Back to skills
extension
Category: Development & EngineeringNo API key required

setup-environment

Set up the embedding model for semantic search. model2vec-rs downloads models automatically; use when build fails or model download issues occur.

personAuthor: jakexiaohubgithub

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.