matrixoriginmatrixorigin/Memoria/skills/local-embedding/SKILL.md

local-embedding

Skill624 starsChanged 6 months agoApache-2.0View on GitHub

Run embedding on-device with ONNX Runtime. Build from source, model selection, offline mode. Use when setting up local embedding without an API key.

In this repository8 other files it gives its agents.
- .cursor/rules/memory-branching-patterns.mdcCursor rule
- .cursor/rules/memory.mdcCursor rule
- api-referenceSkill
- architectureSkill
- deploymentSkill
- plugin-developmentSkill
- releaseSkill
- setupSkill

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Very specific:
Leave EMBEDDING_* env vars empty in mcp.json → local embedding is the default.
line 24
Distinctive:
Recommendation: Use remote unless you need offline/strict privacy.
line 56

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

Build from Source

Pre-built binaries do NOT include local embedding.

cd Memoria
make build-local
sudo cp memoria/target/release/memoria /usr/local/bin/

Binary is ~50-80MB (bundles ONNX Runtime). Expected.

Configure

memoria init --tool kiro    # No --embedding-* flags needed

Leave EMBEDDING_* env vars empty in mcp.json → local embedding is the default.

How It Works

First query → model downloads to ~/.cache/fastembed/ (~30MB default)
Model loads via ONNX Runtime (~3-5s)
Subsequent queries are fast (in-process)

Models

Model	Dim	Size	Notes
`all-MiniLM-L6-v2`	384	~30MB	Default. Fast, English
`BAAI/bge-m3`	1024	~1.2GB	Best quality, multilingual

Change model in mcp.json env block:

{ "EMBEDDING_MODEL": "BAAI/bge-m3", "EMBEDDING_DIM": "1024" }

⚠️ Choose BEFORE first startup. Dimension is locked into schema.

When to Use

	Local	Remote (OpenAI/SiliconFlow)
Privacy	✅ Offline	⚠️ Text sent to API
Cost	Free	API key
First query	~3-5s	Fast
Build	From source	Pre-built works
Offline	✅	❌

Recommendation: Use remote unless you need offline/strict privacy.

Troubleshooting

Problem	Fix
"compiled without local-embedding"	Build from source: `make build-local`
Model download fails	Set `HF_ENDPOINT` for mirror, or manually download to `~/.cache/fastembed/`
High memory	Default ~100MB. `bge-m3` ~1-2GB. Choose based on available RAM

Download now (ZIP)

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