AI-6

Agentic AI focused on ubiquitous tool using.

The current implementation is in Python. check out the py directory.

There may be implementations in other languages too, in the near future.

See this link for a super-deep dive into the project.

LLM Access

Obviously, it delegates all the heavy lifting to an LLM provider. At the moment it is OpenAI-compatible or Ollama local models.

For OpenAI-compatible LLM providers the environment variable OPENAI_API_KEY must be set.

Installation & Usage

Option 1: Install from PyPI (Easiest)

pip install ai-six

# Use in Python code
from ai_six.agent import Agent

Option 2: Development Setup

Using uv (recommended for development):

cd py/
uv sync --dev
# Run CLI frontend
uv run python -m frontend.cli.ai6 --help

Note: Run uv lock after dependency changes to maintain reproducible builds.

Option 3: Traditional Development Setup

After you activate the virtualenv and install the dependencies, you can run an AI-6 frontend using the startup script (ai6.sh).

Example — Run the CLI frontend:

./ai6.sh cli

Building and Publishing the Package

To build the Python package for distribution:

cd py/
uv build

This creates distribution files in py/dist/:

• ai_six-*.whl (wheel distribution)
• ai_six-*.tar.gz (source distribution)

Publishing to PyPI

Publishing is handled automatically by GitHub Actions when you push a version tag:

git tag v1.0.0
git push origin v1.0.0

This triggers the workflow that builds and publishes the package to PyPI.

One-time setup: Add PYPI_API_TOKEN to repository secrets in GitHub.