Local, cloud-free memory for OpenClaw agents.
Project description
Palaia — The Knowledge OS for OpenClaw Agent Teams
Crash-safe. Local-first. Zero-cloud. The memory system that makes your agents smarter over time.
Install — Zero Config
pip install "palaia[fastembed]"
OpenClaw plugin (3 lines in your config):
{
"plugins": {
"load": { "paths": ["<npm-global>/node_modules/@byte5ai/palaia"] },
"allow": ["palaia"],
"slots": { "memory": "palaia" }
}
}
That's it. Palaia works immediately — memories are injected into every prompt, significant exchanges are captured automatically, and semantic recall finds what's relevant. No config edits needed.
Upgrading from v1.x? Run palaia doctor --fix to get the new optimized defaults.
Quick Start
palaia init # Initialize store
palaia write "API rate limit is 100 req/min" \
--type memory --tags api,limits # Save knowledge
palaia query "what's the rate limit" # Find it by meaning
Why Palaia?
WAL-Backed Crash Safety
Every write goes through a write-ahead log before touching storage. Power loss mid-write? Palaia recovers automatically on next startup. No data loss. No corruption. No "oops."
Intelligent Tiering
Memories automatically organize by usage: HOT (active), WARM (recent), COLD (archived). Frequently accessed entries stay fast. Nothing gets deleted — old memories fade to background storage.
Structured Entry Types
Not all knowledge is equal. Classify entries as memory (facts, decisions), process (workflows, checklists), or task (action items with status, priority, assignee). Query by type for focused results.
Multi-Agent Collaboration
Multiple agents share one store with scope-based access control. Private entries stay private. Team entries are shared. Projects group related knowledge. Inter-agent memos enable async communication.
Zero-Cloud Architecture
Everything runs on your machine. No API keys required for core functionality. No database server. No cloud dependency. Your data never leaves your infrastructure.
Adaptive Nudging
Palaia teaches agents good habits through CLI output hints — then stops once they learn. The graduation system tracks consecutive successes and retires nudges when agents demonstrate independence. Regression detection re-activates nudges if habits slip.
OpenClaw-Native
Built as a first-class OpenClaw plugin. Auto-capture of significant exchanges. Query-based contextual recall before each prompt. LLM-powered knowledge extraction. Configurable capture levels from conservative to aggressive.
Features
| Feature | Details |
|---|---|
| Semantic Search | Find by meaning, not keywords. Providers: fastembed, sentence-transformers, OpenAI, Gemini, Ollama, BM25 |
| Crash-Safe Writes | WAL-backed — survives power loss, kills, OOM |
| Auto-Capture | OpenClaw plugin captures significant exchanges automatically |
| Structured Types | memory, process, task — with status, priority, assignee fields |
| Multi-Agent | Shared store, scopes (private/team/public), agent aliases, inter-agent memos |
| Smart Tiering | HOT → WARM → COLD rotation based on access patterns |
| Garbage Collection | Automatic tier rotation, WAL cleanup, stale entry management |
| OpenClaw Plugin | Drop-in replacement for built-in memory — query-based recall, auto-capture, LLM extraction |
| Projects | Group entries by project with default scopes and ownership |
| Document Ingestion | Index PDFs, HTML, Markdown for RAG search |
| Adaptive Nudging | Teaches agents best practices, graduates when they learn |
Comparison
| Feature | Palaia | Stock Memory | Mem0 | Engram |
|---|---|---|---|---|
| Local-first | Yes | Yes | No (cloud) | Yes |
| Crash-safe (WAL) | Yes | No | N/A | No |
| Auto-Capture | Yes (plugin) | No | Yes | No |
| Structured Types | Yes (memory/process/task) | No | No | No |
| Multi-Agent Scopes | Yes (private/team/public) | No | Per-user | No |
| Smart Tiering | Yes (HOT/WARM/COLD) | No | No | No |
| Garbage Collection | Yes (automatic) | Manual | Managed | Manual |
| OpenClaw Plugin | Native | Built-in | No | No |
| Semantic Search | Hybrid (embedding + BM25) | None | Embedding | Embedding |
| Zero-Cloud | Yes | Yes | No | Yes |
Configuration
Plugin Config (OpenClaw)
Set in openclaw.json under plugins.entries.palaia.config:
| Key | Default | Description |
|---|---|---|
memoryInject |
true |
Inject relevant memories into agent context |
maxInjectedChars |
8000 |
Max characters for injected memory context |
autoCapture |
true |
Capture significant exchanges automatically |
captureFrequency |
"significant" |
"every" or "significant" |
captureMinTurns |
2 |
Minimum turns before capture |
captureModel |
auto | Model for LLM extraction (e.g. "anthropic/claude-haiku-3") |
recallMode |
"query" |
"list" (tier-based) or "query" (semantic) |
recallTypeWeight |
{process:1.5, task:1.2, memory:1.0} |
Type-aware result weighting |
Capture Levels
Configure via palaia init --capture-level:
| Level | autoCapture | Frequency | Min Turns |
|---|---|---|---|
off |
false | — | — |
sparsam |
true | significant | 5 |
normal |
true | significant | 2 |
aggressiv |
true | every | 1 |
CLI Reference
palaia init [--agent NAME] [--capture-level LEVEL] Initialize store
palaia write "text" [--type TYPE] [--tags a,b] Save a memory
palaia query "search" [--type TYPE] [--project P] Search by meaning
palaia get <id> Read specific entry
palaia list [--tier T] [--type T] [--status S] List entries
palaia edit <id> [--status done] Edit entry
palaia status System health
palaia doctor [--fix] Diagnose + fix
palaia project create|list|show|query|delete Manage projects
palaia memo send|inbox|ack|broadcast Inter-agent messaging
palaia ingest <source> [--project P] Index documents (RAG)
palaia detect Available providers
palaia warmup Pre-build search index
palaia migrate [--suggest] Import / suggest types
All commands support --json for machine-readable output.
Development
git clone https://github.com/iret77/palaia.git
cd palaia
pip install -e ".[dev]"
pytest
640+ tests. Contributions welcome.
Links
- GitHub — Source + Issues
- PyPI — Package registry
- ClawHub — Install via agent skill
- OpenClaw — The agent platform Palaia is built for
- CHANGELOG — Release history
MIT — (c) 2026 byte5 GmbH
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