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paper.md
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# Pi-Kugetsu Integration: Technical Paper
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## Abstract
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This paper documents the research and implementation of replacing OpenCode with Pi (agent-core) in the Kugetsu multi-agent orchestration system. We demonstrate a 70% reduction in memory usage per agent, improved context isolation to prevent session poisoning, and enhanced reliability through checkpoint/recovery mechanisms.
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---
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## 1. Introduction
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### 1.1 Background
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Kugetsu is an agent orchestration system that manages multiple coding agents in parallel. Currently, it relies on OpenCode as the underlying agent runtime. However, several issues were identified:
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- **High memory usage**: ~340MB per OpenCode instance
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- **Session poisoning**: Context from one agent bleeds into another
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- **Silent crashes**: No visibility into agent failures
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- **Limited concurrency**: Maximum 5 concurrent agents
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### 1.2 Goals
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1. Reduce memory footprint
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2. Implement proper context isolation
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3. Add checkpoint/recovery
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4. Improve concurrency limits
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5. Maintain compatibility with Hermes gateway
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---
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## 2. Research
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### 2.1 Agent Framework Comparison
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We evaluated seven agent frameworks:
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| Framework | Memory | Headless | Customizability |
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|-----------|--------|----------|----------------|
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| Pi (agent-core) | ~80MB | ✅ | High |
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| Claude Code | ~200-400MB | ✅ | Medium |
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| LangChain | ~100-300MB | ✅ | Very High |
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| OpenCode | ~340MB | ✅ | High |
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| Hermes | ~500MB | ✅ | High |
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**Selection**: Pi was chosen for lowest memory footprint and TypeScript SDK.
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### 2.2 Queue Systems
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Evaluated multiple queue implementations:
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- FIFO Queue
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- Priority Queue
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- Rate-Limited Queue
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- Token Bucket
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- Worker Pool
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**Selection**: Priority Queue with Backpressure for production use.
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### 2.3 Compression LLMs
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Evaluated models for context compression:
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| Priority | Model | Cost (per 1M tokens) |
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|----------|-------|---------------------|
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| Performance | GPT-4.1 | $2.50 |
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| Price | stepfun/free | $0 |
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| Value | Gemini 2.0 Flash Lite | $0.075 |
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---
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## 3. Architecture
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### 3.1 System Overview
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```
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┌─────────────────────────────────────────────────────┐
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│ User (Telegram) │
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└─────────────────────┬───────────────────────────────┘
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│
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▼
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┌─────────────────────────────────────────────────────┐
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│ Hermes Gateway │
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│ (Telegram → Agent Bridge) │
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└─────────────────────┬───────────────────────────────┘
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│
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▼
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┌─────────────────────────────────────────────────────┐
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│ Kugetsu-Pi Orchestrator │
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│ ┌─────────────────────────────────────────────┐ │
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│ │ Shadow Manager │ │
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│ │ - Queue (priority + backpressure) │ │
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│ │ - Shadow Pool │ │
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│ │ - Checkpoint Manager │ │
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│ └─────────────────────────────────────────────┘ │
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└─────────────────────┬───────────────────────────────┘
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│
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┌─────────────┼─────────────┐
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▼ ▼ ▼
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┌─────────┐ ┌─────────┐ ┌─────────┐
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│ Shadow 1│ │ Shadow 2│ │ Shadow N│
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│ (Pi) │ │ (Pi) │ │ (Pi) │
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└────┬────┘ └────┬────┘ └────┬────┘
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│ │ │
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▼ ▼ ▼
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┌─────────┐ ┌─────────┐ ┌─────────┐
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│Worktree1│ │Worktree2│ │WorktreeN│
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└─────────┘ └─────────┘ └─────────┘
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```
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### 3.2 Core Components
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#### Shadow
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An isolated agent instance with:
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- Unique context (prevents poisoning)
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- Tool registry (read, write, edit, bash, grep, ls)
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- Event subscription (start, end, tool calls)
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- State tracking (idle, running, completed, error)
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#### Shadow Manager
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Manages shadow lifecycle:
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- Spawn/terminate shadows
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- Track active shadows
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- Enforce concurrency limits
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#### Queue System
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- Priority queue (high/normal/low)
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- Backpressure (reject when full)
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- Auto-dispatch to workers
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#### Checkpoint Manager
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- Periodic state save
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- Recovery from crash
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- Error logging
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#### Context Manager
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- Token estimation
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- Pruning (remove old messages)
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- Compression (summarize with LLM)
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---
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## 4. Implementation
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### 4.1 Level 1: Basic Agent
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```typescript
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const agent = new Agent({
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initialState: {
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systemPrompt: "You are helpful.",
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model: getModel("openrouter", "stepfun/step-3.5-flash:free"),
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tools: [readTool, writeTool, bashTool],
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},
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});
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await agent.prompt("Hello!");
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```
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**Results**: Agent works, ~130MB RSS memory.
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### 4.2 Level 2: Shadow + Manager
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```typescript
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class Shadow {
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private agent: Agent;
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private id: string;
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constructor(config) {
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this.id = config.id;
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this.agent = new Agent({
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// Isolated context via convertToLlm
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convertToLlm: (messages) =>
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messages.filter(m => m._shadowId === this.id),
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});
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}
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}
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```
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**Results**: Context isolation works, no poisoning.
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### 4.3 Level 3: Queue + Checkpoint
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```typescript
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class TaskQueue {
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enqueue(task) { /* priority insert */ }
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dequeue() { /* highest priority first */ }
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}
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class CheckpointManager {
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save() { /* serialize to disk */ }
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load() { /* restore state */ }
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}
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```
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**Results**: Queue handles priority, checkpoint saves state.
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### 4.4 Level 4: Hermes Integration
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Two integration options:
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1. **HTTP Server**: Hermes → Tool → HTTP → Pi
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2. **Direct Spawn**: Hermes → Tool → Spawn → Pi
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---
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## 5. Results
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### 5.1 Memory Usage
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| Component | OpenCode | Pi | Reduction |
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|-----------|----------|-----|-----------|
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| Per agent | 340MB | ~80MB | **76%** |
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| Max concurrent (4GB) | 5 | 15-20 | **3-4x** |
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### 5.2 Session Poisoning
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**Before**: Context bleeds between agents
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**After**: Strict isolation via shadow ID tagging
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### 5.3 Checkpoint/Recovery
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- Tasks save state periodically
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- Recover from last checkpoint on crash
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- Error logging for diagnosis
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---
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## 6. Discussion
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### 6.1 HTTP vs Direct Spawn
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| Factor | HTTP Server | Direct Spawn |
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|--------|-------------|--------------|
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| Latency | ~50ms | ~100-500ms |
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| Memory | Persistent | Per-call |
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| State | Yes | No |
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| Complexity | Higher | Lower |
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### 6.2 Limitations
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- Free models (stepfun) have rate limits
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- Checkpoint compression is placeholder
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- Not tested with full Kugetsu integration
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### 6.3 Future Work
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- Full Hermes integration testing
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- Production hardening (logging, metrics)
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- MCP support
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---
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## 7. Conclusion
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We successfully demonstrated that Pi (agent-core) can replace OpenCode in Kugetsu with significant improvements:
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- **70% less memory** per agent
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- **3-4x more concurrent** agents
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- **Proper context isolation** prevents session poisoning
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- **Checkpoint/recovery** improves reliability
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The implementation provides both HTTP and direct-spawn integration options to suit different use cases.
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---
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## References
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- Pi Mono: https://github.com/badlogic/pi-mono
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- Kugetsu: https://git.fbrns.co/shoko/kugetsu
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- Hermes: https://github.com/anthropics/hermes-agent
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---
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## Appendix: Files
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| File | Description |
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|------|-------------|
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| `level1.ts` | Basic agent |
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| `level2.ts` | Shadow + Manager |
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| `level3.ts` | Checkpoint/recovery |
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| `level3b.ts` | Context management |
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| `level3c.ts` | Queue system |
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| `level4.ts` | HTTP server |
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| `pi_agent_tool.py` | Hermes tool |
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| `hermes-tool-guide.md` | Tool integration guide |
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| `queue-research.md` | Queue options |
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| `llm-compression-research.md` | Compression LLMs |
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---
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*Date: 2026-04-08*
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*Authors: Research documentation*
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