0.6.0 training session: Oracle Bot, RL combat, Mind's Eye, multilingual pipeline
Major changes from this session: Training: - 0.6.0 training running: 9B on steel141 3090 Ti, 27B on rented H100 NVL - 7,256 merged training examples (up from 3,183) - New training data: failure modes (85), midloop messaging (27), prompt injection defense (29), personality (32), gold from quarantine bank (232), new tool examples (30), claude's own experience (10) - All training data RCON-validated at 100% pass rate - Bake-off: gemma3:27b 66%, qwen3.5:27b 61%, translategemma:27b 56% Oracle Bot (Mind's Eye): - Invisible spectator bot (mineflayer) streams world state via WebSocket - HTML5 Canvas frontend at mind.mortdec.ai - Real-time tool trace visualization with expandable entries - Streaming model tokens during inference - Gateway integration: fire-and-forget POST /trace on every tool call Reinforcement Learning: - Gymnasium environment wrapping mineflayer bot (minecraft_env.py) - PPO training via Stable Baselines3 (10K param policy network) - Behavioral cloning pretraining (97.5% accuracy on expert policy) - Infinite training loop with auto-restart and checkpoint resume - Bot learns combat, survival, navigation from raw experience Bot Army: - 8-soldier marching formation with autonomous combat - Combat bots using mineflayer-pvp, pathfinder, armor-manager - Multilingual prayer bots via translategemma:27b (18 languages) - Frame-based AI architecture: LLM planner + reactive micro-scripts Infrastructure: - Fixed mattpc.sethpc.xyz billing gateway (API key + player list parser) - Billing gateway now tracks all LAN traffic (LAN auto-auth) - Gateway fallback for empty god-mode responses - Updated mortdec.ai landing page Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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# Oracle Bot — Mortdecai Mind's Eye
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Live HTML5 viewport that renders what the Mortdecai AI model "sees" during Minecraft server interactions.
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**Public URL:** `mind.mortdec.ai`
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## Quick Start (local dev)
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```bash
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cd oracle-bot
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npm install
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node server.js
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# Open http://localhost:3333
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```
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## Deploy to CT 644
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```bash
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# 1. Copy files to CT 644
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ssh pve112 "pct exec 644 -- mkdir -p /opt/oracle-bot"
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scp -r oracle-bot/* pve112:/tmp/oracle-bot/
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ssh pve112 "pct push 644 /tmp/oracle-bot/ /opt/oracle-bot/ --recursive"
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# 2. Install deps on CT 644
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ssh pve112 "pct exec 644 -- bash -c 'cd /opt/oracle-bot && npm install --production'"
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# 3. Install systemd service
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ssh pve112 "pct exec 644 -- cp /opt/oracle-bot/oracle-bot.service /etc/systemd/system/"
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ssh pve112 "pct exec 644 -- systemctl daemon-reload"
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ssh pve112 "pct exec 644 -- systemctl enable --now oracle-bot"
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# 4. Verify
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ssh pve112 "pct exec 644 -- curl -s http://localhost:3333/health"
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```
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## Caddy Config (CT 600)
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Add to `/etc/caddy/Caddyfile`:
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```
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mind.mortdec.ai {
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@internal path /trace /command
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respond @internal 404
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reverse_proxy 192.168.0.244:3333
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}
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```
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Then: `caddy reload --config /etc/caddy/Caddyfile`
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## Endpoints
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| Endpoint | Access | Description |
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|----------|--------|-------------|
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| `GET /` | Public | Frontend (index.html) |
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| `WS /ws` | Public | WebSocket stream |
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| `GET /health` | Public | Health check |
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| `POST /trace` | Internal | Gateway tool traces |
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| `POST /command` | Internal | Bot commands |
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## Test with simulated traces
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```bash
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curl -X POST http://localhost:3333/trace \
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-H "Content-Type: application/json" \
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-d '{"tool":"rcon.execute","input":{"command":"give slingshooter08 diamond 16"},"ok":true,"step":0,"mode":"god","player":"slingshooter08","session_id":"test-001"}'
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```
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