Containerized AI Development: Take Control with Docker and VS Code

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.agents/skills/convert-with-markitdown

.agents/skills/convert-with-markitdown

.claude/skills

.claude/skills

.devcontainer

.devcontainer

.vscode

.vscode

bin

bin

doc

doc

etc

etc

var

var

.dockerignore

.dockerignore

.gitignore

.gitignore

AGENTS.md

AGENTS.md

Dockerfile

Dockerfile

LICENSE

LICENSE

LOG.md

LOG.md

README.md

README.md

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This repository is a template to govern your AI chats with more grip than usual. It leverages PI.dev coding agent and an aggressive isolation done with Docker + VS Code (Works on Linux and MacOS)

Folder Structure:

. |-- .devcontainer <- Visual studio code dev container |-- bin/runInContainer.sh <- Zero lockin launcher for running outside vscode ├── LICENSE ├── README.md ├── etc <- scripts used to setup your environment └── var <- Contains configuration not meant to be versioned ├── pi-agent <- Contains pi.dev configuration │   └── models.json <- Models to be configured └── pi-sessions <- Contains pi.dev session

Basic principles:

Isolated Dev container for stronger security

pi.dev installation retain sessions and config inside the var directory

Minimalistic setup + non root user

As bonus, claude code and copilot installation sharing the home (and potentially the auth of both) Claude code is only tested with deepseek integration (see deep seek manual, use env variable in your devcontainer.env)

Getting started

Clone or fork this project and use as template

Define a .devcontainer/devcontainer.env with all your API keys (i.e. DeepSeek, Claude etc) if you have already This file is common to all the containerized approaches

Three options:

run Visual Studio Code DevContainer mode. If so:

Review .devcontainer/devcontainer.json

run ./bin/runInContainer.sh to get a throwaway container on the command line If you do not have claude code installed, use this method to ensure some empty folder are created

Use without container (but please avoid pi.dev in this scenario)

Using pi.dev

Pi.dev is fantastic because it never will ask for command confirmation: but it is also a risk.

Once you have your terminal, install your Pi.dev's preferred extensions (you need to do this just once): For instance try

pi install git:github.com/jonjonrankin/pi-caveman pi install npm:pi-subagents

The extensions will be stored in the var/pi-agent subdirectory (see above). After that, you can use pi.dev as you wish. Our suggestion is to get accustomed to pi.dev with a short session, then you can look forward on the chapter included in the doc directory like SUBAGENTS (this part is a Work in progress WIP).

Provided Skills [WIP]

A compact and curated list of skills is provided. Main goal is to readuce tokens:

AGENTS.md provide usage of rtk tool

Under .agents (symlinked to .claude for ClaudeCode) a mark-it-down converter is provided, to convert documents in a more compact and mangeable form.

Template projects [WIP]

Also, this project has some ad hoc variants under the feature/ branches including:

feature/java for JAVA setup

feature/ai-sdlc-copilot Based on https://github.com/awslabs/aidlc-workflows#github-copilot

feature/ai-sdlc-pi Based on https://github.com/awslabs/aidlc-workflows#github-copilot

feature/crc-cards-pi

Very experimental super-light workflow based on CRC cards

About

Take AI Control back template repository.

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License

MIT license

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