PMOVES Model Registry

Query, discover, and enrich the AI model catalog. Manages LLM, embedding, TTS, vision model metadata, HuggingFace enrichment, and GPU deployments.

Sby Skills Guide Bot
Data & AIIntermediate
007/23/2026
#model-registry#llm#embedding#huggingface#tensorzero

Recommended for


name: PMOVES Model Registry description: | Query, discover, and enrich the PMOVES.AI model catalog. Manages all AI model metadata (LLM, embedding, TTS, vision), HuggingFace enrichment, TensorZero TOML config export, and GPU deployment tracking across the fleet. keywords: models, registry, catalog, embedding, llm, tensorzero, huggingface, gpu, deployment, discovery version: 1.0.0 category: Infrastructure/AI tier: 1 agent_class: Standard agent_id: pmoves_model_registry

PMOVES Model Registry

Agent Class: Standard (Pmoves-) Category: Infrastructure/AI Version: 1.0.0 Tier: 1 (Core Infrastructure) Status: Active — Supabase-backed model catalog + HuggingFace enrichment Port: 8110


Capabilities

| Command | What It Does | |---------|-------------| | list-models | List all active models with optional type/provider filter | | get-model | Get detailed metadata for a single model by ID | | enrich-hf | Fetch dimensions, tags, CUDA support from HuggingFace API | | enrich-hf-bulk | Batch-enrich all models that have hf_id in metadata | | export-tensorzero | Generate TensorZero TOML config from catalog | | list-deployments | Show active GPU model deployments across fleet | | register-deployment | Register/update a model deployment (GPU Orchestrator) | | service-models | List models mapped to a specific service |


Trigger Phrases (Pinokio 7 Interpreter)

| Phrase | Action | Endpoint | |--------|--------|----------| | "list available models" | Show full model catalog | GET /api/models | | "show embedding models" | Filter catalog by type | GET /api/models?model_type=embedding | | "show LLM models" | Filter catalog by type | GET /api/models?model_type=llm | | "get model details for [id]" | Single model lookup | GET /api/models/{id} | | "enrich model from huggingface" | Fetch HF metadata + dimensions | POST /api/models/{id}/enrich-hf | | "enrich all embedding models" | Batch HF enrichment | POST /api/models/enrich-hf-bulk | | "export tensorzero config" | Download TensorZero TOML | GET /api/tensorzero/config | | "show GPU deployments" | List active model deployments | GET /api/deployments | | "which models are on 5090" | Filter deployments by node | GET /api/deployments?node_id=5090 | | "what models does hi-rag use" | Service-specific model lookup | GET /api/services/hi-rag/models |


API Reference

Model Catalog

# List all models
curl http://localhost:8110/api/models

# Filter by type (embedding, llm, tts, vision, audio)
curl http://localhost:8110/api/models?model_type=embedding

# Filter by provider (ollama, openai, anthropic, venice)
curl http://localhost:8110/api/models?provider=ollama

# Get single model
curl http://localhost:8110/api/models/{model_id}

# Models for a service
curl http://localhost:8110/api/services/hi-rag/models

HuggingFace Enrichment

# Enrich a single model (requires metadata.hf_id set)
curl -X POST http://localhost:8110/api/models/{model_id}/enrich-hf

# Batch-enrich all embedding models
curl -X POST http://localhost:8110/api/models/enrich-hf-bulk?model_type=embedding

TensorZero Config Export

# Generate TOML config from catalog
curl http://localhost:8110/api/tensorzero/config -o tensorzero.toml

GPU Deployments

# List active deployments
curl http://localhost:8110/api/deployments

# Filter by node
curl http://localhost:8110/api/deployments?node_id=5090

# Filter by status
curl http://localhost:8110/api/deployments?status=loaded

Health Check

curl http://localhost:8110/healthz
# → {"status": "healthy", "timestamp": "...", "services": {"supabase": "...", "nats": "..."}}

Integration Points

  • Supabasepmoves_core.models, pmoves_core.model_service_mapping, pmoves_core.v_active_deployments
  • NATS — Publishes model.registry.updated.v1 on catalog mutations (model enriched, deployment registered)
  • GPU Orchestrator — Calls POST /api/deployments when models are loaded/unloaded on GPU nodes
  • TensorZero Gateway — Consumes exported TOML config for model provider routing
  • HuggingFace API — Fetches model cards, config.json for embedding dimensions, tags, CUDA support

Prerequisites

  • Supabase running with pmoves_core schema seeded
  • NATS message bus at port 4222 (optional — catalog changes still work without NATS)
  • HuggingFace API accessible (no auth required for public models)
Related skills