openclaw/docs/plugins/memory-lancedb.md

---
summary: "Configure the bundled LanceDB memory plugin, including local Ollama-compatible embeddings"
read_when:
  - You are configuring the bundled memory-lancedb plugin
  - You want LanceDB-backed long-term memory with auto-recall or auto-capture
  - You are using local OpenAI-compatible embeddings such as Ollama
title: "Memory LanceDB"
sidebarTitle: "Memory LanceDB"
---

`memory-lancedb` is a bundled memory plugin that stores long-term memory in
LanceDB and uses embeddings for recall. It can automatically recall relevant
memories before a model turn and capture important facts after a response.

Use it when you want a local vector database for memory, need an
OpenAI-compatible embedding endpoint, or want to keep a memory database outside
the default built-in memory store.

<Note>
`memory-lancedb` is an active memory plugin. Enable it by selecting the memory
slot with `plugins.slots.memory = "memory-lancedb"`. Companion plugins such as
`memory-wiki` can run beside it, but only one plugin owns the active memory slot.
</Note>

## Quick start

```json5
{
  plugins: {
    slots: {
      memory: "memory-lancedb",
    },
    entries: {
      "memory-lancedb": {
        enabled: true,
        config: {
          embedding: {
            apiKey: "${OPENAI_API_KEY}",
            model: "text-embedding-3-small",
          },
          autoRecall: true,
          autoCapture: false,
        },
      },
    },
  },
}
```

Restart the Gateway after changing plugin config:

```bash
openclaw gateway restart
```

Then verify the plugin is loaded:

```bash
openclaw plugins list
```

## Ollama embeddings

`memory-lancedb` calls embeddings through an OpenAI-compatible embeddings API.
For Ollama embeddings, use the Ollama `/v1` compatibility endpoint here. This
is only for embeddings; the Ollama chat/model provider uses the native Ollama
API URL documented in [Ollama](/providers/ollama).

```json5
{
  plugins: {
    slots: {
      memory: "memory-lancedb",
    },
    entries: {
      "memory-lancedb": {
        enabled: true,
        config: {
          embedding: {
            apiKey: "ollama",
            baseUrl: "http://127.0.0.1:11434/v1",
            model: "mxbai-embed-large",
            dimensions: 1024,
          },
          recallMaxChars: 400,
          autoRecall: true,
          autoCapture: false,
        },
      },
    },
  },
}
```

Set `dimensions` for non-standard embedding models. OpenClaw knows the
dimensions for `text-embedding-3-small` and `text-embedding-3-large`; custom
models need the value in config so LanceDB can create the vector column.

For small local embedding models, lower `recallMaxChars` if you see context
length errors from the local server.

## Recall and capture limits

`memory-lancedb` has two separate text limits:

| Setting           | Default | Range     | Applies to                                    |
| ----------------- | ------- | --------- | --------------------------------------------- |
| `recallMaxChars`  | `1000`  | 100-10000 | text sent to the embedding API for recall     |
| `captureMaxChars` | `500`   | 100-10000 | assistant message length eligible for capture |

`recallMaxChars` controls auto-recall, the `memory_recall` tool, the
`memory_forget` query path, and `openclaw ltm search`. Auto-recall prefers the
latest user message from the turn and falls back to the full prompt only when no
user message is available. This keeps channel metadata and large prompt blocks
out of the embedding request.

`captureMaxChars` controls whether a response is short enough to be considered
for automatic capture. It does not cap recall query embeddings.

## Commands

When `memory-lancedb` is the active memory plugin, it registers the `ltm` CLI
namespace:

```bash
openclaw ltm list
openclaw ltm search "project preferences"
openclaw ltm stats
```

Agents also get LanceDB memory tools from the active memory plugin:

- `memory_recall` for LanceDB-backed recall
- `memory_store` for saving important facts, preferences, decisions, and entities
- `memory_forget` for removing matching memories

## Storage

By default, LanceDB data lives under `~/.openclaw/memory/lancedb`. Override the
path with `dbPath`:

```json5
{
  plugins: {
    entries: {
      "memory-lancedb": {
        enabled: true,
        config: {
          dbPath: "~/.openclaw/memory/lancedb",
          embedding: {
            apiKey: "${OPENAI_API_KEY}",
            model: "text-embedding-3-small",
          },
        },
      },
    },
  },
}
```

`storageOptions` accepts string key/value pairs for LanceDB storage backends and
supports `${ENV_VAR}` expansion:

```json5
{
  plugins: {
    entries: {
      "memory-lancedb": {
        enabled: true,
        config: {
          dbPath: "s3://memory-bucket/openclaw",
          storageOptions: {
            access_key: "${AWS_ACCESS_KEY_ID}",
            secret_key: "${AWS_SECRET_ACCESS_KEY}",
            endpoint: "${AWS_ENDPOINT_URL}",
          },
          embedding: {
            apiKey: "${OPENAI_API_KEY}",
            model: "text-embedding-3-small",
          },
        },
      },
    },
  },
}
```

## Runtime dependencies

`memory-lancedb` depends on the native `@lancedb/lancedb` package. Packaged
OpenClaw installs first try the bundled runtime dependency and can repair the
plugin runtime dependency under OpenClaw state when the bundled import is not
available.

If an older install logs a missing `dist/package.json` or missing
`@lancedb/lancedb` error during plugin load, upgrade OpenClaw and restart the
Gateway.

If the plugin logs that LanceDB is unavailable on `darwin-x64`, use the default
memory backend on that machine, move the Gateway to a supported platform, or
disable `memory-lancedb`.

## Troubleshooting

### Input length exceeds the context length

This usually means the embedding model rejected the recall query:

```text
memory-lancedb: recall failed: Error: 400 the input length exceeds the context length
```

Set a lower `recallMaxChars`, then restart the Gateway:

```json5
{
  plugins: {
    entries: {
      "memory-lancedb": {
        config: {
          recallMaxChars: 400,
        },
      },
    },
  },
}
```

For Ollama, also verify the embedding server is reachable from the Gateway host:

```bash
curl http://127.0.0.1:11434/v1/embeddings \
  -H "Content-Type: application/json" \
  -d '{"model":"mxbai-embed-large","input":"hello"}'
```

### Unsupported embedding model

Without `dimensions`, only the built-in OpenAI embedding dimensions are known.
For local or custom embedding models, set `embedding.dimensions` to the vector
size reported by that model.

### Plugin loads but no memories appear

Check that `plugins.slots.memory` points at `memory-lancedb`, then run:

```bash
openclaw ltm stats
openclaw ltm search "recent preference"
```

If `autoCapture` is disabled, the plugin will recall existing memories but will
not automatically store new ones. Use the `memory_store` tool or enable
`autoCapture` if you want automatic capture.

## Related

- [Memory overview](/concepts/memory)
- [Active memory](/concepts/active-memory)
- [Memory search](/concepts/memory-search)
- [Memory Wiki](/plugins/memory-wiki)
- [Ollama](/providers/ollama)