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grisun0 edited this page Oct 25, 2026 · 22 revisions

API (page 21 of 24)

Previous: API_p20.md

skills/swan_agent.py

Depends on: core/logging.py, modules/detection_oracle.py, modules/logging_config.py, modules/moe_router.py, modules/rl_trainer.py, skills/hive_mind.py, skills/lazyown_groq_agents.py, skills/lazyown_policy.py Imported by: modules/loop_ai_bridge.py, skills/autonomous_daemon.py, skills/lazyown_mcp.py, skills/unified_orchestrator.py, tests/test_moe_rl_swan.py

  • SwanResult.is_success (method) skills/swan_agent.py:167 def is_success(self)
  • IResultAggregator.aggregate (method) skills/swan_agent.py:209 def aggregate(self, task_type, goal, votes) -- Return (synthesis_text, consensus_confidence).
  • ISwanOrchestrator.run (method) skills/swan_agent.py:226 def run(self, task_type, goal, engagement_phase, timeout) -- Execute with the best single expert and return result.
  • ISwanOrchestrator.ensemble_run (method) skills/swan_agent.py:236 def ensemble_run(self, task_type, goal, n_experts, engagement_phase, timeout) -- Execute with top-N experts in parallel and synthesize results.
  • WeightedTextAggregator.aggregate (method) skills/swan_agent.py:264 def aggregate(self, task_type, goal, votes)
  • ExpertExecutor.execute (method) skills/swan_agent.py:351 def execute(self, expert_id, backend, model, goal, task_type, timeout, api_key) -- Run the expert and return a SwanResult.
  • OutcomeEvaluator.evaluate (method) skills/swan_agent.py:479 def evaluate(self, result, task_type) -- Return (reward, detection_prob).
  • SwanOrchestrator.__init__ (method) skills/swan_agent.py:572 def __init__(self, executor, evaluator, aggregator, api_key)
  • SwanOrchestrator.run (method) skills/swan_agent.py:592 def run(self, task_type, goal, engagement_phase, timeout) -- Execute the task with the best single expert selected by the MoE+RL router.
  • SwanOrchestrator.ensemble_run (method) skills/swan_agent.py:680 def ensemble_run(self, task_type, goal, n_experts, engagement_phase, timeout) -- Execute with top-N experts in parallel and synthesize results.
  • SwanOrchestrator.status (method) skills/swan_agent.py:763 def status(self) -- Return a diagnostic snapshot of the SWAN system.
  • mcp_swan_run (function) skills/swan_agent.py:945 def mcp_swan_run(task_type, goal, phase) -- Route and execute a task with the best MoE+RL-selected expert.
  • mcp_swan_ensemble (function) skills/swan_agent.py:968 def mcp_swan_ensemble(task_type, goal, n_experts, phase) -- Run top-N experts in parallel and return a synthesized result.
  • mcp_swan_status (function) skills/swan_agent.py:996 def mcp_swan_status() -- Return SWAN system status: expert weights, RL epsilon, performance.
  • mcp_swan_route (function) skills/swan_agent.py:1003 def mcp_swan_route(task_type, goal) -- Show which expert would be selected for a task without executing.
  • get_swan (function) skills/swan_agent.py:1039 def get_swan(api_key) -- Return (or create) the module-level singleton SwanOrchestrator.

skills/toposwarm_autonomous.py

Depends on: core/logging.py, modules/logging_config.py, modules/reactive_engine.py, modules/toposwarm_bridge.py

skills/unified_orchestrator.py

Depends on: modules/engage_summary.py, skills/autonomous_daemon.py, skills/hive_mind.py, skills/swan_agent.py Imported by: lazyown.py, tests/test_improvements_spec.py

skills/update_knowledge.py

Depends on: core/logging.py, modules/logging_config.py, skills/lazyown_parquet_db.py

slack_c2_bot.py

Depends on: core/parsers.py, lazyown.py, modules/llm_adapter.py, utils.py

static/js/3d-force-graph-1.73.4.min.js

Depends on: cli/assign.py, lazyown-docker/init.sh, modules/exp.c

static/js/bootstrap-4.5.2.min.js

Depends on: cli/show.py

static/js/bootstrap-5.3.0.bundle.min.js

Depends on: cli/assign.py, cli/show.py

static/js/chart.min.js

Depends on: cli/assign.py, cli/show.py, lazyown-docker/init.sh, modules/notify.py

static/js/force-graph-1.43.5.min.js

Depends on: cli/assign.py, cli/style.py, modules/exp.c

Next: API_p22.md

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