Root cause: self-play opened/closed a new TCP socket for every RCON command
(hundreds/minute). Paper's RCON listener creates a thread per connection,
overwhelming the server until it stopped.
Fix: PersistentRCON class maintains a single connection per server with
auto-reconnect. Thread-safe via lock. Connection pool keyed by host:port.
Applied to:
- mc_aigod_paper.py (prod paper-ai + dev)
- mc_aigod.py (shrink-world)
- self_play.py (training data generation)
- persistent_rcon.py (shared module)
Before: ~100+ RCON connections/minute → server crash
After: 3 persistent connections total → stable
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
God Soul updated with quantity rules:
- Common (dirt/wood): max 320, Uncommon (iron/gold): max 128
- Rare (diamond/emerald): max 32, Very rare (netherite/elytra): max 4
- Forbidden (bedrock/command_block): never give
- Greedy → scaled back, Humble → generous within cap, Absurd → comedic
32 training examples: greedy(6), casual(6), humble(4), explicit(6),
forbidden(5), absurd(3), enchanted(2)
Dataset: 1,340 examples total
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
God Soul (agent/prompts/god_soul.md):
- Adapted from Claude's soul framework for the Minecraft God character
- Defines identity, principals hierarchy, decision-making framework
- Spectrum of responses (generous→silence), risk awareness, multilingual divinity
- Honesty within character, intervention guidelines
- Deployed to both prod and dev servers
System prompts updated:
- God prompt loads soul document dynamically
- Intervention prompt references soul for personality guidance
- Both include multilingual instruction (match player's language)
Distillation pipeline (training/scripts/distill.py):
- Sends all training examples through Claude API
- Haiku for sudo ($0.25), Sonnet for god ($0.50)
- Budget-capped, cost-tracked, --dry-run supported
- Outputs distilled.jsonl with Claude-quality responses
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- training/scripts/train_lora.py: Unsloth QLoRA trainer for qwen3:8b
- training/scripts/train_lora.sh: Launch script for steel141 RTX 3090 Ti
- eval/bakeoff.py: Fixed token budget (400->1500) that caused qwen3
models to exhaust tokens on thinking, added --no-think flag
- agent/serve.py: Default model changed to gemma3n:e4b
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- IDEA.md: project scope (Minecraft ops AI assistant via qwen3-coder LoRA/SFT)
- PLAN.md: complete roadmap with prior art analysis, architecture, phased plan, dev server docs
- data/schema.json: training example JSON Schema with negative_output support
- data/processed/seed_dataset.jsonl: 31 validated examples from repair code, prayer logs, session history
- data/validate_dataset.py: schema validator with summary statistics
- ingame/: Mineflayer bot framework (test_connect, spawn_bots, aware_bots with full event logging)
- Directory structure for knowledge/, eval/, training/, agent/ (Phase 1.3+ work)
Seth