> ## Documentation Index
> Fetch the complete documentation index at: https://docs.10et.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Memory Search

> BM25+ hybrid search with Reciprocal Rank Fusion

TENET's memory search combines lexical (BM25+) and semantic (embedding cosine similarity) scoring, merged via Reciprocal Rank Fusion.

## Search Methods

| Method      | When Used                   | Requires API Key             |
| ----------- | --------------------------- | ---------------------------- |
| `bm25`      | Keyword-focused queries     | No                           |
| `embedding` | Semantic/conceptual queries | Yes                          |
| `hybrid`    | Best of both (default)      | Partial — falls back to BM25 |

## BM25+ Improvements

* **Stopword removal** — cleaner term matching
* **Phrase detection** — multi-word terms kept together
* **Adaptive b parameter** — adjusts to corpus length variance
* **Positive IDF floor** — common terms still contribute (BM25+ variant)
* **Query term weighting** — rare terms get more weight

## Boosts

| Boost    | Factor | Condition       |
| -------- | ------ | --------------- |
| Recency  | 1.3x   | Within 7 days   |
| Decision | 1.4x   | Type = decision |
| Feature  | 1.2x   | Type = feature  |

## API

```bash theme={null}
curl -X POST http://localhost:4360/api/memory/search \
  -H "Authorization: Bearer $TOKEN" \
  -d '{"query": "startup optimization", "limit": 5, "type": "decision"}'
```