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TokenRing Writer

A unified platform for writing and managing news articles & blog posts

TokenRing Writer (tr-writer) provides a powerful interface where you can create, edit, and publish content, leveraging AI to assist with writing, editing, formatting, and publishing workflows.

Features​

  • Agent-based architecture: Multiple specialized AI agents for different content creation tasks (writer, editor, researcher, publisher)
  • Interactive chat interface: Talk to agents in a conversational REPL for content creation assistance
  • Persistent content history: Sessions and content drafts are saved in a SQLite database
  • Command system: Issue commands prefixed with / to manage agents, content, and workflows
  • Publishing integration: Works directly with your content directory; can initialize with a TokenRing config
  • Multi-model support: Support for various AI models from different providers
  • Research capabilities: Built-in web search and Wikipedia integration for content research
  • File system integration: Direct integration with local and cloud file systems

Available Agents​

TokenRing Writer includes specialized AI agents for different content creation workflows:

  • Content Writer: Expert content writer specializing in creating engaging, well-structured articles and blog posts. Excels at research, storytelling, and adapting writing style to different audiences.
  • Managing Editor: Coordinates content creation by searching for trending news topics, evaluating newsworthiness, creating article assignments, and dispatching tasks to specialized writing agents.

Getting Started​

Quick Start (NPM)​

Run directly using npx without installation:

npx @tokenring-ai/writer --source ./path-to-your-content --initialize

Quick Start (Docker)​

Pull and run from GitHub Container Registry:

docker pull ghcr.io/tokenring-ai/writer:latest
docker run -ti --net host $(env | grep '_KEY' | sed 's/^/-e /') -v ./path-to-your-content:/repo:rw ghcr.io/tokenring-ai/writer:latest

Prerequisites​

  • Bun (for local development)
  • Git initialized content directory

Installation (local development)​

  1. Sync git submodules: This project uses git submodules that need to be initialized and updated before installation:

    git submodule update --init --recursive

  2. Install dependencies: This project uses Bun as the package manager in a monorepo structure:

    bun install

  3. Run the application: Use Bun to start the application:

    bun src/tr-writer.ts --source ./path-to-your-content

Installation (As local docker container)​

  1. Sync git submodules: This project uses git submodules that need to be initialized and updated before installation:

    git submodule update --init --recursive

  2. Build the docker container:

    # This command must be run in the root directory of the repo
    docker build -t token-ring/writer:latest -f docker/Dockerfile .

  3. Run the docker container:

    docker run -ti --net host $(env | grep '_KEY' | sed 's/^/-e /') -v ./:/repo:rw token-ring/writer:latest

Container Registry​

The Docker image is automatically built and published to GitHub Container Registry on version tags. Available tags:

  • latest: Latest stable release
  • v*.*.*: Specific version tags
  • main: Latest build from main branch
docker pull ghcr.io/tokenring-ai/writer:latest

Initialization​

To initialize your content directory with the necessary TokenRing configuration file, pass the --initialize flag after your content directory. This will initialize a new .tokenring directory in your project, which stores a writer-config.js config file for your project that you can customize, as well as a sqlite database which stores your content history.

tr-writer --source ./path-to-your-content --initialize

This copies a default .tokenring/writer-config.js into your content directory.

Chat and Commands​

Once started, you enter the agent chat REPL:

  • Type natural language queries to interact with AI agents for content creation
  • Use commands with / prefix, e.g., /help, /agent switch writer, /tools enable
  • Switch between different agents specialized for writing, editing, research, and publishing
  • Control commands: /quit to exit, /agent list to see available agents

Commands​

Some example commands:

  • /help: Show available commands
  • /agent list: List available agents
  • /agent switch <name>: Switch to a specific agent
  • /tools list: Show available tools
  • /tools enable <pattern>: Enable specific tools

Architecture​

  • CLI: Entry point with argument parsing and agent team initialization (tr-writer.ts)
  • Agents: Specialized AI agents for different content creation tasks (writer, editor, researcher, publisher)
  • Services: Core services for file system, web search, models, and database management
  • Configuration: Flexible configuration system supporting multiple models and services

Data Persistence​

Content data and sessions are stored in a SQLite database (writer-database.sqlite) managed through the Bun SQLite package.

Extensibility​

The system supports:

  • Custom agents: Define new agents with specific roles and capabilities
  • Multiple AI models: Support for various providers (OpenAI, Anthropic, Google, etc.)
  • Service providers: Pluggable services for file systems, web search, and content publishing
  • Tool integration: Extensible tool system for agent capabilities

Contributing​

Contributions are welcome! Feel free to fork the repository and submit pull requests.

License​

This project is MIT licensed

This documentation provides a high-level overview of the TokenRing Writer (tr-writer) functionality and usage. For detailed command usage, use /help inside the chat REPL.