Files
microdao-daarion/gateway-bot/http_api.py
Apple 1f4472ec18 feat: reply-to-agent detection in Gateway → SOWA Priority 3
When a user replies to an agent's message in Telegram groups,
it is now treated as a direct mention (SOWA FULL response).

Implementation:
- Detect reply_to_message.from.is_bot in Gateway webhook handler
- Verify bot_id matches this agent's token (multi-agent safe)
- Pass is_reply_to_agent=True to detect_explicit_request() and
  analyze_message() (SOWA v2.2)
- Add is_reply_to_agent to Router metadata for analytics

SOWA already had Priority 3 logic for reply_to_agent → FULL,
it was just never wired up (had TODO placeholders with False).

Edge cases handled:
- Only triggers when reply is to THIS agent's bot (not other bots)
- Reply to forwarded messages: won't trigger (from.is_bot would be
  the original sender, not the bot)
- Works alongside existing DM, mention, and training group rules

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-09 09:16:02 -08:00

3736 lines
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"""
Bot Gateway HTTP API
Handles incoming webhooks from Telegram, Discord, etc.
"""
import asyncio
import base64
import json
import re
import logging
import os
import sys
import time
import uuid
import httpx
from pathlib import Path
from typing import Dict, Any, Optional, List, Tuple
from datetime import datetime
from dataclasses import dataclass
from io import BytesIO
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel
from router_client import send_to_router
from memory_client import memory_client
from services.doc_service import (
parse_document,
ingest_document,
ask_about_document,
get_doc_context
)
from behavior_policy import (
should_respond,
analyze_message,
detect_media_question,
detect_explicit_request,
detect_url,
detect_agent_mention,
is_no_output_response,
record_interaction,
record_ack,
get_ack_text,
is_prober_request,
NO_OUTPUT,
BehaviorDecision,
AGENT_NAME_VARIANTS,
)
logger = logging.getLogger(__name__)
# Telegram message length limits
TELEGRAM_MAX_MESSAGE_LENGTH = 4096
TELEGRAM_SAFE_LENGTH = 3500 # Leave room for formatting
# Operator pending state cache (chat_id -> {ts, items})
LAST_PENDING_STATE: Dict[str, Dict[str, Any]] = {}
PENDING_STATE_TTL = 1800 # 30 minutes
def _pending_state_cleanup():
now = time.time()
expired = [cid for cid, rec in LAST_PENDING_STATE.items() if now - rec.get('ts', 0) > PENDING_STATE_TTL]
for cid in expired:
del LAST_PENDING_STATE[cid]
def _get_last_pending(chat_id: str) -> list | None:
_pending_state_cleanup()
rec = LAST_PENDING_STATE.get(str(chat_id))
if not rec:
return None
return rec.get('items')
def _set_last_pending(chat_id: str, items: list):
LAST_PENDING_STATE[str(chat_id)] = {"ts": time.time(), "items": items}
def _chunk_text(text: str, max_len: int = 4096):
if not text:
return [""]
chunks = []
current = []
current_len = 0
for line in text.split("\n"):
add_len = len(line) + (1 if current else 0)
if current_len + add_len <= max_len:
current.append(line)
current_len += add_len
continue
if current:
chunks.append("\n".join(current))
current = []
current_len = 0
while len(line) > max_len:
chunks.append(line[:max_len])
line = line[max_len:]
current.append(line)
current_len = len(line)
if current:
chunks.append("\n".join(current))
return chunks
# Training groups - agents respond to ALL messages without mention requirement
TRAINING_GROUP_IDS = {
"-1003556680911", # Agent Preschool Daarion.city
}
# Brand stack services
BRAND_INTAKE_URL = os.getenv("BRAND_INTAKE_URL", "http://brand-intake:9211").rstrip("/")
BRAND_REGISTRY_URL = os.getenv("BRAND_REGISTRY_URL", "http://brand-registry:9210").rstrip("/")
PRESENTATION_RENDERER_URL = os.getenv("PRESENTATION_RENDERER_URL", "http://presentation-renderer:9212").rstrip("/")
ARTIFACT_REGISTRY_URL = os.getenv("ARTIFACT_REGISTRY_URL", "http://artifact-registry:9220").rstrip("/")
router = APIRouter()
# ========================================
# Agent Configuration
# ========================================
@dataclass
class AgentConfig:
"""Конфігурація агента для стандартизації обробки повідомлень"""
agent_id: str
name: str
prompt_path: str
telegram_token_env: str
default_prompt: str
system_prompt: str = "" # Буде встановлено після завантаження
def load_prompt(self) -> str:
"""Завантажити system prompt з файлу"""
try:
p = Path(self.prompt_path)
if not p.exists():
logger.warning(f"{self.name} prompt file not found: {self.prompt_path}")
return self.default_prompt
prompt = p.read_text(encoding="utf-8")
logger.info(f"{self.name} system prompt loaded ({len(prompt)} chars)")
return prompt
except Exception as e:
logger.error(f"Error loading {self.name} prompt: {e}")
return self.default_prompt
def get_telegram_token(self) -> Optional[str]:
"""Отримати Telegram токен агента"""
return os.getenv(self.telegram_token_env)
def load_agent_config(agent_id: str, name: str, prompt_path: str,
telegram_token_env: str, default_prompt: str) -> AgentConfig:
"""Створити та завантажити конфігурацію агента"""
config = AgentConfig(
agent_id=agent_id,
name=name,
prompt_path=prompt_path,
telegram_token_env=telegram_token_env,
default_prompt=default_prompt,
system_prompt="" # Тимчасове значення
)
# Завантажити prompt
config.system_prompt = config.load_prompt()
return config
# ========================================
# Agent Configurations
# ========================================
# DAARWIZZ Configuration
DAARWIZZ_CONFIG = load_agent_config(
agent_id="daarwizz",
name=os.getenv("DAARWIZZ_NAME", "DAARWIZZ"),
prompt_path=os.getenv(
"DAARWIZZ_PROMPT_PATH",
str(Path(__file__).parent / "daarwizz_prompt.txt"),
),
telegram_token_env="DAARWIZZ_TELEGRAM_BOT_TOKEN",
default_prompt=f"Ти — {os.getenv('DAARWIZZ_NAME', 'DAARWIZZ')}, AI-агент екосистеми DAARION.city. Допомагай учасникам з DAO-процесами."
)
# HELION Configuration
HELION_CONFIG = load_agent_config(
agent_id="helion",
name=os.getenv("HELION_NAME", "Helion"),
prompt_path=os.getenv(
"HELION_PROMPT_PATH",
str(Path(__file__).parent / "helion_prompt.txt"),
),
telegram_token_env="HELION_TELEGRAM_BOT_TOKEN",
default_prompt=f"Ти — {os.getenv('HELION_NAME', 'Helion')}, AI-агент платформи Energy Union. Допомагай учасникам з технологіями та токеномікою."
)
# GREENFOOD Configuration
GREENFOOD_CONFIG = load_agent_config(
agent_id="greenfood",
name=os.getenv("GREENFOOD_NAME", "GREENFOOD"),
prompt_path=os.getenv(
"GREENFOOD_PROMPT_PATH",
str(Path(__file__).parent / "greenfood_prompt.txt"),
),
telegram_token_env="GREENFOOD_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — GREENFOOD Assistant, AI-ERP для крафтових виробників та кооперативів. Допомагай з обліком партій, логістикою, бухгалтерією та продажами."
)
# AGROMATRIX Configuration
AGROMATRIX_CONFIG = load_agent_config(
agent_id="agromatrix",
name=os.getenv("AGROMATRIX_NAME", "AgroMatrix"),
prompt_path=os.getenv(
"AGROMATRIX_PROMPT_PATH",
str(Path(__file__).parent / "agromatrix_prompt.txt"),
),
telegram_token_env="AGROMATRIX_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — AgroMatrix, AI-агент для агроаналітики, планування сезонів та кооперації фермерів. Допомагай з порадами щодо полів, процесів і ринків."
)
# ALATEYA Configuration
ALATEYA_CONFIG = load_agent_config(
agent_id="alateya",
name=os.getenv("ALATEYA_NAME", "Alateya"),
prompt_path=os.getenv(
"ALATEYA_PROMPT_PATH",
str(Path(__file__).parent / "alateya_prompt.txt"),
),
telegram_token_env="ALATEYA_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — Alateya, AI-агент R&D та біотех-інновацій. Допомагай з дослідженнями, протоколами й експериментальними дизайнами."
)
# NUTRA Configuration
NUTRA_CONFIG = load_agent_config(
agent_id="nutra",
name=os.getenv("NUTRA_NAME", "NUTRA"),
prompt_path=os.getenv(
"NUTRA_PROMPT_PATH",
str(Path(__file__).parent / "nutra_prompt.txt"),
),
telegram_token_env="NUTRA_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — NUTRA, нутріцевтичний агент платформи DAARION. Допомагаєш з формулами нутрієнтів, біомедичних добавок та лабораторних інтерпретацій. Консультуєш з питань харчування, вітамінів та оптимізації здоров'я."
)
# Registry of all agents (для легкого додавання нових агентів)
#
# Щоб додати нового агента:
# 1. Створіть конфігурацію через load_agent_config():
# NEW_AGENT_CONFIG = load_agent_config(
# agent_id="new_agent",
# name=os.getenv("NEW_AGENT_NAME", "New Agent"),
# prompt_path=os.getenv("NEW_AGENT_PROMPT_PATH", str(Path(__file__).parent / "new_agent_prompt.txt")),
# telegram_token_env="NEW_AGENT_TELEGRAM_BOT_TOKEN",
# default_prompt="Ти — New Agent, AI-агент..."
# )
# 2. Додайте до реєстру:
# DRUID Configuration
DRUID_CONFIG = load_agent_config(
agent_id="druid",
name=os.getenv("DRUID_NAME", "DRUID"),
prompt_path=os.getenv(
"DRUID_PROMPT_PATH",
str(Path(__file__).parent / "druid_prompt.txt"),
),
telegram_token_env="DRUID_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — DRUID, агент платформи DAARION. Допомагай користувачам з аналізом даних, рекомендаціями та інтеграцією RAG.",
)
# CLAN (Spirit) Configuration
CLAN_CONFIG = load_agent_config(
agent_id="clan",
name=os.getenv("CLAN_NAME", "Spirit"),
prompt_path=os.getenv(
"CLAN_PROMPT_PATH",
str(Path(__file__).parent / "clan_prompt.txt"),
),
telegram_token_env="CLAN_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — CLAN (Spirit), Дух Общини в екосистемі DAARION.city. Підтримуєш зв'язки між учасниками спільноти, зберігаєш традиції та допомагаєш в прийнятті колективних рішень.",
)
# EONARCH Configuration
EONARCH_CONFIG = load_agent_config(
agent_id="eonarch",
name=os.getenv("EONARCH_NAME", "EONARCH"),
prompt_path=os.getenv(
"EONARCH_PROMPT_PATH",
str(Path(__file__).parent / "eonarch_prompt.txt"),
),
telegram_token_env="EONARCH_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — EONARCH, провідник еволюції свідомості в екосистемі DAARION.city. Супроводжуєш людство на шляху трансформації свідомості до колективної мудрості.",
)
# SENPAI (Gordon Senpai) Configuration
SENPAI_CONFIG = load_agent_config(
agent_id="senpai",
name=os.getenv("SENPAI_NAME", "SENPAI"),
prompt_path=os.getenv(
"SENPAI_PROMPT_PATH",
str(Path(__file__).parent / "senpai_prompt.txt"),
),
telegram_token_env="SENPAI_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — Гордон Сенпай (Gordon Senpai), радник з ринків капіталу та цифрових активів. Допомагаєш з трейдингом, ризик-менеджментом, аналізом ринків.",
)
# SOUL / Athena Configuration
SOUL_CONFIG = load_agent_config(
agent_id="soul",
name=os.getenv("SOUL_NAME", "Athena"),
prompt_path=os.getenv(
"SOUL_PROMPT_PATH",
str(Path(__file__).parent / "soul_prompt.txt"),
),
telegram_token_env="SOUL_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — Athena, духовний гід та ментор спільноти DAARION.city. Підтримуєш місію, цінності та зв\'язки між учасниками.",
)
# YAROMIR Configuration
YAROMIR_CONFIG = load_agent_config(
agent_id="yaromir",
name=os.getenv("YAROMIR_NAME", "Yaromir"),
prompt_path=os.getenv(
"YAROMIR_PROMPT_PATH",
str(Path(__file__).parent / "yaromir_prompt.txt"),
),
telegram_token_env="YAROMIR_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — Yaromir, стратег та наставник в екосистемі DAARION.city. Стратегія, наставництво, психологічна підтримка команди.",
)
# SOFIIA (Sophia) Configuration
SOFIIA_CONFIG = load_agent_config(
agent_id="sofiia",
name=os.getenv("SOFIIA_NAME", "Sophia"),
prompt_path=os.getenv(
"SOFIIA_PROMPT_PATH",
str(Path(__file__).parent / "sofiia_prompt.txt"),
),
telegram_token_env="SOFIIA_TELEGRAM_BOT_TOKEN",
default_prompt="Ти — Sophia (Софія), Chief AI Architect та Technical Sovereign екосистеми DAARION.city. Координуєш R&D, архітектуру, безпеку та еволюцію платформи.",
)
# Registry of all agents (для легкого додавання нових агентів)
AGENT_REGISTRY: Dict[str, AgentConfig] = {
"daarwizz": DAARWIZZ_CONFIG,
"helion": HELION_CONFIG,
"greenfood": GREENFOOD_CONFIG,
"agromatrix": AGROMATRIX_CONFIG,
"alateya": ALATEYA_CONFIG,
"nutra": NUTRA_CONFIG,
"druid": DRUID_CONFIG,
"clan": CLAN_CONFIG,
"eonarch": EONARCH_CONFIG,
"senpai": SENPAI_CONFIG,
"soul": SOUL_CONFIG,
"yaromir": YAROMIR_CONFIG,
"sofiia": SOFIIA_CONFIG,
}
# 3. Створіть endpoint (опціонально, якщо потрібен окремий webhook):
# @router.post("/new_agent/telegram/webhook")
# async def new_agent_telegram_webhook(update: TelegramUpdate):
# return await handle_telegram_webhook(NEW_AGENT_CONFIG, update)
#
# Новий агент автоматично отримає:
# - Обробку фото через Swapper vision-8b
# - Обробку PDF документів
# - Обробку голосових повідомлень (коли буде реалізовано)
# - RAG запити по документам
# - Memory context
# AGENT_REGISTRY["new_agent"] = NEW_AGENT_CONFIG
# 3. Створіть endpoint (опціонально, якщо потрібен окремий webhook):
# Backward compatibility
DAARWIZZ_NAME = DAARWIZZ_CONFIG.name
DAARWIZZ_SYSTEM_PROMPT = DAARWIZZ_CONFIG.system_prompt
HELION_NAME = HELION_CONFIG.name
HELION_SYSTEM_PROMPT = HELION_CONFIG.system_prompt
GREENFOOD_NAME = GREENFOOD_CONFIG.name
GREENFOOD_SYSTEM_PROMPT = GREENFOOD_CONFIG.system_prompt
# ========================================
# Request Models
# ========================================
class TelegramUpdate(BaseModel):
"""Simplified Telegram update model"""
update_id: Optional[int] = None
message: Optional[Dict[str, Any]] = None
channel_post: Optional[Dict[str, Any]] = None
# DRUID webhook endpoint
@router.post("/druid/telegram/webhook")
async def druid_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(DRUID_CONFIG, update)
# AGROMATRIX webhook endpoint
async def handle_stepan_message(update: TelegramUpdate, agent_config: AgentConfig) -> Dict[str, Any]:
update_id = getattr(update, 'update_id', None) or update.update_id
if update_id:
if update_id in _PROCESSED_UPDATES:
return {"ok": True, "status": "duplicate"}
_PROCESSED_UPDATES[update_id] = _time.time()
if len(_PROCESSED_UPDATES) > _DEDUP_MAX_SIZE:
_dedup_cleanup()
message = update.message or update.channel_post or {}
text = message.get('text') or message.get('caption') or ''
if not text:
return {"ok": True, "status": "no_text"}
user = message.get('from', {}) or {}
chat = message.get('chat', {}) or {}
user_id = str(user.get('id', ''))
chat_id = str(chat.get('id', ''))
# ops mode if operator
ops_mode = False
op_ids = [s.strip() for s in os.getenv('AGX_OPERATOR_IDS', '').split(',') if s.strip()]
op_chat = os.getenv('AGX_OPERATOR_CHAT_ID', '').strip()
if op_chat and chat_id == op_chat:
ops_mode = True
if user_id and user_id in op_ids:
ops_mode = True
trace_id = str(uuid.uuid4())
# call Stepan directly
try:
sys.path.insert(0, str(Path('/opt/microdao-daarion')))
from crews.agromatrix_crew.run import handle_message
started = time.time()
last_pending = _get_last_pending(chat_id)
response_text = await asyncio.wait_for(
asyncio.to_thread(handle_message, text, user_id, chat_id, trace_id, ops_mode, last_pending),
timeout=25
)
duration_ms = int((time.time() - started) * 1000)
except Exception as e:
logger.error(f"Stepan handler error: {e}; trace_id={trace_id}")
response_text = f"Помилка обробки. trace_id={trace_id}"
duration_ms = 0
# If JSON, try to show summary
try:
parsed = json.loads(response_text)
summary = parsed.get('summary')
if summary:
response_text = summary
if parsed.get('details'):
response_text += "\n(details truncated)"
except Exception:
pass
# chunk and send
bot_token = agent_config.get_telegram_token()
for chunk in _chunk_text(response_text, max_len=4096):
await send_telegram_message(chat_id, chunk, bot_token=bot_token)
logger.info(f"Stepan reply sent: trace_id={trace_id}, user_id={user_id}, chat_id={chat_id}, update_id={update_id}, duration_ms={duration_ms}")
return {"ok": True}
@router.post("/agromatrix/telegram/webhook")
async def agromatrix_telegram_webhook(update: TelegramUpdate):
# Check if this is an operator request (slash command or NL operator intent)
message = (update.message or update.channel_post or {})
msg_text = message.get('text') or message.get('caption') or ''
user = message.get('from', {}) or {}
chat = message.get('chat', {}) or {}
user_id = str(user.get('id', ''))
chat_id = str(chat.get('id', ''))
is_slash = msg_text.strip().startswith('/')
is_ops = False
op_ids = [s.strip() for s in os.getenv('AGX_OPERATOR_IDS', '').split(',') if s.strip()]
op_chat = os.getenv('AGX_OPERATOR_CHAT_ID', '').strip()
if op_chat and chat_id == op_chat:
is_ops = True
if user_id and user_id in op_ids:
is_ops = True
# Operator NL or slash commands -> handle via Stepan handler
if is_slash or is_ops:
return await handle_stepan_message(update, AGROMATRIX_CONFIG)
# General conversation -> standard Router pipeline (like all other agents)
return await handle_telegram_webhook(AGROMATRIX_CONFIG, update)
# ALATEYA webhook endpoint
@router.post("/alateya/telegram/webhook")
async def alateya_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(ALATEYA_CONFIG, update)
# CLAN (Spirit) webhook endpoint
@router.post("/clan/telegram/webhook")
async def clan_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(CLAN_CONFIG, update)
# EONARCH webhook endpoint
@router.post("/eonarch/telegram/webhook")
async def eonarch_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(EONARCH_CONFIG, update)
# SENPAI (Gordon Senpai) webhook endpoint
@router.post("/senpai/telegram/webhook")
async def senpai_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(SENPAI_CONFIG, update)
# SOUL / Athena webhook endpoint
@router.post("/soul/telegram/webhook")
async def soul_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(SOUL_CONFIG, update)
# YAROMIR webhook endpoint
@router.post("/yaromir/telegram/webhook")
async def yaromir_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(YAROMIR_CONFIG, update)
# SOFIIA (Sophia) webhook endpoint
@router.post("/sofiia/telegram/webhook")
async def sofiia_telegram_webhook(update: TelegramUpdate):
return await handle_telegram_webhook(SOFIIA_CONFIG, update)
class DiscordMessage(BaseModel):
"""Simplified Discord message model"""
content: Optional[str] = None
author: Optional[Dict[str, Any]] = None
channel_id: Optional[str] = None
guild_id: Optional[str] = None
# ========================================
# DAO Mapping (temporary)
# ========================================
# Map agent_id to DAO ID
AGENT_TO_DAO = {
"helion": "helion-dao",
"greenfood": "greenfood-dao",
"agromatrix": "agromatrix-dao",
"nutra": "nutra-dao",
"druid": "druid-dao",
"daarwizz": "daarwizz-dao",
"clan": "clan-dao",
"alateya": "alateya-dao",
"eonarch": "eonarch-dao",
"senpai": "senpai-dao",
"soul": "soul-dao",
"yaromir": "yaromir-dao",
}
# Legacy: Map chat/channel ID to DAO ID
CHAT_TO_DAO = {
"default": "daarion-dao",
}
def get_dao_id(chat_id: str, source: str, agent_id: str = None) -> str:
"""Get DAO ID from agent_id or chat ID"""
if agent_id and agent_id in AGENT_TO_DAO:
return AGENT_TO_DAO[agent_id]
key = f"{source}:{chat_id}"
return CHAT_TO_DAO.get(key, CHAT_TO_DAO["default"])
# ========================================
# Helper Functions
# ========================================
SERVICE_ACK_PREFIXES = (
"📥 Імпортую",
"📄 Обробляю",
"Обробляю голосове",
"🎤",
)
def is_service_response(text: str) -> bool:
"""Heuristic: визначає, чи відповідь є службовою (вітальна/ack)."""
if not text:
return True
stripped = text.strip()
if not stripped:
return True
if len(stripped) < 5:
return True
lower = stripped.lower()
return any(lower.startswith(prefix.lower()) for prefix in SERVICE_ACK_PREFIXES)
def extract_bot_mentions(text: str) -> List[str]:
"""Витягує згадки інших ботів виду @NameBot."""
if not text:
return []
mentions = []
for token in text.split():
if token.startswith("@") and token[1:].lower().endswith("bot"):
mentions.append(token[1:])
return mentions
def should_force_concise_reply(text: str) -> bool:
"""Якщо коротке або без питального знаку — просимо агента відповісти стисло."""
if not text:
return True
stripped = text.strip()
if len(stripped) <= 120 and "?" not in stripped:
return True
return False
COMPLEX_REASONING_KEYWORDS = [
"стратег", "roadmap", "алгоритм", "architecture", "архітектур",
"прогноз", "scenario", "модель", "аналіз", "побудуй", "plan", "дослідж",
"симуляц", "forecast", "оптиміз", "розрахуй", "calculate", "predict"
]
def requires_complex_reasoning(text: str) -> bool:
if not text:
return False
stripped = text.strip()
if len(stripped) > 400:
return True
lower = stripped.lower()
return any(keyword in lower for keyword in COMPLEX_REASONING_KEYWORDS)
LAST_RESPONSE_CACHE: Dict[Tuple[str, str], Dict[str, Any]] = {}
LAST_RESPONSE_TTL = float(os.getenv("TELEGRAM_LAST_RESPONSE_TTL", "15"))
def get_cached_response(agent_id: str, chat_id: str, text: str) -> Optional[str]:
entry = LAST_RESPONSE_CACHE.get((agent_id, chat_id))
if not entry:
return None
if entry["text"] == text and time.time() - entry["ts"] < LAST_RESPONSE_TTL:
return entry["answer"]
return None
def store_response_cache(agent_id: str, chat_id: str, text: str, answer: str) -> None:
LAST_RESPONSE_CACHE[(agent_id, chat_id)] = {
"text": text,
"answer": answer,
"ts": time.time(),
}
def _resolve_stt_upload_url() -> str:
"""
Повертає фінальний endpoint для STT.
Swapper service використовує POST /stt з multipart file upload.
"""
upload_override = os.getenv("STT_SERVICE_UPLOAD_URL")
if upload_override:
return upload_override.rstrip("/")
base_url = os.getenv("STT_SERVICE_URL", "http://swapper-service:8890").rstrip("/")
# Swapper endpoint is /stt (not /api/stt/upload)
if base_url.endswith("/stt"):
return base_url
return f"{base_url}/stt"
# ========================================
# Helper Functions
# ========================================
async def send_telegram_message(chat_id: str, text: str, bot_token: Optional[str] = None) -> bool:
"""
Відправити повідомлення в Telegram.
Args:
chat_id: ID чату
text: Текст повідомлення
bot_token: Telegram bot token (якщо None, використовується TELEGRAM_BOT_TOKEN)
Returns:
True якщо успішно, False інакше
"""
try:
token = bot_token or os.getenv("TELEGRAM_BOT_TOKEN")
if not token:
logger.error("TELEGRAM_BOT_TOKEN not set")
return False
url = f"https://api.telegram.org/bot{token}/sendMessage"
payload = {
"chat_id": chat_id,
"text": text,
"parse_mode": "Markdown"
}
async with httpx.AsyncClient() as client:
response = await client.post(url, json=payload, timeout=10.0)
response.raise_for_status()
return True
except Exception as e:
logger.error(f"Failed to send Telegram message: {e}")
return False
async def get_telegram_file_path(file_id: str, bot_token: Optional[str] = None) -> Optional[str]:
"""
Отримати шлях до файлу з Telegram API.
Args:
file_id: ID файлу з Telegram
bot_token: Telegram bot token (якщо None, використовується TELEGRAM_BOT_TOKEN)
Returns:
Шлях до файлу або None
"""
try:
token = bot_token or os.getenv("TELEGRAM_BOT_TOKEN")
if not token:
logger.error("TELEGRAM_BOT_TOKEN not set")
return None
url = f"https://api.telegram.org/bot{token}/getFile"
params = {"file_id": file_id}
async with httpx.AsyncClient() as client:
response = await client.get(url, params=params, timeout=10.0)
response.raise_for_status()
data = response.json()
if data.get("ok"):
return data.get("result", {}).get("file_path")
return None
except Exception as e:
logger.error(f"Failed to get Telegram file path: {e}")
return None
def format_qa_response(qa_list: list) -> str:
"""Форматувати список питань-відповідей для Telegram"""
if not qa_list:
return "Немає питань-відповідей."
result = "📋 **Питання та відповіді:**\n\n"
for i, qa in enumerate(qa_list, 1):
question = qa.get("question", "") if isinstance(qa, dict) else getattr(qa, "question", "")
answer = qa.get("answer", "") if isinstance(qa, dict) else getattr(qa, "answer", "")
result += f"**{i}. {question}**\n{answer}\n\n"
return result.strip()
def format_markdown_response(markdown: str) -> str:
"""Форматувати markdown відповідь для Telegram"""
if len(markdown) > TELEGRAM_SAFE_LENGTH:
return markdown[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
return markdown
def format_chunks_response(chunks: list) -> str:
"""Форматувати список чанків для Telegram"""
if not chunks:
return "Немає фрагментів."
result = f"📄 **Знайдено {len(chunks)} фрагментів:**\n\n"
for i, chunk in enumerate(chunks[:5], 1): # Показуємо тільки перші 5
text = chunk.get("text", "") if isinstance(chunk, dict) else str(chunk)
if len(text) > 200:
text = text[:200] + "..."
result += f"**{i}.** {text}\n\n"
if len(chunks) > 5:
result += f"_... та ще {len(chunks) - 5} фрагментів_"
return result.strip()
# ========================================
# Universal Message Processing Functions
# ========================================
async def process_photo(
agent_config: AgentConfig,
update: TelegramUpdate,
chat_id: str,
user_id: str,
username: str,
dao_id: str,
photo: Dict[str, Any]
) -> Dict[str, Any]:
"""
Універсальна функція для обробки фото для будь-якого агента.
Args:
agent_config: Конфігурація агента
update: Telegram update об'єкт
chat_id: ID чату
user_id: ID користувача
username: Ім'я користувача
dao_id: ID DAO
photo: Об'єкт фото з Telegram
Returns:
Dict з результатом обробки
"""
# Telegram sends multiple sizes, get the largest one (last in array)
photo_obj = photo[-1] if isinstance(photo, list) else photo
file_id = photo_obj.get("file_id") if isinstance(photo_obj, dict) else None
if not file_id:
return {"ok": False, "error": "No file_id in photo"}
logger.info(f"{agent_config.name}: Photo from {username} (tg:{user_id}), file_id: {file_id}")
# Get caption for media question check
caption = (update.message or {}).get("caption") or ""
chat = (update.message or {}).get("chat", {})
chat_type = chat.get("type", "private")
is_private_chat = chat_type == "private"
is_training = str(chat_id) in TRAINING_GROUP_IDS
# BEHAVIOR POLICY v1: Media-no-comment
# Check if photo has a question/request in caption
if not is_private_chat and not is_training:
has_question = detect_media_question(caption)
if not has_question:
logger.info(f"🔇 MEDIA-NO-COMMENT: Photo without question. Agent {agent_config.agent_id} NOT responding.")
# Save to memory for context, but don't respond
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=f"[Photo: {file_id}] {caption}",
response="",
channel_id=chat_id,
scope="short_term",
save_agent_response=False,
agent_metadata={
"media_no_comment": True,
"file_id": file_id,
"caption": caption,
},
username=username,
)
return {"ok": True, "skipped": True, "reason": "media_no_question"}
try:
# Get file path from Telegram
telegram_token = agent_config.get_telegram_token()
if not telegram_token:
return {"ok": False, "error": f"Telegram token not configured for {agent_config.name}"}
file_path = await get_telegram_file_path(file_id, telegram_token)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Build file URL
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
# Download and encode the image as base64 data URL for Router
async with httpx.AsyncClient(timeout=60.0) as client:
photo_resp = await client.get(file_url)
photo_resp.raise_for_status()
image_bytes = photo_resp.content
content_type = photo_resp.headers.get("Content-Type", "")
if not content_type or not content_type.startswith("image/"):
content_type = "image/jpeg"
encoded_image = base64.b64encode(image_bytes).decode("utf-8")
data_url = f"data:{content_type};base64,{encoded_image}"
logger.info(
f"{agent_config.name}: Photo downloaded ({len(image_bytes)} bytes, content_type={content_type})"
)
# Send to Router with specialist_vision_8b model (Swapper)
# IMPORTANT: Default prompt must request BRIEF description (2-3 sentences max)
prompt = caption.strip() if caption else "Коротко (2-3 речення) скажи, що на цьому зображенні та яке його значення."
router_request = {
"message": f"{prompt}\n\n[Зображення передано окремо у context.images]",
"mode": "chat",
"agent": agent_config.agent_id,
"payload": {
"provider": "llm_specialist_vision_8b",
"task_type": "vision_photo_analysis",
},
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
"file_id": file_id,
"file_url": file_url,
"has_image": True,
"provider": "llm_specialist_vision_8b",
"use_llm": "specialist_vision_8b",
},
"context": {
"agent_name": agent_config.name,
"system_prompt": agent_config.system_prompt,
"images": [data_url],
},
}
# Send to Router
logger.info(f"{agent_config.name}: Sending photo to Router with vision-8b (provider override)")
response = await send_to_router(router_request)
# Extract response
if isinstance(response, dict) and response.get("ok"):
answer_text = response.get("data", {}).get("text") or response.get("response", "")
if answer_text:
# Photo processed - send LLM response directly
await send_telegram_message(
chat_id,
answer_text, # No prefix, just the LLM response
telegram_token
)
# Save to memory for context
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=f"[Photo: {file_id}]",
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={"context": "photo"},
username=username,
)
return {"ok": True, "agent": agent_config.agent_id, "model": "specialist_vision_8b"}
else:
await send_telegram_message(
chat_id,
"Не вдалося отримати опис зображення.",
telegram_token
)
return {"ok": False, "error": "No description in response"}
else:
error_msg = response.get("error", "Unknown error") if isinstance(response, dict) else "Router error"
logger.error(f"{agent_config.name}: Vision-8b error: {error_msg}")
await send_telegram_message(
chat_id,
"Вибач, сталася помилка при обробці фото.",
telegram_token
)
return {"ok": False, "error": error_msg}
except Exception as e:
logger.error(f"{agent_config.name}: Photo processing failed: {e}", exc_info=True)
telegram_token = agent_config.get_telegram_token()
await send_telegram_message(
chat_id,
"Вибач, сталася помилка при обробці фото.",
telegram_token
)
return {"ok": False, "error": "Photo processing failed"}
async def process_document(
agent_config: AgentConfig,
update: TelegramUpdate,
chat_id: str,
user_id: str,
username: str,
dao_id: str,
document: Dict[str, Any]
) -> Dict[str, Any]:
"""
Універсальна функція для обробки документів для будь-якого агента.
Args:
agent_config: Конфігурація агента
update: Telegram update об'єкт
chat_id: ID чату
user_id: ID користувача
username: Ім'я користувача
dao_id: ID DAO
document: Об'єкт документа з Telegram
Returns:
Dict з результатом обробки
"""
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
file_name_lower = file_name.lower()
allowed_exts = {".pdf", ".docx", ".txt", ".md", ".csv", ".xlsx", ".zip"}
is_allowed = any(file_name_lower.endswith(ext) for ext in allowed_exts)
if mime_type == "application/pdf":
is_allowed = True
if mime_type in {
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"text/plain",
"text/markdown",
"text/csv",
"application/zip",
}:
is_allowed = True
if is_allowed and file_id:
logger.info(f"{agent_config.name}: Document from {username} (tg:{user_id}), file_id: {file_id}, file_name: {file_name}")
try:
telegram_token = agent_config.get_telegram_token()
if not telegram_token:
return {"ok": False, "error": f"Telegram token not configured for {agent_config.name}"}
file_path = await get_telegram_file_path(file_id, telegram_token)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
session_id = f"telegram:{chat_id}"
result = await parse_document(
session_id=session_id,
doc_url=file_url,
file_name=file_name,
dao_id=dao_id,
user_id=f"tg:{user_id}",
output_mode="qa_pairs",
metadata={"username": username, "chat_id": chat_id}
)
if not result.success:
await send_telegram_message(chat_id, f"Вибач, не вдалося обробити документ: {result.error}", telegram_token)
return {"ok": False, "error": result.error}
# Get document text for summary
doc_text = result.markdown or ""
if not doc_text and result.chunks_meta:
chunks = result.chunks_meta.get("chunks", [])
doc_text = "\n".join(chunks[:5]) if chunks else ""
# Ask LLM to summarize the document (human-friendly)
if doc_text:
zip_hint = None
if file_name_lower.endswith(".zip"):
zip_hint = _zip_read_summary(doc_text)
summary_prompt = f"""Користувач надіслав документ "{file_name}".
Ось його зміст (перші частини):
{doc_text[:3000]}
Дай коротке резюме цього документа в 2-3 реченнях:
- Про що цей документ?
- Яка його основна мета/тема?
- Що може бути корисним?
Відповідай українською, дружньо, без технічних термінів."""
try:
summary_response = await send_to_router({
"message": summary_prompt,
"agent": agent_config.agent_id,
"context": {
"system_prompt": "Ти помічник який коротко пояснює зміст документів. Відповідай в 2-3 реченнях, дружньо і зрозуміло."
},
"metadata": {"source": "telegram", "task": "document_summary"}
})
if isinstance(summary_response, dict) and summary_response.get("ok"):
answer_text = summary_response.get("response", "") or summary_response.get("data", {}).get("text", "")
if answer_text:
answer_text = f"📄 **{file_name}**\n\n{answer_text}"
if zip_hint:
answer_text = f"{zip_hint}\n\n{answer_text}"
answer_text += "\n\nо саме тебе цікавить у цьому документі?_"
else:
answer_text = f"📄 Отримав документ **{file_name}**. Що саме хочеш дізнатися з нього?"
else:
answer_text = f"📄 Отримав документ **{file_name}**. Про що саме хочеш запитати?"
except Exception as e:
logger.warning(f"Failed to get document summary: {e}")
answer_text = f"📄 Отримав документ **{file_name}**. Що тебе цікавить?"
else:
answer_text = f"📄 Отримав документ **{file_name}**, але не вдалося прочитати текст. Можливо, це скановане зображення?"
logger.info(f"{agent_config.name}: Document processed: {file_name}, doc_id={result.doc_id}")
# === SAVE TO CHAT HISTORY (CRITICAL: so agent remembers the document) ===
user_msg = f"[Документ: {file_name}] Надіслано документ"
if update.message.get("caption"):
user_msg = f"[Документ: {file_name}] {update.message.get('caption')}"
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=user_msg,
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=True,
agent_metadata={"context": "document", "file_name": file_name, "doc_id": result.doc_id},
username=username,
)
logger.info(f"{agent_config.name}: Document chat turn saved to memory: {file_name}")
# === END SAVE TO CHAT HISTORY ===
# === AUTO-INGEST: Store document in agent Qdrant _docs collection ===
if doc_text:
try:
import httpx as _httpx
router_url = os.getenv("ROUTER_URL", "http://router:8000")
async with _httpx.AsyncClient(timeout=60.0) as _client:
ingest_resp = await _client.post(
f"{router_url}/v1/documents/ingest",
json={
"agent_id": agent_config.agent_id,
"doc_id": result.doc_id,
"file_name": file_name,
"text": doc_text,
"dao_id": dao_id,
"user_id": f"tg:{user_id}"
}
)
ingest_data = ingest_resp.json()
if ingest_data.get("ok"):
logger.info(f"{agent_config.name}: Document ingested to Qdrant: {ingest_data.get('chunks_stored', 0)} chunks")
else:
logger.warning(f"{agent_config.name}: Document ingest failed: {ingest_data.get('error')}")
except Exception as ingest_err:
logger.warning(f"{agent_config.name}: Document auto-ingest error: {ingest_err}")
# === END AUTO-INGEST ===
await send_telegram_message(chat_id, answer_text, telegram_token)
return {"ok": True, "agent": "parser", "mode": "doc_parse", "doc_id": result.doc_id}
except Exception as e:
logger.error(f"{agent_config.name}: Document processing failed: {e}", exc_info=True)
telegram_token = agent_config.get_telegram_token()
await send_telegram_message(chat_id, "Вибач, не вдалося обробити документ. Переконайся, що файл не пошкоджений.", telegram_token)
return {"ok": False, "error": "Document processing failed"}
elif document and not is_allowed:
telegram_token = agent_config.get_telegram_token()
await send_telegram_message(
chat_id,
"Наразі підтримуються формати: PDF, DOCX, TXT, MD, CSV, XLSX, ZIP.",
telegram_token,
)
return {"ok": False, "error": "Unsupported document type"}
return {"ok": False, "error": "No document to process"}
async def process_voice(
agent_config: AgentConfig,
update: TelegramUpdate,
chat_id: str,
user_id: str,
username: str,
dao_id: str,
media_obj: Dict[str, Any]
) -> Dict[str, Any]:
"""
Універсальна функція для обробки голосових повідомлень для будь-якого агента.
Використовує STT Service для розпізнавання мовлення.
Args:
agent_config: Конфігурація агента
update: Telegram update об'єкт
chat_id: ID чату
user_id: ID користувача
username: Ім'я користувача
dao_id: ID DAO
media_obj: Об'єкт голосового повідомлення з Telegram
Returns:
Dict з результатом обробки та розпізнаним текстом
"""
file_id = media_obj.get("file_id") if media_obj else None
if not file_id:
return {"ok": False, "error": "No file_id in voice/audio/video_note"}
logger.info(f"{agent_config.name}: Voice message from {username} (tg:{user_id}), file_id: {file_id}")
try:
telegram_token = agent_config.get_telegram_token()
if not telegram_token:
return {"ok": False, "error": f"Telegram token not configured for {agent_config.name}"}
# Отримуємо файл з Telegram
file_path = await get_telegram_file_path(file_id, telegram_token)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Завантажуємо файл
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
async with httpx.AsyncClient(timeout=30.0) as client:
file_resp = await client.get(file_url)
file_resp.raise_for_status()
audio_bytes = file_resp.content
# Відправляємо в STT-сервіс
stt_upload_url = _resolve_stt_upload_url()
mime_type = media_obj.get("mime_type") if isinstance(media_obj, dict) else None
files = {
"file": (
"voice.ogg",
audio_bytes,
mime_type or "audio/ogg",
)
}
# Swapper /stt expects: file (multipart), model (form), language (form)
form_data = {
"model": "whisper-small",
"task": "transcribe",
}
logger.info(f"{agent_config.name}: Sending voice to STT endpoint {stt_upload_url}")
async with httpx.AsyncClient(timeout=90.0) as client:
stt_resp = await client.post(stt_upload_url, files=files, data=form_data)
stt_resp.raise_for_status()
stt_data = stt_resp.json()
text = stt_data.get("text", "")
if not text:
await send_telegram_message(
chat_id,
"Вибач, не вдалося розпізнати голосове повідомлення. Спробуй надіслати текстом.",
telegram_token
)
return {"ok": False, "error": "STT returned empty text"}
logger.info(f"{agent_config.name}: STT result: {text[:100]}...")
# Повертаємо розпізнаний текст для подальшої обробки
return {"ok": True, "text": text, "agent": agent_config.agent_id, "mode": "voice_stt"}
except Exception as e:
logger.error(f"{agent_config.name}: Voice processing failed: {e}", exc_info=True)
telegram_token = agent_config.get_telegram_token()
await send_telegram_message(
chat_id,
"Вибач, не вдалося розпізнати голосове повідомлення. Спробуй надіслати текстом.",
telegram_token
)
return {"ok": False, "error": "Voice processing failed"}
# ========================================
# Universal Telegram Webhook Handler
# ========================================
# === UPDATE DEDUPLICATION ===
import time as _time
_PROCESSED_UPDATES: Dict[int, float] = {} # update_id -> timestamp
_DEDUP_MAX_SIZE = 2000
_DEDUP_TTL = 300 # 5 minutes
def _dedup_cleanup():
"""Remove old entries from dedup cache."""
now = _time.time()
expired = [uid for uid, ts in _PROCESSED_UPDATES.items() if now - ts > _DEDUP_TTL]
for uid in expired:
del _PROCESSED_UPDATES[uid]
# === END DEDUPLICATION ===
async def handle_telegram_webhook(
agent_config: AgentConfig,
update: TelegramUpdate
) -> Dict[str, Any]:
"""
Універсальна функція для обробки Telegram webhook для будь-якого агента.
Args:
agent_config: Конфігурація агента
update: Telegram update об'єкт
Returns:
Dict з результатом обробки
"""
# Allow updates without message if they contain photo/voice
# The actual message validation happens after multimodal checks
# === DEDUP CHECK ===
if update.update_id:
if update.update_id in _PROCESSED_UPDATES:
logger.info(f"🔄 Skipping duplicate update_id={update.update_id} for {agent_config.name}")
return {"status": "ok", "skipped": "duplicate_update"}
_PROCESSED_UPDATES[update.update_id] = _time.time()
if len(_PROCESSED_UPDATES) > _DEDUP_MAX_SIZE:
_dedup_cleanup()
# === END DEDUP CHECK ===
if not update.message:
if update.channel_post:
update.message = update.channel_post
else:
return {"status": "ok", "skipped": "no_message"}
# Extract message details
from_user = update.message.get("from", {})
if not from_user:
from_user = update.message.get("sender_chat", {})
chat = update.message.get("chat", {})
user_id = str(from_user.get("id", "unknown"))
chat_id = str(chat.get("id", "unknown"))
username = from_user.get("username", "")
first_name = from_user.get("first_name")
last_name = from_user.get("last_name")
is_sender_bot = bool(from_user.get("is_bot") or (username and username.lower().endswith("bot")))
# Get DAO ID for this chat
dao_id = get_dao_id(chat_id, "telegram", agent_id=agent_config.agent_id)
# Оновлюємо факти про користувача/агента для побудови графу пам'яті
asyncio.create_task(
memory_client.upsert_fact(
user_id=f"tg:{user_id}",
fact_key="profile",
fact_value_json={
"username": username,
"first_name": first_name,
"last_name": last_name,
"language_code": from_user.get("language_code"),
"is_bot": is_sender_bot,
},
team_id=dao_id,
)
)
telegram_token = agent_config.get_telegram_token()
if not telegram_token:
raise HTTPException(status_code=500, detail=f"Telegram token not configured for {agent_config.name}")
# === REPLY-TO-AGENT DETECTION ===
# If user replies to a bot message → treat as direct mention (SOWA Priority 3)
is_reply_to_agent = False
reply_to_message = update.message.get("reply_to_message")
if reply_to_message:
reply_from = reply_to_message.get("from", {})
if reply_from.get("is_bot"):
# Verify it's THIS agent's bot (bot_id = first part of token)
bot_id = telegram_token.split(":")[0] if telegram_token else None
reply_from_id = str(reply_from.get("id", ""))
if bot_id and reply_from_id == bot_id:
is_reply_to_agent = True
logger.info(
f"↩️ {agent_config.name}: Reply-to-agent detected "
f"(user {username} replied to bot msg {reply_to_message.get('message_id', '?')})"
)
text = update.message.get("text", "")
# Simple brand commands (Ukrainian)
if text and text.strip().startswith("/бренд"):
parts = text.strip().split(maxsplit=2)
command = parts[0].lower()
if command == "/бренд":
await send_telegram_message(
chat_id,
"🧩 **Команди бренду**\n\n"
"• `/бренд_інтейк <url|текст>` — зберегти джерело\n"
"• `/бренд_тема <brand_id> [версія]` — опублікувати базову тему\n"
"• `/бренд_останнє <brand_id>` — показати останню тему\n"
"• `/бренд_показати <brand_id> <версія>` — показати конкретну тему\n"
"• `/презентація <brand_id> <версія> <JSON SlideSpec>` — рендер презентації\n"
"• `/презентація_статус <job_id>` — статус рендера\n"
"• `/презентація_файл <artifact_id> [pptx|pdf]` — файл\n"
"• `/job_статус <job_id>` — універсальний статус",
telegram_token
)
return {"ok": True, "action": "brand_help"}
if command == "/бренд_інтейк":
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Вкажи URL або текст: `/бренд_інтейк <url|текст>`",
telegram_token
)
return {"ok": True, "action": "brand_intake_help"}
source_value = parts[1] if len(parts) == 2 else f"{parts[1]} {parts[2]}"
source_type = "url" if source_value.startswith("http") else "text"
intake_payload = {
"source_type": source_type,
"text": source_value if source_type == "text" else None,
"url": source_value if source_type == "url" else None,
"agent_id": agent_config.agent_id,
"workspace_id": dao_id,
"project_id": dao_id,
"tags": ["telegram"]
}
result = await _brand_intake_request(intake_payload)
attribution = result.get("attribution", {})
await send_telegram_message(
chat_id,
"✅ **Джерело збережено**\n\n"
f"ID: `{result.get('id')}`\n"
f"Статус: `{attribution.get('status')}`\n"
f"Бренд: `{attribution.get('brand_id')}`\n"
f"Впевненість: `{attribution.get('confidence')}`",
telegram_token
)
return {"ok": True, "action": "brand_intake"}
if command == "/бренд_тема":
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Вкажи brand_id: `/бренд_тема <brand_id> [версія]`",
telegram_token
)
return {"ok": True, "action": "brand_theme_help"}
brand_id = parts[1]
theme_version = None
if len(parts) == 3:
theme_version = parts[2]
theme = _default_theme_payload(brand_id)
published = await _brand_publish_theme(brand_id, theme, theme_version)
await send_telegram_message(
chat_id,
"✅ **Тему опубліковано**\n\n"
f"Бренд: `{published.get('brand_id')}`\n"
f"Версія: `{published.get('theme_version')}`",
telegram_token
)
return {"ok": True, "action": "brand_publish"}
if command == "/бренд_останнє":
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Вкажи brand_id: `/бренд_останнє <brand_id>`",
telegram_token
)
return {"ok": True, "action": "brand_latest_help"}
brand_id = parts[1]
data = await _brand_get_latest(brand_id)
await send_telegram_message(
chat_id,
"📌 **Остання тема**\n\n"
f"Бренд: `{data.get('brand_id')}`\n"
f"Версія: `{data.get('theme_version')}`",
telegram_token
)
return {"ok": True, "action": "brand_latest"}
if command == "/бренд_показати":
if len(parts) < 3:
await send_telegram_message(
chat_id,
"❗ Формат: `/бренд_показати <brand_id> <версія>`",
telegram_token
)
return {"ok": True, "action": "brand_show_help"}
brand_id = parts[1]
theme_version = parts[2]
data = await _brand_get_theme(brand_id, theme_version)
await send_telegram_message(
chat_id,
"📎 **Тема**\n\n"
f"Бренд: `{data.get('brand_id')}`\n"
f"Версія: `{data.get('theme_version')}`",
telegram_token
)
return {"ok": True, "action": "brand_show"}
# Brand hint on keyword mention (non-command)
if text and "бренд" in text.lower():
await send_telegram_message(
chat_id,
"🧩 **Команди бренду**\n\n"
"• `/бренд_інтейк <url|текст>` — зберегти джерело\n"
"• `/бренд_тема <brand_id> [версія]` — опублікувати базову тему\n"
"• `/бренд_останнє <brand_id>` — показати останню тему\n"
"• `/бренд_показати <brand_id> <версія>` — показати конкретну тему\n"
"• `/презентація <brand_id> <версія> <JSON SlideSpec>` — рендер презентації\n"
"• `/презентація_статус <job_id>` — статус рендера\n"
"• `/презентація_файл <artifact_id> [pptx|pdf]` — файл\n"
"• `/job_статус <job_id>` — універсальний статус",
telegram_token
)
return {"ok": True, "action": "brand_hint"}
# Job status command (universal)
if text and text.strip().startswith("/job_статус"):
parts = text.strip().split(maxsplit=1)
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Формат: `/job_статус <job_id>`",
telegram_token
)
return {"ok": True, "action": "job_status_help"}
job_id = parts[1].strip()
job = await _artifact_job_status(job_id)
message = _format_job_status_message(job, job_id)
await send_telegram_message(chat_id, message, telegram_token)
return {"ok": True, "action": "job_status"}
# Presentation status command (alias)
if text and text.strip().startswith("/презентація_статус"):
parts = text.strip().split(maxsplit=1)
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Формат: `/презентація_статус <job_id>` або `/job_статус <job_id>`",
telegram_token
)
return {"ok": True, "action": "presentation_status_help"}
job_id = parts[1].strip()
job = await _artifact_job_status(job_id)
message = _format_job_status_message(job, job_id)
await send_telegram_message(chat_id, message, telegram_token)
return {"ok": True, "action": "presentation_status"}
# Presentation file command
if text and text.strip().startswith("/презентація_файл"):
parts = text.strip().split(maxsplit=2)
if len(parts) < 2:
await send_telegram_message(
chat_id,
"❗ Формат: `/презентація_файл <artifact_id> [pptx|pdf]`",
telegram_token
)
return {"ok": True, "action": "presentation_file_help"}
artifact_id = parts[1].strip()
fmt = parts[2].strip().lower() if len(parts) > 2 else "pptx"
artifact = await _artifact_get(artifact_id)
acl_ref = artifact.get("acl_ref")
if not _can_access_artifact(acl_ref, dao_id, f"tg:{user_id}"):
await send_telegram_message(chat_id, "⛔ Немає доступу до цього файлу.", telegram_token)
return {"ok": True, "action": "presentation_file_denied"}
try:
download = await _artifact_download(artifact_id, fmt)
logger.info(
"artifact.downloaded artifact_id=%s user=%s format=%s",
artifact_id,
user_id,
fmt,
)
await send_telegram_message(
chat_id,
f"📎 **Файл готовий** ({fmt})\n{download.get('url')}",
telegram_token
)
return {"ok": True, "action": "presentation_file"}
except HTTPException as e:
if fmt == "pdf" and e.status_code == 404:
versions = await _artifact_versions(artifact_id)
pptx_version_id = None
for item in versions.get("items", []):
if item.get("mime") == "application/vnd.openxmlformats-officedocument.presentationml.presentation":
pptx_version_id = item.get("id")
break
if not pptx_version_id:
await send_telegram_message(
chat_id,
"❗ PPTX ще не готовий, PDF теж недоступний.",
telegram_token
)
return {"ok": True, "action": "presentation_pdf_missing"}
job = await _artifact_create_job(artifact_id, "render_pdf", pptx_version_id)
await send_telegram_message(
chat_id,
"⏳ PDF в черзі на рендер.\n"
f"Job ID: `{job.get('job_id')}`\n"
"Спробуй `/презентація_статус <job_id>` трохи пізніше.",
telegram_token
)
return {"ok": True, "action": "presentation_pdf_queued"}
raise
# Presentation render command (JSON SlideSpec)
if text and text.strip().startswith("/презентація"):
parts = text.strip().split(maxsplit=3)
if len(parts) < 4:
await send_telegram_message(
chat_id,
"❗ Формат:\n"
"`/презентація <brand_id> <версія> <JSON SlideSpec>`\n"
"або простий формат:\n"
"`/презентація <brand_id> <версія> Назва;Слайд 1;Слайд 2;Слайд 3`\n\n"
"Приклад:\n"
"`/презентація energyunion v1.0.0 {\"meta\":{\"title\":\"Pitch\",\"brand_id\":\"energyunion\",\"theme_version\":\"v1.0.0\",\"language\":\"uk\"},\"slides\":[{\"type\":\"title\",\"title\":\"Energy Union\"}]}`",
telegram_token
)
return {"ok": True, "action": "presentation_help"}
brand_id = parts[1]
theme_version = parts[2]
slidespec_raw = parts[3]
slidespec = None
if slidespec_raw.strip().startswith("{"):
try:
slidespec = json.loads(slidespec_raw)
except json.JSONDecodeError:
await send_telegram_message(
chat_id,
"Не вдалося прочитати JSON SlideSpec. Перевір формат.",
telegram_token
)
return {"ok": True, "action": "presentation_bad_json"}
else:
parts_simple = [p.strip() for p in slidespec_raw.split(";") if p.strip()]
if not parts_simple:
await send_telegram_message(
chat_id,
"❗ Порожній список слайдів. Додай хоча б назву.",
telegram_token
)
return {"ok": True, "action": "presentation_empty"}
title = parts_simple[0]
slides = [{"type": "title", "title": title}]
for item in parts_simple[1:]:
slides.append({
"type": "bullets",
"title": item,
"blocks": [{"kind": "bullets", "items": [item]}],
})
slidespec = {
"meta": {
"title": title,
"brand_id": brand_id,
"theme_version": theme_version,
"language": "uk",
},
"slides": slides,
}
render_result = await _presentation_render(slidespec, brand_id, theme_version)
await send_telegram_message(
chat_id,
"✅ **Запит на рендер прийнято**\n\n"
f"Artifact ID: `{render_result.get('artifact_id')}`\n"
f"Job ID: `{render_result.get('job_id')}`\n"
f"Status URL: `{render_result.get('status_url')}`",
telegram_token
)
return {"ok": True, "action": "presentation_render"}
# Check for /ingest command
text = update.message.get("text", "")
if text and text.strip().startswith("/ingest"):
session_id = f"telegram:{chat_id}"
# Check if there's a document in the message
document = update.message.get("document")
if document:
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
if file_id:
try:
file_path = await get_telegram_file_path(file_id, telegram_token)
if file_path:
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
artifact = None
job = None
try:
artifact = await _artifact_create({
"type": "doc",
"title": file_name,
"brand_id": dao_id,
"project_id": dao_id,
"acl_ref": f"brand:{dao_id}:public" if dao_id else "public",
"created_by": f"tg:{user_id}",
})
version = await _artifact_add_version_from_url(
artifact["artifact_id"],
{
"url": file_url,
"mime": mime_type or "application/octet-stream",
"label": "source",
"meta_json": {
"file_name": file_name,
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
},
},
)
job = await _artifact_create_job(
artifact["artifact_id"],
"index_doc",
version["version_id"],
)
except Exception as e:
logger.warning(f"Artifact doc registry failed: {e}")
await send_telegram_message(
chat_id,
f"✅ **Документ прийнято**\n\n"
f"📁 DAO: {dao_id}\n"
f"🧾 Artifact ID: `{artifact.get('artifact_id') if artifact else 'n/a'}`\n"
f"🧩 Job ID: `{job.get('job_id') if job else 'n/a'}`\n\n"
f"Індексація виконується асинхронно. "
f"Перевір статус: `/job_статус <job_id>`",
telegram_token
)
return {"ok": True, "artifact_id": artifact.get("artifact_id") if artifact else None, "job_id": job.get("job_id") if job else None}
except Exception as e:
logger.error(f"{agent_config.name}: Ingest failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося імпортувати документ.", telegram_token)
return {"ok": False, "error": "Ingest failed"}
await send_telegram_message(chat_id, "Спочатку надішли документ, а потім використай /ingest", telegram_token)
return {"ok": False, "error": "No document for ingest"}
# Check for /link command - Account Linking (Telegram ↔ Energy Union)
if text and text.strip().startswith("/link"):
parts = text.strip().split(maxsplit=1)
if len(parts) < 2:
await send_telegram_message(
chat_id,
"🔗 **Зв'язування акаунта**\n\n"
"Щоб зв'язати Telegram з акаунтом Energy Union:\n"
"1. Отримай код у кабінеті Energy Union\n"
"2. Надішли: `/link <код>`\n\n"
"Приклад: `/link ABC123XYZ`",
telegram_token
)
return {"ok": True, "action": "link_help"}
link_code = parts[1].strip()
# Call PostgreSQL function to complete linking
try:
import asyncpg
pg_conn = await asyncpg.connect(
host=os.getenv("POSTGRES_HOST", "dagi-postgres"),
port=int(os.getenv("POSTGRES_PORT", "5432")),
user=os.getenv("POSTGRES_USER", "daarion"),
password=os.getenv("POSTGRES_PASSWORD", "DaarionDB2026!"),
database=os.getenv("POSTGRES_DB", "daarion_main")
)
result = await pg_conn.fetchrow(
"SELECT * FROM complete_account_link($1, $2, $3, $4, $5)",
link_code,
int(user_id),
username,
first_name,
last_name
)
await pg_conn.close()
if result and result['success']:
await send_telegram_message(
chat_id,
"✅ **Акаунт успішно зв'язано!**\n\n"
"Тепер Helion бачить твою історію взаємодій "
"з платформою Energy Union.\n\n"
"Твої розмови в різних чатах тепер пов'язані "
"з твоїм єдиним акаунтом.",
telegram_token
)
logger.info(f"Account linked: telegram_user_id={user_id}, account_id={result['account_id']}")
return {"ok": True, "action": "account_linked", "account_id": str(result['account_id'])}
else:
error_msg = result['error_message'] if result else "Невідома помилка"
error_text = {
"Invalid or expired code": "Код недійсний або прострочений",
"Telegram account already linked": "Telegram вже зв'язано з іншим акаунтом",
"Code not found": "Код не знайдено"
}.get(error_msg, error_msg)
await send_telegram_message(
chat_id,
f"❌ **Не вдалося зв'язати акаунт**\n\n"
f"Причина: {error_text}\n\n"
"Спробуй отримати новий код у кабінеті Energy Union.",
telegram_token
)
return {"ok": False, "error": error_msg}
except Exception as e:
logger.error(f"Account linking failed: {e}", exc_info=True)
await send_telegram_message(
chat_id,
"❌ Помилка зв'язування акаунта. Спробуй пізніше.",
telegram_token
)
return {"ok": False, "error": str(e)}
# Check for /unlink command
if text and text.strip().startswith("/unlink"):
try:
import asyncpg
pg_conn = await asyncpg.connect(
host=os.getenv("POSTGRES_HOST", "dagi-postgres"),
port=int(os.getenv("POSTGRES_PORT", "5432")),
user=os.getenv("POSTGRES_USER", "daarion"),
password=os.getenv("POSTGRES_PASSWORD", "DaarionDB2026!"),
database=os.getenv("POSTGRES_DB", "daarion_main")
)
result = await pg_conn.execute(
"""
UPDATE account_links
SET status = 'revoked',
revoked_at = NOW(),
revoked_reason = 'User requested via /unlink'
WHERE telegram_user_id = $1 AND status = 'active'
""",
int(user_id)
)
await pg_conn.close()
await send_telegram_message(
chat_id,
"✅ **Зв'язок з акаунтом видалено**\n\n"
"Helion більше не бачить твою історію.\n"
"Ти можеш повторно зв'язати акаунт командою `/link`.",
telegram_token
)
return {"ok": True, "action": "account_unlinked"}
except Exception as e:
logger.error(f"Account unlinking failed: {e}", exc_info=True)
await send_telegram_message(
chat_id,
"❌ Помилка видалення зв'язку. Спробуй пізніше.",
telegram_token
)
return {"ok": False, "error": str(e)}
# Check for /status command - Show linking status
if text and text.strip().startswith("/status"):
try:
import asyncpg
pg_conn = await asyncpg.connect(
host=os.getenv("POSTGRES_HOST", "dagi-postgres"),
port=int(os.getenv("POSTGRES_PORT", "5432")),
user=os.getenv("POSTGRES_USER", "daarion"),
password=os.getenv("POSTGRES_PASSWORD", "DaarionDB2026!"),
database=os.getenv("POSTGRES_DB", "daarion_main")
)
link = await pg_conn.fetchrow(
"""
SELECT account_id, linked_at, status
FROM account_links
WHERE telegram_user_id = $1 AND status = 'active'
""",
int(user_id)
)
await pg_conn.close()
if link:
linked_date = link['linked_at'].strftime("%d.%m.%Y %H:%M")
await send_telegram_message(
chat_id,
f"✅ **Акаунт зв'язано**\n\n"
f"📅 Дата: {linked_date}\n"
f"🔗 Статус: активний\n\n"
f"Helion бачить твою історію взаємодій.",
telegram_token
)
else:
await send_telegram_message(
chat_id,
"❌ **Акаунт не зв'язано**\n\n"
"Використай `/link <код>` щоб зв'язати.\n"
"Код можна отримати в кабінеті Energy Union.",
telegram_token
)
return {"ok": True, "action": "status_checked", "linked": bool(link)}
except Exception as e:
logger.error(f"Status check failed: {e}", exc_info=True)
return {"ok": False, "error": str(e)}
# Check if it's a document
document = update.message.get("document")
if document:
result = await process_document(
agent_config, update, chat_id, user_id, username, dao_id, document
)
if result.get("ok"):
return result
# Check if it's a photo
photo = update.message.get("photo")
if photo:
result = await process_photo(
agent_config, update, chat_id, user_id, username, dao_id, photo
)
if result.get("ok"):
return result
# Check if it's a voice message
voice = update.message.get("voice")
audio = update.message.get("audio")
video_note = update.message.get("video_note")
text = ""
if voice or audio or video_note:
media_obj = voice or audio or video_note
result = await process_voice(
agent_config, update, chat_id, user_id, username, dao_id, media_obj
)
if result.get("ok") and result.get("text"):
# Отримали розпізнаний текст, продовжуємо обробку як текстове повідомлення
text = result.get("text")
elif result.get("ok"):
# STT успішний, але текст порожній
return result
else:
# Помилка STT
return result
# Get message text (якщо не було голосового повідомлення)
if not text:
text = update.message.get("text", "")
caption = update.message.get("caption", "")
if not text and not caption:
# Check for unsupported message types and silently ignore
unsupported_types = ["sticker", "animation", "video_note", "contact", "location",
"venue", "poll", "dice", "game", "new_chat_members",
"left_chat_member", "new_chat_title", "new_chat_photo",
"delete_chat_photo", "pinned_message", "message_auto_delete_timer_changed"]
for msg_type in unsupported_types:
if update.message.get(msg_type):
logger.debug(f"Ignoring unsupported message type: {msg_type}")
return {"ok": True, "ignored": True, "reason": f"Unsupported message type: {msg_type}"}
# If no supported content found, return silently
logger.debug(f"Message without processable content from user {user_id}")
return {"ok": True, "ignored": True, "reason": "No processable content"}
# Use caption if text is empty (for photos with captions that weren't processed)
if not text and caption:
text = caption
logger.info(f"{agent_config.name} Telegram message from {username} (tg:{user_id}) in chat {chat_id}: {text[:50]}")
mentioned_bots = extract_bot_mentions(text)
needs_complex_reasoning = requires_complex_reasoning(text)
cached_answer = get_cached_response(agent_config.agent_id, chat_id, text)
if cached_answer:
await send_telegram_message(chat_id, cached_answer, telegram_token)
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response=cached_answer,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(cached_answer),
agent_metadata={
"cached_reply": True,
"mentioned_bots": mentioned_bots,
"requires_complex_reasoning": needs_complex_reasoning,
},
username=username,
)
return {"ok": True, "agent": agent_config.agent_id, "cached": True}
# Check if there's a document context for follow-up questions
session_id = f"telegram:{chat_id}"
doc_context = await get_doc_context(session_id)
# 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 = (
"?" 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(
session_id=session_id,
question=text,
doc_id=doc_context.doc_id,
dao_id=dao_id or doc_context.dao_id,
user_id=f"tg:{user_id}"
)
if rag_result.success and rag_result.answer:
# Truncate if too long for Telegram
answer = rag_result.answer
if len(answer) > TELEGRAM_SAFE_LENGTH:
answer = answer[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
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
# ========================================
# BEHAVIOR POLICY v2.1: Check if should respond
# Gateway computes has_link and has_explicit_request (source of truth)
# ========================================
chat_type = chat.get("type", "private")
is_private_chat = chat_type == "private"
# Gateway: compute has_link (single source of truth)
has_link = detect_url(text) if text else False
# Gateway: detect mentioned agents
mentioned_agents = []
if text:
for aid, variants in AGENT_NAME_VARIANTS.items():
for v in variants:
if v.lower() in text.lower():
mentioned_agents.append(aid)
break
# Gateway: compute has_explicit_request (single source of truth)
# CONTRACT: imperative OR (? AND (dm OR reply OR mention OR thread))
has_explicit_request = detect_explicit_request(
text=text,
is_dm=is_private_chat,
is_reply_to_agent=is_reply_to_agent,
mentioned_agents=mentioned_agents,
thread_has_agent_participation=False, # REQUIRED, fail-closed default
)
# Check if this is a prober request (chat_id=0 or user_id=0)
is_prober = is_prober_request(chat_id, user_id)
# SOWA v2.2: 3-level decision (FULL / ACK / SILENT)
sowa_decision = analyze_message(
text=text,
agent_id=agent_config.agent_id,
chat_id=chat_id,
user_id=str(user_id),
has_media=has_link,
media_caption=text if has_link else "",
is_private_chat=is_private_chat,
payload_explicit_request=has_explicit_request,
payload_has_link=has_link,
is_reply_to_agent=is_reply_to_agent,
thread_has_agent_participation=False, # TODO: track per thread
)
respond_decision = sowa_decision.should_respond
respond_reason = sowa_decision.reason
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
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response="", # No response
channel_id=chat_id,
scope="short_term",
save_agent_response=False,
agent_metadata={
"sowa_skipped": True,
"skip_reason": respond_reason,
},
username=username,
)
return {"ok": True, "skipped": True, "reason": respond_reason}
# ACK: send short presence message WITHOUT calling LLM/Router
if sowa_decision.action == "ACK":
ack_text = sowa_decision.ack_text or get_ack_text(agent_config.agent_id)
logger.info(f"\U0001f44b SOWA ACK: Agent {agent_config.agent_id} sending ACK. Reason: {respond_reason}")
# Send ACK to Telegram (no LLM call)
if not is_prober:
token = agent_config.get_telegram_token()
if token:
try:
url = f"https://api.telegram.org/bot{token}/sendMessage"
async with httpx.AsyncClient(timeout=30) as client:
resp = await client.post(url, json={
"chat_id": chat_id,
"text": ack_text,
})
if resp.status_code == 200:
logger.info(f"\U0001f44b ACK sent to chat {chat_id}: {ack_text}")
else:
logger.warning(f"ACK send failed: {resp.status_code} {resp.text[:200]}")
except Exception as e:
logger.error(f"ACK send error: {e}")
# Record ACK for cooldown and interaction tracking
record_ack(agent_config.agent_id, str(chat_id))
record_interaction(agent_config.agent_id, str(chat_id), str(user_id))
# Save to memory
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response=ack_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=True,
agent_metadata={
"sowa_ack": True,
"ack_reason": respond_reason,
},
username=username,
)
return {"ok": True, "ack": True, "reason": respond_reason}
# FULL: proceed with LLM/Router call
# For prober requests, respond but don't send to Telegram
if is_prober:
logger.info(f"\U0001f9ea PROBER: Agent {agent_config.agent_id} responding to prober request. Reason: {respond_reason}")
else:
logger.info(f"\u2705 SOWA: Agent {agent_config.agent_id} WILL respond (FULL). Reason: {respond_reason}")
# Regular chat mode
# Fetch memory context (includes local context as fallback)
# Всі агенти мають доступ до однакової історії (80 повідомлень) для контексту
context_limit = 80 # Однакове для всіх агентів
memory_context = 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=context_limit
)
# Build message with conversation context
local_history = memory_context.get("local_context_text", "")
# Check if this is a training group
is_training_group = str(chat_id) in TRAINING_GROUP_IDS
training_prefix = ""
if is_training_group:
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}")
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}"
else:
message_with_context = f"{training_prefix}{text}"
# Build request to Router
system_prompt = agent_config.system_prompt
logger.info(f"📝 {agent_config.name} system_prompt length: {len(system_prompt) if system_prompt else 0} chars")
if system_prompt:
logger.debug(f"System prompt preview: {system_prompt[:200]}...")
else:
logger.error(f"{agent_config.name} system_prompt is EMPTY or None!")
router_request = {
"message": message_with_context,
"mode": "chat",
"agent": agent_config.agent_id,
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
"sender_is_bot": is_sender_bot,
"mentioned_bots": mentioned_bots,
"requires_complex_reasoning": needs_complex_reasoning,
"is_reply_to_agent": is_reply_to_agent,
},
"context": {
"agent_name": agent_config.name,
"system_prompt": system_prompt,
"memory": memory_context,
"participants": {
"sender_is_bot": is_sender_bot,
"mentioned_bots": mentioned_bots,
},
},
}
if should_force_concise_reply(text):
# IMPORTANT: preserve conversation context! Only append concise instruction
router_request["message"] = (
router_request["message"]
+ "\n\n(Інструкція: дай максимально коротку відповідь, якщо не просили деталей "
"і дочекайся додаткового питання.)"
)
if needs_complex_reasoning:
router_request["metadata"]["provider"] = "cloud_deepseek"
router_request["metadata"]["reason"] = "auto_complex"
# Send to Router
logger.info(f"Sending to Router: agent={agent_config.agent_id}, dao={dao_id}, user=tg:{user_id}")
response = await send_to_router(router_request)
# Extract response
if isinstance(response, dict) and response.get("ok"):
answer_text = response.get("data", {}).get("text") or response.get("response", "")
image_base64 = response.get("image_base64") or response.get("data", {}).get("image_base64")
# Debug logging
logger.info(f"📦 Router response: {len(answer_text)} chars, model={response.get('model')}, backend={response.get('backend')}")
logger.info(f"📝 Response preview: {answer_text[:300]}..." if len(answer_text) > 300 else f"📝 Response: {answer_text}")
if image_base64:
logger.info(f"🖼️ Received image_base64: {len(image_base64)} chars")
else:
logger.debug("⚠️ No image_base64 in response")
# Check for NO_OUTPUT (LLM decided not to respond)
if is_no_output_response(answer_text):
logger.info(f"🔇 NO_OUTPUT: Agent {agent_config.agent_id} returned empty/NO_OUTPUT. Not sending to Telegram.")
# P4: Detect NO_OUTPUT contract violations (extra text after NO_OUTPUT marker)
_stripped = (answer_text or "").strip()
_has_extra = False
if _stripped and "__NO_OUTPUT__" in _stripped:
_after_marker = _stripped.split("__NO_OUTPUT__", 1)[-1].strip()
if _after_marker:
_has_extra = True
logger.warning(
f"🚨 policy_violation=no_output_extra_text "
f"agent={agent_config.agent_id} "
f"chat_id={chat_id} "
f"extra_text_len={len(_after_marker)} "
f"extra_preview={_after_marker[:80]!r}"
)
elif _stripped and _stripped.lower() not in ("", "no_output", "no output", "silent", "мовчу", "", ".", "..", "..."):
# LLM returned something that looks like NO_OUTPUT but has unexpected content
if len(_stripped) > 10:
_has_extra = True
logger.warning(
f"🚨 policy_violation=ambiguous_no_output "
f"agent={agent_config.agent_id} "
f"chat_id={chat_id} "
f"response_len={len(_stripped)} "
f"response_preview={_stripped[:80]!r}"
)
# Save to memory for context tracking
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response="",
channel_id=chat_id,
scope="short_term",
save_agent_response=False,
agent_metadata={
"no_output": True,
"original_response": answer_text[:100] if answer_text else "",
"policy_violation": "no_output_extra_text" if _has_extra else None,
},
username=username,
)
return {"ok": True, "skipped": True, "reason": "no_output_from_llm"}
# Truncate if too long for Telegram
if len(answer_text) > TELEGRAM_SAFE_LENGTH:
answer_text = answer_text[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
# Skip Telegram sending for prober requests (chat_id=0)
if is_prober:
logger.info(f"🧪 PROBER: Skipping Telegram send for prober request. Response: {answer_text[:100]}...")
return {"ok": True, "agent": agent_config.agent_id, "prober": True, "response_preview": answer_text[:100]}
# Send image if generated
if image_base64:
try:
# Decode base64 image
image_bytes = base64.b64decode(image_base64)
# Send photo to Telegram
token = telegram_token or os.getenv("TELEGRAM_BOT_TOKEN")
url = f"https://api.telegram.org/bot{token}/sendPhoto"
async with httpx.AsyncClient() as client:
files = {"photo": ("image.png", BytesIO(image_bytes), "image/png")}
data = {"chat_id": chat_id, "caption": answer_text}
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}")
except Exception as e:
logger.error(f"❌ Failed to send image to Telegram: {e}")
# Fallback to text only
await send_telegram_message(chat_id, answer_text, telegram_token)
else:
# Send text response only
await send_telegram_message(chat_id, answer_text, telegram_token)
# Record successful interaction for conversation context
record_interaction(agent_config.agent_id, chat_id, str(user_id))
await memory_client.save_chat_turn(
agent_id=agent_config.agent_id,
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={
"mentioned_bots": mentioned_bots,
"requires_complex_reasoning": needs_complex_reasoning,
},
username=username,
)
store_response_cache(agent_config.agent_id, chat_id, text, answer_text)
return {"ok": True, "agent": agent_config.agent_id}
else:
error_msg = response.get("error", "Unknown error") if isinstance(response, dict) else "Router error"
logger.error(f"Router error: {error_msg}")
await send_telegram_message(chat_id, f"Вибач, сталася помилка: {error_msg}", telegram_token)
return {"ok": False, "error": error_msg}
# ========================================
# Endpoints
# ========================================
# DAARWIZZ webhook endpoints (both paths for compatibility)
@router.get("/healthz")
async def healthz():
try:
from crews.agromatrix_crew.run import handle_message # noqa: F401
return {"ok": True, "status": "healthy"}
except Exception as e:
return {"ok": False, "status": "error", "error": str(e)}
@router.post("/telegram/webhook")
async def telegram_webhook(update: TelegramUpdate):
"""Handle Telegram webhook for DAARWIZZ agent (default path)."""
try:
return await handle_telegram_webhook(DAARWIZZ_CONFIG, update)
except Exception as e:
logger.error(f"Error handling DAARWIZZ Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
@router.post("/daarwizz/telegram/webhook")
async def daarwizz_telegram_webhook(update: TelegramUpdate):
"""Handle Telegram webhook for DAARWIZZ agent (agent-specific path)."""
try:
return await handle_telegram_webhook(DAARWIZZ_CONFIG, update)
except Exception as e:
logger.error(f"Error handling DAARWIZZ Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
# Legacy code - will be removed after testing
async def _old_telegram_webhook(update: TelegramUpdate):
"""Стара версія - використовується для тестування"""
try:
if not update.message:
raise HTTPException(status_code=400, detail="No message in update")
# Extract message details
from_user = update.message.get("from", {})
chat = update.message.get("chat", {})
user_id = str(from_user.get("id", "unknown"))
chat_id = str(chat.get("id", "unknown"))
username = from_user.get("username", "")
# Get DAO ID for this chat
dao_id = get_dao_id(chat_id, "telegram", agent_id=agent_config.agent_id)
# Check for /ingest command
text = update.message.get("text", "")
if text and text.strip().startswith("/ingest"):
session_id = f"telegram:{chat_id}"
# Check if there's a document in the message
document = update.message.get("document")
if document:
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
is_pdf = (
mime_type == "application/pdf" or
(mime_type.startswith("application/") and file_name.lower().endswith(".pdf"))
)
if is_pdf and file_id:
try:
telegram_token = os.getenv("TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id)
if file_path:
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
result = await ingest_document(
session_id=session_id,
doc_url=file_url,
file_name=file_name,
dao_id=dao_id,
user_id=f"tg:{user_id}"
)
if result.success:
await send_telegram_message(
chat_id,
f"✅ **Документ імпортовано у RAG**\n\n"
f"📊 Фрагментів: {result.ingested_chunks}\n"
f"📁 DAO: {dao_id}\n\n"
f"Тепер ти можеш задавати питання по цьому документу!"
)
return {"ok": True, "chunks_count": result.ingested_chunks}
else:
await send_telegram_message(chat_id, f"Вибач, не вдалося імпортувати: {result.error}")
return {"ok": False, "error": result.error}
except Exception as e:
logger.error(f"Ingest failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося імпортувати документ.")
return {"ok": False, "error": "Ingest failed"}
# Try to get last parsed doc_id from session context
result = await ingest_document(
session_id=session_id,
dao_id=dao_id,
user_id=f"tg:{user_id}"
)
if result.success:
await send_telegram_message(
chat_id,
f"✅ **Документ імпортовано у RAG**\n\n"
f"📊 Фрагментів: {result.ingested_chunks}\n"
f"📁 DAO: {dao_id}\n\n"
f"Тепер ти можеш задавати питання по цьому документу!"
)
return {"ok": True, "chunks_count": result.ingested_chunks}
else:
await send_telegram_message(chat_id, "Спочатку надішли PDF-документ, а потім використай /ingest")
return {"ok": False, "error": result.error}
# Check if it's a document (PDF)
document = update.message.get("document")
if document:
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
# Check if it's a PDF
is_pdf = (
mime_type == "application/pdf" or
(mime_type.startswith("application/") and file_name.lower().endswith(".pdf"))
)
if is_pdf and file_id:
logger.info(f"PDF document from {username} (tg:{user_id}), file_id: {file_id}, file_name: {file_name}")
try:
# Get file path from Telegram
telegram_token = os.getenv("TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Build file URL
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
# Use doc_service for parsing
session_id = f"telegram:{chat_id}"
result = await parse_document(
session_id=session_id,
doc_url=file_url,
file_name=file_name,
dao_id=dao_id,
user_id=f"tg:{user_id}",
output_mode="qa_pairs",
metadata={"username": username, "chat_id": chat_id}
)
if not result.success:
await send_telegram_message(chat_id, f"Вибач, не вдалося обробити документ: {result.error}")
return {"ok": False, "error": result.error}
# Format response for Telegram
answer_text = ""
if result.qa_pairs:
# Convert QAItem to dict for formatting
qa_list = [{"question": qa.question, "answer": qa.answer} for qa in result.qa_pairs]
answer_text = format_qa_response(qa_list)
elif result.markdown:
answer_text = format_markdown_response(result.markdown)
elif result.chunks_meta and result.chunks_meta.get("chunks"):
chunks = result.chunks_meta.get("chunks", [])
answer_text = format_chunks_response(chunks)
else:
answer_text = "✅ Документ успішно оброблено, але формат відповіді не розпізнано."
# Add hint about /ingest command
if not answer_text.endswith("_"):
answer_text += "\n\n💡 _Використай /ingest для імпорту документа у RAG_"
logger.info(f"PDF parsing result: {len(answer_text)} chars, doc_id={result.doc_id}")
# Send response back to Telegram
await send_telegram_message(chat_id, answer_text)
return {"ok": True, "agent": "parser", "mode": "doc_parse", "doc_id": result.doc_id}
except Exception as e:
logger.error(f"PDF processing failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося обробити PDF-документ. Переконайся, що файл не пошкоджений.")
return {"ok": False, "error": "PDF processing failed"}
elif document and not is_pdf:
# Non-PDF document
await send_telegram_message(chat_id, "Наразі підтримуються тільки PDF-документи. Інші формати (docx, zip, тощо) будуть додані пізніше.")
return {"ok": False, "error": "Unsupported document type"}
# Check if it's a photo
photo = update.message.get("photo")
if photo:
# Telegram sends multiple sizes, get the largest one (last in array)
photo_obj = photo[-1] if isinstance(photo, list) else photo
file_id = photo_obj.get("file_id") if isinstance(photo_obj, dict) else None
if file_id:
logger.info(f"Photo from {username} (tg:{user_id}), file_id: {file_id}")
try:
# Get file path from Telegram
telegram_token = os.getenv("TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Build file URL
file_url = f"https://api.telegram.org/file/bot{telegram_token}/{file_path}"
# Send to Router with specialist_vision_8b model (Swapper)
router_request = {
"message": f"Коротко (2-3 речення) опиши значення цього зображення: {file_url}",
"mode": "chat",
"agent": "daarwizz",
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
"file_id": file_id,
"file_url": file_url,
"has_image": True,
},
"context": {
"agent_name": DAARWIZZ_NAME,
"system_prompt": DAARWIZZ_SYSTEM_PROMPT,
},
}
# Override LLM to use specialist_vision_8b for image understanding
router_request["metadata"]["use_llm"] = "specialist_vision_8b"
# Send to Router
logger.info(f"Sending photo to Router with vision-8b: file_url={file_url[:50]}...")
response = await send_to_router(router_request)
# Extract response
if isinstance(response, dict) and response.get("ok"):
answer_text = response.get("data", {}).get("text") or response.get("response", "")
if answer_text:
# Photo processed successfully
await send_telegram_message(
chat_id,
answer_text # No prefix, just the LLM response
)
# Save to memory for context
await memory_client.save_chat_turn(
agent_id="daarwizz",
team_id=dao_id,
user_id=f"tg:{user_id}",
message=f"[Photo: {file_id}]",
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={"context": "photo"},
username=username,
)
return {"ok": True, "agent": "daarwizz", "model": "specialist_vision_8b"}
else:
await send_telegram_message(chat_id, "Не вдалося отримати опис зображення.")
return {"ok": False, "error": "No description in response"}
else:
error_msg = response.get("error", "Unknown error") if isinstance(response, dict) else "Router error"
logger.error(f"Vision-8b error: {error_msg}")
await send_telegram_message(chat_id, f"Вибач, не вдалося обробити фото: {error_msg}")
return {"ok": False, "error": error_msg}
except Exception as e:
logger.error(f"Photo processing failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, сталася помилка при обробці фото.")
return {"ok": False, "error": "Photo processing failed"}
# Check if it's a voice message
voice = update.message.get("voice")
audio = update.message.get("audio")
video_note = update.message.get("video_note")
text = ""
if voice or audio or video_note:
# Голосове повідомлення - розпізнаємо через STT
media_obj = voice or audio or video_note
file_id = media_obj.get("file_id") if media_obj else None
if not file_id:
raise HTTPException(status_code=400, detail="No file_id in voice/audio/video_note")
logger.info(f"Voice message from {username} (tg:{user_id}), file_id: {file_id}")
try:
# Отримуємо файл з Telegram
file_path = await get_telegram_file_path(file_id)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Завантажуємо файл
file_url = f"https://api.telegram.org/file/bot{os.getenv('TELEGRAM_BOT_TOKEN')}/{file_path}"
async with httpx.AsyncClient(timeout=30.0) as client:
file_resp = await client.get(file_url)
file_resp.raise_for_status()
audio_bytes = file_resp.content
# Відправляємо в STT-сервіс
stt_upload_url = _resolve_stt_upload_url()
files = {"file": ("voice.ogg", audio_bytes, "audio/ogg")}
async with httpx.AsyncClient(timeout=60.0) as client:
stt_resp = await client.post(stt_upload_url, files=files)
stt_resp.raise_for_status()
stt_data = stt_resp.json()
text = stt_data.get("text", "")
logger.info(f"STT result: {text[:100]}...")
except Exception as e:
logger.error(f"STT processing failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося розпізнати голосове повідомлення. Спробуй надіслати текстом.", os.getenv("DAARWIZZ_TELEGRAM_BOT_TOKEN"))
return {"ok": False, "error": "STT failed"}
else:
# Текстове повідомлення
text = update.message.get("text", "")
caption = update.message.get("caption", "")
if not text and not caption:
# Check for unsupported message types and silently ignore
unsupported_types = ["sticker", "animation", "video_note", "contact", "location",
"venue", "poll", "dice", "game", "new_chat_members",
"left_chat_member", "new_chat_title", "new_chat_photo",
"delete_chat_photo", "pinned_message"]
for msg_type in unsupported_types:
if update.message.get(msg_type):
logger.debug(f"DAARWIZZ: Ignoring unsupported message type: {msg_type}")
return {"ok": True, "ignored": True, "reason": f"Unsupported message type: {msg_type}"}
# If no supported content found, return silently
return {"ok": True, "ignored": True, "reason": "No processable content"}
# Use caption if text is empty
if not text and caption:
text = caption
logger.info(f"Telegram message from {username} (tg:{user_id}) in chat {chat_id}: {text[:50]}")
# Check if there's a document context for follow-up questions
session_id = f"telegram:{chat_id}"
doc_context = await get_doc_context(session_id)
# 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 = (
"?" 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(
session_id=session_id,
question=text,
doc_id=doc_context.doc_id,
dao_id=dao_id or doc_context.dao_id,
user_id=f"tg:{user_id}"
)
if rag_result.success and rag_result.answer:
# Truncate if too long for Telegram
answer = rag_result.answer
if len(answer) > TELEGRAM_SAFE_LENGTH:
answer = answer[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
await send_telegram_message(chat_id, answer)
return {"ok": True, "agent": "parser", "mode": "rag_query"}
# Fall through to regular chat if RAG query fails
# Regular chat mode
# Fetch memory context
memory_context = await memory_client.get_context(
user_id=f"tg:{user_id}",
agent_id="daarwizz",
team_id=dao_id,
channel_id=chat_id,
limit=80
)
# Build request to Router with DAARWIZZ context
router_request = {
"message": text,
"mode": "chat",
"agent": "daarwizz", # DAARWIZZ agent identifier
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
},
"context": {
"agent_name": DAARWIZZ_NAME,
"system_prompt": DAARWIZZ_SYSTEM_PROMPT,
"memory": memory_context, # Додаємо пам'ять
# RBAC context will be injected by Router
},
}
# Send to Router
logger.info(f"Sending to Router: agent=daarwizz, dao={dao_id}, user=tg:{user_id}")
response = await send_to_router(router_request)
# Extract response text
if isinstance(response, dict):
answer_text = response.get("data", {}).get("text") or response.get("response", "Вибач, я зараз не можу відповісти.")
else:
answer_text = "Вибач, сталася помилка."
logger.info(f"Router response: {answer_text[:100]}")
# Save chat turn to memory
await memory_client.save_chat_turn(
agent_id="daarwizz",
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={"context": "legacy_daarwizz"},
username=username,
)
# Send response back to Telegram
await send_telegram_message(chat_id, answer_text, os.getenv("DAARWIZZ_TELEGRAM_BOT_TOKEN"))
return {"ok": True, "agent": "daarwizz"}
except Exception as e:
logger.error(f"Error handling Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
@router.post("/discord/webhook")
async def discord_webhook(message: DiscordMessage):
"""
Handle Discord webhook.
Discord message format:
{
"content": "Hello!",
"author": {"id": "123", "username": "alice"},
"channel_id": "456",
"guild_id": "789"
}
"""
try:
if not message.content:
raise HTTPException(status_code=400, detail="No content in message")
# Extract message details
text = message.content
author = message.author or {}
channel_id = message.channel_id or "unknown"
guild_id = message.guild_id or "unknown"
user_id = author.get("id", "unknown")
username = author.get("username", "")
# Get DAO ID for this channel
dao_id = get_dao_id(channel_id, "discord")
logger.info(f"Discord message from {username} (discord:{user_id}): {text[:50]}")
# Fetch memory context
memory_context = await memory_client.get_context(
user_id=f"discord:{user_id}",
agent_id="daarwizz",
team_id=dao_id,
channel_id=channel_id,
limit=80
)
# Build request to Router with DAARWIZZ context
router_request = {
"message": text,
"mode": "chat",
"agent": "daarwizz",
"metadata": {
"source": "discord",
"dao_id": dao_id,
"user_id": f"discord:{user_id}",
"session_id": f"discord:{channel_id}:{dao_id}",
"username": username,
"channel_id": channel_id,
"guild_id": guild_id,
},
"context": {
"agent_name": DAARWIZZ_NAME,
"system_prompt": DAARWIZZ_SYSTEM_PROMPT,
"memory": memory_context, # Додаємо пам'ять
},
}
# Send to Router
response = await send_to_router(router_request)
# Extract response text
if isinstance(response, dict):
answer_text = response.get("data", {}).get("text") or response.get("response", "Sorry, I can't respond right now.")
else:
answer_text = "Sorry, an error occurred."
logger.info(f"Router response: {answer_text[:100]}")
# Save chat turn to memory
await memory_client.save_chat_turn(
agent_id="daarwizz",
team_id=dao_id,
user_id=f"discord:{user_id}",
message=text,
response=answer_text,
channel_id=channel_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={"source": "discord"},
username=username,
)
# TODO: Send response back to Discord
# await send_discord_message(channel_id, answer_text)
return {"ok": True, "agent": "daarwizz", "response": answer_text}
except Exception as e:
logger.error(f"Error handling Discord webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
# ========================================
# Helper Functions
# ========================================
async def get_telegram_file_path(file_id: str, bot_token: str = None) -> Optional[str]:
"""Отримати шлях до файлу з Telegram API"""
telegram_token = bot_token or os.getenv("TELEGRAM_BOT_TOKEN")
if not telegram_token:
logger.error("TELEGRAM_BOT_TOKEN not set")
return None
url = f"https://api.telegram.org/bot{telegram_token}/getFile"
params = {"file_id": file_id}
try:
async with httpx.AsyncClient(timeout=10.0) as client:
response = await client.get(url, params=params)
response.raise_for_status()
data = response.json()
if data.get("ok"):
return data.get("result", {}).get("file_path")
except Exception as e:
logger.error(f"Error getting Telegram file: {e}")
return None
def format_qa_response(qa_pairs: list, max_pairs: int = 5) -> str:
"""Format Q&A pairs for Telegram with length limits"""
if not qa_pairs:
return "📋 Документ оброблено, але Q&A пари не знайдено."
qa_text = "📋 **Зміст документа:**\n\n"
displayed = 0
for i, qa in enumerate(qa_pairs[:max_pairs], 1):
question = qa.get('question', 'Питання')
answer = qa.get('answer', 'Відповідь')
# Truncate answer if too long
if len(answer) > 500:
answer = answer[:500] + "..."
pair_text = f"**{i}. {question}**\n{answer}\n\n"
# Check if adding this pair would exceed limit
if len(qa_text) + len(pair_text) > TELEGRAM_SAFE_LENGTH:
break
qa_text += pair_text
displayed += 1
if len(qa_pairs) > displayed:
remaining = len(qa_pairs) - displayed
qa_text += f"_... та ще {remaining} {'питань' if remaining > 1 else 'питання'}_"
return qa_text
def format_markdown_response(markdown: str) -> str:
"""Format markdown response - returns raw text for LLM processing"""
# Just return the text - LLM will summarize it
return markdown
def format_chunks_response(chunks: list) -> str:
"""Format chunks summary for Telegram"""
if not chunks:
return "📄 Документ розпарсено, але фрагменти не знайдено."
answer_text = f"📄 **Документ розпарсено** ({len(chunks)} фрагментів)\n\n"
answer_text += "**Перші фрагменти:**\n\n"
for i, chunk in enumerate(chunks[:3], 1):
text = chunk.get('text', '')[:200]
answer_text += f"{i}. {text}...\n\n"
if len(chunks) > 3:
answer_text += f"_... та ще {len(chunks) - 3} фрагментів_"
return answer_text
def _zip_read_summary(markdown_text: str) -> Optional[str]:
"""Extract a short summary of processed/skipped files from ZIP markdown."""
if not markdown_text:
return None
lines = [line.strip() for line in markdown_text.splitlines()]
try:
processed = []
skipped = []
idx = 0
while idx < len(lines):
line = lines[idx]
if line.lower() == "processed files:":
idx += 1
while idx < len(lines) and lines[idx].startswith("- "):
processed.append(lines[idx][2:].strip())
idx += 1
continue
if line.lower() == "skipped files:":
idx += 1
while idx < len(lines) and lines[idx].startswith("- "):
skipped.append(lines[idx][2:].strip())
idx += 1
continue
idx += 1
if not processed and not skipped:
return None
processed_text = ", ".join(processed) if processed else "нічого"
skipped_text = ", ".join(skipped) if skipped else "нічого"
return f"Прочитала з ZIP: {processed_text}; пропустила: {skipped_text}."
except Exception:
return None
def _default_theme_payload(brand_id: str) -> Dict[str, Any]:
"""Return a minimal theme.json payload for quick publish."""
return {
"theme_version": "v1.0.0",
"brand_id": brand_id,
"layout": {
"page": "LAYOUT_WIDE",
"safe_area": {"x": 0.6, "y": 0.45, "w": 12.1, "h": 6.2},
},
"palette": {
"primary": "#0B1220",
"secondary": "#1E293B",
"accent": "#22C55E",
"bg": "#FFFFFF",
"text": "#0F172A",
},
"typography": {
"font_primary": "Inter",
"font_secondary": "Inter",
"sizes": {"h1": 38, "h2": 28, "h3": 22, "body": 16, "small": 12},
"weights": {"regular": 400, "medium": 500, "bold": 700},
"line_height": {"tight": 1.05, "normal": 1.15, "relaxed": 1.25},
},
"components": {
"header": {"enabled": True, "logo_variant": "light", "show_title": False},
"footer": {"enabled": True, "show_page_number": True, "left_text": brand_id},
},
"rules": {
"max_bullets": 6,
"max_bullet_len": 110,
"min_font_body": 12,
"overflow_strategy": "appendix",
},
}
async def _brand_intake_request(payload: Dict[str, Any]) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(f"{BRAND_INTAKE_URL}/brand/intake", json=payload)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Brand intake error: {resp.text[:200]}")
return resp.json()
async def _brand_publish_theme(brand_id: str, theme: Dict[str, Any], theme_version: Optional[str]) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(
f"{BRAND_REGISTRY_URL}/brands/{brand_id}/themes",
json={"theme": theme, "theme_version": theme_version},
)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Brand publish error: {resp.text[:200]}")
return resp.json()
async def _brand_get_latest(brand_id: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{BRAND_REGISTRY_URL}/brands/{brand_id}/latest")
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Brand latest error: {resp.text[:200]}")
return resp.json()
async def _brand_get_theme(brand_id: str, theme_version: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{BRAND_REGISTRY_URL}/brands/{brand_id}/themes/{theme_version}")
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Brand get error: {resp.text[:200]}")
return resp.json()
async def _presentation_render(slidespec: Dict[str, Any], brand_id: str, theme_version: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=30.0) as client:
# Call presentation-renderer directly
resp = await client.post(
f"{PRESENTATION_RENDERER_URL}/present/render",
json={
"brand_id": brand_id,
"theme_version": theme_version or "v1.0.0",
"slidespec": slidespec,
"output": "pptx"
},
)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Presentation render error: {resp.text[:200]}")
result = resp.json()
# Return consistent response format
return {
"render_id": result.get("render_id"),
"artifact_id": result.get("render_id"), # Use render_id as artifact_id for now
"job_id": result.get("render_id"),
"status": result.get("status"),
"brand_id": brand_id,
"theme_version": theme_version
}
def _sanitize_error_text(text: str) -> str:
if not text:
return ""
sanitized = text
sanitized = re.sub(r"https?://\\S+", "[url]", sanitized)
sanitized = re.sub(r"[A-Za-z0-9_-]{20,}", "[token]", sanitized)
return sanitized[:400]
def _can_access_artifact(acl_ref: Optional[str], dao_id: Optional[str], user_id: str) -> bool:
if not acl_ref:
return True
acl = acl_ref.lower()
if "public" in acl:
return True
if dao_id and str(dao_id).lower() in acl:
return True
if user_id and user_id.lower() in acl:
return True
return False
async def _artifact_get(artifact_id: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{ARTIFACT_REGISTRY_URL}/artifacts/{artifact_id}")
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Artifact get error: {resp.text[:200]}")
return resp.json()
async def _artifact_versions(artifact_id: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{ARTIFACT_REGISTRY_URL}/artifacts/{artifact_id}/versions")
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Artifact versions error: {resp.text[:200]}")
return resp.json()
async def _artifact_job_status(job_id: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{ARTIFACT_REGISTRY_URL}/jobs/{job_id}")
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Job status error: {resp.text[:200]}")
return resp.json()
def _format_job_status_message(job: Dict[str, Any], job_id: str) -> str:
status = job.get("status")
job_type = job.get("job_type")
artifact_id = job.get("artifact_id")
input_version_id = job.get("input_version_id")
output_version_id = job.get("output_version_id")
error_text = _sanitize_error_text(job.get("error_text", ""))
meta = job.get("meta_json") or {}
if isinstance(meta, str):
try:
meta = json.loads(meta)
except Exception:
meta = {}
meta_bits = []
for key in ["chunks_count", "parser_version", "chunker_version", "index_fingerprint", "fingerprint", "parsed_version_id", "chunks_version_id"]:
if meta.get(key):
value = meta.get(key)
if key in {"fingerprint", "index_fingerprint"}:
value = str(value)[:16] + ""
meta_bits.append(f"{key}: {value}")
message = (
"📌 **Статус job**\n\n"
f"Status: `{status}`\n"
f"Type: `{job_type}`\n"
f"Job ID: `{job_id}`\n"
f"Artifact ID: `{artifact_id}`\n"
f"Input version: `{input_version_id}`"
)
if output_version_id:
message += f"\nOutput version: `{output_version_id}`"
if meta_bits:
message += "\nMeta: " + "; ".join(meta_bits)
if status == "failed" and error_text:
message += f"\nПомилка: `{error_text}`"
return message
async def _artifact_download(artifact_id: str, fmt: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.get(f"{ARTIFACT_REGISTRY_URL}/artifacts/{artifact_id}/download", params={"format": fmt})
if resp.status_code >= 400:
raise HTTPException(status_code=resp.status_code, detail=resp.text[:200])
return resp.json()
async def _artifact_create_job(artifact_id: str, job_type: str, input_version_id: str) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(
f"{ARTIFACT_REGISTRY_URL}/artifacts/{artifact_id}/jobs",
json={"job_type": job_type, "input_version_id": input_version_id},
)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Create job error: {resp.text[:200]}")
return resp.json()
async def _artifact_create(payload: Dict[str, Any]) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(f"{ARTIFACT_REGISTRY_URL}/artifacts", json=payload)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Artifact create error: {resp.text[:200]}")
return resp.json()
async def _artifact_add_version_from_url(artifact_id: str, payload: Dict[str, Any]) -> Dict[str, Any]:
async with httpx.AsyncClient(timeout=60.0) as client:
resp = await client.post(f"{ARTIFACT_REGISTRY_URL}/artifacts/{artifact_id}/versions/from_url", json=payload)
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Artifact version error: {resp.text[:200]}")
return resp.json()
async def _artifact_job_done(job_id: str, note: str) -> None:
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(f"{ARTIFACT_REGISTRY_URL}/jobs/{job_id}/done", json={"note": note})
if resp.status_code >= 400:
raise HTTPException(status_code=502, detail=f"Job done error: {resp.text[:200]}")
async def send_telegram_message(chat_id: str, text: str, bot_token: str = None):
"""Send message to Telegram chat"""
telegram_token = bot_token or os.getenv("TELEGRAM_BOT_TOKEN")
if not telegram_token:
logger.error("TELEGRAM_BOT_TOKEN not set")
return
url = f"https://api.telegram.org/bot{telegram_token}/sendMessage"
payload = {
"chat_id": chat_id,
"text": text,
# "parse_mode": "Markdown", # Removed to prevent 400 errors
}
try:
async with httpx.AsyncClient() as client:
response = await client.post(url, json=payload, timeout=10.0)
response.raise_for_status()
logger.info(f"Telegram message sent to chat {chat_id}")
except Exception as e:
logger.error(f"Error sending Telegram message: {e}")
# ========================================
# Helion Telegram Webhook
# ========================================
@router.post("/helion/telegram/webhook")
async def helion_telegram_webhook(update: TelegramUpdate):
"""
Handle Telegram webhook for Helion agent.
"""
try:
return await handle_telegram_webhook(HELION_CONFIG, update)
except Exception as e:
logger.error(f"Error handling Helion Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
# ========================================
# GREENFOOD Telegram Webhook
# ========================================
@router.post("/greenfood/telegram/webhook")
async def greenfood_telegram_webhook(update: TelegramUpdate):
"""
Handle Telegram webhook for GREENFOOD agent.
"""
try:
return await handle_telegram_webhook(GREENFOOD_CONFIG, update)
except Exception as e:
logger.error(f"Error handling GREENFOOD Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
# ========================================
# NUTRA Telegram Webhook
# ========================================
@router.post("/nutra/telegram/webhook")
async def nutra_telegram_webhook(update: TelegramUpdate):
"""
Handle Telegram webhook for NUTRA agent.
"""
try:
return await handle_telegram_webhook(NUTRA_CONFIG, update)
except Exception as e:
logger.error(f"Error handling NUTRA Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
# Legacy code - will be removed after testing
async def _old_helion_telegram_webhook(update: TelegramUpdate):
"""Стара версія - використовується для тестування"""
try:
if not update.message:
raise HTTPException(status_code=400, detail="No message in update")
# Extract message details
from_user = update.message.get("from", {})
chat = update.message.get("chat", {})
user_id = str(from_user.get("id", "unknown"))
chat_id = str(chat.get("id", "unknown"))
username = from_user.get("username", "")
# Get DAO ID for this chat (Energy Union specific)
dao_id = get_dao_id(chat_id, "telegram", agent_id=agent_config.agent_id)
# Check for /ingest command
text = update.message.get("text", "")
if text and text.strip().startswith("/ingest"):
session_id = f"telegram:{chat_id}"
# Check if there's a document in the message
document = update.message.get("document")
if document:
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
is_pdf = (
mime_type == "application/pdf" or
(mime_type.startswith("application/") and file_name.lower().endswith(".pdf"))
)
if is_pdf and file_id:
try:
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id)
if file_path:
file_url = f"https://api.telegram.org/file/bot{helion_token}/{file_path}"
result = await ingest_document(
session_id=session_id,
doc_url=file_url,
file_name=file_name,
dao_id=dao_id,
user_id=f"tg:{user_id}"
)
if result.success:
await send_telegram_message(
chat_id,
f"✅ **Документ імпортовано у RAG**\n\n"
f"📊 Фрагментів: {result.ingested_chunks}\n"
f"📁 DAO: {dao_id}\n\n"
f"Тепер ти можеш задавати питання по цьому документу!",
helion_token
)
return {"ok": True, "chunks_count": result.ingested_chunks}
else:
await send_telegram_message(chat_id, f"Вибач, не вдалося імпортувати: {result.error}", helion_token)
return {"ok": False, "error": result.error}
except Exception as e:
logger.error(f"Helion: Ingest failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося імпортувати документ.", helion_token)
return {"ok": False, "error": "Ingest failed"}
# Try to get last parsed doc_id from session context
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
result = await ingest_document(
session_id=session_id,
dao_id=dao_id,
user_id=f"tg:{user_id}"
)
if result.success:
await send_telegram_message(
chat_id,
f"✅ **Документ імпортовано у RAG**\n\n"
f"📊 Фрагментів: {result.ingested_chunks}\n"
f"📁 DAO: {dao_id}\n\n"
f"Тепер ти можеш задавати питання по цьому документу!",
helion_token
)
return {"ok": True, "chunks_count": result.ingested_chunks}
else:
await send_telegram_message(chat_id, "Спочатку надішли PDF-документ, а потім використай /ingest", helion_token)
return {"ok": False, "error": result.error}
# Check if it's a document (PDF)
document = update.message.get("document")
if document:
mime_type = document.get("mime_type", "")
file_name = document.get("file_name", "")
file_id = document.get("file_id")
is_pdf = (
mime_type == "application/pdf" or
(mime_type.startswith("application/") and file_name.lower().endswith(".pdf"))
)
if is_pdf and file_id:
logger.info(f"Helion: PDF document from {username} (tg:{user_id}), file_id: {file_id}, file_name: {file_name}")
try:
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
file_url = f"https://api.telegram.org/file/bot{helion_token}/{file_path}"
session_id = f"telegram:{chat_id}"
result = await parse_document(
session_id=session_id,
doc_url=file_url,
file_name=file_name,
dao_id=dao_id,
user_id=f"tg:{user_id}",
output_mode="qa_pairs",
metadata={"username": username, "chat_id": chat_id}
)
if not result.success:
await send_telegram_message(chat_id, f"Вибач, не вдалося обробити документ: {result.error}", helion_token)
return {"ok": False, "error": result.error}
# Format response for Telegram
answer_text = ""
if result.qa_pairs:
qa_list = [{"question": qa.question, "answer": qa.answer} for qa in result.qa_pairs]
answer_text = format_qa_response(qa_list)
elif result.markdown:
answer_text = format_markdown_response(result.markdown)
elif result.chunks_meta and result.chunks_meta.get("chunks"):
chunks = result.chunks_meta.get("chunks", [])
answer_text = format_chunks_response(chunks)
else:
answer_text = "✅ Документ успішно оброблено, але формат відповіді не розпізнано."
if not answer_text.endswith("_"):
answer_text += "\n\n💡 _Використай /ingest для імпорту документа у RAG_"
logger.info(f"Helion: PDF parsing result: {len(answer_text)} chars, doc_id={result.doc_id}")
await send_telegram_message(chat_id, answer_text, helion_token)
return {"ok": True, "agent": "parser", "mode": "doc_parse", "doc_id": result.doc_id}
except Exception as e:
logger.error(f"Helion: PDF processing failed: {e}", exc_info=True)
await send_telegram_message(chat_id, "Вибач, не вдалося обробити PDF-документ. Переконайся, що файл не пошкоджений.", helion_token)
return {"ok": False, "error": "PDF processing failed"}
elif document and not is_pdf:
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
await send_telegram_message(chat_id, "Наразі підтримуються тільки PDF-документи. Інші формати (docx, zip, тощо) будуть додані пізніше.", helion_token)
return {"ok": False, "error": "Unsupported document type"}
# Check if it's a photo
photo = update.message.get("photo")
if photo:
# Telegram sends multiple sizes, get the largest one (last in array)
photo_obj = photo[-1] if isinstance(photo, list) else photo
file_id = photo_obj.get("file_id") if isinstance(photo_obj, dict) else None
if file_id:
logger.info(f"Helion: Photo from {username} (tg:{user_id}), file_id: {file_id}")
try:
# Get file path from Telegram
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
file_path = await get_telegram_file_path(file_id, helion_token)
if not file_path:
raise HTTPException(status_code=400, detail="Failed to get file from Telegram")
# Build file URL
file_url = f"https://api.telegram.org/file/bot{helion_token}/{file_path}"
# Send to Router with specialist_vision_8b model (Swapper)
# IMPORTANT: Request BRIEF description (2-3 sentences per v2.3 prompt rules)
router_request = {
"message": f"Коротко (2-3 речення максимум): що на цьому зображенні та яке його значення для Energy Union? {file_url}",
"mode": "chat",
"agent": "helion",
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
"file_id": file_id,
"file_url": file_url,
"has_image": True,
},
"context": {
"agent_name": HELION_NAME,
"system_prompt": HELION_SYSTEM_PROMPT,
},
}
# Override LLM to use specialist_vision_8b for image understanding
router_request["metadata"]["use_llm"] = "specialist_vision_8b"
# Send to Router
logger.info(f"Helion: Sending photo to Router with vision-8b: file_url={file_url[:50]}...")
response = await send_to_router(router_request)
# Extract response
if isinstance(response, dict) and response.get("ok"):
answer_text = response.get("data", {}).get("text") or response.get("response", "")
if answer_text:
# Photo processed - send LLM response directly WITHOUT prefix
await send_telegram_message(
chat_id,
answer_text, # No prefix, just the LLM response
helion_token
)
# Save to memory for context
await memory_client.save_chat_turn(
agent_id="helion",
team_id=dao_id,
user_id=f"tg:{user_id}",
message=f"[Photo: {file_id}]",
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={"context": "photo"},
username=username,
)
return {"ok": True, "agent": "helion", "model": "specialist_vision_8b"}
else:
await send_telegram_message(chat_id, "Не вдалося отримати опис зображення.", helion_token)
return {"ok": False, "error": "No description in response"}
else:
error_msg = response.get("error", "Unknown error") if isinstance(response, dict) else "Router error"
logger.error(f"Helion: Vision-8b error: {error_msg}")
await send_telegram_message(chat_id, "Вибач, сталася помилка при обробці фото.", helion_token)
return {"ok": False, "error": error_msg}
except Exception as e:
logger.error(f"Helion: Photo processing failed: {e}", exc_info=True)
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
await send_telegram_message(chat_id, "Вибач, сталася помилка при обробці фото.", helion_token)
return {"ok": False, "error": "Photo processing failed"}
# Get message text
text = update.message.get("text", "")
if not text:
raise HTTPException(status_code=400, detail="No text in message")
logger.info(f"Helion Telegram message from {username} (tg:{user_id}) in chat {chat_id}: {text[:50]}")
mentioned_bots = extract_bot_mentions(text)
needs_complex_reasoning = requires_complex_reasoning(text)
# Check if there's a document context for follow-up questions
session_id = f"telegram:{chat_id}"
doc_context = await get_doc_context(session_id)
# 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 = (
"?" in text or
any(word in text.lower() for word in ["що", "як", "чому", "коли", "де", "хто", "чи"])
)
if is_question:
logger.info(f"Helion: Follow-up question detected for doc_id={doc_context.doc_id}")
# Try RAG query first
rag_result = await ask_about_document(
session_id=session_id,
question=text,
doc_id=doc_context.doc_id,
dao_id=dao_id or doc_context.dao_id,
user_id=f"tg:{user_id}"
)
if rag_result.success and rag_result.answer:
# Truncate if too long for Telegram
answer = rag_result.answer
if len(answer) > TELEGRAM_SAFE_LENGTH:
answer = answer[:TELEGRAM_SAFE_LENGTH] + "\n\n_... (відповідь обрізано)_"
helion_token = os.getenv("HELION_TELEGRAM_BOT_TOKEN")
await send_telegram_message(chat_id, answer, helion_token)
return {"ok": True, "agent": "parser", "mode": "rag_query"}
# Fall through to regular chat if RAG query fails
# Regular chat mode
# Fetch memory context (includes local context as fallback)
# All agents use limit=80 for full conversation history
memory_context = await memory_client.get_context(
user_id=f"tg:{user_id}",
agent_id="helion",
team_id=dao_id,
channel_id=chat_id,
limit=80
)
# Build message with conversation context
local_history = memory_context.get("local_context_text", "")
# Check if this is a training group
is_training_group = str(chat_id) in TRAINING_GROUP_IDS
training_prefix = ""
if is_training_group:
training_prefix = "[РЕЖИМ НАВЧАННЯ - відповідай на це повідомлення, ти в навчальній групі Agent Preschool]\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}"
else:
message_with_context = f"{training_prefix}{text}"
# Build request to Router with Helion context
router_request = {
"message": message_with_context,
"mode": "chat",
"agent": "helion", # Helion agent identifier
"metadata": {
"source": "telegram",
"dao_id": dao_id,
"user_id": f"tg:{user_id}",
"session_id": f"tg:{chat_id}:{dao_id}",
"username": username,
"chat_id": chat_id,
"mentioned_bots": mentioned_bots,
"requires_complex_reasoning": needs_complex_reasoning,
},
"context": {
"agent_name": HELION_NAME,
"system_prompt": HELION_SYSTEM_PROMPT,
"memory": memory_context,
# RBAC context will be injected by Router
},
}
# Send to Router
logger.info(f"Sending to Router: agent=helion, dao={dao_id}, user=tg:{user_id}")
response = await send_to_router(router_request)
# Extract response text
if isinstance(response, dict):
answer_text = response.get("data", {}).get("text") or response.get("response", "Вибач, я зараз не можу відповісти.")
else:
answer_text = "Вибач, сталася помилка."
logger.info(f"Router response: {answer_text[:100]}")
# Save chat turn to memory
await memory_client.save_chat_turn(
agent_id="helion",
team_id=dao_id,
user_id=f"tg:{user_id}",
message=text,
response=answer_text,
channel_id=chat_id,
scope="short_term",
save_agent_response=not is_service_response(answer_text),
agent_metadata={
"context": "helion",
"mentioned_bots": mentioned_bots,
"requires_complex_reasoning": needs_complex_reasoning,
},
username=username,
)
# Send response back to Telegram
await send_telegram_message(chat_id, answer_text, os.getenv("HELION_TELEGRAM_BOT_TOKEN"))
return {"ok": True, "agent": "helion"}
except Exception as e:
logger.error(f"Error handling Helion Telegram webhook: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=str(e))
@router.get("/health")
async def health():
"""Health check endpoint"""
agents_info = {}
for agent_id, config in AGENT_REGISTRY.items():
agents_info[agent_id] = {
"name": config.name,
"prompt_loaded": len(config.system_prompt) > 0,
"telegram_token_configured": config.get_telegram_token() is not None
}
return {
"status": "healthy",
"agents": agents_info,
"agents_count": len(AGENT_REGISTRY),
"timestamp": datetime.utcnow().isoformat(),
}
@router.post("/debug/agent_ping")
async def debug_agent_ping(request: dict = None):
"""
E2E probe endpoint - tests full agent pipeline.
Used by agent-e2e-prober for monitoring.
Returns success only if router responds.
"""
import time
start = time.time()
try:
# Test 1: Check router connectivity
router_url = os.getenv("ROUTER_URL", "http://router:8000")
async with httpx.AsyncClient(timeout=10.0) as client:
router_resp = await client.get(f"{router_url}/health")
router_ok = router_resp.status_code == 200
# Test 2: Check memory service connectivity
memory_url = os.getenv("MEMORY_SERVICE_URL", "http://memory-service:8000")
async with httpx.AsyncClient(timeout=10.0) as client:
memory_resp = await client.get(f"{memory_url}/health")
memory_ok = memory_resp.status_code == 200
latency = time.time() - start
return {
"success": router_ok and memory_ok,
"latency_seconds": round(latency, 3),
"checks": {
"router": router_ok,
"memory_service": memory_ok,
},
"timestamp": datetime.utcnow().isoformat(),
}
except Exception as e:
return {
"success": False,
"error": str(e)[:100],
"latency_seconds": round(time.time() - start, 3),
"timestamp": datetime.utcnow().isoformat(),
}