.name}: Follow-up question detected for doc_id={doc_context.doc_id}")
             # Try RAG query first
-            rag_result = await ask_about_document(
+            try:
-                session_id=session_id,
+                rag_result = await asyncio.wait_for(
-                question=text,
+                    ask_about_document(
-                doc_id=doc_context.doc_id,
+                        session_id=session_id,
-                dao_id=dao_id or doc_context.dao_id,
+                        question=text,
-                user_id=f"tg:{user_id}"
+                        doc_id=doc_context.doc_id,
-            )
+                        dao_id=dao_id or doc_context.dao_id,
+                        user_id=f"tg:{user_id}",
+                        agent_id=agent_config.agent_id,
+                    ),
+                    timeout=25.0,
+                )
+            except asyncio.TimeoutError:
+                logger.warning(
+                    f"{agent_config.name}: doc follow-up timeout for doc_id={doc_context.doc_id}; "
+                    "fallback to regular chat path"
+                )
+                rag_result = None
             
-            if rag_result.success and rag_result.answer:
+            if rag_result and rag_result.success and rag_result.answer:
                 # Truncate if too long for Telegram
-                answer = rag_result.answer
+                answer = postprocess_agent_answer(
+                    agent_id=agent_config.agent_id,
+                    user_text=text or "",
+                    answer_text=rag_result.answer,
+                    force_detailed=should_force_detailed_reply(text),
+                    needs_complex_reasoning=requires_complex_reasoning(text),
+                )
                 if len(answer) > TELEGRAM_SAFE_LENGTH:
                     answer = answer[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
                 
+                answer = _sanitize_agent_answer(agent_config.agent_id, text or "", answer)
                 await send_telegram_message(chat_id, answer, telegram_token)
                 return {"ok": True, "agent": "parser", "mode": "rag_query"}
-            # Fall through to regular chat if RAG query fails
+            # Source-lock: with active document context answer only from that document.
+            await send_telegram_message(
+                chat_id,
+                "Не знайшов точну відповідь у поточному документі. Уточни питання або надішли файл повторно.",
+                telegram_token,
+            )
+            return {"ok": True, "agent": "parser", "mode": "source_lock_no_answer"}
     
     # ========================================
     # BEHAVIOR POLICY v2.1: Check if should respond
@@ -2297,6 +2712,19 @@ async def handle_telegram_webhook(
     respond_decision = sowa_decision.should_respond
     respond_reason = sowa_decision.reason
 
+    # AgroMatrix usability guard:
+    # In dedicated chats users often ask short operational questions without explicit mention.
+    # Do not silence clear question turns for agromatrix.
+    if (
+        sowa_decision.action == "SILENT"
+        and agent_config.agent_id == "agromatrix"
+        and _is_question_like(text)
+    ):
+        sowa_decision.action = "FULL"
+        sowa_decision.should_respond = True
+        respond_decision = True
+        respond_reason = "agromatrix_question_guard"
+    
     if sowa_decision.action == "SILENT":
         logger.info(f"\U0001f507 SOWA: Agent {agent_config.agent_id} NOT responding. Reason: {respond_reason}")
         # Save to memory for context tracking, but don't respond
@@ -2398,11 +2826,30 @@ async def handle_telegram_webhook(
         training_prefix = "[РЕЖИМ НАВЧАННЯ - відповідай на це повідомлення, ти в навчальній групі Agent Preschool]\n\n"
         logger.info(f"🎓 Training mode activated for chat {chat_id}")
     
+    unresolved_questions = _extract_unanswered_user_messages(
+        memory_context=memory_context,
+        current_user_id=f"tg:{user_id}",
+        max_items=3,
+    )
+    unresolved_block = ""
+    if unresolved_questions:
+        # Do not duplicate current prompt if it matches one pending message.
+        filtered = [q for q in unresolved_questions if q.strip() != (text or "").strip()]
+        if filtered:
+            unresolved_block = "[Невідповідані питання цього користувача]\n" + "\n".join(
+                f"- {q}" for q in filtered
+            ) + "\n\n"
+
     if local_history:
         # Add conversation history to message for better context understanding
-        message_with_context = f"{training_prefix}[Контекст розмови]\n{local_history}\n\n[Поточне повідомлення від {username}]\n{text}"
+        message_with_context = (
+            f"{training_prefix}"
+            f"[Контекст розмови]\n{local_history}\n\n"
+            f"{unresolved_block}"
+            f"[Поточне повідомлення від {username}]\n{text}"
+        )
     else:
-        message_with_context = f"{training_prefix}{text}"
+        message_with_context = f"{training_prefix}{unresolved_block}{text}"
     
     preferred_lang = await resolve_preferred_language_persistent(
         chat_id=chat_id,
@@ -2412,6 +2859,15 @@ async def handle_telegram_webhook(
         team_id=dao_id,
     )
     preferred_lang_label = preferred_language_label(preferred_lang)
+    response_style_pref = await resolve_response_style_preference(
+        agent_id=agent_config.agent_id,
+        chat_id=chat_id,
+        user_id=str(user_id),
+        text=text or "",
+        team_id=dao_id,
+    )
+    force_detailed = should_force_detailed_reply(text) or response_style_pref == "detailed"
+    force_concise = (not force_detailed) and (should_force_concise_reply(text) or response_style_pref == "concise")
 
     # Build request to Router
     system_prompt = agent_config.system_prompt
@@ -2432,6 +2888,7 @@ async def handle_telegram_webhook(
             "session_id": f"tg:{chat_id}:{dao_id}",
             "username": username,
             "chat_id": chat_id,
+            "raw_user_text": text,
             "sender_is_bot": is_sender_bot,
             "mentioned_bots": mentioned_bots,
             "requires_complex_reasoning": needs_complex_reasoning,
@@ -2439,6 +2896,7 @@ async def handle_telegram_webhook(
             "is_training_group": is_training_group,
             "preferred_response_language": preferred_lang,
             "preferred_response_language_label": preferred_lang_label,
+            "response_style_preference": response_style_pref,
         },
         "context": {
             "agent_name": agent_config.name,
@@ -2451,10 +2909,10 @@ async def handle_telegram_webhook(
         },
     }
     
-    if should_force_detailed_reply(text):
+    if force_detailed:
         router_request["metadata"]["force_detailed"] = True
 
-    if should_force_concise_reply(text):
+    if force_concise:
         # IMPORTANT: preserve conversation context! Only append concise instruction
         router_request["metadata"]["force_concise"] = True
         router_request["message"] = (
@@ -2473,7 +2931,7 @@ async def handle_telegram_webhook(
         router_request["metadata"]["provider"] = "cloud_deepseek"
         router_request["metadata"]["reason"] = "auto_complex"
 
-    if not should_force_concise_reply(text):
+    if not force_concise:
         router_request["message"] = (
             router_request["message"]
             + f"\n\n(Мова відповіді: {preferred_lang_label}.)"
@@ -2551,9 +3009,39 @@ async def handle_telegram_webhook(
             )
             return {"ok": True, "skipped": True, "reason": "no_output_from_llm"}
 
-        # Truncate if too long for Telegram
+        # Retry policy: if response drifts from current intent, do one strict reroute.
-        if len(answer_text) > TELEGRAM_SAFE_LENGTH:
+        if _answer_seems_off_intent(text or "", answer_text):
-            answer_text = answer_text[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
+            try:
+                strict_request = copy.deepcopy(router_request)
+                strict_request["metadata"]["intent_retry"] = 1
+                strict_request["metadata"]["disable_tools"] = True
+                strict_request["metadata"]["max_tool_rounds"] = 1
+                strict_request["metadata"]["temperature"] = 0.1
+                strict_request["message"] = (
+                    f"{message_with_context}\n\n"
+                    "(Жорстка інструкція: відповідай тільки на ПОТОЧНЕ питання користувача. "
+                    "Не змінюй тему, не генеруй презентацію/план, якщо цього не просили. "
+                    "Для числових питань: дай value + unit + джерело (лист/рядок).)"
+                )
+                retry_response = await send_to_router(strict_request)
+                if isinstance(retry_response, dict) and retry_response.get("ok"):
+                    retry_text = retry_response.get("data", {}).get("text") or retry_response.get("response", "")
+                    if retry_text and not is_no_output_response(retry_text):
+                        answer_text = retry_text
+                        router_request = strict_request
+                        logger.info("Intent retry succeeded with strict prompt")
+            except Exception as retry_err:
+                logger.warning(f"Intent retry failed: {retry_err}")
+        
+        force_detailed_reply = bool(router_request.get("metadata", {}).get("force_detailed"))
+        answer_text = postprocess_agent_answer(
+            agent_id=agent_config.agent_id,
+            user_text=text or "",
+            answer_text=answer_text,
+            force_detailed=force_detailed_reply,
+            needs_complex_reasoning=needs_complex_reasoning,
+        )
+        answer_text = _sanitize_agent_answer(agent_config.agent_id, text or "", answer_text)
         
         # Skip Telegram sending for prober requests (chat_id=0)
         if is_prober:
@@ -2591,7 +3079,9 @@ async def handle_telegram_webhook(
                 
                 async with httpx.AsyncClient() as client:
                     files = {"photo": ("image.png", BytesIO(image_bytes), "image/png")}
-                    data = {"chat_id": chat_id, "caption": answer_text}
+                    # Telegram caption limit is 1024 chars.
+                    safe_caption = (answer_text or "")[:1024]
+                    data = {"chat_id": chat_id, "caption": safe_caption}
                     response_photo = await client.post(url, files=files, data=data, timeout=30.0)
                     response_photo.raise_for_status()
                     logger.info(f"✅ Sent generated image to Telegram chat {chat_id}")
@@ -2995,26 +3485,39 @@ async def _old_telegram_webhook(update: TelegramUpdate):
         
         # If there's a doc_id and the message looks like a question about the document
         if doc_context and doc_context.doc_id:
-            # Check if it's a question (simple heuristic: contains question words or ends with ?)
+            is_question = _is_question_like(text)
-            is_question = (
-                "?" in text or
-                any(word in text.lower() for word in ["що", "як", "чому", "коли", "де", "хто", "чи"])
-            )
             
             if is_question:
                 logger.info(f"Follow-up question detected for doc_id={doc_context.doc_id}")
                 # Try RAG query first
-                rag_result = await ask_about_document(
+                try:
-                    session_id=session_id,
+                    rag_result = await asyncio.wait_for(
-                    question=text,
+                        ask_about_document(
-                    doc_id=doc_context.doc_id,
+                            session_id=session_id,
-                    dao_id=dao_id or doc_context.dao_id,
+                            question=text,
-                    user_id=f"tg:{user_id}"
+                            doc_id=doc_context.doc_id,
-                )
+                            dao_id=dao_id or doc_context.dao_id,
+                            user_id=f"tg:{user_id}",
+                            agent_id=agent_config.agent_id,
+                        ),
+                        timeout=25.0,
+                    )
+                except asyncio.TimeoutError:
+                    logger.warning(
+                        f"Doc follow-up timeout for agent={agent_config.agent_id}, "
+                        f"doc_id={doc_context.doc_id}; fallback to regular chat path"
+                    )
+                    rag_result = None
                 
-                if rag_result.success and rag_result.answer:
+                if rag_result and rag_result.success and rag_result.answer:
                     # Truncate if too long for Telegram
-                    answer = rag_result.answer
+                    answer = postprocess_agent_answer(
+                        agent_id=agent_config.agent_id,
+                        user_text=text or "",
+                        answer_text=rag_result.answer,
+                        force_detailed=should_force_detailed_reply(text),
+                        needs_complex_reasoning=requires_complex_reasoning(text),
+                    )
                     if len(answer) > TELEGRAM_SAFE_LENGTH:
                         answer = answer[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
                     
@@ -3532,44 +4035,51 @@ async def send_telegram_message(chat_id: str, text: str, bot_token: Optional[str
         return False
 
     # Defensive cleanup for occasional reasoning/markup leaks.
-    import re
     safe_text = re.sub(r'<think>.*?</think>', '', text or "", flags=re.DOTALL)
     safe_text = re.sub(r'<think>.*$', '', safe_text, flags=re.DOTALL)
     safe_text = safe_text.strip() or "..."
 
     token_id = telegram_token.split(":", 1)[0] if ":" in telegram_token else "unknown"
     url = f"https://api.telegram.org/bot{telegram_token}/sendMessage"
-    payload = {
-        "chat_id": str(chat_id),
-        "text": safe_text,
-        "disable_web_page_preview": True,
-    }
 
-    try:
+    async def _send_chunk(chunk: str) -> bool:
-        async with httpx.AsyncClient() as client:
+        payload = {
-            response = await client.post(url, json=payload, timeout=15.0)
+            "chat_id": str(chat_id),
+            "text": chunk,
+            "disable_web_page_preview": True,
+        }
+        try:
+            async with httpx.AsyncClient() as client:
+                response = await client.post(url, json=payload, timeout=15.0)
 
-        if response.status_code >= 400:
+            if response.status_code >= 400:
-            err_desc = response.text[:300]
+                err_desc = response.text[:300]
-            try:
+                try:
-                body = response.json()
+                    body = response.json()
-                err_desc = body.get("description") or err_desc
+                    err_desc = body.get("description") or err_desc
-            except Exception:
+                except Exception:
-                pass
+                    pass
-            logger.error(
+                logger.error(
-                "Telegram sendMessage failed: bot_id=%s chat_id=%s status=%s desc=%s",
+                    "Telegram sendMessage failed: bot_id=%s chat_id=%s status=%s desc=%s",
-                token_id,
+                    token_id,
-                chat_id,
+                    chat_id,
-                response.status_code,
+                    response.status_code,
-                err_desc,
+                    err_desc,
-            )
+                )
+                return False
+            return True
+        except Exception as e:
+            logger.error("Telegram sendMessage exception: bot_id=%s chat_id=%s error=%s", token_id, chat_id, e)
             return False
 
-        logger.info("Telegram message sent: bot_id=%s chat_id=%s", token_id, chat_id)
+    all_ok = True
-        return True
+    chunks = _chunk_text(safe_text, max_len=TELEGRAM_MAX_MESSAGE_LENGTH)
-    except Exception as e:
+    for chunk in chunks:
-        logger.error("Telegram sendMessage exception: bot_id=%s chat_id=%s error=%s", token_id, chat_id, e)
+        sent = await _send_chunk(chunk)
-        return False
+        all_ok = all_ok and sent
+    if all_ok:
+        logger.info("Telegram message sent: bot_id=%s chat_id=%s chunks=%s", token_id, chat_id, len(chunks))
+    return all_ok
 
 
 # ========================================