Mortdecai

Seth/Mortdecai

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Author	SHA1	Message	Date
Mortdecai	da8f557219	GPU scheduler, 14-tool architecture, plugin deployment, event dispatcher GPU Scheduler (gpu.sethpc.xyz): - Live dashboard with 4 GPUs, training monitor, loss sparklines - Preset-based job scheduler with 3 triggers (time, finish_training, cost) - Model selection per GPU, pipeline configuration - Tool self-play and training pipeline types - Behind Google OAuth, live-refresh without page reload Tool Architecture (14 tools): - 3 new tools: world.nearby_entities, memory.read, memory.write - 7 script.* tools: write, validate, execute, read, list, delete, schedule - ScriptManager: full mcfunction datapack CRUD with RCON validation - Training data: 1,430 tool examples (up from 1,159) Plugin Deployment (paper-ai-25567): - WorldGuard 7.0.12, CoreProtect CE 23.1, EssentialsX 2.21.2, Vault 1.7.3 - Fresh greenfield world reset - 104 RCON-validated plugin training examples Event Dispatcher: - Watches server log for deaths, joins, advancements, PvP kills - Configurable trigger probability and cooldowns per event type - Deployed to dev server, fires god_system prompts on events - 21 event-response training examples Training Infrastructure: - train_lora.py: --save-steps 50, --resume from checkpoint - run_training.sh: stops Ollama, activates conda, restarts after - Passwordless sudo for ollama services on steel141 - Dev server added to MCSManager with autoStart Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-03-21 03:14:45 -04:00
Seth	027b835286	Session final: bakeoff fix, branding fonts, 3-GPU parallel self-play Current running state: - Prod: mortdecai-v4 on RTX 4000, single-call, error correction, fall protection - Dev: Gemini 3.1 Flash Lite (preview) + 5 bots generating training data - Bake-off: v4 running on steel141 (3090 Ti) - Self-play: ready for overnight — 3 GPUs parallel (3090 Ti + 2080 Ti + RTX 4000) Changes: - Bakeoff parser: strips think blocks, handles dict/list types - Branding fonts: Rajdhani-Bold (official), Exo2, Orbitron, Oxanium, SpaceGrotesk - Gemini 3.1 pricing added to cost tracker Active data collection: - Gemini 3.1 Flash Lite bots on dev ($20 budget, ~$4/hr with 5 bots) - Self-play overnight: 3 tiers × 3 GPUs = ~9x throughput - Training audit logging on all servers Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-03-20 00:56:45 -04:00

Author

SHA1

Message

Date

Mortdecai

da8f557219

GPU scheduler, 14-tool architecture, plugin deployment, event dispatcher

GPU Scheduler (gpu.sethpc.xyz):
- Live dashboard with 4 GPUs, training monitor, loss sparklines
- Preset-based job scheduler with 3 triggers (time, finish_training, cost)
- Model selection per GPU, pipeline configuration
- Tool self-play and training pipeline types
- Behind Google OAuth, live-refresh without page reload

Tool Architecture (14 tools):
- 3 new tools: world.nearby_entities, memory.read, memory.write
- 7 script.* tools: write, validate, execute, read, list, delete, schedule
- ScriptManager: full mcfunction datapack CRUD with RCON validation
- Training data: 1,430 tool examples (up from 1,159)

Plugin Deployment (paper-ai-25567):
- WorldGuard 7.0.12, CoreProtect CE 23.1, EssentialsX 2.21.2, Vault 1.7.3
- Fresh greenfield world reset
- 104 RCON-validated plugin training examples

Event Dispatcher:
- Watches server log for deaths, joins, advancements, PvP kills
- Configurable trigger probability and cooldowns per event type
- Deployed to dev server, fires god_system prompts on events
- 21 event-response training examples

Training Infrastructure:
- train_lora.py: --save-steps 50, --resume from checkpoint
- run_training.sh: stops Ollama, activates conda, restarts after
- Passwordless sudo for ollama services on steel141
- Dev server added to MCSManager with autoStart

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-21 03:14:45 -04:00

Seth

027b835286

Session final: bakeoff fix, branding fonts, 3-GPU parallel self-play

Current running state:
- Prod: mortdecai-v4 on RTX 4000, single-call, error correction, fall protection
- Dev: Gemini 3.1 Flash Lite (preview) + 5 bots generating training data
- Bake-off: v4 running on steel141 (3090 Ti)
- Self-play: ready for overnight — 3 GPUs parallel (3090 Ti + 2080 Ti + RTX 4000)

Changes:
- Bakeoff parser: strips think blocks, handles dict/list types
- Branding fonts: Rajdhani-Bold (official), Exo2, Orbitron, Oxanium, SpaceGrotesk
- Gemini 3.1 pricing added to cost tracker

Active data collection:
- Gemini 3.1 Flash Lite bots on dev ($20 budget, ~$4/hr with 5 bots)
- Self-play overnight: 3 tiers × 3 GPUs = ~9x throughput
- Training audit logging on all servers

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-20 00:56:45 -04:00

2 Commits