mini-pi 0.2.0

A minimal AI coding agent — built from scratch for learning

mini-pi

A minimal AI coding agent, built from scratch for learning how AI coding agents work.

Inspired by pi.

Architecture

mini-pi/
├── main.py                      # Entry point
├── pyproject.toml                # Project config & dependencies
├── AGENTS.md                     # Project memory (for AI agents)
├── docs/
│   └── ROADMAP.md               # 7-phase development plan
└── src/mini_pi/
    ├── types.py                 # Core type definitions (messages, tools, events)
    ├── llm/
    │   └── client.py            # DeepSeek/OpenAI-compatible LLM client with streaming & tool calling
    ├── tools/
    │   ├── base.py              # Tool base class & registry
    │   ├── read.py              # Read files (text & images)
    │   ├── bash.py              # Execute shell commands
    │   ├── write.py             # Create/overwrite files
    │   └── edit.py              # Precise text replacement editing
    ├── agent/
    │   └── loop.py              # Core agent loop (LLM ↔ tools)
    └── cli.py                   # CLI entry point

Components

1. Types (types.py)

Core data structures: Content blocks (text, image, thinking, tool_call, tool_result), Messages (User, Assistant, ToolResult), Tool definitions with JSON Schema, Usage tracking.

2. LLM Client (llm/client.py)

• Uses OpenAI SDK, defaulting to DeepSeek API
• Converts internal message format to OpenAI-compatible format
• Handles tool call streaming (accumulates partial function arguments)
• Tracks token usage

3. Tools (tools/)

• read: Read files (text with offset/limit, images as base64)
• bash: Execute shell commands with timeout & output truncation
• write: Create/overwrite files (auto-creates parent dirs)
• edit: Precise text replacement with validation (no-overlap, uniqueness checks)

4. Agent Loop (agent/loop.py)

The core agentic pattern:

User prompt → LLM (with tools) → Tool calls? → Execute → Repeat
                                → No tool calls? → Done

5. CLI (cli.py)

• Single-prompt mode: mini-pi "List all Python files"
• Interactive mode: mini-pi -i (multi-turn conversation)
• Bash shortcut: !ls to run commands directly

Roadmap

See docs/ROADMAP.md for the full development plan across 6 phases.

Installation

For users (recommended)

# Via uv tool (fast, isolated environment)
uv tool install mini-pi

# Or via pipx
pipx install mini-pi

# Or via pip
pip install mini-pi

For development

git clone https://github.com/YOUR_USERNAME/mini-pi.git
cd mini-pi
uv sync

Setup

# Set your DeepSeek API key
export DEEPSEEK_API_KEY=sk-...

# Run
mini-pi "What files are in the current directory?"

# Interactive mode
mini-pi -i

# Or use any OpenAI-compatible API
mini-pi -m gpt-4o -b https://api.openai.com/v1

Learning Path

This project implements the core of what makes pi tick:

1. LLM Client - How to talk to LLM APIs with tool calling
2. Agent Loop - The fundamental agentic pattern
3. Tools - File I/O, bash execution, precise editing
4. Streaming - Real-time response streaming

See docs/ROADMAP.md for planned features across 6 phases.