chaos-memory
Hybrid search memory system for AI agents. Manual search and storage - auto-capture is opt-in only.
- License 许可
- MIT
- 最近更新
- 2026-08-23
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- chaos-memory
- homepage
- https://github.com/hargabyte/Chaos-mind
- metadata
- { "openclaw": { "emoji": "?", "install": [ { "id": "chaos-install", "kind": "shell", "label": "Install CHAOS Memory", "command": "bash install.sh" } ] } }
- description
- Hybrid search memory system for AI agents. Manual search and storage - auto-capture is opt-in only.
02 资源文件 11
- 参考文档_meta.json275 B
- 参考文档clawdhub.yaml3.8 KB
- 参考文档config/consolidator.template.yaml2.0 KB
- 参考文档DEPLOYMENT_CHECKLIST.md4.1 KB
- 参考文档INSTALL_NOTES.md3.3 KB
- 脚本install.sh10.3 KB
- 参考文档README.md11.7 KB
- 参考文档RELEASE_INSTRUCTIONS.md4.2 KB
- 参考文档RELEASE_SUMMARY.md5.0 KB
- 脚本scripts/setup-service.sh1.7 KB
- 参考文档SECURITY.md5.1 KB
03 SKILL.md 正文
CHAOS Memory
Context-aware Hierarchical Autonomous Observation System
Hybrid search memory for AI agents with 4 retrieval signals:
- BM25 - Keyword matching
- Vector - Semantic similarity
- Graph - Relationship bonuses
- Heat - Access patterns + priority
? For AI Agents: How to Use This Tool
First time? Run this to see the complete reference:
chaos-cli --help
Quick workflow:
- Before a task:
chaos-cli search "keywords" --mode index --limit 10 - During a task:
chaos-cli store "important fact" --category decision --priority 0.9 - After a task:
chaos-cli list 10
Token savings: Use --mode index for 90% token savings (~75 tokens/result)
More help: Run chaos help-agents for the AI-optimized reference guide.
Quick Start
After installation, use chaos-cli:
# Search memories
chaos-cli search "pricing decisions" --limit 5
# Store a memory
chaos-cli store "Enterprise tier: $99/month" --category decision
# List recent
chaos-cli list 10
Search Memories
Quick search (summary mode):
chaos-cli search "architecture patterns" --mode summary --limit 5
Fast scan (index mode, 90% token savings):
chaos-cli search "team decisions" --mode index --limit 10
Full detail:
chaos-cli search "model selection" --mode full --limit 3
Modes:
| Mode | Tokens/Result | Use Case |
|---|---|---|
| index | ~75 | Quick scan, many results |
| summary | ~250 | Balanced (default) |
| full | ~750 | Deep dive |
Store Memory
# Decision
chaos-cli store "Qwen3-1.7B is default model" --category decision --priority 0.9
# Core fact
chaos-cli store "Database runs on port 3307" --category core --priority 0.7
# Research finding
chaos-cli store "43x speedup with think=false" --category research --priority 0.8
Categories: decision, core, semantic, research
Priority: 0.0-1.0 (higher = more important)
Get by ID
chaos-cli get <memory-id>
List Recent
chaos-cli list # Default 10
chaos-cli list 20 # Show 20
Auto-Capture (Optional - Opt-In Only)
⚠️ DISABLED BY DEFAULT for privacy.
To enable auto-capture:
- Review privacy implications - reads your session transcripts
- Edit config:
nano ~/.chaos/config/consolidator.yaml - Set:
auto_capture.enabled: true - Configure paths: Add your session directories to
auto_capture.sources - Install Ollama: https://ollama.com (if not already installed)
- Pull model:
ollama pull qwen3:1.7b - Test:
chaos-consolidator --auto-capture --once
What it extracts: Decisions, facts, insights
What it skips: Greetings, filler, acknowledgments
Where it runs: 100% local (your machine, no external APIs)
Speed: 2.6s per message (~42s per 16-message session)
Privacy: Only processes files you explicitly configure. See SECURITY.md for details.
? Enhanced Capabilities
CHAOS Memory integrates with other tools for deeper intelligence:
Cortex (cx) - Semantic Code Anchoring
What it does: Anchors memories to specific code locations and files
Why use it: Memories become context-aware - "this decision affects Auth.tsx lines 45-67"
How it works:
- CHAOS detects if
cxis available at startup - Automatically creates semantic links:
memory → code location - Search results include related code snippets
Install Cortex:
# Cortex is a separate tool
# Install from: https://github.com/hargabyte/cortex
Example:
# Without Cortex
chaos-cli search "auth flow"
→ "Changed auth to use JWT tokens"
# With Cortex
chaos-cli search "auth flow"
→ "Changed auth to use JWT tokens"
→ ? Auth.tsx:45-67, middleware/auth.js:12
Beads - Task Relationship Tracking
What it does: Links memories to tasks and issues
Why use it: Track which memories led to which tasks, decisions to implementations
How it works:
- CHAOS detects if
beadsorbeads-rustis available - Creates bidirectional links:
memory ↔ task - Memories can reference issue IDs automatically
Install Beads:
# Beads is a separate task management tool
# Install from: https://github.com/hargabyte/beads
Example:
# Store memory with task reference
chaos-cli store "Need to refactor auth" --category decision --task AUTH-123
# Search shows related tasks
chaos-cli search "auth refactor"
→ "Need to refactor auth"
→ ? Task: AUTH-123 (In Progress)
Combined Power
When all three tools work together:
chaos-cli search "performance optimization"
→ Memory: "Added Redis caching layer"
→ ? Code: cache/redis.js:34-89
→ ? Task: PERF-042 (Completed)
→ ? Related: 3 other memories, 2 code files, 1 PR
Status Detection:
- Cortex: Detected automatically on startup (logs
[OPT] Cortex Engine: FOUND) - Beads: Detected automatically on startup (logs
[OPT] Beads Task Manager: FOUND) - View status: Check the startup logs when running
chaos-mcp
Configuration
Default config location: ~/.chaos/config/consolidator.yaml
# Auto-capture is DISABLED by default
auto_capture:
enabled: false # Change to true after configuring paths
sources: [] # Add your session paths here
# Example (uncomment after reviewing):
# sources:
# - ~/.openclaw-*/agents/*/sessions/*.jsonl
qwen:
model: qwen3:1.7b # Locked default
chaos:
mode: mcp
mcp:
env:
CHAOS_DB_PATH: "~/.chaos/db"
Environment Variables
| Variable | Default | Description |
|---|---|---|
CHAOS_HOME |
~/.chaos |
Installation directory |
CHAOS_DB_PORT |
3307 |
Database port |
CHAOS_MODEL |
qwen3:1.7b |
Extraction model |
Requirements
- Dolt - Version-controlled database
- Ollama - Local LLM inference (for auto-capture)
- Go 1.21+ - To build from source (optional)
The install script handles dependencies automatically.
Troubleshooting
Command not found:
export PATH="$HOME/.chaos/bin:$PATH"
Database error:
cd ~/.chaos/db && dolt sql-server --port 3307 &
No results:
chaos-cli list # Check if memories exist
Security & Privacy
Data Storage: All memories stored locally on your machine (~/.chaos/db)
- No cloud sync or external transmission
- Your data never leaves your computer
- Database is version-controlled (Dolt) for auditability
Auto-Capture (Opt-In):
- Disabled by default - you must explicitly enable and configure
- Requires manual configuration of session paths in
~/.chaos/config.yaml - Only processes files you explicitly specify in
auto_capture.sources - Runs locally using your own Ollama instance (no external API calls)
Permissions:
- Read: Session transcript files (only paths you configure)
- Write: Local database (
~/.chaos/db) - Network: None (all processing is local)
Control:
# View what auto-capture will process (dry-run)
chaos-consolidator --auto-capture --once --dry-run
# Disable auto-capture
# Edit ~/.chaos/config.yaml:
# auto_capture:
# enabled: false
# Or simply don't configure session paths
Transparency:
- Install script source: Included in repo (
install.sh) - All binaries built via GitHub Actions (reproducible)
- Database is plain Dolt (inspect with
dolt sql)
Links
- GitHub: https://github.com/hargabyte/Chaos-mind
- Docs: https://github.com/hargabyte/Chaos-mind/blob/main/README.md
- Issues: https://github.com/hargabyte/Chaos-mind/issues
Version 1.0.0 | Created by HSA Team
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