Lambda Agent

A minimal, function-driven AI coding assistant built for speed and simplicity.

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Overview

Lambda is a lightweight, command-line AI coding agent driven by Google's Gemini models. Unlike massive IDE extensions or bloated web setups, Lambda lives right in your terminal. It uses a ReAct (Reasoning and Acting) loop to autonomously navigate your codebase, read and write files, run shell commands, and orchestrate complex coding tasks from a single prompt.

With a beautiful UI powered by Rich, Lambda makes pair programming with AI feel fast, natural, and highly contextual.

Key Features

• Autonomous Tool Execution: Powered by Gemini's function calling, Lambda can read_file, write_file, search_repo, and run_command directly on your host machine to get things done.
• Parallel Sub-Agents: Delegate independent tasks (like extensive code analysis or small edits) to parallel background threads using dispatch_subagent.
• Agentic Scratchpad: Lambda uses a hidden local scratchpad (.scratchpad/) to draft implementation plans, think through complex logic, and maintain context across long execution chains.
• Stunning CLI Experience: Built with Rich, featuring distinct conversational bubbles, syntax highlighting, active token monitoring, and beautiful live spinners.
• Hot-Swappable Models: Instantly switch between different Gemini models mid-conversation using the /models slash command.
• Zero-Friction Configuration: Global configurations (~/.config/lambda-agent/config.env) mean you can run lambda in any directory on your machine instantly.

Installation

Requires Python 3.10+. Install Lambda directly from PyPI:

pip install lambda-agent

For local development, clone the repository and run pip install -e . instead.

Usage

Spin up the agent from any directory simply by running:

lambda

First-Time Setup

On your first run, Lambda will securely prompt you for your Gemini API Key and model preference. This is saved to ~/.config/lambda-agent/config.env.

Note: You can override global settings by placing a .env file in your specific project directory.

Built-in Slash Commands

During your interactive session, you can use the following commands:

• /models — Display a menu to hot-swap your active AI model (e.g., from Gemini Flash to Pro).
• /config — Quickly update your API key mid-session.
• /help — List all available slash commands.
• exit or quit — End the session and review your total token usage.

Under the Hood

Lambda acts autonomously using an extensible set of Python tools:

• search_repo(query, path): Deep file inspection ignoring .git, .venv, and binary caches.
• run_command(command): Real shell execution (with 30s timeout guards).
• dispatch_subagent(task): Parallelize isolated tasks via lightweight background Gemini sessions.
• ask_user(question): Ability to explicitly pause and ask the human for clarification.
• read_file, write_file: Direct file manipulations.
• Scratchpad API: read_scratchpad, write_scratchpad, append_scratchpad for planning.

Contributing

Contributions make the open-source community an amazing place to learn and build!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License & Attribution

Distributed under the Apache 2.0 License. See LICENSE for more information.

• Engine powered by Google GenAI SDK.
• Lambda icon by shohanur.rahman13 from Flaticon