0c8bef82f4
## Agents Added - Alateya: R&D, biotech, innovations - Clan (Spirit): Community spirit agent - Eonarch: Consciousness evolution agent ## Changes - docker-compose.node1.yml: Added tokens for all 3 new agents - gateway-bot/http_api.py: Added configs and webhook endpoints - gateway-bot/clan_prompt.txt: New prompt file - gateway-bot/eonarch_prompt.txt: New prompt file ## Fixes - Fixed ROUTER_URL from :9102 to :8000 (internal container port) - All 9 Telegram agents now working ## Documentation - Created PROJECT-MASTER-INDEX.md - single entry point - Added various status documents and scripts Tokens configured: - Helion, NUTRA, Agromatrix (existing) - Alateya, Clan, Eonarch (new) - Druid, GreenFood, DAARWIZZ (configured)
343 lines
13 KiB
Python
343 lines
13 KiB
Python
import asyncio
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import os
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import logging
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import time
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from typing import Optional, Dict, Any, List, Tuple
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from datetime import datetime
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from collections import deque
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import httpx
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logger = logging.getLogger(__name__)
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MEMORY_SERVICE_URL = os.getenv("MEMORY_SERVICE_URL", "http://memory-service:8000")
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CONTEXT_CACHE_TTL = float(os.getenv("MEMORY_CONTEXT_CACHE_TTL", "5"))
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LOCAL_CONTEXT_MAX_MESSAGES = int(os.getenv("LOCAL_CONTEXT_MAX_MESSAGES", "50"))
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# =====================================
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# LOCAL CONTEXT STORE (fallback when Memory Service unavailable)
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# =====================================
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class LocalContextStore:
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"""Локальне сховище контексту (in-memory) для випадків, коли Memory Service недоступний"""
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def __init__(self, max_messages: int = LOCAL_CONTEXT_MAX_MESSAGES):
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self.max_messages = max_messages
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# {chat_id: deque([(role, text, timestamp), ...])}
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self._store: Dict[str, deque] = {}
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def add_message(self, chat_id: str, role: str, text: str):
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"""Додати повідомлення до контексту"""
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if chat_id not in self._store:
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self._store[chat_id] = deque(maxlen=self.max_messages)
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self._store[chat_id].append({
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"role": role,
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"text": text,
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"timestamp": datetime.now().isoformat()
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})
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def get_context(self, chat_id: str, limit: int = 30) -> List[Dict[str, Any]]:
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"""Отримати останні повідомлення для контексту"""
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if chat_id not in self._store:
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return []
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messages = list(self._store[chat_id])
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return messages[-limit:] if limit else messages
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def clear_chat(self, chat_id: str):
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"""Очистити контекст чату"""
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if chat_id in self._store:
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del self._store[chat_id]
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def format_for_prompt(self, chat_id: str, limit: int = 30) -> str:
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"""Форматувати контекст для system prompt"""
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messages = self.get_context(chat_id, limit)
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if not messages:
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return ""
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lines = []
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for msg in messages:
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role = "User" if msg["role"] == "user" else "Assistant"
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lines.append(f"{role}: {msg['text']}")
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return "\n".join(lines)
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# Global local context store
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local_context = LocalContextStore()
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class MemoryClient:
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"""Клієнт для роботи з Memory Service"""
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def __init__(self, base_url: str = MEMORY_SERVICE_URL):
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self.base_url = base_url.rstrip("/")
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self.timeout = 10.0
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self._context_cache: Dict[str, Tuple[float, Dict[str, Any]]] = {}
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def _cache_key(
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self,
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user_id: str,
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agent_id: str,
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team_id: str,
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channel_id: Optional[str],
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limit: int
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) -> str:
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return f"{user_id}:{agent_id}:{team_id}:{channel_id}:{limit}"
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async def get_context(
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self,
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user_id: str,
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agent_id: str,
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team_id: str,
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channel_id: Optional[str] = None,
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limit: int = 10
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) -> Dict[str, Any]:
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"""
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Отримати контекст пам'яті для діалогу.
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Використовує локальний кеш як fallback, якщо Memory Service недоступний.
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"""
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cache_key = self._cache_key(user_id, agent_id, team_id, channel_id, limit)
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cached = self._context_cache.get(cache_key)
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now = time.monotonic()
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if cached and now - cached[0] < CONTEXT_CACHE_TTL:
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return cached[1]
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# Спроба отримати контекст із Memory Service
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try:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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params = {
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"user_id": user_id,
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"channel_id": channel_id,
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"limit": limit,
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}
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resp = await client.get(
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f"{self.base_url}/agents/{agent_id}/memory",
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params=params,
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headers={"Authorization": f"Bearer {user_id}"},
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)
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if resp.status_code == 200:
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data = resp.json()
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events = data.get("events", [])
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# Сортуємо за timestamp, якщо є
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events = sorted(
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events,
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key=lambda e: e.get("timestamp", ""),
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)
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recent_events = [
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{
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"body_text": e.get("content", ""),
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"kind": e.get("kind", "message"),
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"type": "user" if e.get("role") == "user" else "agent",
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}
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for e in events
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if e.get("content")
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]
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# Формуємо контекст для prompt
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lines = []
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for e in events:
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content = e.get("content", "")
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if not content:
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continue
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role = "User" if e.get("role") == "user" else "Assistant"
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lines.append(f"{role}: {content}")
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result = {
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"facts": [],
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"recent_events": recent_events,
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"dialog_summaries": [],
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"local_context_text": "\n".join(lines[-limit:]),
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}
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self._context_cache[cache_key] = (now, result)
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return result
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except Exception as e:
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logger.debug(f"Memory Service context fetch failed, using local: {e}")
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# FALLBACK: локальний контекст (in-memory)
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local_messages = local_context.get_context(str(channel_id or user_id), limit)
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local_events = [
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{"body_text": msg["text"], "kind": "message", "type": "user" if msg["role"] == "user" else "agent"}
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for msg in local_messages
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]
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result = {
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"facts": [],
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"recent_events": local_events,
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"dialog_summaries": [],
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"local_context_text": local_context.format_for_prompt(str(channel_id or user_id), limit),
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}
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self._context_cache[cache_key] = (now, result)
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return result
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async def save_chat_turn(
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self,
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agent_id: str,
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team_id: str,
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user_id: str,
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message: str,
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response: str,
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channel_id: Optional[str] = None,
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scope: str = "short_term",
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save_agent_response: bool = True,
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agent_metadata: Optional[Dict[str, Any]] = None
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) -> bool:
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"""
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Зберегти один turn діалогу (повідомлення + відповідь).
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Завжди зберігає в локальний контекст + намагається зберегти в Memory Service.
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"""
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chat_key = str(channel_id or user_id)
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# ЗАВЖДИ зберігаємо в локальний контекст
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local_context.add_message(chat_key, "user", message)
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if save_agent_response and response:
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local_context.add_message(chat_key, "assistant", response)
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logger.info(f"💾 Saved to local context: chat={chat_key}, messages={len(local_context.get_context(chat_key))}")
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# Спроба зберегти в Memory Service (може бути недоступний)
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try:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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user_event = {
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"agent_id": agent_id,
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"team_id": team_id,
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"channel_id": channel_id,
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"user_id": user_id,
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"scope": scope,
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"kind": "message",
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"body_text": message,
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"body_json": {"type": "user_message", "source": "telegram"}
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}
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await client.post(
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f"{self.base_url}/agents/{agent_id}/memory",
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json=user_event,
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headers={"Authorization": f"Bearer {user_id}"}
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)
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if save_agent_response and response:
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agent_event = {
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"agent_id": agent_id,
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"team_id": team_id,
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"channel_id": channel_id,
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"user_id": user_id,
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"scope": scope,
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"kind": "message",
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"body_text": response,
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"body_json": {
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"type": "agent_response",
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"source": "telegram",
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**(agent_metadata or {})
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}
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}
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await client.post(
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f"{self.base_url}/agents/{agent_id}/memory",
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json=agent_event,
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headers={"Authorization": f"Bearer {user_id}"}
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)
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return True
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except Exception as e:
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# Memory Service недоступний - але локальний контекст вже збережено
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logger.debug(f"Memory Service unavailable (using local context): {e}")
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return True # Return True because local context was saved
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async def create_dialog_summary(
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self,
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team_id: str,
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channel_id: Optional[str],
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agent_id: str,
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user_id: Optional[str],
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period_start: datetime,
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period_end: datetime,
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summary_text: str,
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message_count: int = 0,
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participant_count: int = 0,
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topics: Optional[List[str]] = None,
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summary_json: Optional[Dict[str, Any]] = None
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) -> bool:
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"""
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Створити підсумок діалогу для масштабування без переповнення контексту
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"""
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try:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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response = await client.post(
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f"{self.base_url}/summaries",
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json={
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"team_id": team_id,
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"channel_id": channel_id,
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"agent_id": agent_id,
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"user_id": user_id,
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"period_start": period_start.isoformat(),
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"period_end": period_end.isoformat(),
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"summary_text": summary_text,
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"summary_json": summary_json,
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"message_count": message_count,
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"participant_count": participant_count,
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"topics": topics or [],
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"meta": {}
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},
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headers={"Authorization": f"Bearer {user_id or 'system'}"}
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)
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return response.status_code in [200, 201]
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except Exception as e:
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logger.warning(f"Failed to create dialog summary: {e}")
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return False
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async def upsert_fact(
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self,
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user_id: str,
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fact_key: str,
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fact_value: Optional[str] = None,
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fact_value_json: Optional[Dict[str, Any]] = None,
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team_id: Optional[str] = None
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) -> bool:
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"""
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Створити або оновити факт користувача
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"""
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try:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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response = await client.post(
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f"{self.base_url}/facts/upsert",
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json={
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"user_id": user_id,
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"fact_key": fact_key,
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"fact_value": fact_value,
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"fact_value_json": fact_value_json,
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"team_id": team_id
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},
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headers={"Authorization": f"Bearer {user_id}"}
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)
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return response.status_code in [200, 201]
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except Exception as e:
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logger.warning(f"Failed to upsert fact: {e}")
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return False
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async def get_fact(
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self,
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user_id: str,
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fact_key: str,
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team_id: Optional[str] = None
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) -> Optional[Dict[str, Any]]:
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"""
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Отримати факт користувача
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Returns:
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Fact dict with fact_value and fact_value_json, or None if not found
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"""
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try:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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response = await client.get(
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f"{self.base_url}/facts/{fact_key}",
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params={
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"user_id": user_id,
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"team_id": team_id
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},
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headers={"Authorization": f"Bearer {user_id}"}
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)
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if response.status_code == 200:
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return response.json()
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return None
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except Exception as e:
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logger.warning(f"Failed to get fact: {e}")
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return None
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# Глобальний екземпляр клієнта
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memory_client = MemoryClient()
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