Phase 3.5: Automation & Agents Plugin
Neues automation Plugin (app/plugins/builtins/automation/): - 7 DB-Modelle: AgentDefinition, AgentVersion, AutomationDefinition, AutomationVersion, AutomationCronJob, AgentRun, AutomationRun - Migration 0001_initial.sql mit allen Tabellen + RLS - PluginManifest erweitert: agent_definitions, automation_templates, cron_jobs, heartbeat_configs, miniapps Contribution-Felder - 21 API-Endpoints: /api/v1/automation (CRUD, execute, dry-run, runs, versions, restore, settings, miniapps) + /api/v1/agents (CRUD, execute, test-run, runs, versions, restore, tools, send-message) Backend Features: - Cron-Scheduler (scheduler.py): ARQ-basiert, liest CronJob-Tabelle, enqueued run_agent/run_automation, croniter fuer next_run_at - Workflow-Timeout-Worker (workflow_timeout.py): prueft abgelaufene WorkflowInstances, setzt cancelled, sendet Notification - Agent Runner (agent_runner.py): LiteLLM + ToolRegistry, proactive/ reactive mode, Rate-Limiting, Budget-Limit, Infinite-Loop-Detection - Automation Execution Engine (execution_engine.py): Condition evaluation (eq/ne/gt/lt/contains/exists), Actions (api_call/ notification/workflow_start), Dry-Run mode - Agent-to-Agent Communication (agent_comm.py): send_agent_message tool, kommunikation plugin integration - Plugin-Beitraege: register/unregister on activate/deactivate, Konfliktloesung mit Plugin-Name als Prefix - Heartbeat-Migration: ai_proactive heartbeat als Cron-Job - Versionshistorie: Auto-Versioning bei Updates, Restore-Endpoint - Settings: GET/PATCH /api/v1/automation/settings - ARQ Worker: 11 functions, 2 cron_jobs (scheduler_tick 30s, check_workflow_timeouts 5min) Frontend: - AutomationDashboard.tsx: Automation Builder UI mit Trigger, Conditions, Actions, Execute, Dry-Run, Run-History, Versions - AgentDashboard.tsx: Agent Builder UI mit Model, Tools, Prompt, Heartbeat, Rate-Limits, Execute, Test-Run, Agent-Chat - AutomationSettings.tsx: Settings + MiniApp-Builder - automation.ts: 24 React Query Hooks - automation.ts types: TypeScript Interfaces - routes/index.tsx: /automation, /agents, /settings/automation Tests: - 22 Frontend-Tests (AutomationDashboard, AgentDashboard, API) — alle bestanden - Backend-Tests: test_automation.py (CRUD, versions, conditions, dry-run, rate-limiting) - TSC: keine neuen Errors (nur pre-existing Dms.tsx) - croniter dependency installiert
This commit is contained in:
Agent Zero
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"""Agent-to-Agent communication router."""
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from __future__ import annotations
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import json
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import logging
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import uuid
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from typing import Any
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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logger = logging.getLogger(__name__)
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async def send_agent_message(
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from_agent_id: str,
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to_agent_name: str,
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message: str,
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db: AsyncSession,
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tenant_id: uuid.UUID,
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) -> dict:
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"""Send a message from one agent to another.
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1. Find target agent by name
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2. Create a kommunikation message in a dedicated agent room
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3. Enqueue run_agent for the target agent with the message as trigger_data
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4. Return delivery status
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"""
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from app.plugins.builtins.automation.models import AgentDefinition
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from app.plugins.builtins.automation.agent_runner import run_agent
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# 1. Find target agent by name
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result = await db.execute(
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select(AgentDefinition)
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.where(AgentDefinition.name == to_agent_name)
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.where(AgentDefinition.tenant_id == tenant_id)
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.limit(1)
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)
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target_agent = result.scalar_one_or_none()
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if target_agent is None:
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logger.warning(
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"Target agent '%s' not found for message from agent %s",
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to_agent_name, from_agent_id,
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)
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return {"status": "error", "error": f"Target agent '{to_agent_name}' not found"}
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if not target_agent.is_active:
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logger.warning(
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"Target agent '%s' is inactive, cannot deliver message from %s",
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to_agent_name, from_agent_id,
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)
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return {"status": "error", "error": f"Target agent '{to_agent_name}' is inactive"}
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# 2. Create a kommunikation message in a dedicated agent room
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try:
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from app.plugins.builtins.kommunikation.models import Message, Room
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from app.plugins.builtins.kommunikation.services import RoomService
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# Find or create the agent-to-agent room
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room_name = f"agent:{from_agent_id}:{target_agent.id}"
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room_result = await db.execute(
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select(Room).where(Room.name == room_name).limit(1)
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)
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room = room_result.scalar_one_or_none()
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if room is None:
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# Create a new room for agent communication
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room = Room(
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tenant_id=tenant_id,
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name=room_name,
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display_name=f"Agent Chat: {from_agent_id} -> {to_agent_name}",
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room_type="agent_comm",
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is_direct=True,
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)
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db.add(room)
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await db.flush()
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# Create the message
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msg = Message(
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tenant_id=tenant_id,
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room_id=room.id,
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sender_id=from_agent_id,
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sender_type="agent",
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content=message,
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message_type="agent_comm",
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)
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db.add(msg)
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await db.flush()
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logger.info(
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"Agent message created: %s -> %s in room %s",
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from_agent_id, to_agent_name, room_name,
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)
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except ImportError:
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logger.warning("Kommunikation plugin not available, skipping message storage")
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except Exception as e:
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logger.exception("Failed to create kommunikation message: %s", e)
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# 3. Enqueue run_agent for the target agent with the message as trigger_data
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try:
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trigger_data = {
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"from_agent_id": from_agent_id,
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"message": message,
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"type": "agent_comm",
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}
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# Run the target agent with the message as trigger data
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result_data = await run_agent(
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ctx={},
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agent_id=str(target_agent.id),
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trigger_type="agent_comm",
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trigger_data=trigger_data,
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)
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logger.info(
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"Target agent %s executed with message from %s: status=%s",
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to_agent_name, from_agent_id, result_data.get("status"),
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)
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except Exception as e:
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logger.exception("Failed to run target agent %s: %s", to_agent_name, e)
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return {"status": "error", "error": f"Failed to activate target agent: {e}"}
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return {
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"status": "sent",
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"target_agent": to_agent_name,
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"target_agent_id": str(target_agent.id),
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}
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def register_agent_comm_tool():
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"""Register the send_agent_message tool in the global tool registry."""
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from app.plugins.builtins.ai_assistant.tool_registry import get_tool_registry
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registry = get_tool_registry()
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async def handler(arguments: dict[str, Any], context: dict[str, Any]) -> str:
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"""Handle send_agent_message tool call from an AI agent."""
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from app.core.db import get_session_factory
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to_agent_name = arguments.get("to_agent_name", "")
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message = arguments.get("message", "")
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from_agent_id = context.get("agent_id", "unknown")
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tenant_id_str = context.get("tenant_id", "")
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if not to_agent_name or not message:
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return json.dumps({"status": "error", "error": "Missing to_agent_name or message"})
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try:
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tenant_id = uuid.UUID(tenant_id_str) if tenant_id_str else uuid.uuid4()
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except (ValueError, TypeError):
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return json.dumps({"status": "error", "error": "Invalid tenant_id"})
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factory = get_session_factory()
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async with factory() as db:
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result = await send_agent_message(
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from_agent_id=from_agent_id,
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to_agent_name=to_agent_name,
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message=message,
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db=db,
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tenant_id=tenant_id,
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)
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return json.dumps(result)
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registry.register(
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name="send_agent_message",
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description="Send a message to another agent. The target agent will be activated with your message.",
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parameters={
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"type": "object",
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"properties": {
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"to_agent_name": {
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"type": "string",
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"description": "Name of the target agent",
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},
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"message": {
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"type": "string",
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"description": "Message to send",
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},
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},
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"required": ["to_agent_name", "message"],
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},
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handler=handler,
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plugin_name="automation",
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required_permission="agents:execute",
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category="communication",
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)
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logger.info("Agent communication tool 'send_agent_message' registered")
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def unregister_agent_comm_tool():
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"""Unregister the send_agent_message tool."""
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from app.plugins.builtins.ai_assistant.tool_registry import get_tool_registry
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registry = get_tool_registry()
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registry.unregister("send_agent_message")
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logger.info("Agent communication tool 'send_agent_message' unregistered")
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