Spracherkennung für: .md vermutete Sprache: Unknown {[0] [0] [0]} [Methode: Schwerpunktbildung, einfache Gewichte, sechs Dimensionen]
---
summary: "The default SQLite-based memory backend with keyword, vector, and hybrid search"
title: "Builtin memory engine"
read_when:
- You want to understand the default memory backend
- You want to configure embedding providers or hybrid search
---
The builtin engine is the default memory backend. It stores your memory index in
a per-agent SQLite database and needs no extra dependencies to get started.
## What it provides
- **Keyword search** via FTS5 full-text indexing (BM25 scoring).
- **Vector search** via embeddings from any supported provider.
- **Hybrid search** that combines both for best results.
- **CJK support** via trigram tokenization for Chinese, Japanese, and Korean.
- **sqlite-vec acceleration** for in-database vector queries (optional).
## Getting started
If you have an API key for OpenAI, Gemini, Voyage, or Mistral, the builtin
engine auto-detects it and enables vector search. No config needed.
To set a provider explicitly:
```json5
{
agents: {
defaults: {
memorySearch: {
provider: "openai",
},
},
},
}
```
Without an embedding provider, only keyword search is available.
To force the built-in local embedding provider, install the optional
`node-llama-cpp` runtime package next to OpenClaw, then point `local.modelPath`
at a GGUF file:
```json5
{
agents: {
defaults: {
memorySearch: {
provider: "local",
fallback: "none",
local: {
modelPath: "~/.node-llama-cpp/models/embeddinggemma-300m-qat-Q8_0.gguf",
},
},
},
},
}
```
## Supported embedding providers
| Provider | ID | Auto-detected | Notes |
| -------- | --------- | ------------- | ----------------------------------- |
| OpenAI | `openai` | Yes | Default: `text-embedding-3-small` |
| Gemini | `gemini` | Yes | Supports multimodal (image + audio) |
| Voyage | `voyage` | Yes | |
| Mistral | `mistral` | Yes | |
| Ollama | `ollama` | No | Local, set explicitly |
| Local | `local` | Yes (first) | Optional `node-llama-cpp` runtime |
Auto-detection picks the first provider whose API key can be resolved, in the
order shown. Set `memorySearch.provider` to override.
## How indexing works
OpenClaw indexes `MEMORY.md` and `memory/*.md` into chunks (~400 tokens with
80-token overlap) and stores them in a per-agent SQLite database.
- **Index location:** `~/.openclaw/memory/<agentId>.sqlite`
- **File watching:** changes to memory files trigger a debounced reindex (1.5s).
- **Auto-reindex:** when the embedding provider, model, or chunking config
changes, the entire index is rebuilt automatically.
- **Reindex on demand:** `openclaw memory index --force`
<Info>
You can also index Markdown files outside the workspace with
`memorySearch.extraPaths`. See the
[configuration reference](/reference/memory-config#additional-memory-paths).
</Info>
## When to use
The builtin engine is the right choice for most users:
- Works out of the box with no extra dependencies.
- Handles keyword and vector search well.
- Supports all embedding providers.
- Hybrid search combines the best of both retrieval approaches.
Consider switching to [QMD](/concepts/memory-qmd) if you need reranking, query
expansion, or want to index directories outside the workspace.
Consider [Honcho](/concepts/memory-honcho) if you want cross-session memory with
automatic user modeling.
## Troubleshooting
**Memory search disabled?** Check `openclaw memory status`. If no provider is
detected, set one explicitly or add an API key.
**Local provider not detected?** Confirm the local path exists and run:
```bash
openclaw memory status --deep --agent main
openclaw memory index --force --agent main
```
Both standalone CLI commands and the Gateway use the same `local` provider id.
If the provider is set to `auto`, local embeddings are considered first only
when `memorySearch.local.modelPath` points to an existing local file.
**Stale results?** Run `openclaw memory index --force` to rebuild. The watcher
may miss changes in rare edge cases.
**sqlite-vec not loading?** OpenClaw falls back to in-process cosine similarity
automatically. Check logs for the specific load error.
## Configuration
For embedding provider setup, hybrid search tuning (weights, MMR, temporal
decay), batch indexing, multimodal memory, sqlite-vec, extra paths, and all
other config knobs, see the
[Memory configuration reference](/reference/memory-config).
## Related
- [Memory overview](/concepts/memory)
- [Memory search](/concepts/memory-search)
- [Active memory](/concepts/active-memory)
