실제로 생산에서 일하는 AI 대리인을 건설하는 생산 ready 기구.

⭐ 빠른 시작

먼저 copier을 설치해야 합니다. 우리는 uv (https://docs.astral.sh/uv/getting-started/installation/#installation-methods):)로 그것을 할 것을 제안합니다

[!팁] uvx] 앞에 copier copy] 명령어를 사용할 수도 있습니다.

이 템플릿을 사용하려면, 실행:

대신 $TARGET_DIRECTORY] 디렉토리 이름을 입력하면 프로젝트를 생성할 수 있습니다. 직접 경로를 사용할 수 있습니다.

[! 중요]

• copier copy DOESN’T create new directory, 그냥 복사 파일을 $TARGET DIRECTORY
• 최신 버전에서 버전을 복사합니다
• 최신 공개 된 커밋에서 fetch를 원하면 flag -r HEAD]를 사용하십시오. (또한 원격 이름을 받아들입니다)

이미 만든 프로젝트 및 템플릿이 업데이트되면 프로젝트를 업데이트 할 수 있습니다.

[! 중요]

• HAS는 이 명령을 사용하기 위해 git repo가 될 것입니다.
• omit --defaults flag, 답변 업데이트하려는 경우 ([T9]])
• 당신은 또한 플래그를 사용할 수 있습니다 -r 해제 된 버전에서 템플릿 버전으로 업데이트

선택 추가 기능

Python AI Kit

A production-ready framework for building AI agents that actually work in production.

🚀 Quick Start

First, you need to have copier installed. We suggest to do it with uv (https://docs.astral.sh/uv/getting-started/installation/#installation-methods):

uv tool install copier

[!TIP] You can also just use uvx before copier copy command if you don’t want to install this tool.

To use this template, run:

copier copy https://github.com/the-momentum/python-ai-kit $TARGET_DIRECTORY --trust
# uvx copier copy https://github.com/the-momentum/python-ai-kit $TARGET_DIRECTORY --trust

Instead of $TARGET_DIRECTORY put directory name where you want to generate your project. You can use indirect path.

[!IMPORTANT]

• copier copy DOESN’T create new directory, it just copies files to $TARGET_DIRECTORY
• it will copy version from latest release
• if you want to fetch from latest unreleased commit, use flag -r HEAD (also accepts remote branches names)

If you’ve already created project and templates get updated, you can still update your project:

copier update --trust --defaults
# run this inside ypur project directory

[!IMPORTANT]

• your project HAS to be a git repo in order to use this command
• omit --defaults flag, if you want to update answers (like python_versions)
• you can also use flag -r here to update with template version from unreleased versions

🔧 Optional add-ons

Some setup options require extra tools to be installed beforehand. If you skip them, the template will fail when that option is selected.

DVC (Data Version Control)

• Requires: dvc installed (e.g. uv tool install dvc) and, when enabled, AWS CLI with a profile that has access to your DVC S3 bucket.
• During setup: You can enable DVC when prompted; you will then provide the full S3 path (starting with s3://) for the remote and the AWS region.
• After generation: Set your AWS profile locally in the project root (stays out of Git):
  dvc remote modify --local profile (use the remote name you chose during setup)

Features

Core Framework

• Multi-agent orchestration - Built-in support for coordinating multiple specialized agents with defined workflows and error handling
• State management - Persistent memory across sessions using dedicated database storage and thread preservation
• Observability by default - Integrated logging, tracing, and monitoring with Pydantic Logfire or Opik
• Structured prompt management - Modular, versioned prompts with POML patterns instead of monolithic strings

Development & Testing