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letscode

A minimal, OpenAI-compatible coding agent for the terminal — written in Python.

Point it at any OpenAI-API-compatible endpoint (Ollama, Fireworks, OpenRouter, vLLM, llama.cpp's llama-server, …) and get a streaming agent loop with the four tools that cover 95% of coding sessions — read, write, edit, bash — plus skills, slash commands, and a plugin system you can extend.

  • Get started in 60 seconds

    Install, set an API key, type a prompt.

    Getting started

  • Configure to your taste

    User and project TOML, env vars, CLI flags — predictable precedence.

    Configuration

  • Extend with plugins

    Pluggy + entry points. Bring your own tools, commands, skills, frontends.

    Plugin authoring

  • Understand the model

    Stable contracts, ten hooks, versioning rule, what's internal vs public.

    Extension model

What it is

A three-layer Python application: LLM client at the bottom (openai.AsyncOpenAI with base_url set), agent loop in the middle (event-driven async generator, parallel tool execution, hooks for everything), basic terminal frontend on top (prompt_toolkit + rich). Plugins extend any layer.

flowchart TD
    User[User input] --> Frontend
    Frontend[Basic TUI<br/>prompt_toolkit + rich] --> Agent
    Agent[Agent loop<br/>event-driven async] --> LLM
    LLM[LLM client<br/>OpenAI Chat Completions] --> Provider[(Any OpenAI-<br/>compatible<br/>endpoint)]
    Agent --> Tools[Built-in tools<br/>read · write · edit · bash]
    Plugins[(Pluggy + entry points)] -.extend.-> Tools
    Plugins -.extend.-> Frontend
    Plugins -.lifecycle hooks.-> Agent

What it isn't

Deliberate non-goals

  • Not a Claude Code competitor. Anthropic ships its own first-class harness; letscode is for people who want a small, hackable Python harness against whatever endpoint they prefer.
  • Not a framework. It's an application. The plugin system shapes this app; it isn't a library for building agents.
  • No subscription OAuth flows, no bespoke package manager, no permission popups, no built-in to-dos. See the full list.

Providers

letscode speaks the OpenAI Chat Completions wire format, so any endpoint that implements it works without per-provider code paths.

export OPENAI_API_KEY="sk-..."
letscode --model gpt-4o "your prompt here"

export OPENAI_BASE_URL="http://localhost:11434/v1"
export OPENAI_API_KEY="ollama"  # any non-empty string
letscode --model llama3.2 "your prompt here"

export OPENAI_BASE_URL="https://api.fireworks.ai/inference/v1"
export OPENAI_API_KEY="$FIREWORKS_API_KEY"
letscode --model accounts/fireworks/models/minimax-m2p5 "your prompt"

export OPENAI_BASE_URL="https://openrouter.ai/api/v1"
export OPENAI_API_KEY="$OPENROUTER_API_KEY"
letscode --model anthropic/claude-sonnet-4-5 "your prompt"

Works without changes against Groq, DeepSeek, Together, vLLM, LM Studio, xAI, Cerebras, Mistral, ZAI — anything OpenAI-compatible.

Status

Latest release: v0.3.0 — 2026-05-13. Extension model design + reference plugin + ergonomics. 549 tests passing, ruff + mypy --strict clean.

The roadmap tracks where the project is going. The lessons learned tracks what we've learned along the way.