Architecture Overview
This library, OpenCode, is designed to empower developers with AI-driven assistance directly within their terminal workflows. Its core value proposition lies in abstracting complex AI interactions into a user-friendly, terminal-first experience. Developers primarily interact with OpenCode through its opencode-ai SDK or its CLI Entry Point. The SDK exposes a programmatic interface for integrating OpenCode's AI capabilities into other applications, while the CLI serves as the direct gateway for users to invoke the agent, manage sessions, and leverage its features from the command line.
Under the hood, the opencode-ai core package acts as the central nervous system, orchestrating all AI interactions and managing agent states. This core relies heavily on the Agent Orchestration Engine to manage the lifecycle of specialized agents, such as 'build' and 'plan', ensuring they operate within defined scopes and permissions. Communication with various AI providers is abstracted through the AI Provider Abstraction directory, which is then managed by the AI Model Communication Handler. This modular approach allows the opencode-ai core to remain agnostic to the specific AI models being used, enhancing flexibility.
The data flow within OpenCode typically begins with a user input, processed either through the CLI Entry Point or the opencode-ai SDK. This input is then handed off to the opencode-ai core. The Agent Orchestration Engine determines which specialized agent should handle the request. This agent, in turn, uses the AI Provider Abstraction to communicate with an AI model via the AI Model Communication Handler. The raw output from the AI model is then parsed by the Language Model Response Parser to extract actionable information, which is finally processed by the opencode-ai core to generate a response or perform an action. The Console TUI package then renders this information back to the user in a visually intuitive format.
What makes OpenCode particularly noteworthy is its commitment to a terminal-first experience and its multi-agent architecture. The Console TUI provides a rich, Neovim-like interface, aiming for seamless integration into developer workflows. The architectural decision to use distinct agents like 'plan' (often in a read-only mode) highlights a focus on security and controlled AI execution. Furthermore, the Language Server Protocol (LSP) Integration allows OpenCode to leverage existing IDE tooling, enhancing its code intelligence capabilities without requiring developers to switch environments.
For developers looking to contribute, understanding the opencode-ai core package is paramount, as it houses the fundamental logic and agent management. The AI Provider Abstraction and Agent Management directories are key areas for extending AI model support or refining agent behaviors, respectively. Familiarity with the opencode-ai SDK is also essential for building integrations. The Configuration Management subsystem is crucial for understanding how users customize the agent's behavior, and the Language Model Response Parser is vital for grasping how AI outputs are translated into actionable commands.