What is Floword

Floword is a backend implementation designed for building workflows using natural language, enabling users to create and manage processes intuitively.

Use cases

Use cases for Floword include automating repetitive tasks, managing project workflows, and integrating with other applications to streamline processes.

How to use

To use Floword, install it using the recommended environment manager ‘uv’ or via Docker. Run the server with the command ‘uvx floword@latest strat’ or pull the Docker image with ‘docker pull ghcr.io/ai-zerolab/floword:latest’.

Key features

Key features of Floword include natural language processing for workflow creation, support for JWT authentication, and flexible configuration through environment variables.

Where to use

Floword can be used in various fields such as software development, project management, and automation, where workflow management is essential.

floword

Backend implementation for building workflow with natural language

• Github repository: https://github.com/ai-zerolab/floword/
• (WIP)Documentation https://ai-zerolab.github.io/floword/

Installation

We recommend using uv to manage your environment.

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh  # For macOS/Linux
# or
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"  # For Windows

Then you can use uvx floword@latest strat as commands for running the floword server.

Docker is also supported. You can use docker pull ghcr.io/ai-zerolab/floword:latest to pull the image from Github Container Registry.

(WIP) You can found deployment instructions in deploy directory.

Configuration

Via Environment Variables

You can use .env file or environment variables to configure floword. All environment variables should be prefixed with FLOWORD_ (case-insensitive).

Available options:

Authentication

• FLOWORD_JWT_SECRET_TOKEN: Secret token for JWT authentication. Default: None
• FLOWORD_ALLOW_ANONYMOUS: Allow anonymous access. Default: True

Database Configuration

• FLOWORD_SQLITE_FILE_PATH: Path to SQLite database file. Default: ./floword.sqlite (in current working directory)
• FLOWORD_USE_POSTGRES: Use PostgreSQL instead of SQLite. Default: False
• FLOWORD_PG_USER: PostgreSQL username. Default: postgres
• FLOWORD_PG_PASSWORD: PostgreSQL password. Default: postgres
• FLOWORD_PG_HOST: PostgreSQL host. Default: localhost
• FLOWORD_PG_PORT: PostgreSQL port. Default: 5432
• FLOWORD_PG_DATABASE: PostgreSQL database name. Default: floword

Streamer Configuration

• FLOWORD_REDIS_URL: Redis URL for streaming messages in distributed mode. Default: None

Model Configuration

• FLOWORD_DEFAULT_MODEL_PROVIDER: Default LLM provider. Default: openai
• FLOWORD_DEFAULT_MODEL_NAME: Default model name. Default: None
• FLOWORD_DEFAULT_MODEL_KWARGS: Additional arguments for the model (as JSON string). Default: None
• FLOWORD_DEFAULT_CONVERSATION_SYSTEM_PROMPT: Default system prompt for conversations. Default: Content from floword/prompts/system-conversation.md
• FLOWORD_DEFAULT_WORKFLOW_SYSTEM_PROMPT: Default system prompt for workflows. Default: Content from floword/prompts/system-workflow.md

Config MCP Server

Use FLOWORD_MCP_CONFIG_PATH to specify the path to the MCP configuration file. Default: ./mcp.json (in current working directory)

The MCP configuration file should be a json file with the following structure:

{
  "mcpServers": {
    "zerolab-toolbox": {
      "args": [
        "mcp-toolbox@latest",
        "stdio"
      ],
      "command": "uvx",
      "env": {
        "FIGMA_API_KEY": "your-figma-api-key"
      }
    },
    "sse-server": {
      "url": "http://localhost:8000",
      "headers": {},
      "timeout": 5,
      "sse_read_timeout": 300
    }
  }
}

Development

Local Setup

Fork the repository and clone it to your local machine.

# Install in development mode
make install
# Activate a virtual environment
source .venv/bin/activate  # For macOS/Linux
# or
.venv\Scripts\activate  # For Windows

Running Tests

make test

Running Checks

make check

Building Documentation

make docs

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the terms of the license included in the repository.