ReddRadar
Agent skill
setup-environment
Set up the embedding model for semantic search. model2vec-rs downloads models automatically; use when build fails or model download issues occur.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/setup-environment-trevors-glhf
SKILL.md
Environment Setup for Semantic Search
Instructions
glhf uses model2vec-rs with Potion-base-32M for embeddings. The model downloads automatically on first use.
Quick Setup
No manual setup required:
cargo build --release
./target/release/glhf index
The embedding model (~130MB) will download to the HuggingFace cache on first run.
Model Details
| Property | Value |
|---|---|
| Model | minishlab/potion-base-32M |
| Dimensions | 512 |
| Size | ~130MB |
| Cache Location | ~/.cache/huggingface/ |
Verify Setup
# Run embedding tests
cargo test embed -- --ignored
Common Issues
| Error | Solution |
|---|---|
Failed to load model |
Check internet connection, model will auto-download |
No space left |
Clear HuggingFace cache: rm -rf ~/.cache/huggingface/ |
Slow first run |
Normal - model downloads once, then cached |
Skip Embeddings
For text-only search (faster indexing, no model download):
glhf index --skip-embeddings
This enables FTS5 search but disables semantic/hybrid modes.
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