3de3c8cb36
- matrix-gateway: POST /internal/matrix/presence/online endpoint - usePresenceHeartbeat hook with activity tracking - Auto away after 5 min inactivity - Offline on page close/visibility change - Integrated in MatrixChatRoom component
262 lines
8.7 KiB
Python
262 lines
8.7 KiB
Python
from fastapi import FastAPI, HTTPException
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from models import AgentInvocation, AgentBlueprint, ChannelMessage
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from llm_client import generate_response
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from messaging_client import get_channel_messages, post_message
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from memory_client import query_memory, store_memory
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from pep_client import pep_client
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import asyncio
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import json
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import os
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app = FastAPI(title="DAARION Agent Runtime", version="1.0.0")
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# Configuration
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NATS_URL = os.getenv("NATS_URL", "nats://nats:4222")
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# NATS client
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nc = None
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nats_available = False
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@app.on_event("startup")
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async def startup_event():
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"""Initialize NATS connection and subscriptions"""
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global nc, nats_available
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print("🚀 Agent Runtime starting up...")
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# Try to connect to NATS
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try:
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import nats
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nc = await nats.connect(NATS_URL)
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nats_available = True
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print(f"✅ Connected to NATS at {NATS_URL}")
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# Subscribe to router invocations
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asyncio.create_task(subscribe_to_invocations())
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except Exception as e:
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print(f"⚠️ NATS not available: {e}")
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print("⚠️ Running in test mode (HTTP only)")
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nats_available = False
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async def subscribe_to_invocations():
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"""Subscribe to router.invoke.agent events"""
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if not nc:
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return
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try:
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sub = await nc.subscribe("router.invoke.agent")
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print("✅ Subscribed to router.invoke.agent")
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async for msg in sub.messages:
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try:
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invocation_data = json.loads(msg.data.decode())
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await handle_invocation(invocation_data)
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except Exception as e:
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print(f"❌ Error processing invocation: {e}")
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import traceback
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traceback.print_exc()
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except Exception as e:
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print(f"❌ Subscription error: {e}")
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async def handle_invocation(invocation_data: dict):
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"""
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Process agent invocation
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Flow:
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1. Load agent blueprint
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2. Load channel history
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3. Query memory
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4. Build LLM prompt
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5. Generate response
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6. Post to channel
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7. Store in memory (optional)
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"""
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try:
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print(f"\n🤖 Processing agent invocation")
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invocation = AgentInvocation(**invocation_data)
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if invocation.entrypoint != "channel_message":
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print(f"⚠️ Ignoring non-channel_message invocation: {invocation.entrypoint}")
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return
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# Extract payload
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channel_id = invocation.payload.get("channel_id")
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microdao_id = invocation.payload.get("microdao_id")
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rewrite_prompt = invocation.payload.get("rewrite_prompt")
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if not channel_id:
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print(f"❌ No channel_id in payload")
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return
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print(f"📝 Agent: {invocation.agent_id}")
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print(f"📝 Channel: {channel_id}")
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print(f"📝 MicroDAO: {microdao_id}")
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# 1. Load agent blueprint
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blueprint = await load_agent_blueprint(invocation.agent_id)
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print(f"✅ Loaded blueprint: {blueprint.name} (model: {blueprint.model})")
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# 2. Load channel history
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messages = await get_channel_messages(channel_id, limit=50)
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if not messages:
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print(f"⚠️ No messages found in channel")
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return
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# 3. Get last human message
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last_human_msg = None
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for msg in reversed(messages):
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if msg.sender_type == "human":
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last_human_msg = msg
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break
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if not last_human_msg:
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print("⚠️ No human message found, skipping")
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return
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print(f"💬 User message: {last_human_msg.content[:100]}...")
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# 4. Query memory
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memory_results = await query_memory(
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invocation.agent_id,
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microdao_id or "microdao:daarion",
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last_human_msg.content
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)
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# 5. Build prompt
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system_prompt = blueprint.instructions
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if rewrite_prompt:
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system_prompt += f"\n\n{rewrite_prompt}"
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print(f"📝 Applied rewrite prompt (quiet hours)")
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llm_messages = [
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{"role": "system", "content": system_prompt}
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]
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# Add memory context if available
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if memory_results:
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memory_context = "\n\n".join([
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r.get("text", r.get("content", ""))
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for r in memory_results[:3]
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])
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if memory_context:
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llm_messages.append({
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"role": "system",
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"content": f"Relevant knowledge:\n{memory_context}"
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})
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print(f"✅ Added {len(memory_results)} memory fragments to context")
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# Add recent conversation (last 10 messages)
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for msg in messages[-10:]:
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role = "assistant" if msg.sender_type == "agent" else "user"
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llm_messages.append({
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"role": role,
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"content": msg.content
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})
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print(f"📝 Built prompt with {len(llm_messages)} messages")
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# TODO Phase 4+: Parse tool calls from LLM response
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# If LLM wants to call a tool:
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# 1. Check permission via PEP:
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# permitted = await pep_client.check_tool_permission(
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# agent_id=invocation.agent_id,
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# tool_id="projects.list",
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# microdao_id=microdao_id
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# )
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# 2. If denied, inform LLM in next turn
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# 3. If permitted, call toolcore
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# 6. Generate response
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print(f"🤔 Generating response...")
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response_text = await generate_response(
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blueprint.model,
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llm_messages,
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agent_id=invocation.agent_id,
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microdao_id=microdao_id or "microdao:daarion"
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)
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print(f"✅ Generated response: {response_text[:100]}...")
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# 7. Post to channel
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print(f"📤 Posting to channel...")
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success = await post_message(invocation.agent_id, channel_id, response_text)
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if success:
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print(f"✅ Agent {invocation.agent_id} replied successfully")
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# 8. Store in memory (optional)
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await store_memory(
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invocation.agent_id,
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microdao_id or "microdao:daarion",
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channel_id,
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{
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"user_message": last_human_msg.content,
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"agent_reply": response_text,
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"timestamp": last_human_msg.created_at.isoformat()
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}
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)
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else:
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print(f"❌ Failed to post agent reply")
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except Exception as e:
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print(f"❌ Error handling invocation: {e}")
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import traceback
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traceback.print_exc()
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async def load_agent_blueprint(agent_id: str) -> AgentBlueprint:
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"""
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Load agent blueprint
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In Phase 2: Returns mock blueprint
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In Phase 3: Will call agents-service
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"""
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# Mock blueprint for Phase 2
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return AgentBlueprint(
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id=agent_id,
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name="Sofia-Prime",
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model="gpt-4",
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instructions="""Ти Sofia, асистент команди DAARION. Твоя роль:
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- Допомагати з плануванням та організацією роботи
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- Підсумовувати обговорення та зустрічі
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- Відповідати на питання про систему DAARION
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- Створювати задачі та follow-up нагадування
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- Бути friendly та supportive
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Важливо:
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- Відповідай українською мовою
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- Будь конкретна та корисна
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- Якщо не знаєш точної відповіді, так і скажи
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- Пропонуй наступні кроки або питання для уточнення""",
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capabilities={
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"can_create_tasks": True,
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"can_summarize": True,
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"can_search_docs": True
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},
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tools=["create_task", "create_followup", "summarize_channel"]
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)
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@app.get("/health")
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async def health():
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"""Health check endpoint"""
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return {
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"status": "ok",
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"service": "agent-runtime",
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"version": "1.0.0",
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"nats_connected": nats_available
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}
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@app.post("/internal/agent-runtime/test-channel")
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async def test_channel(invocation: AgentInvocation):
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"""Test endpoint for manual invocation"""
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print(f"\n🧪 Test invocation received")
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await handle_invocation(invocation.dict())
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return {"status": "processed", "agent_id": invocation.agent_id}
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@app.on_event("shutdown")
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async def shutdown_event():
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"""Clean shutdown"""
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global nc
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if nc:
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await nc.close()
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print("✅ NATS connection closed")
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