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docs: clarify memory plugin adapter ids

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Peter Steinberger
2026-03-27 00:43:44 +00:00
parent dbf78de7c6
commit c9556c257e
3 changed files with 34 additions and 10 deletions
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21
docs/reference/memory-config.md
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@@ -20,7 +20,12 @@ automatic flush), see [Memory](/concepts/memory).
- Watches memory files for changes (debounced).
- Configure memory search under `agents.defaults.memorySearch` (not top-level
`memorySearch`).
- Uses remote embeddings by default. If `memorySearch.provider` is not set, OpenClaw auto-selects:
- `memorySearch.provider` and `memorySearch.fallback` accept **adapter ids**
registered by the active memory plugin.
- The default `memory-core` plugin registers these built-in adapter ids:
`local`, `openai`, `gemini`, `voyage`, `mistral`, and `ollama`.
- With the default `memory-core` plugin, if `memorySearch.provider` is not set,
OpenClaw auto-selects:
1. `local` if a `memorySearch.local.modelPath` is configured and the file exists.
2. `openai` if an OpenAI key can be resolved.
3. `gemini` if a Gemini key can be resolved.
@@ -29,8 +34,9 @@ automatic flush), see [Memory](/concepts/memory).
6. Otherwise memory search stays disabled until configured.
- Local mode uses node-llama-cpp and may require `pnpm approve-builds`.
- Uses sqlite-vec (when available) to accelerate vector search inside SQLite.
- `memorySearch.provider = "ollama"` is also supported for local/self-hosted
Ollama embeddings (`/api/embeddings`), but it is not auto-selected.
- With the default `memory-core` plugin, `memorySearch.provider = "ollama"` is
also supported for local/self-hosted Ollama embeddings (`/api/embeddings`),
but it is not auto-selected.
Remote embeddings **require** an API key for the embedding provider. OpenClaw
resolves keys from auth profiles, `models.providers.*.apiKey`, or environment
@@ -317,15 +323,16 @@ If you don't want to set an API key, use `memorySearch.provider = "local"` or se
### Fallbacks
- `memorySearch.fallback` can be `openai`, `gemini`, `voyage`, `mistral`, `ollama`, `local`, or `none`.
- `memorySearch.fallback` can be any registered memory embedding adapter id, or `none`.
- With the default `memory-core` plugin, valid built-in fallback ids are `openai`, `gemini`, `voyage`, `mistral`, `ollama`, and `local`.
- The fallback provider is only used when the primary embedding provider fails.
### Batch indexing (OpenAI + Gemini + Voyage)
### Batch indexing
- Disabled by default. Set `agents.defaults.memorySearch.remote.batch.enabled = true` to enable for large-corpus indexing (OpenAI, Gemini, and Voyage).
- Disabled by default. Set `agents.defaults.memorySearch.remote.batch.enabled = true` to enable batch indexing for providers whose adapter exposes batch support.
- Default behavior waits for batch completion; tune `remote.batch.wait`, `remote.batch.pollIntervalMs`, and `remote.batch.timeoutMinutes` if needed.
- Set `remote.batch.concurrency` to control how many batch jobs we submit in parallel (default: 2).
- Batch mode applies when `memorySearch.provider = "openai"` or `"gemini"` and uses the corresponding API key.
- With the default `memory-core` plugin, batch indexing is available for `openai`, `gemini`, and `voyage`.
- Gemini batch jobs use the async embeddings batch endpoint and require Gemini Batch API availability.
Why OpenAI batch is fast and cheap: