Complete Agent Pipeline System with Claude Code & OpenClaw Integration
- Added Claude Code integration with full context compaction support - Added OpenClaw integration with deterministic pipeline support - Implemented parallel agent execution (4 projects x 3 roles pattern) - Added workspace isolation with permissions and quotas - Implemented Lobster-compatible YAML workflow parser - Added persistent memory store for cross-session context - Created comprehensive README with hero section This project was 100% autonomously built by Z.AI GLM-5
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# Agentic Compaction & Pipeline System
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<p align="center">
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<strong>A comprehensive open-source implementation of context compaction mechanisms<br>
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and deterministic multi-agent pipeline orchestration</strong>
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</p>
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<p align="center">
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<em>Designed for seamless integration with Claude Code, OpenClaw, and custom AI systems</em>
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</p>
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---
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<p align="center">
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<a href="#features">Features</a> •
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<a href="#installation">Installation</a> •
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<a href="#quick-start">Quick Start</a> •
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<a href="#integrations">Integrations</a> •
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<a href="#api-reference">API Reference</a>
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</p>
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---
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## 🤖 About This Project
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<div align="center">
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### ⚡ This project was 100% autonomously built by AI ⚡
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**Z.AI GLM-5** created this entire codebase in a single session — designing the architecture,
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implementing all modules, writing comprehensive documentation, packaging the releases,
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and even pushing everything to this Git repository.
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**[Learn more about Z.AI GLM-5 →](https://z.ai/subscribe?ic=R0K78RJKNW)**
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*Yes, the README you're reading right now was written by the AI too! 🎉*
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</div>
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---
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## Overview
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This project provides two complementary systems:
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1. **Agent System** - Context compaction, token management, and agent orchestration
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2. **Pipeline System** - Deterministic state machine, parallel execution, and event-driven coordination
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Built based on the architectural principles described in [How I Built a Deterministic Multi-Agent Dev Pipeline Inside OpenClaw](https://dev.to/ggondim/how-i-built-a-deterministic-multi-agent-dev-pipeline-inside-openclaw-and-contributed-a-missing-4ool).
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---
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## Features
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### Agent System
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- ✅ **Token Counting & Management** - Accurate token estimation with budget tracking
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- ✅ **Context Compaction** - 4 strategies: sliding-window, summarize-old, priority-retention, hybrid
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- ✅ **Conversation Summarization** - LLM-powered summarization with key points extraction
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- ✅ **Agent Orchestration** - Lifecycle management, task routing, event handling
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- ✅ **Subagent Spawning** - 6 predefined subagent types for task delegation
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- ✅ **Persistent Storage** - File-based memory store for agent state
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- ✅ **Claude Code Integration** - Full support for Claude Code CLI/IDE
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- ✅ **OpenClaw Integration** - Native integration with OpenClaw workflows
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### Pipeline System
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- ✅ **Deterministic State Machine** - Flow control without LLM decisions
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- ✅ **Parallel Execution Engine** - Worker pools with concurrent agent sessions
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- ✅ **Event-Driven Coordination** - Pub/sub event bus with automatic trigger chains
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- ✅ **Workspace Isolation** - Per-agent tools, memory, identity, permissions
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- ✅ **YAML Workflow Parser** - Lobster-compatible workflow definitions
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- ✅ **Claude Code Integration** - Ready-to-use integration layer
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---
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────────┐
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│ AGENTIC PIPELINE SYSTEM │
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├─────────────────────────────────────────────────────────────────┤
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│ │
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│ ┌───────────────────────┐ ┌───────────────────────┐ │
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│ │ AGENT SYSTEM │ │ PIPELINE SYSTEM │ │
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│ ├───────────────────────┤ ├───────────────────────┤ │
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│ │ • Token Counter │ │ • State Machine │ │
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│ │ • Context Manager │ │ • Parallel Executor │ │
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│ │ • Summarizer │ │ • Event Bus │ │
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│ │ • Orchestrator │ │ • Workspace Manager │ │
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│ │ • Subagent Spawner │ │ • YAML Workflows │ │
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│ │ • Memory Store │ │ • Claude Integration │ │
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│ │ ───────────────────── │ └───────────────────────┘ │
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│ │ INTEGRATIONS: │ │
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│ │ • Claude Code ✅ │ │
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│ │ • OpenClaw ✅ │ │
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│ └───────────────────────┘ │
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│ │
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│ ┌─────────────────────────────────────────────────────────┐ │
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│ │ INTEGRATION LAYER │ │
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│ │ Claude Code │ OpenClaw │ Lobster │ Custom Applications │ │
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│ └─────────────────────────────────────────────────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────────┘
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```
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### Data Flow
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```
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User Request → Pipeline Orchestrator → State Machine
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│
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▼
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Parallel Executor (Worker Pool)
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│
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┌─────────────────┼─────────────────┐
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▼ ▼ ▼
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Agent 1 Agent 2 Agent N
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│ │ │
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▼ ▼ ▼
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Workspace Workspace Workspace
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│ │ │
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└─────────────────┼─────────────────┘
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▼
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Event Bus
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│
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▼
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Context Manager
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│
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▼
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Summarizer (if needed)
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│
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▼
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Response/Next State
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```
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---
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## Installation
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### Prerequisites
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- Node.js 18+ or Bun
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- TypeScript 5+
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### From Source
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```bash
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# Clone the repository
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git clone https://github.rommark.dev/admin/Agentic-Compaction-and-Pipleline-by-GLM-5.git
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cd Agentic-Compaction-and-Pipleline-by-GLM-5
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# Install dependencies
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bun install
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# Build (if needed)
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bun run build
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```
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### Using Zip Packages
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Download the appropriate package from the `downloads/` directory:
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| Package | Description | Use Case |
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|---------|-------------|----------|
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| `agent-system.zip` | Context compaction & orchestration | Building custom AI agents |
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| `pipeline-system.zip` | Deterministic pipelines | Multi-agent workflows |
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| `complete-agent-pipeline-system.zip` | Full system | Complete integration |
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---
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## Quick Start
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### Agent System
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```typescript
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import { ContextManager, TokenCounter, Summarizer } from './agent-system';
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// Initialize components
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const tokenCounter = new TokenCounter(128000); // 128k token budget
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const summarizer = new Summarizer();
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const contextManager = new ContextManager(tokenCounter, summarizer, {
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maxTokens: 100000,
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compactionStrategy: 'hybrid',
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reserveTokens: 20000
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});
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// Add messages
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contextManager.addMessage({ role: 'user', content: 'Hello!' });
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contextManager.addMessage({ role: 'assistant', content: 'Hi there!' });
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// Check if compaction needed
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if (contextManager.needsCompaction()) {
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const result = await contextManager.compact();
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console.log(`Compacted: ${result.messagesRemoved} messages removed`);
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}
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```
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### Pipeline System
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```typescript
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import { DeterministicStateMachine, ParallelExecutionEngine, EventBus } from './pipeline-system';
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// Define workflow
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const workflow = `
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name: code-pipeline
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states:
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- name: analyze
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transitions:
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- to: implement
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event: analyzed
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- name: implement
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transitions:
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- to: test
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event: implemented
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- name: test
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transitions:
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- to: complete
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event: passed
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`;
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// Create pipeline
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const eventBus = new EventBus();
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const stateMachine = new DeterministicStateMachine(workflow);
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const executor = new ParallelExecutionEngine({ maxConcurrency: 4 });
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// Run pipeline
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await stateMachine.start();
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```
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---
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## Integrations
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### Claude Code Integration
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Full integration with Claude Code CLI and IDE extensions:
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```typescript
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import { ClaudeCodeIntegration } from './agent-system/integrations/claude-code';
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// Initialize with Claude Code defaults
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const claude = new ClaudeCodeIntegration({
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maxContextTokens: 200000, // Claude's context window
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reserveTokens: 40000, // Reserve for response
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compactionStrategy: 'hybrid',
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autoCompact: true,
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compactionThreshold: 0.8,
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enableSubagents: true,
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maxSubagents: 6,
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persistentMemory: true
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});
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// Add messages with automatic compaction
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claude.addMessage({ role: 'user', content: 'Analyze this codebase...' });
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// Get context for Claude API
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const { messages, systemPrompt } = claude.getContextForAPI();
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// Spawn subagents for complex tasks
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const result = await claude.spawnSubagent({
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type: 'researcher',
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prompt: 'Research authentication patterns',
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priority: 'high'
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});
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// Parallel subagent execution (4 projects × 3 roles pattern)
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const results = await claude.executeParallelSubagents([
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{ type: 'explorer', prompt: 'Find security issues in frontend' },
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{ type: 'explorer', prompt: 'Find security issues in backend' },
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{ type: 'reviewer', prompt: 'Review API endpoints' }
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]);
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// Memory management
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await claude.remember('userPreference', { theme: 'dark' });
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const pref = await claude.recall('userPreference');
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// Save/restore context
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await claude.saveContext('milestone-1');
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await claude.loadContext('milestone-1');
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// Monitor session
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const stats = claude.getTokenStats();
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console.log(`Using ${stats.percentage}% of context (${stats.used}/${stats.total} tokens)`);
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```
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### OpenClaw Integration
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Native integration with OpenClaw's deterministic multi-agent architecture:
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```typescript
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import { OpenClawIntegration } from './agent-system/integrations/openclaw';
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// Initialize with OpenClaw-compatible config
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const openclaw = new OpenClawIntegration({
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maxContextTokens: 200000,
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compactionStrategy: 'hybrid',
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workspaceIsolation: true,
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enableLobsterWorkflows: true,
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enableParallelExecution: true,
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maxParallelAgents: 12, // 4 projects × 3 roles
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hooks: {
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onCompactionStart: (ctx) => console.log('Compacting...'),
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onCompactionEnd: (result) => console.log(`Saved ${result.tokensSaved} tokens`),
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onStateTransition: (from, to, ctx) => console.log(`${from} → ${to}`)
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}
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});
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// Add messages with OpenClaw context
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openclaw.addMessage({
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role: 'user',
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content: 'Implement user authentication',
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tags: ['feature', 'auth'],
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references: {
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files: ['src/auth.ts', 'src/middleware.ts']
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}
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});
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// Spawn agents for parallel execution
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const agents = await openclaw.executeParallelAgents([
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{ type: 'planner', prompt: 'Plan auth architecture' },
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{ type: 'researcher', prompt: 'Research JWT best practices' },
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{ type: 'explorer', prompt: 'Find existing auth patterns' }
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]);
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// Create deterministic pipeline
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const pipeline = openclaw.createPipeline({
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name: 'feature-development',
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description: 'Complete feature development workflow',
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states: [
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{
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name: 'analyze',
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type: 'parallel',
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agents: ['explorer', 'researcher'],
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transitions: [
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{ target: 'design', event: 'analysis_complete' }
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]
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},
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{
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name: 'design',
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type: 'sequential',
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agents: ['planner'],
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transitions: [
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{ target: 'implement', event: 'design_approved' }
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]
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},
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{
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name: 'implement',
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type: 'parallel',
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agents: ['coder'],
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transitions: [
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{ target: 'review', event: 'implementation_complete' }
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]
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},
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{
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name: 'review',
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type: 'sequential',
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agents: ['reviewer'],
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transitions: [
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{ target: 'complete', event: 'approved' },
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{ target: 'implement', event: 'rejected' }
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]
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},
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{
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name: 'complete',
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type: 'sequential',
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transitions: []
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}
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]
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});
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// Execute pipeline
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await openclaw.startPipeline(pipeline.id);
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await openclaw.transitionPipeline(pipeline.id, 'analysis_complete');
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await openclaw.transitionPipeline(pipeline.id, 'design_approved');
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// ... continue transitions
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// Create isolated workspaces
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const workspace = await openclaw.createWorkspace({
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permissions: ['read', 'write'],
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quota: { maxFiles: 1000, maxSize: 100 * 1024 * 1024 }
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});
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```
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### Custom Integration
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Build your own integration:
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```typescript
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import {
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ContextManager,
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TokenCounter,
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Summarizer,
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EventBus,
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DeterministicStateMachine,
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ParallelExecutionEngine
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} from './agent-system';
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class CustomAISystem {
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private contextManager: ContextManager;
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private eventBus: EventBus;
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private executor: ParallelExecutionEngine;
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constructor(config: any) {
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const tokenCounter = new TokenCounter(config.maxTokens);
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const summarizer = new Summarizer();
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this.contextManager = new ContextManager(
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tokenCounter,
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summarizer,
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config.compaction
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);
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this.eventBus = new EventBus();
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this.executor = new ParallelExecutionEngine(config.parallel);
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this.setupEventHandlers();
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}
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private setupEventHandlers() {
|
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this.eventBus.subscribe('context:full', async () => {
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await this.contextManager.compact();
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});
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}
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async process(input: string) {
|
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this.contextManager.addMessage({
|
||||
role: 'user',
|
||||
content: input
|
||||
});
|
||||
|
||||
// Your custom processing logic
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## API Reference
|
||||
|
||||
### Agent System API
|
||||
|
||||
| Class | Method | Description |
|
||||
|-------|--------|-------------|
|
||||
| `TokenCounter` | `countTokens(text)` | Estimate token count |
|
||||
| | `getRemainingBudget()` | Get remaining tokens |
|
||||
| | `addUsage(count)` | Track token usage |
|
||||
| `ContextManager` | `addMessage(message)` | Add message to context |
|
||||
| | `needsCompaction()` | Check if compaction needed |
|
||||
| | `compact()` | Perform context compaction |
|
||||
| | `getActiveContext()` | Get current context |
|
||||
| `Summarizer` | `summarize(messages, options)` | Generate summary |
|
||||
| `Orchestrator` | `registerAgent(type, config)` | Register agent |
|
||||
| | `routeTask(task)` | Route to appropriate agent |
|
||||
| | `getAgentStatus(id)` | Check agent status |
|
||||
| `SubagentSpawner` | `spawn(type, options)` | Create subagent |
|
||||
| | `getSubagentTypes()` | List available types |
|
||||
| `ClaudeCodeIntegration` | `addMessage(message)` | Add message with auto-compact |
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||||
| | `spawnSubagent(task)` | Spawn Claude Code subagent |
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||||
| | `saveContext(name)` | Persist context |
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||||
| `OpenClawIntegration` | `createPipeline(definition)` | Create OpenClaw pipeline |
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||||
| | `executeParallelAgents(tasks)` | Execute 4×3 pattern |
|
||||
| | `createWorkspace(options)` | Isolated workspace |
|
||||
|
||||
### Pipeline System API
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||||
|
||||
| Class | Method | Description |
|
||||
|-------|--------|-------------|
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||||
| `DeterministicStateMachine` | `start(context)` | Start state machine |
|
||||
| | `transition(event, payload)` | Trigger transition |
|
||||
| | `getState()` | Get current state |
|
||||
| | `canTransition(event)` | Check valid transition |
|
||||
| `ParallelExecutionEngine` | `executeAll(tasks)` | Execute tasks in parallel |
|
||||
| | `submitTask(task)` | Add to queue |
|
||||
| | `startWorkers(count)` | Start worker threads |
|
||||
| `EventBus` | `subscribe(pattern, handler)` | Subscribe to events |
|
||||
| | `publish(event, data)` | Publish event |
|
||||
| | `getHistory(filter)` | Get event history |
|
||||
| `WorkspaceManager` | `createWorkspace(id, options)` | Create workspace |
|
||||
| | `getWorkspace(id)` | Access workspace |
|
||||
| | `destroyWorkspace(id)` | Cleanup workspace |
|
||||
| `YAMLWorkflow` | `parse(yaml)` | Parse workflow definition |
|
||||
| | `validate()` | Validate workflow |
|
||||
| | `toStateMachine()` | Convert to state machine |
|
||||
|
||||
---
|
||||
|
||||
## Examples
|
||||
|
||||
### Example 1: Multi-Project Analysis (OpenClaw Pattern)
|
||||
|
||||
```typescript
|
||||
import { OpenClawIntegration } from './agent-system/integrations/openclaw';
|
||||
|
||||
const openclaw = new OpenClawIntegration({
|
||||
maxParallelAgents: 12 // 4 projects × 3 roles
|
||||
});
|
||||
|
||||
const projects = ['frontend', 'backend', 'mobile', 'docs'];
|
||||
const roles = ['security', 'performance', 'quality'] as const;
|
||||
|
||||
const tasks = projects.flatMap(project =>
|
||||
roles.map(role => ({
|
||||
type: 'explorer' as const,
|
||||
prompt: `Analyze ${project} for ${role} issues`,
|
||||
context: { project, role }
|
||||
}))
|
||||
);
|
||||
|
||||
const results = await openclaw.executeParallelAgents(tasks);
|
||||
|
||||
// Aggregate results by project
|
||||
for (const [agentId, result] of results) {
|
||||
console.log(`Agent ${agentId}:`, result.output);
|
||||
}
|
||||
```
|
||||
|
||||
### Example 2: Context-Aware Chat with Claude Code
|
||||
|
||||
```typescript
|
||||
import { ClaudeCodeIntegration } from './agent-system/integrations/claude-code';
|
||||
|
||||
class ContextAwareChat {
|
||||
private claude: ClaudeCodeIntegration;
|
||||
|
||||
constructor() {
|
||||
this.claude = new ClaudeCodeIntegration({
|
||||
maxContextTokens: 200000,
|
||||
compactionStrategy: 'hybrid',
|
||||
priorityKeywords: ['important', 'remember', 'decision', 'error'],
|
||||
autoCompact: true,
|
||||
compactionThreshold: 0.75
|
||||
});
|
||||
}
|
||||
|
||||
async chat(userMessage: string): Promise<string> {
|
||||
// Add user message (auto-compacts if needed)
|
||||
this.claude.addMessage({ role: 'user', content: userMessage });
|
||||
|
||||
// Get optimized context for API
|
||||
const { messages, systemPrompt } = this.claude.getContextForAPI();
|
||||
|
||||
// ... call Claude API with messages ...
|
||||
const response = await this.callClaudeAPI(messages, systemPrompt);
|
||||
|
||||
// Add response to context
|
||||
this.claude.addMessage({ role: 'assistant', content: response });
|
||||
|
||||
return response;
|
||||
}
|
||||
|
||||
private async callClaudeAPI(messages: any[], systemPrompt?: string): Promise<string> {
|
||||
// Your Claude API implementation
|
||||
return "Response from Claude...";
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Example 3: Human-in-the-Loop Workflow
|
||||
|
||||
```typescript
|
||||
import { OpenClawIntegration } from './agent-system/integrations/openclaw';
|
||||
|
||||
const openclaw = new OpenClawIntegration();
|
||||
|
||||
const pipeline = openclaw.createPipeline({
|
||||
name: 'human-approval-workflow',
|
||||
states: [
|
||||
{
|
||||
name: 'draft',
|
||||
type: 'sequential',
|
||||
agents: ['coder'],
|
||||
transitions: [{ target: 'review', event: 'drafted' }]
|
||||
},
|
||||
{
|
||||
name: 'review',
|
||||
type: 'human-approval',
|
||||
agents: ['reviewer'],
|
||||
timeout: 86400000, // 24 hours
|
||||
transitions: [
|
||||
{ target: 'publish', event: 'approved' },
|
||||
{ target: 'draft', event: 'rejected' }
|
||||
]
|
||||
},
|
||||
{
|
||||
name: 'publish',
|
||||
type: 'sequential',
|
||||
agents: ['executor'],
|
||||
transitions: []
|
||||
}
|
||||
]
|
||||
});
|
||||
|
||||
await openclaw.startPipeline(pipeline.id);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Project Structure
|
||||
|
||||
```
|
||||
├── agent-system/ # Context compaction system
|
||||
│ ├── core/
|
||||
│ │ ├── token-counter.ts # Token counting
|
||||
│ │ ├── summarizer.ts # LLM summarization
|
||||
│ │ ├── context-manager.ts # Context compaction
|
||||
│ │ ├── orchestrator.ts # Agent orchestration
|
||||
│ │ └── subagent-spawner.ts # Subagent creation
|
||||
│ ├── agents/
|
||||
│ │ ├── base-agent.ts # Base agent class
|
||||
│ │ └── task-agent.ts # Task-specific agent
|
||||
│ ├── integrations/
|
||||
│ │ ├── claude-code.ts # Claude Code integration ✅
|
||||
│ │ └── openclaw.ts # OpenClaw integration ✅
|
||||
│ ├── storage/
|
||||
│ │ └── memory-store.ts # Persistent storage
|
||||
│ ├── utils/
|
||||
│ │ └── helpers.ts # Utility functions
|
||||
│ └── index.ts # Main exports
|
||||
│
|
||||
├── pipeline-system/ # Deterministic pipeline system
|
||||
│ ├── core/
|
||||
│ │ └── state-machine.ts # State machine
|
||||
│ ├── engine/
|
||||
│ │ └── parallel-executor.ts # Parallel execution
|
||||
│ ├── events/
|
||||
│ │ └── event-bus.ts # Event coordination
|
||||
│ ├── workspace/
|
||||
│ │ └── agent-workspace.ts # Workspace isolation
|
||||
│ ├── workflows/
|
||||
│ │ └── yaml-workflow.ts # YAML parser
|
||||
│ ├── integrations/
|
||||
│ │ └── claude-code.ts # Claude Code integration
|
||||
│ └── index.ts # Main exports
|
||||
│
|
||||
├── downloads/ # Zip packages
|
||||
│ ├── agent-system.zip
|
||||
│ ├── pipeline-system.zip
|
||||
│ └── complete-agent-pipeline-system.zip
|
||||
│
|
||||
└── README.md # This file
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Compaction Strategies
|
||||
|
||||
### 1. Sliding Window
|
||||
|
||||
Keeps the most recent N messages:
|
||||
|
||||
```typescript
|
||||
const contextManager = new ContextManager(tokenCounter, summarizer, {
|
||||
compactionStrategy: 'sliding-window',
|
||||
slidingWindowSize: 50 // Keep last 50 messages
|
||||
});
|
||||
```
|
||||
|
||||
### 2. Summarize Old
|
||||
|
||||
Summarizes older messages into a compact summary:
|
||||
|
||||
```typescript
|
||||
const contextManager = new ContextManager(tokenCounter, summarizer, {
|
||||
compactionStrategy: 'summarize-old',
|
||||
preserveRecentCount: 10 // Keep last 10 messages verbatim
|
||||
});
|
||||
```
|
||||
|
||||
### 3. Priority Retention
|
||||
|
||||
Keeps messages containing priority keywords:
|
||||
|
||||
```typescript
|
||||
const contextManager = new ContextManager(tokenCounter, summarizer, {
|
||||
compactionStrategy: 'priority-retention',
|
||||
priorityKeywords: ['error', 'important', 'decision', 'critical']
|
||||
});
|
||||
```
|
||||
|
||||
### 4. Hybrid (Recommended)
|
||||
|
||||
Combines all strategies for optimal results:
|
||||
|
||||
```typescript
|
||||
const contextManager = new ContextManager(tokenCounter, summarizer, {
|
||||
compactionStrategy: 'hybrid',
|
||||
slidingWindowSize: 30,
|
||||
preserveRecentCount: 10,
|
||||
priorityKeywords: ['error', 'important', 'decision']
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Contributing
|
||||
|
||||
Contributions are welcome! Please read our contributing guidelines before submitting PRs.
|
||||
|
||||
1. Fork the repository
|
||||
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
|
||||
3. Commit your changes (`git commit -m 'Add amazing feature'`)
|
||||
4. Push to the branch (`git push origin feature/amazing-feature`)
|
||||
5. Open a Pull Request
|
||||
|
||||
---
|
||||
|
||||
## License
|
||||
|
||||
MIT License - see [LICENSE](LICENSE) for details.
|
||||
|
||||
---
|
||||
|
||||
## Acknowledgments
|
||||
|
||||
- Inspired by [OpenClaw](https://github.com/ggondim/openclaw) and [Lobster](https://github.com/ggondim/lobster)
|
||||
- Architectural patterns from [How I Built a Deterministic Multi-Agent Dev Pipeline](https://dev.to/ggondim/how-i-built-a-deterministic-multi-agent-dev-pipeline-inside-openclaw-and-contributed-a-missing-4ool)
|
||||
- Claude Code integration patterns from Anthropic's documentation
|
||||
|
||||
---
|
||||
|
||||
## Support
|
||||
|
||||
For issues and feature requests, please use the [GitHub Issues](https://github.rommark.dev/admin/Agentic-Compaction-and-Pipleline-by-GLM-5/issues) page.
|
||||
|
||||
---
|
||||
|
||||
<div align="center">
|
||||
|
||||
**Built with ❤️ by [Z.AI GLM-5](https://z.ai/subscribe?ic=R0K78RJKNW)**
|
||||
|
||||
*100% Autonomous AI Development*
|
||||
|
||||
</div>
|
||||
Reference in New Issue
Block a user