# Runner-Pi Implementation Summary

## ✅ Completed

Successfully created `@bunny-agent/runner-pi` - a new runner implementation for Bunny Agent that uses the Pi agent framework.

### What Was Built

1. **packages/runner-pi/** - New package implementing Pi agent runtime
   - `src/pi-runner.ts` - Core runner implementation using `@earendil-works/pi-agent-core`
   - `src/index.ts` - Package exports
   - `package.json` - Dependencies: pi-agent-core, pi-ai
   - `tsconfig.json` - TypeScript configuration with declaration files

2. **apps/runner-cli/** - Updated to support Pi runner
   - Added `--runner pi` option
   - Added Pi runner case in `src/runner.ts`
   - Added Pi dependencies to `package.json`
   - Updated esbuild config to external Pi packages

### Architecture

```
User Command:
  npx bunny-agent run --runner pi -m "google:gemini-2.5-flash-lite-preview-06-17" -- "task"
                              ↓
runner-cli (apps/runner-cli/src/cli.ts)
  - Parses --runner flag
  - Validates runner type (claude, codex, copilot, pi)
                              ↓
runner.ts (apps/runner-cli/src/runner.ts)
  - Switch on runner type
  - Creates appropriate runner instance
                              ↓
runner-pi (packages/runner-pi/src/pi-runner.ts)
  - createPiRunner() factory function
  - Returns { run(input): AsyncIterable<string> }
                              ↓
Pi Agent Core (@earendil-works/pi-agent-core)
  - Agent class with event system
  - Subscribes to agent events
  - Converts to AI SDK UI format
                              ↓
Pi AI (@earendil-works/pi-ai)
  - Multi-provider LLM API
  - Supports Google, OpenAI, Anthropic, etc.
```

### Key Design Decisions

1. **Factory Pattern**: Used `createPiRunner()` instead of class export to match Claude runner's interface
2. **Event Streaming**: Pi Agent uses event-based architecture, converted to AI SDK UI stream format
3. **External Dependencies**: Pi packages marked as external in esbuild to avoid bundling issues
4. **TypeScript**: Standalone tsconfig with `skipLibCheck` to avoid dependency type errors

### API Compatibility

Pi Runner implements the same interface as Claude Runner:

```typescript
interface Runner {
  run(userInput: string): AsyncIterable<string>;
}
```

Output format: AI SDK UI stream (same as Claude runner)
- `0:` - Text chunks
- `9:` - Tool calls
- `a:` - Tool results  
- `d:` - Finish reason
- `3:` - Errors

### Environment Variables

Pi runner requires provider-specific API keys:
- `GEMINI_API_KEY` - For Google Gemini models
- `OPENAI_API_KEY` - For OpenAI models
- `ANTHROPIC_API_KEY` - For Anthropic models

### Testing

```bash
# Build
cd packages/runner-pi && pnpm build
cd apps/runner-cli && pnpm build

# Test (requires valid GEMINI_API_KEY)
export GEMINI_API_KEY="your-key"
npx bunny-agent run --runner pi -m "google:gemini-2.5-flash-lite-preview-06-17" -- "Say hello"
```

### Files Modified

1. `/home/kelly/Documents/projects/bunny-agent/packages/runner-pi/` (new)
   - `package.json`
   - `tsconfig.json`
   - `src/pi-runner.ts`
   - `src/index.ts`

2. `/home/kelly/Documents/projects/bunny-agent/apps/runner-cli/`
   - `package.json` - Added runner-pi dependency
   - `src/cli.ts` - Added "pi" to runner validation
   - `src/runner.ts` - Added Pi runner case

### Next Steps

1. **Add Tools**: Pi Agent supports custom tools - can add file operations, bash, etc.
2. **Add MCP Support**: Pi supports Model Context Protocol
3. **Add More Providers**: Pi supports OpenAI, Anthropic, Azure, etc.
4. **Documentation**: Add Pi runner docs to Bunny Agent website
5. **Tests**: Add unit tests for Pi runner

### Comparison: Pi vs Claude vs Gemini CLI

| Feature | Claude Runner | Pi Runner | Gemini CLI |
|---------|--------------|-----------|------------|
| **Provider** | Anthropic only | Multi-provider | Google only |
| **Models** | Claude 3/4 | Any (OpenAI, Anthropic, Google, etc.) | Gemini only |
| **Tools** | Built-in (file, bash, web) | Extensible | Built-in |
| **MCP** | Yes | Yes | Yes |
| **License** | Proprietary SDK | MIT | Apache 2.0 |
| **Complexity** | High (official SDK) | Medium (clean API) | High (monorepo) |
| **Integration** | ✅ Done | ✅ Done | ❌ Not started |

### Why Pi Was Chosen

1. **Multi-provider**: Supports Google, OpenAI, Anthropic, Azure, etc.
2. **Clean API**: Simple Agent class with event system
3. **TypeScript**: Easy to integrate with Bunny Agent
4. **MIT License**: Fully open source
5. **Modular**: Separate packages for AI, agent, TUI
6. **Active Development**: Regular updates from author

### Conclusion

Pi runner is now fully integrated into Bunny Agent's runner-cli. Users can choose between:
- `--runner claude` - Anthropic Claude (official SDK)
- `--runner pi` - Multi-provider (Google, OpenAI, Anthropic, etc.)
- `--runner codex` - OpenAI Codex (planned)
- `--runner copilot` - GitHub Copilot (planned)

This demonstrates Bunny Agent's pluggable architecture and ability to support multiple agent runtimes.
