| name | kilocode-model-populate |
| description | Pull and register Ollama models on the 5090 GPU node, sync with TensorZero config, and manage model availability for the PMOVES fleet. Use when adding new local models or updating model routing. |
| keywords | ["model","ollama","pull","register","tensorzero","sync"] |
| version | 1.0.0 |
| category | PMOVES/KiloCode-GLM |
KiloCode Model Populate
Model pulling, registration, and TensorZero sync using GLM-5.2 for model card analysis and routing decisions.
Purpose
Pull new models to the 5090's Ollama instance, register them in TensorZero, and sync the model routing configuration across the PMOVES fleet.
Capabilities
- 📦 Pull models via
ollama pull
- 🗒️ Analyze model cards via HuggingFace MCP
- 🔀 Register models in TensorZero config
- 📊 Sync model profiles via
models_sync.py
- 🏷️ Tag models with PMOVES-specific metadata
Integration Points
- Ollama:
http://localhost:11434
- TensorZero Gateway:
http://localhost:3030
- Model Sync Tool:
pmoves/tools/models/models_sync.py
- Provider Catalog:
pmoves/config/provider_catalog.yaml
- Model Suits:
pmoves/configs/model-suits/
- HuggingFace MCP: For model card research
Workflow
Step 1: Research Model
# Use HuggingFace MCP to study the model card
# Check VRAM requirements vs available GPU memory
# Verify license compatibility
Step 2: Pull Model
ollama pull <model-name>
Step 3: Verify Pull
ollama list
ollama show <model-name>
Step 4: Sync to TensorZero
python pmoves/tools/models/models_sync.py sync
python pmoves/tools/models/models_sync.py sync-dynamic
Step 5: Publish Mesh Event
nats pub mesh.gpu.model.loaded.v1 '{"model":"<name>","node":"5090","vram_gb":<n>}'
Trigger Phrases
- "pull model"
- "register model"
- "model populate"
- "sync models"
- "add ollama model"