 Jon Saad-FalconandClaude Opus 4.6
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8d538cd1b0
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Add orchestrator training, channels, LiteLLM engine, and simplify learning taxonomy
Major changes across parallel sessions:
- Add orchestrator SFT & GRPO training subpackage (learning/orchestrator/)
with episode types, multi-objective reward, prompt registry, policy model,
RL environment, and registered learning policies
- Add structured THOUGHT/TOOL/INPUT/FINAL_ANSWER mode to OrchestratorAgent
- Add 15 channel backends (Discord, Slack, Telegram, Email, Webhook, IRC,
Matrix, Teams, WhatsApp, Signal, Mattermost, BlueBubbles, Feishu,
Google Chat, Webchat) with channel tools and config
- Add LiteLLM engine backend for unified LLM provider access
- Add RLM agent and REPL tool
- Remove ToolLearningPolicy — learning taxonomy now only targets
Intelligence (LM weights/routing) and Agents (logic/ICL/tool strategies)
- Rename SFTPolicy to SFTRouterPolicy (backward-compat alias kept)
- Remove OpenClaw agent infrastructure (openclaw*.py, openclaw_bridge.py)
- Fix async streaming tests (asyncio.run vs deprecated get_event_loop)
- Fix server channel route tests (pytest.importorskip for optional fastapi)
- Track uv.lock for reproducibility
- Update CLAUDE.md and docs to reflect all changes
1676 tests pass, 37 skipped.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-23 18:32:32 +00:00 |
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