openclaw/docs/reference/memory-config.md

title, summary, read_when

title	summary	read_when
Memory configuration reference	All configuration knobs for memory search, embedding providers, QMD, hybrid search, and multimodal indexing	You want to configure memory search providers or embedding models You want to set up the QMD backend You want to tune hybrid search, MMR, or temporal decay You want to enable multimodal memory indexing

Memory configuration reference

This page lists every configuration knob for OpenClaw memory search. For conceptual overviews, see:

• Memory Overview -- how memory works
• Builtin Engine -- default SQLite backend
• QMD Engine -- local-first sidecar
• Memory Search -- search pipeline and tuning

All memory search settings live under agents.defaults.memorySearch in openclaw.json unless noted otherwise.

---

Provider selection

Key	Type	Default	Description
provider	string	auto-detected	Embedding adapter ID: openai, gemini, voyage, mistral, bedrock, ollama, local
model	string	provider default	Embedding model name
fallback	string	"none"	Fallback adapter ID when the primary fails
enabled	boolean	true	Enable or disable memory search

Auto-detection order

When provider is not set, OpenClaw selects the first available:

1. local -- if 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.
4. voyage -- if a Voyage key can be resolved.
5. mistral -- if a Mistral key can be resolved.
6. bedrock -- if the AWS SDK credential chain resolves (instance role, access keys, profile, SSO, web identity, or shared config).

ollama is supported but not auto-detected (set it explicitly).

API key resolution

Remote embeddings require an API key. Bedrock uses the AWS SDK default credential chain instead (instance roles, SSO, access keys).

Provider	Env var	Config key
OpenAI	OPENAI_API_KEY	models.providers.openai.apiKey
Gemini	GEMINI_API_KEY	models.providers.google.apiKey
Voyage	VOYAGE_API_KEY	models.providers.voyage.apiKey
Mistral	MISTRAL_API_KEY	models.providers.mistral.apiKey
Bedrock	AWS credential chain	No API key needed
Ollama	OLLAMA_API_KEY (placeholder)	--

Codex OAuth covers chat/completions only and does not satisfy embedding requests.

---

Remote endpoint config

For custom OpenAI-compatible endpoints or overriding provider defaults:

Key	Type	Description
remote.baseUrl	string	Custom API base URL
remote.apiKey	string	Override API key
remote.headers	object	Extra HTTP headers (merged with provider defaults)

{
  agents: {
    defaults: {
      memorySearch: {
        provider: "openai",
        model: "text-embedding-3-small",
        remote: {
          baseUrl: "https://api.example.com/v1/",
          apiKey: "YOUR_KEY",
        },
      },
    },
  },
}

---

Gemini-specific config

Key	Type	Default	Description
model	string	gemini-embedding-001	Also supports gemini-embedding-2-preview
outputDimensionality	number	3072	For Embedding 2: 768, 1536, or 3072

Changing model or `outputDimensionality` triggers an automatic full reindex.

---

Bedrock embedding config

Bedrock uses the AWS SDK default credential chain -- no API keys needed. If OpenClaw runs on EC2 with a Bedrock-enabled instance role, just set the provider and model:

{
  agents: {
    defaults: {
      memorySearch: {
        provider: "bedrock",
        model: "amazon.titan-embed-text-v2:0",
      },
    },
  },
}

Key	Type	Default	Description
model	string	amazon.titan-embed-text-v2:0	Any Bedrock embedding model ID
outputDimensionality	number	model default	For Titan V2: 256, 512, or 1024

Supported models

The following models are supported (with family detection and dimension defaults):

Model ID	Provider	Default Dims	Configurable Dims
amazon.titan-embed-text-v2:0	Amazon	1024	256, 512, 1024
amazon.titan-embed-text-v1	Amazon	1536	--
amazon.titan-embed-g1-text-02	Amazon	1536	--
amazon.titan-embed-image-v1	Amazon	1024	--
amazon.nova-2-multimodal-embeddings-v1:0	Amazon	1024	256, 384, 1024, 3072
cohere.embed-english-v3	Cohere	1024	--
cohere.embed-multilingual-v3	Cohere	1024	--
cohere.embed-v4:0	Cohere	1536	256-1536
twelvelabs.marengo-embed-3-0-v1:0	TwelveLabs	512	--
twelvelabs.marengo-embed-2-7-v1:0	TwelveLabs	1024	--

Throughput-suffixed variants (e.g., amazon.titan-embed-text-v1:2:8k) inherit the base model's configuration.

Authentication

Bedrock auth uses the standard AWS SDK credential resolution order:

1. Environment variables (AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY)
2. SSO token cache
3. Web identity token credentials
4. Shared credentials and config files
5. ECS or EC2 metadata credentials

Region is resolved from AWS_REGION, AWS_DEFAULT_REGION, the amazon-bedrock provider baseUrl, or defaults to us-east-1.

IAM permissions

The IAM role or user needs:

{
  "Effect": "Allow",
  "Action": "bedrock:InvokeModel",
  "Resource": "*"
}

For least-privilege, scope InvokeModel to the specific model:

arn:aws:bedrock:*::foundation-model/amazon.titan-embed-text-v2:0

---

Local embedding config

Key	Type	Default	Description
local.modelPath	string	auto-downloaded	Path to GGUF model file
local.modelCacheDir	string	node-llama-cpp default	Cache dir for downloaded models

Default model: embeddinggemma-300m-qat-Q8_0.gguf (~0.6 GB, auto-downloaded). Requires native build: pnpm approve-builds then pnpm rebuild node-llama-cpp.

---

Hybrid search config

All under memorySearch.query.hybrid:

Key	Type	Default	Description
enabled	boolean	true	Enable hybrid BM25 + vector search
vectorWeight	number	0.7	Weight for vector scores (0-1)
textWeight	number	0.3	Weight for BM25 scores (0-1)
candidateMultiplier	number	4	Candidate pool size multiplier

MMR (diversity)

Key	Type	Default	Description
mmr.enabled	boolean	false	Enable MMR re-ranking
mmr.lambda	number	0.7	0 = max diversity, 1 = max relevance

Temporal decay (recency)

Key	Type	Default	Description
temporalDecay.enabled	boolean	false	Enable recency boost
temporalDecay.halfLifeDays	number	30	Score halves every N days

Evergreen files (MEMORY.md, non-dated files in memory/) are never decayed.

Full example

{
  agents: {
    defaults: {
      memorySearch: {
        query: {
          hybrid: {
            vectorWeight: 0.7,
            textWeight: 0.3,
            mmr: { enabled: true, lambda: 0.7 },
            temporalDecay: { enabled: true, halfLifeDays: 30 },
          },
        },
      },
    },
  },
}

---

Additional memory paths

Key	Type	Description
extraPaths	string[]	Additional directories or files to index

{
  agents: {
    defaults: {
      memorySearch: {
        extraPaths: ["../team-docs", "/srv/shared-notes"],
      },
    },
  },
}

Paths can be absolute or workspace-relative. Directories are scanned recursively for .md files. Symlink handling depends on the active backend: the builtin engine ignores symlinks, while QMD follows the underlying QMD scanner behavior.

For agent-scoped cross-agent transcript search, use agents.list[].memorySearch.qmd.extraCollections instead of memory.qmd.paths. Those extra collections follow the same { path, name, pattern? } shape, but they are merged per agent and can preserve explicit shared names when the path points outside the current workspace. If the same resolved path appears in both memory.qmd.paths and memorySearch.qmd.extraCollections, QMD keeps the first entry and skips the duplicate.

---

Multimodal memory (Gemini)

Index images and audio alongside Markdown using Gemini Embedding 2:

Key	Type	Default	Description
multimodal.enabled	boolean	false	Enable multimodal indexing
multimodal.modalities	string[]	--	["image"], ["audio"], or ["all"]
multimodal.maxFileBytes	number	10000000	Max file size for indexing

Only applies to files in extraPaths. Default memory roots stay Markdown-only. Requires gemini-embedding-2-preview. fallback must be "none".

Supported formats: .jpg, .jpeg, .png, .webp, .gif, .heic, .heif (images); .mp3, .wav, .ogg, .opus, .m4a, .aac, .flac (audio).

---

Embedding cache

Key	Type	Default	Description
cache.enabled	boolean	false	Cache chunk embeddings in SQLite
cache.maxEntries	number	50000	Max cached embeddings

Prevents re-embedding unchanged text during reindex or transcript updates.

---

Batch indexing

Key	Type	Default	Description
remote.batch.enabled	boolean	false	Enable batch embedding API
remote.batch.concurrency	number	2	Parallel batch jobs
remote.batch.wait	boolean	true	Wait for batch completion
remote.batch.pollIntervalMs	number	--	Poll interval
remote.batch.timeoutMinutes	number	--	Batch timeout

Available for openai, gemini, and voyage. OpenAI batch is typically fastest and cheapest for large backfills.

---

Session memory search (experimental)

Index session transcripts and surface them via memory_search:

Key	Type	Default	Description
experimental.sessionMemory	boolean	false	Enable session indexing
sources	string[]	["memory"]	Add "sessions" to include transcripts
sync.sessions.deltaBytes	number	100000	Byte threshold for reindex
sync.sessions.deltaMessages	number	50	Message threshold for reindex

Session indexing is opt-in and runs asynchronously. Results can be slightly stale. Session logs live on disk, so treat filesystem access as the trust boundary.

---

SQLite vector acceleration (sqlite-vec)

Key	Type	Default	Description
store.vector.enabled	boolean	true	Use sqlite-vec for vector queries
store.vector.extensionPath	string	bundled	Override sqlite-vec path

When sqlite-vec is unavailable, OpenClaw falls back to in-process cosine similarity automatically.

---

Index storage

Key	Type	Default	Description
store.path	string	~/.openclaw/memory/{agentId}.sqlite	Index location (supports {agentId} token)
store.fts.tokenizer	string	unicode61	FTS5 tokenizer (unicode61 or trigram)

---

QMD backend config

Set memory.backend = "qmd" to enable. All QMD settings live under memory.qmd:

Key	Type	Default	Description
command	string	qmd	QMD executable path
searchMode	string	search	Search command: search, vsearch, query
includeDefaultMemory	boolean	true	Auto-index MEMORY.md + memory/**/*.md
paths[]	array	--	Extra paths: { name, path, pattern? }
sessions.enabled	boolean	false	Index session transcripts
sessions.retentionDays	number	--	Transcript retention
sessions.exportDir	string	--	Export directory

OpenClaw prefers the current QMD collection and MCP query shapes, but keeps older QMD releases working by falling back to legacy --mask collection flags and older MCP tool names when needed.

QMD model overrides stay on the QMD side, not OpenClaw config. If you need to override QMD's models globally, set environment variables such as QMD_EMBED_MODEL, QMD_RERANK_MODEL, and QMD_GENERATE_MODEL in the gateway runtime environment.

Update schedule

Key	Type	Default	Description
update.interval	string	5m	Refresh interval
update.debounceMs	number	15000	Debounce file changes
update.onBoot	boolean	true	Refresh on startup
update.waitForBootSync	boolean	false	Block startup until refresh completes
update.embedInterval	string	--	Separate embed cadence
update.commandTimeoutMs	number	--	Timeout for QMD commands
update.updateTimeoutMs	number	--	Timeout for QMD update operations
update.embedTimeoutMs	number	--	Timeout for QMD embed operations

Limits

Key	Type	Default	Description
limits.maxResults	number	6	Max search results
limits.maxSnippetChars	number	--	Clamp snippet length
limits.maxInjectedChars	number	--	Clamp total injected chars
limits.timeoutMs	number	4000	Search timeout

Scope

Controls which sessions can receive QMD search results. Same schema as session.sendPolicy:

{
  memory: {
    qmd: {
      scope: {
        default: "deny",
        rules: [{ action: "allow", match: { chatType: "direct" } }],
      },
    },
  },
}

Default is DM-only. match.keyPrefix matches the normalized session key; match.rawKeyPrefix matches the raw key including agent:<id>:.

Citations

memory.citations applies to all backends:

Value	Behavior
auto (default)	Include Source: <path#line> footer in snippets
on	Always include footer
off	Omit footer (path still passed to agent internally)

Full QMD example

{
  memory: {
    backend: "qmd",
    citations: "auto",
    qmd: {
      includeDefaultMemory: true,
      update: { interval: "5m", debounceMs: 15000 },
      limits: { maxResults: 6, timeoutMs: 4000 },
      scope: {
        default: "deny",
        rules: [{ action: "allow", match: { chatType: "direct" } }],
      },
      paths: [{ name: "docs", path: "~/notes", pattern: "**/*.md" }],
    },
  },
}

---

Dreaming (experimental)

Dreaming is configured under plugins.entries.memory-core.config.dreaming, not under agents.defaults.memorySearch.

Dreaming runs as one scheduled sweep and uses internal light/deep/REM phases as an implementation detail.

For conceptual behavior and slash commands, see Dreaming.

User settings

Key	Type	Default	Description
enabled	boolean	false	Enable or disable dreaming entirely
frequency	string	0 3 * * *	Optional cron cadence for the full dreaming sweep

Example

{
  plugins: {
    entries: {
      "memory-core": {
        config: {
          dreaming: {
            enabled: true,
            frequency: "0 3 * * *",
          },
        },
      },
    },
  },
}

Notes:

• Dreaming writes machine state to memory/.dreams/.
• Dreaming writes human-readable narrative output to DREAMS.md (or existing dreams.md).
• The light/deep/REM phase policy and thresholds are internal behavior, not user-facing config.