bolt.diy

Categories: Coding & Developer Tools, Automation / Agents, Productivity | Pricing: Free | Official Website ↗

An open-source AI coding assistant that allows users to prompt, run, edit, and deploy full-stack web applications using various LLMs.

bolt.diy is an open-source AI coding assistant designed for full-stack web development, primarily for NodeJS-based applications. It operates directly in the browser and offers extensive flexibility by supporting over 19 different Large Language Models (LLMs), with an architecture that allows for easy integration of additional models via the Vercel AI SDK. Users can attach images to prompts for enhanced contextual understanding, revert code to earlier versions for debugging, and download projects as ZIP files for portability. The platform includes an integrated terminal for viewing command outputs, Docker support for isolated environments, and direct deployment options to Netlify, Vercel, or GitHub Pages. It also features an Electron desktop app for a native experience, data visualization tools, Git integration, and a file locking system to prevent conflicts during AI code generation. The project is a community effort, with ongoing developments like enhanced file locking, a backend agent architecture, and VSCode integration.

Key Features

AI-powered full-stack web development
Support for 19+ LLM providers (extensible)
Image attachment to prompts
Integrated terminal
Code version reversion
Project download as ZIP
Docker support
Direct deployment to Netlify, Vercel, GitHub Pages

Pros

Supports a wide range of LLMs with an extensible architecture.
Offers multiple deployment options (Netlify, Vercel, GitHub Pages).
Provides a native desktop experience via an Electron app.
Includes essential developer tools like Git integration and a terminal.
Open-source and community-driven, allowing for customization and contributions.

Cons

Requires manual setup and configuration of API keys for LLM providers.
Installation involves command-line steps, which might be challenging for non-developers.
Relies on external LLM providers, potentially incurring separate costs.
Documentation might require technical understanding for full utilization.
Features like file locking and diff improvements are still in progress.

Use Cases

Generating full-stack web application code
Experimenting with different LLMs for coding tasks
Rapid prototyping of web applications
Learning and contributing to AI-powered developer tools
Deploying web projects directly from an AI assistant

Best For

Full-stack web developers
Developers experimenting with LLMs for code generation
Open-source contributors
Teams needing flexible AI coding assistants

Integrations: OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek

Platforms: Web, macOS, Windows, Linux

Watch demo on YouTube ↗

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