AI Tools for Developers

Agentic AI workflows enabled by Docker containers.

Source for many experiments in our LinkedIn newsletter

Docker Desktop Extension: https://hub.docker.com/extensions/docker/labs-ai-tools-for-devs

VSCode Extension: https://github.com/docker/labs-make-runbook

What is this?

Project-First Design

To get help from an assistant in your software development loop, the only context necessary is the project you are working on.

Extracting project context

An extractor is a Docker image that runs against a project and extracts information into a JSON context.

Prompts as a trackable artifact

Prompts are stored in a git repo and can be versioned, tracked, and shared.

Dockerized Tools

OpenAI API compatiable LLM's already support function calling. This is our workbench to test the same spec, but with functions as Docker images. Some of the benefits using Docker based on our research are enabling the LLM to:

• take more complex actions
• deliver relevant context to the LLM without too many tokens
• work across a wider range of environments
• operate in a sandboxed environment

Get Started

Running a Conversation Loop

Set OpenAI key

echo $OPENAI_API_KEY > $HOME/.openai-api-key

Run

docker run 
  --rm \
  --pull=always \
  -it \
  -v /var/run/docker.sock:/var/run/docker.sock \
  --mount type=volume,source=docker-prompts,target=/prompts \
  --mount type=bind,source=$HOME/.openai-api-key,target=/root/.openai-api-key \
  vonwig/prompts:latest \
    run \
    --host-dir $PWD \
    --user $USER \
    --platform "$(uname -o)" \
    --prompts "github:docker/labs-githooks?ref=main&path=prompts/git_hooks"

See docs for more details on how to run the conversation loop, and especially how to use it to run local prompts that are not yet in GitHub.

PROMPTS KNOWLEDGE GRAPH

Building

#docker:command=build

docker build -t vonwig/prompts:local -f Dockerfile .