feat: Behavior Policy v1 - Silent-by-default + Short-first + Media-no-comment

NODA1 agents now: - Don't respond to broadcasts/posters/announcements without direct mention - Don't respond to media (photo/link) without explicit question - Keep responses short (1-2 sentences by default) - No emoji, no "ready to help", no self-promotion Added: - behavior_policy.py: detect_directed_to_agent(), detect_broadcast_intent(), should_respond() - behavior_policy_v1.txt: unified policy block for all prompts - Pre-LLM check in http_api.py: skip Router call if should_respond=False - NO_OUTPUT handling: don't send to Telegram if LLM returns empty - Updated all 9 agent prompts with Behavior Policy v1 - Unit and E2E tests for 5 acceptance cases
2026-02-04 09:03:14 -08:00
parent c8698f6a1d
commit 134c044c21
13 changed files with 1477 additions and 134 deletions
--- a/gateway-bot/behavior_policy.py
+++ b/gateway-bot/behavior_policy.py
@@ -0,0 +1,451 @@
+"""
+Behavior Policy v1: Silent-by-default + Short-first + Media-no-comment
+Уніфікована логіка для всіх агентів НОДА1.
+
+Правила:
+1. SOWA (Speak-Only-When-Asked) — не відповідай, якщо не питали
+2. Short-First — 1-2 речення за замовчуванням
+3. Media-no-comment — медіа без питання = мовчанка
+"""
+import re
+import logging
+from typing import Dict, Any, Optional, List, Tuple
+from dataclasses import dataclass
+
+logger = logging.getLogger(__name__)
+
+# Marker for "no response needed"
+NO_OUTPUT = "__NO_OUTPUT__"
+
+# Training groups where agents respond to ALL messages
+TRAINING_GROUP_IDS = {
+    "-1003556680911",  # Agent Preschool Daarion.city
+}
+
+# Agent name variants for mention detection
+AGENT_NAME_VARIANTS: Dict[str, List[str]] = {
+    "helion": ["helion", "хеліон", "hélion", "helios", "@energyunionbot"],
+    "daarwizz": ["daarwizz", "даарвіз", "@daarwizzbot"],
+    "greenfood": ["greenfood", "грінфуд", "@greenfoodlivebot"],
+    "agromatrix": ["agromatrix", "агроматрікс", "@agromatrixbot"],
+    "alateya": ["alateya", "алатея", "@alateyabot"],
+    "nutra": ["nutra", "нутра", "@nutrachat_bot"],
+    "druid": ["druid", "друїд", "@druidbot"],
+    "clan": ["clan", "spirit", "клан", "спіріт", "@clanbot"],
+    "eonarch": ["eonarch", "еонарх", "@eonarchbot"],
+}
+
+# Commands that trigger response
+COMMAND_PREFIXES = [
+    "/ask", "/agent", "/help", "/start", "/status", "/link",
+    "/daarwizz", "/helion", "/greenfood", "/agromatrix", "/alateya",
+    "/nutra", "/druid", "/clan", "/eonarch",
+    "/ingest", "/бренд", "/презентація", "/job",
+]
+
+# Question markers (Ukrainian + English)
+QUESTION_MARKERS = [
+    "?", "що", "як", "чому", "коли", "де", "хто", "чи", "який", "яка", "яке",
+    "скільки", "навіщо", "звідки", "куди", "котрий", "котра",
+    "what", "how", "why", "when", "where", "who", "which", "whose",
+]
+
+# Imperative markers (commands/requests)
+IMPERATIVE_MARKERS = [
+    "поясни", "розкажи", "зроби", "допоможи", "покажи", "дай", "скажи",
+    "знайди", "перевір", "аналізуй", "порівняй", "підсумуй", "витягни",
+    "опиши", "переклади", "напиши", "створи", "згенеруй", "порахуй",
+    "explain", "tell", "do", "help", "show", "give", "say", "find",
+    "check", "analyze", "compare", "summarize", "extract", "describe",
+    "translate", "write", "create", "generate", "calculate",
+]
+
+# Broadcast/poster patterns
+BROADCAST_PATTERNS = [
+    r"^\d{1,2}[:.]\d{2}\s",  # Time pattern: "20:00", "14.30"
+    r"^\d{1,2}[:.]\d{2}\s+\d{1,2}[./]\d{1,2}",  # "20:00 10.02"
+    r"^[\u2705\u274c\u23f0\u2b50\u26a1\u2764]",  # Starts with common emoji
+    r"^(анонс|запрошуємо|нагадуємо|увага|важливо|news|update|alert)",  # Announcement words
+    r"^https?://",  # URL only
+    r"#\w+.*#\w+",  # Multiple hashtags
+]
+
+# Short note patterns (timing, reactions, status updates)
+SHORT_NOTE_PATTERNS = [
+    r"^[\u2705\u274c\u2611\u2612]+$",  # Only checkmarks
+    r"^\d{1,2}[:.]\d{2}(\s+\d{1,2}[./]\d{1,2})?\s*[\u2705\u274c]?$",  # "20:00 10.02 ✅"
+    r"^[+\-ok\u2705\u274c]{1,3}$",  # +, -, ok, ✅, ❌
+    r"^(ok|ок|добре|так|ні|yes|no|done|готово)$",  # Short confirmations
+]
+
+
+@dataclass
+class BehaviorDecision:
+    """Result of behavior analysis"""
+    should_respond: bool
+    reason: str
+    is_training_group: bool = False
+    is_direct_mention: bool = False
+    is_command: bool = False
+    is_question: bool = False
+    is_imperative: bool = False
+    is_broadcast: bool = False
+    is_short_note: bool = False
+    has_media: bool = False
+    media_has_question: bool = False
+
+
+def _normalize_text(text: str) -> str:
+    """Normalize text for pattern matching"""
+    if not text:
+        return ""
+    return text.lower().strip()
+
+
+def detect_agent_mention(text: str, agent_id: str) -> bool:
+    """
+    Check if message mentions the agent.
+    
+    Args:
+        text: Message text
+        agent_id: Agent ID (e.g., "helion", "daarwizz")
+    
+    Returns:
+        True if agent is mentioned
+    """
+    if not text:
+        return False
+    
+    normalized = _normalize_text(text)
+    
+    # Get agent name variants
+    variants = AGENT_NAME_VARIANTS.get(agent_id, [agent_id])
+    
+    for variant in variants:
+        if variant.lower() in normalized:
+            return True
+    
+    return False
+
+
+def detect_any_agent_mention(text: str) -> Optional[str]:
+    """
+    Check if message mentions any agent.
+    
+    Returns:
+        Agent ID if mentioned, None otherwise
+    """
+    if not text:
+        return None
+    
+    normalized = _normalize_text(text)
+    
+    for agent_id, variants in AGENT_NAME_VARIANTS.items():
+        for variant in variants:
+            if variant.lower() in normalized:
+                return agent_id
+    
+    return None
+
+
+def detect_command(text: str) -> bool:
+    """Check if message starts with a command"""
+    if not text:
+        return False
+    
+    stripped = text.strip()
+    for prefix in COMMAND_PREFIXES:
+        if stripped.lower().startswith(prefix):
+            return True
+    
+    return False
+
+
+def detect_question(text: str) -> bool:
+    """Check if message contains a question"""
+    if not text:
+        return False
+    
+    normalized = _normalize_text(text)
+    
+    # Check for question mark
+    if "?" in normalized:
+        return True
+    
+    # Check for question words at start or after punctuation
+    words = normalized.split()
+    if words and words[0] in QUESTION_MARKERS:
+        return True
+    
+    # Check for question markers anywhere (less strict)
+    for marker in QUESTION_MARKERS:
+        if f" {marker} " in f" {normalized} ":
+            return True
+    
+    return False
+
+
+def detect_imperative(text: str) -> bool:
+    """Check if message contains an imperative (command/request)"""
+    if not text:
+        return False
+    
+    normalized = _normalize_text(text)
+    words = normalized.split()
+    
+    if not words:
+        return False
+    
+    # Check if starts with imperative
+    first_word = words[0].rstrip(",.:!?")
+    if first_word in IMPERATIVE_MARKERS:
+        return True
+    
+    # Check for imperative after mention (e.g., "@Helion поясни")
+    if len(words) >= 2:
+        second_word = words[1].rstrip(",.:!?")
+        if second_word in IMPERATIVE_MARKERS:
+            return True
+    
+    return False
+
+
+def detect_broadcast_intent(text: str) -> bool:
+    """
+    Check if message is a broadcast/announcement/poster.
+    These should NOT trigger a response.
+    """
+    if not text:
+        return False
+    
+    stripped = text.strip()
+    
+    # Check patterns
+    for pattern in BROADCAST_PATTERNS:
+        if re.match(pattern, stripped, re.IGNORECASE | re.UNICODE):
+            logger.debug(f"Broadcast pattern matched: {pattern}")
+            return True
+    
+    # Very short messages with only emojis/special chars
+    if len(stripped) <= 5 and not any(c.isalpha() for c in stripped):
+        return True
+    
+    return False
+
+
+def detect_short_note(text: str) -> bool:
+    """
+    Check if message is a short note without request.
+    E.g., "20:00 10.02 ✅", "+", "ok"
+    """
+    if not text:
+        return True
+    
+    stripped = text.strip()
+    
+    # Very short messages
+    if len(stripped) <= 10:
+        for pattern in SHORT_NOTE_PATTERNS:
+            if re.match(pattern, stripped, re.IGNORECASE | re.UNICODE):
+                logger.debug(f"Short note pattern matched: {pattern}")
+                return True
+    
+    return False
+
+
+def detect_media_question(caption: str) -> bool:
+    """
+    Check if media caption contains a question/request.
+    Media without question = no response.
+    """
+    if not caption:
+        return False
+    
+    # Has question
+    if detect_question(caption):
+        return True
+    
+    # Has imperative
+    if detect_imperative(caption):
+        return True
+    
+    return False
+
+
+def analyze_message(
+    text: str,
+    agent_id: str,
+    chat_id: str,
+    has_media: bool = False,
+    media_caption: str = "",
+    is_private_chat: bool = False,
+    payload_explicit_request: bool = False,
+) -> BehaviorDecision:
+    """
+    Main function to analyze message and decide if agent should respond.
+    
+    Args:
+        text: Message text
+        agent_id: Agent ID
+        chat_id: Chat ID
+        has_media: Whether message has photo/video/file/link
+        media_caption: Caption for media (if any)
+        is_private_chat: Whether this is a private DM
+        payload_explicit_request: Gateway flag for explicit request
+    
+    Returns:
+        BehaviorDecision with should_respond and reason
+    """
+    decision = BehaviorDecision(
+        should_respond=False,
+        reason="",
+        is_training_group=str(chat_id) in TRAINING_GROUP_IDS,
+        has_media=has_media,
+    )
+    
+    # 1. Training groups: always respond
+    if decision.is_training_group:
+        decision.should_respond = True
+        decision.reason = "training_group"
+        return decision
+    
+    # 2. Private chat: always respond
+    if is_private_chat:
+        decision.should_respond = True
+        decision.reason = "private_chat"
+        return decision
+    
+    # 3. Explicit request from gateway payload
+    if payload_explicit_request:
+        decision.should_respond = True
+        decision.reason = "explicit_request"
+        return decision
+    
+    # 4. Media handling
+    if has_media:
+        decision.media_has_question = detect_media_question(media_caption)
+        
+        if not decision.media_has_question:
+            # Media without question = NO_OUTPUT
+            decision.should_respond = False
+            decision.reason = "media_no_question"
+            return decision
+        else:
+            # Media with question = respond
+            decision.should_respond = True
+            decision.reason = "media_with_question"
+            return decision
+    
+    # 5. Check for broadcast/announcement
+    decision.is_broadcast = detect_broadcast_intent(text)
+    if decision.is_broadcast:
+        # Broadcast without direct mention = NO_OUTPUT
+        if not detect_agent_mention(text, agent_id):
+            decision.should_respond = False
+            decision.reason = "broadcast_no_mention"
+            return decision
+    
+    # 6. Check for short note
+    decision.is_short_note = detect_short_note(text)
+    if decision.is_short_note:
+        decision.should_respond = False
+        decision.reason = "short_note"
+        return decision
+    
+    # 7. Check for direct mention
+    decision.is_direct_mention = detect_agent_mention(text, agent_id)
+    
+    # 8. Check for command
+    decision.is_command = detect_command(text)
+    
+    # 9. Check for question
+    decision.is_question = detect_question(text)
+    
+    # 10. Check for imperative
+    decision.is_imperative = detect_imperative(text)
+    
+    # Decision logic
+    if decision.is_direct_mention:
+        decision.should_respond = True
+        decision.reason = "direct_mention"
+        return decision
+    
+    if decision.is_command:
+        decision.should_respond = True
+        decision.reason = "command"
+        return decision
+    
+    # In groups: question/imperative without mention = NO_OUTPUT
+    if decision.is_question or decision.is_imperative:
+        # Only respond if there's no other agent mentioned
+        other_agent = detect_any_agent_mention(text)
+        if other_agent and other_agent != agent_id:
+            decision.should_respond = False
+            decision.reason = f"addressed_to_other_agent_{other_agent}"
+            return decision
+        
+        # General question without mention = NO_OUTPUT in groups
+        decision.should_respond = False
+        decision.reason = "question_no_mention"
+        return decision
+    
+    # Default: don't respond
+    decision.should_respond = False
+    decision.reason = "no_trigger"
+    return decision
+
+
+def should_respond(
+    text: str,
+    agent_id: str,
+    chat_id: str,
+    has_media: bool = False,
+    media_caption: str = "",
+    is_private_chat: bool = False,
+    payload_explicit_request: bool = False,
+) -> Tuple[bool, str]:
+    """
+    Simplified function returning (should_respond, reason).
+    
+    Returns:
+        Tuple of (should_respond: bool, reason: str)
+    """
+    decision = analyze_message(
+        text=text,
+        agent_id=agent_id,
+        chat_id=chat_id,
+        has_media=has_media,
+        media_caption=media_caption,
+        is_private_chat=is_private_chat,
+        payload_explicit_request=payload_explicit_request,
+    )
+    return decision.should_respond, decision.reason
+
+
+def is_no_output_response(text: str) -> bool:
+    """
+    Check if LLM response indicates no output needed.
+    Used when LLM returns empty or marker response.
+    """
+    if not text:
+        return True
+    
+    stripped = text.strip().lower()
+    
+    # Check for NO_OUTPUT marker
+    if NO_OUTPUT.lower() in stripped:
+        return True
+    
+    # Check for common "I won't respond" patterns
+    no_response_patterns = [
+        r"^$",  # Empty
+        r"^\s*$",  # Whitespace only
+        r"^(no_output|no output|silent|мовчу|—)$",
+        r"^\.{1,3}$",  # Just dots
+    ]
+    
+    for pattern in no_response_patterns:
+        if re.match(pattern, stripped, re.IGNORECASE):
+            return True
+    
+    return False