Common building blocks for creating AI agents.
Project description
agent-core
Common building blocks for creating AI agents.
Production-ready components for building AI agents, optimized across LLMs and providers. Uses InteropRouter as a unified AI model provider interface.
[!NOTE] This library is in early development and subject to change.
Getting Started
Installation
# With uv.
uv add agent-core-toolkit
# With pip.
pip install agent-core-toolkit
Optional Dependencies
For the web fetch tool:
uv add agent-core-toolkit[web]
# Run crawl4ai post-installation setup
crawl4ai-setup
Usage
Run the agent CLI.
uv run agent-core --prompt "Your prompt here" --working-dir /path/to/directory
With all options:
uv run agent-core --prompt "Your prompt here" --working-dir "/path/to/directory" --mode "permissive" --model "gpt-5.1-codex-max" --model-friendly-name "gpt-5.1-codex-max" --model-knowledge-cutoff "Sep 30, 2024" --timezone "America/New_York"
Or run with uvx:
uvx --from /path/to/agent-core agent-core --prompt "Your prompt here" --working-dir "/path/to/directory"
Development
Prerequisites
Setup
Create uv virtual environment and install dependencies:
uv sync --frozen --all-extras --all-groups
Set up git hooks:
prek install
To update dependencies (updates the lock file):
uv sync --all-extras --all-groups
Run formatting, linting, type checking, and tests in one command:
uv run ruff format && uv run ruff check --fix && uv run ty check && uv run pytest
Further Information
Project details
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