plans and docs

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"""
Multi-Agent Conductor - 4-tier MMA orchestration engine.
This module implements the ConductorEngine and WorkerPool for executing
implementation tracks via the 4-tier Multi-Model Agent (MMA) hierarchy.
Key Components:
- WorkerPool: Bounded concurrent worker pool with semaphore gating
- ConductorEngine: Main orchestration loop with DAG execution
- run_worker_lifecycle: Tier 3 worker execution function
Architecture Integration:
- Uses TrackDAG and ExecutionEngine from dag_engine.py
- Communicates with GUI via SyncEventQueue
- Manages tier-specific token usage via update_usage()
Thread Safety:
- WorkerPool uses threading.Lock for all state mutations
- ConductorEngine uses _tier_usage_lock for tier usage tracking
- Abort events use threading.Event for worker cancellation
Configuration:
- max_workers: Loaded from config.toml [mma].max_workers (default: 4)
See Also:
- docs/guide_mma.md for full MMA documentation
- src/dag_engine.py for TrackDAG and ExecutionEngine
- src/models.py for Ticket, Track, WorkerContext
"""
"""
Multi-Agent Conductor - MMA 4-Tier orchestration engine.
This module provides the ConductorEngine and WorkerPool for orchestrating
the execution of implementation tickets within a Track using the DAG engine
and the bounded concurrent worker pool with abort event propagation.
Key Components:
- ConductorEngine: Tier 2 orchestrator that owns the execution loop
- WorkerPool: Bounded concurrent worker pool with semaphore gating
- run_worker_lifecycle: Stateless Tier 3 worker execution with context amnesia
Thread Safety:
- All state mutations use locks (_workers_lock, _tier_usage_lock)
- Worker threads are daemon threads that clean up on exit
- Abort events enable per-ticket cancellation
Integration:
- Uses SyncEventQueue for state updates to the GUI
- Uses ai_client.send() for LLM communication
- Uses mcp_client for tool dispatch
See Also:
- docs/guide_mma.md for MMA orchestration documentation
- src/dag_engine.py for TrackDAG and ExecutionEngine
- src/ai_client.py for multi-provider LLM abstraction
- src/models.py for Ticket, Track, WorkerContext data structures
"""
from src import ai_client
import json
import threading