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MoFA on Dora-RS

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This guide explains how to install, deploy, and start the MoFA framework built on Dora-RS.

Getting Started

1. Installation

  1. Clone the project and switch to the specified branch:
git clone <repository-url> && git checkout <branch-name>

Example:

git clone git@github.com:moxin-org/mofa.git && cd mofa
  1. Use Python 3.10 or later:
  • If there's a version mismatch, reinstall the environment using conda. For example:
conda create -n py310 python=3.10.12 -y
  1. Set up the project environment:
  • Install the required dependencies:
cd python && pip3 install -r requirements.txt && pip3 install -e .

Once installed, you can use the command mofa --help to view CLI help information.

  1. Install Rust and Dora-RS:

Since the Dora-RS computing framework is built using Rust, visit the following page to install Rust for your operating system:

https://www.rust-lang.org/tools/install

Then, install Dora-CLI:

cargo install dora-cli --locked

2. Configuration

In the examples directory, we provide some available agent examples. Before use, you need to configure the .yml files in the configs directory of the agent. If the node was installed via pip, locate the node's name in the agent-hub and modify the .yml file accordingly.

Example of configuring the LLM inference API:

Using OpenAI API:

MODEL:
  MODEL_API_KEY:
  MODEL_NAME: gpt-4o-mini
  MODEL_MAX_TOKENS: 2048

You can also configure it to use the Ollama model or the local open-source model provided by Moxin:

Example using Ollama:

MODEL:
  MODEL_API_KEY: ollama
  MODEL_NAME: qwen:14b
  MODEL_MAX_TOKENS: 2048
  MODEL_API_URL: http://192.168.0.1:11434

3. Starting the Framework

Example: Starting the hello_world Agent in the examples directory:

  1. Navigate to the directory:

    Open the terminal, switch to the hello_world directory, and execute the following command:

    cd /mofa/python/examples/hello_world

  2. Build the Dataflow file:

    Open a new terminal window in the current directory and execute the following command to prepare and build the Dataflow:

    dora up && dora build dataflow.yml

    Here, dataflow.yml is the configuration file describing the Agent's execution flow.

  3. Start the Dataflow process:

    In the same terminal, start the Dataflow process:

    dora start dataflow.yml

  4. Handle dynamic nodes:

    If dataflow.yml specifies a node's path as dynamic (e.g., path: dynamic), you need to run that dynamic node in a separate terminal. Example: The node terminal-input is a dynamic node in the following configuration:

    nodes:
  - id: terminal-input
    build: pip install -e ../../node-hub/terminal-input
    path: dynamic
    outputs:
      - data
    inputs:
      agent_response: agent/agent_response

    For the above node, open a new terminal and run the following command to start the dynamic node:

    terminal-input

    This ensures terminal-input runs properly and sends/receives data as required.

4. Detailed Documentation

More detailed documentation is available in the documents subdirectory.