
Audrey
io.github.Evilander由 GitHub 帳號 Evilander 發布v2.1.1更新於 Oct 30, 2026
Local-first biological memory for coding agents: recall, consolidation, and pre-action Guard checks.
概覽
為編碼代理設計的本地優先記憶:保存專案記憶、在工作階段開始時自動召回,並在執行 shell 或編輯操作前對照過往失敗進行檢查。
- 可以做什麼
- 記憶與召回專案記憶,可從「記住……」等明確說法擷取,並在工作階段開始時注入簡報
- 在 Bash、編輯與寫入操作執行前,對照已記錄的失敗、可信規則與矛盾進行檢查,並附上證據編號
- 記錄工具執行結果,將回報的失敗整理成去識別化的失敗記憶
- 整合、衰減記憶並處理矛盾,同時彙整記憶回饋的影響
- 對照儲存庫校驗記憶,標出已不存在的路徑或套件指令碼參照
- 啟用管理工具後可匯出、匯入、遺忘與提升記憶
- 適用情境
- 適合在同一專案上使用 Codex 或 Claude Code、希望代理不再重複已知錯誤並跨工作階段保留決策與偏好的團隊。也適合想透過 HTTP 重用同一記憶執行環境的自訂代理。
- 執行需求
- 以 npm 套件 audrey 在本機執行,需要 Node.js 22.16+(22.x)或 24+。Autopilot 會將生命週期鉤子寫入 Codex 或 Claude Code,需重新啟動並一次性核准鉤子。預設使用本機 SQLite 與本機嵌入模型,首次執行會下載模型檔案。選用的雲端嵌入或 LLM 供應商需自備憑證,REST 服務使用 AUDREY_API_KEY。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Audrey,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Memory that shows up before your coding agent makes the same mistake twice.
Audrey gives Codex and Claude Code one local, evidence-backed memory loop: remember what mattered, recall it automatically, check before acting, and learn from what happened next.
Memory before action
You fix the deploy command on Monday. On Thursday, a fresh session tries the broken version again.
Audrey brings relevant project memory into the next session, checks supported tool calls before they run, and links their reported outcomes to the check that preceded them. A Guard decision carries evidence IDs you can inspect. Grounding can flag memories that reference deleted files or package scripts.
Try the SQLite-backed demo before configuring a host:
The demo simulates a failed deploy, passes read-only inspection commands through the hook, and checks a proposed retry. It does not execute a deployment or change host configuration. After npm fetches the package, the demo needs no API key, model download, or network call.
Meet Audrey Autopilot
Install Audrey once, review the hooks once, and then use Codex or Claude Code normally.
Requires Node.js 22.16+ (22.x) or 24+. SQLite is built into Node, so fresh installs and npx launches work without approving dependency scripts. npm 11.17+ may warn about dependency scripts, and npm 12 may report that it blocked them; those scripts are not required for Audrey's CPU embedding runtime.
auto configures whichever supported CLIs are installed. You can choose one explicitly:
Restart the host after installation. Codex asks you to trust non-managed hooks once through /hooks; Claude Code may also ask you to approve project or plugin components. Audrey is automatic after that explicit install-and-trust step—never secretly installed.
Autopilot then closes the loop:
An outcome reflects the tool's reported status. A zero exit code can still produce stale or incorrect output. Custom integrations can declare required result checks in beforeAction and supply the actual output to afterAction. Guard then records a mismatch as failed and an unverifiable reported success as unknown. Audrey does not generate application-specific checks or infer the expected values.
Each hook event carries a host-declared timeout (30 seconds for the PreToolUse Guard check). Audrey caps individual hosted embedding/LLM requests below that deadline; this is not a deadline for the entire hook, and local model initialization has no equivalent internal timeout. Errors caught by Audrey fail open by default: the hook emits no decision. Set AUDREY_HOOK_FAIL_CLOSED=1 to deny a PreToolUse action on a caught error. If the host terminates the process first, the host determines what happens. Other lifecycle hooks have no deny path and always degrade open on caught errors.
A small story about a failed deploy
The first attempt fails:
Audrey keeps a redacted trace and an action fingerprint. If another session under the same agent identity proposes that action, Guard can deny the retry with evidence. A later recorded success for that fingerprint clears the exact-failure block. If the failed action declared result checks, recovery must pass the same checks. The default exact-failure window is seven days; other memory warnings are evaluated separately.
Fixing a file or deployment target does not itself clear the block. For a deliberate retry, the Guard API accepts acknowledgePriorFailure: true (MCP/REST: acknowledge_prior_failure; CLI: --acknowledge-prior-failure). Autopilot also recognizes retry language in the current user prompt. Acknowledgement lowers the exact-failure block to a warning and preserves its evidence; it does not bypass separate policy warnings.
Guard does not yet evaluate whether a natural-language prerequisite has been satisfied. A trusted must-follow memory can keep blocking even after its suggested repair succeeds. Review the cited rule when that happens; changing a command's spelling is not proof that its underlying problem is fixed.
Looking is not doing
Inspection commands such as grep, git status, and cat normally need no memory check. A non-zero exit from grep can simply mean there was no match.
A command whose every part is positively recognised as read-only skips Guard. The classifier rejects command substitution, redirects other than /dev/null, sudo, xargs, and environment assignments that could change command resolution. Inspection outcomes can be recorded, but are excluded from failure learning. Unrecognised commands remain guarded.
This excerpt illustrates the output of audrey demo --scenario repeated-failure.
When Guard does speak, it names the memory it is speaking from, and a remembered failure is matched to the proposed command by what it runs (npm run deploy against npm run deploy), not by how similar two strings look to an embedding.
Commands with execution-capable options or lifecycle scripts are guarded, including git ls-remote --upload-pack=..., npm pack --dry-run, and ss -K. The classifier is a convenience for ordinary inspection commands, not an operating-system sandbox. Repository configuration, shell expansion, and programs invoked by a reader can change what a command does. Use host permissions or a sandbox when enforcement is required.
What Audrey remembers
Audrey treats memory as more than a pile of text chunks.
- Episodes are things that happened: a user decision, a tool result, a project fact, a preference.
- Semantic memories are principles supported by accumulated evidence.
- Procedural memories are ways of acting: how to retry, verify, avoid, or recover.
- Contradictions stay visible instead of being silently overwritten.
- Confidence changes with source quality, evidence, age, retrieval, interference, context, and feedback.
- Low-value memories decay; repeated evidence can consolidate into longer-lived knowledge.
Every context packet includes memory IDs, confidence, provenance where available, and a reason for inclusion. Uncertain or disputed memories are labeled as such. Retrieved content is wrapped with a simple rule: memory is evidence, not authority; current system and user instructions always win.
Checking memories against the repository
Age is not the only way a memory goes wrong. A note saying "ship with npm run deploy:prod" is perfectly recent, well sourced, and completely wrong the day that script is deleted. Worse, every recall reinforces it, because retrieval counts as evidence that a memory is useful. A confidently stated, well-supported, false instruction is more damaging than no memory at all.
Audrey checks a narrow, useful part of this problem: whether referenced repository paths and package script names still exist. When a memory is written with project context, it records only anchors that resolve at that moment. A missing anchor can then distinguish a later repository change from a reference that never resolved.
Existence does not establish correctness. A script can keep its name while changing behavior, and an intact file can contain obsolete instructions. Grounding does not execute scripts, prove a fix, or verify arbitrary claims in prose.
Broken memories are not deleted. They keep their content, say plainly what they still refer to, and take a confidence penalty so they stop leading by default while remaining readable and repairable. They also stop being eligible for the packet's must-follow section — that is the section that can force a Guard block, and a rule naming a file that no longer exists is a rule nobody can follow.
Repair is symmetric. Restore the file or the script and the next check clears the flag. A checkout that has moved reports unknown rather than broken, because a memory should not be discredited for describing a project this machine cannot currently see.
Memories with no checkable claims are left unlabeled. Silence is not a clean bill of health, and presenting it as one would be the same mistake pointed the other way.
Daily use
Most of this runs on its own once Autopilot is installed. You do not invoke recall, and you do not invoke Guard. The table is here for the parts you would reach for deliberately, and so the automatic parts are legible rather than magic.
What Audrey deliberately does not do
Audrey does not upload your memory to a hosted service by default. It does not treat every sentence as permanent truth. It does not promote instructions from arbitrary tool output into trusted policy. It does not claim that a small local benchmark proves state-of-the-art memory quality.
Raw prompt events and tool bodies are not retained by default. Audrey stores hashes, bounded summaries, fingerprints, and redaction metadata. Explicit user-memory language is persisted intentionally; tool failure memories are sanitized first. Admin export/import/forget/promote surfaces are disabled unless AUDREY_ENABLE_ADMIN_TOOLS=1.
At-rest encryption, identity-bound tenant authorization, rate limiting, and regulated retention remain deployment responsibilities today. They are not hidden behind a “production ready” badge.
Why a team might actually want this
Fewer repeated mistakes
Guard checks memory at the point where it can change an action, not after the damage is done. Exact failure fingerprints avoid the noisy “one Bash command failed, so all Bash commands are suspicious” behavior.
Continuity across agent sessions
Codex and Claude Code use the same memory runtime and evidence contract. Generated configurations use separate codex and claude-code agent identities, so they do not automatically recall each other's memories. Cross-agent Autopilot recall requires the explicit AUDREY_AUTOPILOT_SCOPE=shared setting in the host runtime environment; this broadens recall across the store. MCP, REST, JavaScript, and Python clients make the core usable in custom agents too.
Evidence a human can inspect
Allow, warn, and block decisions carry receipts and evidence IDs. Outcome records connect back to those receipts. Teams can ask not only “what did the agent remember?” but “which memory changed this action, and was that useful?”
Local control
The default store is SQLite, FTS5, and sqlite-vec. Local embeddings are the default. Cloud embedding or LLM providers require explicit configuration.
A safer shared store
Agent-scoped recall continues through validation, contradiction detection, interference, affect, failure lookup, capsules, greetings, Guard, and REST request routing. Recall updates retrieval count and last-reinforced timestamp for returned semantic and procedural memories. Capsule and Guard filtering may further narrow those results. Explicit validation feedback (memory_validate / /v1/validate) separately updates usage and salience from a caller's used/helpful/wrong assessment.
Vector candidates are partitioned by agent before nearest-neighbor ranking, so one busy agent cannot crowd another out of a bounded search. For hard tenant boundaries, still use a distinct AUDREY_DATA_DIR per tenant or security domain.
Technical reference
Everything below is the machinery. The short version above is the product.
Requirements and packages
- Node.js 22.16+ (22.x) or 24+; Node 20 and 23 are no longer supported
- npm package:
audrey - Python client:
audrey-memory - Default storage: local SQLite + FTS5 +
sqlite-vec - Default embeddings: local 384-dimensional model
Audrey uses node:sqlite; sqlite-vec ships its extension in platform packages. The local embedding runtime also includes its CPU binaries, so npm install --ignore-scripts audrey works. Keep optional dependencies enabled: they contain the platform files for sqlite-vec and sharp. GPU acceleration may require additional ONNX Runtime libraries for your platform. Some supported Node releases print an experimental SQLite warning at startup; it does not prevent operation.
For Autopilot, prefer a global or otherwise stable installation. Hook and MCP configuration pins the actual Node executable and Audrey entrypoint; an ephemeral npx cache is not a durable production runtime.
Host configuration
Preview or apply lifecycle hooks independently:
Claude Code scope mapping follows the host’s terminology:
local→.claude/settings.local.jsonproject→.claude/settings.jsonuser→~/.claude/settings.json
Codex supports project .codex/hooks.json and user ~/.codex/hooks.json; it has no local hook scope. Audrey preserves unrelated hooks, replaces older Audrey-owned handlers, writes a private timestamped backup, and is idempotent on repeat installation. Project-adjacent backup names match *.audrey-*.bak; keep that pattern ignored because a host config can contain unrelated credentials.
Audrey respects CLAUDE_CONFIG_DIR and CODEX_HOME. Generated hooks pin the stable Node executable, Audrey entrypoint, data directory, agent identity, and non-secret provider choices used at install time. With local embeddings, an Autopilot install warms the model cache; set AUDREY_DISABLE_WARMUP=1 to skip it. Each hook still runs in a new process and initializes an embedding pipeline when needed, so cached model files do not eliminate startup latency.
Generate MCP configuration without applying it:
Remove Audrey-owned MCP registrations and hooks with the same host and scope you installed:
Add --dry-run to preview uninstall without changing either host. Add --mcp-only only when you intentionally want to preserve Audrey hooks.
Autopilot safety contract
The shared hook adapter normalizes current Codex and Claude Code payloads.
- Context injection is bounded by
AUDREY_CONTEXT_BUDGET_CHARS(default 4000; Autopilot uses a conservative 3200-character packet unless overridden). - Prompt and tool retrieval queries are bounded before embedding. Large edits carry hashes and lengths instead of file bodies; exact Guard identity uses a full redacted digest rather than a truncated prefix.
- The generated default hooks guard and observe
Bash,Edit,MultiEdit,Write,NotebookEdit,apply_patch, and everymcp__*tool from connected MCP servers, excluding Audrey's own memory tools so the Guard never guards itself. - A Bash command is only guarded when it can have side effects. A command whose every part is positively recognised as read-only (
grep,ls,sed -n,git status,npm ls, and similar; no command substitution, no redirect except to/dev/null, nosudo,xargs, oreval) skips the preflight, and a non-zero exit from it is recorded but never treated as a failure to avoid. Anything the classifier does not recognise is guarded. - A remembered Bash failure is matched to a proposed command by the verbs it runs (
npm run deploy,git push), not by how similar the two command strings read. - Pre/post correlation uses
session_id + tool_use_id, so parallel tool calls do not attach to the wrong receipt. - Claude
PostToolUseFailureand Codex responses that explicitly expose a non-zero exit normalize to the same failure path. Current Codex hooks can omit Bash exit status; Audrey records an opaque result asunknown, never as invented success. - On an internal error, every hook logs to stderr and emits
{}(no opinion, so the tool proceeds). OnlyPreToolUsechanges behavior underAUDREY_HOOK_FAIL_CLOSED=1, emitting a deny decision instead; context-injection and post-tool hooks have no deny path and always emit{}. - Stop hooks always emit valid JSON and never continue or block a completed turn.
Codex hook interception is a guardrail, not a complete shell-policy boundary. The current host contract does not intercept every richer unified_exec path and may omit the exit status of silent Bash failures. See the Codex hooks documentation. Use the Guard receipt as evidence, and keep sandboxing, approvals, CI, and deployment controls in place.
JavaScript API
REST sidecar
Core routes:
Use AUDREY_API_KEY for any non-loopback deployment. X-Audrey-Agent scopes encode, recall, capsules, preflight, Guard, consolidation, and greetings inside a trusted deployment; it is a routing header, not an authentication boundary. Bind agent/tenant identity at your gateway rather than trusting an arbitrary public header. Every route also accepts a per-call agent field in the JSON body as a fallback for callers (such as the Python client) that cannot set a header per request; the header wins whenever both are present.
Python client
The Python package is a client for the REST sidecar; the memory runtime remains in the Node process.
Memory and retrieval pipeline
Agent-scoped vector search uses a native sqlite-vec partition key before nearest-neighbor ranking, not post-filtered whole-store candidates. If fusion underfills, Audrey makes one bounded partition-local retry. Semantic and procedural retrieval counts update only as final results are yielded; deduplicated, over-limit, and unconsumed stream candidates receive no authority boost.
MCP surface
Audrey exposes 23 MCP tools plus status, recent-memory, and principle resources and briefing/recall/reflection prompts. The main groups are:
- capture:
memory_encode,memory_reflect,memory_observe_tool - retrieval:
memory_recall,memory_capsule,memory_greeting - action safety:
memory_preflight,memory_guard_before,memory_guard_after,memory_reflexes - lifecycle:
memory_consolidate,memory_dream,memory_decay,memory_resolve_truth,memory_ground - governance:
memory_validate,memory_promote,memory_forget,memory_export,memory_import,memory_status,memory_introspect
The server also sends host instructions explaining the Guard receipt loop when lifecycle hooks are unavailable.
Environment variables
Provider secrets are never embedded in generated hook commands. --include-secrets applies only to MCP registration; prefer host environment injection or a secret manager.
OpenAI API billing uses AUDREY_LLM_PROVIDER=openai and OPENAI_API_KEY. To use a ChatGPT subscription for reflection and consolidation, run audrey auth login, then set AUDREY_LLM_PROVIDER=chatgpt, AUDREY_LLM_MODEL=gpt-6.1-sol, and AUDREY_LLM_REASONING_EFFORT=medium. Reinstall the host configuration after changing provider settings. Subscription requests require account permission and an available model; failures never switch to API billing. Embeddings remain a separate provider and default to local execution. See OpenAI's subscription documentation.
Use audrey auth accounts to list saved registrations, audrey auth select --account <ID> to switch, and audrey auth logout to sign out. Tokens stay in protected local storage outside the memory database. audrey auth status reports connection state without exposing tokens.
New local stores use private directory and database permissions on filesystems that support POSIX modes. Existing database and WAL files are restricted on open. Windows and mounted volumes need appropriate operating-system ACLs. Set AUDREY_SHARED_STORE=1 (SDK: sharedStore: true) only when you manage shared access yourself.
Local models download into the per-user cache on first use. Allow that first run to finish before relying on hooks offline. A failed initialization can be retried in the same process. For a system package installed by root, run the initial model load as the desktop user so the cache remains writable.
Snapshot format 2 preserves grounding anchors, their last known state, and consolidation undo journals; older snapshots remain importable. Worktrees share a repository identity for recall, while grounding checks the checkout where an anchor was recorded. Rollback preserves earlier knowledge when undoing a merge. Legacy merges without an undo journal are refused when they cannot be reversed safely.
The REST API requires JSON request bodies and rejects cross-origin browser requests. Unauthenticated requests require a loopback host unless AUDREY_ALLOW_NO_AUTH=1 is explicitly set. Configure AUDREY_API_KEY for network deployments.
Production checklist
- Give every tenant or hard isolation domain its own
AUDREY_DATA_DIR. - Pin embedding and LLM providers explicitly.
- Back up the store before provider, dimension, or version migrations.
- Put the REST sidecar behind authentication and rate limits; do not expose an agent-selection header as identity.
- Leave REST shared scope disabled unless cross-agent retrieval is intentional and authorized by your own identity layer.
- Keep credentials and regulated raw content out of encoded memories.
- Decide retention, deletion, encryption, and audit policy before regulated use.
- Monitor
audrey status --json --fail-on-unhealthy. - Keep the hook runtime on a stable installed path.
- Load-test concurrent writers for your topology; SQLite WAL is not a distributed coordination layer.
Local embeddings use Transformers.js 4.3+ with sharp 0.35.4+, resolving the earlier libvips/libheif advisories in the published dependency tree. A hosted embedding provider changes runtime execution but does not remove installed packages. Run npm audit --omit=dev against your installation to check current advisories.
Benchmarks and evidence
Run the release gates locally:
GuardBench currently contains ten local, deterministic pre-action scenarios covering repeated failures, procedures, scope changes, recovery, redaction, conflicting instructions, and noisy stores. The checked-in v1 methodology uses a mock 64-dimensional embedding provider and exists to catch regressions. A perfect local pass is not a claim about real-provider latency or production false-positive rates.
Latest local result in this checkout: 10/10 scenarios passed, 100% prevention rate, 0% false-block rate, 0 raw secret leaks, 0 published artifact leaks, and 3.805ms / 13.445ms p50/p95 Guard latency under the mock-provider methodology.
benchmarks/perf-snapshot.js measures encode and hybrid-recall p50/p95/p99 at configurable corpus sizes with machine provenance. It currently uses mock 64-dimensional embeddings; it has no provider-selection flag and does not measure hook process startup. Measure complete hook invocations separately with your intended provider, cache state, corpus, and hardware before using these numbers to estimate interactive latency.
The longer-term public evaluation target includes LongMemEval, MemoryAgentBench, and adversarial memory-poisoning cases. Relevant design directions include bitemporal knowledge graphs in Zep/Graphiti, evolving memory organization in A-MEM, and sleep-time agent compute in Sleep-time Compute.
Development
See CONTRIBUTING.md, SECURITY.md, and docs/MEMORY_BENCHMARKING.md.
Maintainer release gates
These commands are intentionally documented because the paper and release evidence ledger verifies them against the public source tree:
Live Zep runs require ZEP_API_KEY; ZEP_GUARDBENCH_INGEST_DELAY_MS tunes ingestion settling time. The external dry-run matrix proves adapter shape without credentials, while external evidence verification distinguishes pending runs from verified live evidence.
Publication packaging verifies artifact hashes, source bundles, and path redaction. Release readiness separately reports source-control state, live remote-head verification, npm registry/auth readiness, and PyPI publish readiness. Pass -- --target-version <version> to the readiness commands when checking a release; the script's legacy default is 1.1.1.
MIT licensed. Built for agents that should get better at the work without becoming less accountable.
來源:README.md,提交 7303841
工具
0版本歷史
2- v2.1.1最新Oct 29, 2026
- v1.3.0Sep 16, 2026
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