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Quick Start

Get Agentomics-ML running in under 5 minutes using pre-built Docker images.

Prerequisites

Steps

1. Clone the Repository

git clone https://github.com/BioGeMT/Agentomics-ML.git
cd Agentomics-ML

2. Create a .env File and Set a Key

Docker mode requires a .env file in the repo root.

cp .env.example .env
# Edit .env and set at least one API key:
# OPENROUTER_API_KEY or OPENAI_API_KEY

3. Run the Agent

./run.sh --pull-images

The --pull-images flag automatically downloads pre-built Docker images from Docker Hub, which is the fastest way to get started.

4. Follow the Interactive Prompts

The agent will prompt you to:

  1. Select a model - Choose from available LLMs
  2. Select a dataset - Use your own or download examples
  3. Configure iterations - How many optimization cycles to run
  4. Choose validation metric - see ./run.sh --list-metrics

Using Your Own Dataset

Place your data in datasets/<your_dataset_name>/:

datasets/my_dataset/
├── train.csv           # Required: training data
├── validation.csv      # Optional: validation data
├── test.csv            # Optional: hidden test set
└── dataset_description.md  # Optional: domain context

See Preparing Datasets for details.

Example Datasets

Download example datasets to try:

./download_example_datasets.sh

What Happens Next

The agent will:

  1. Prepare your dataset
  2. Run iterative ML development cycles
  3. Save the best model to outputs/<agent_id>/

Results include trained models, inference scripts, and detailed reports in outputs/<agent_id>/reports/, plus PDF reports in outputs/<agent_id>/pdf_reports/.

Next Steps