11 plugins from github.com/librefang/librefang-registry plugins/. index.json / index.json.sig are signed with Arka's Ed25519 key (not upstream stats.librefang.ai). Private key is not in this repo.
1.2 KiB
1.2 KiB
keyword-memory
Extracts keywords and named entities from user messages and returns them as contextual memories. Gives agents awareness of conversation topics without requiring external NLP libraries.
Extraction Techniques
- Plain keywords: Splits words, filters English stopwords (~50 words), removes short tokens
- Capitalized phrases: Detects multi-word proper nouns and mid-sentence capitalized words
- Emails and URLs: Regex pattern matching
- Numbers with units: e.g. 500ms, 10GB, 3.5GHz
- Dates: YYYY-MM-DD, MM/DD/YYYY, DD.MM.YYYY formats
- Technical terms: camelCase, snake_case, dotted identifiers (e.g.
os.path)
Results are deduplicated and capped at 10 keywords.
Hooks
| Hook | Script | Description |
|---|---|---|
| ingest | hooks/ingest.py |
Extracts keywords from the user message and returns them as a memory fragment |
Example Output
{"type": "ingest_result", "memories": [{"content": "[keyword-memory] Key topics: GPT-4, machine_learning, data pipeline, https://example.com"}]}
If no meaningful keywords are found, returns an empty memories list.
Usage
Installed automatically when enabled in agent configuration. No external dependencies required (stdlib only).