open-foundry

Deploy your existing Pi, GitHub Copilot, OpenAI Codex, or OpenCode agent repo to Microsoft Foundry Hosted Agents — by adding 5 standard azd files, nothing else.

Your repo stays the source of truth. No private framework directory is installed. To stop using open-foundry, delete the 5 files and you're out.

How it works

open-foundry gives you two things:

1. Runtime images — containers that handle the Foundry Invocations protocol, harness lifecycle, sessions, streaming, and health checks.
2. A skill that adds the 5 azd files to your repo and runs azd deploy.

your-agent-repo/
  .agents/skills/, prompts/, mcp.config.json, workspace files   ← unchanged
  Dockerfile, azure.yaml, agent.yaml, agent.manifest.yaml, .dockerignore   ← added
                       │
                       ▼
        <harness>-foundry-runtime:<tag>   (image picks the harness)
                       │
                       ▼
         Microsoft Foundry Hosted Agents

The runtime image name selects the harness:

Image	Harness	Model auth
pi-foundry-runtime	Pi	API key or managed identity
ghcp-foundry-runtime	GitHub Copilot	API key only
codex-foundry-runtime	OpenAI Codex	API key only
opencode-foundry-runtime	OpenCode	API key only

Public images: ghcr.io/1openwindow/<image>:0.1.

Install the skill

npx skills add 1openwindow/open-foundry

Then, in an agent session inside your repo, just ask: "Deploy this agent to Foundry."

Quickstart

You need: azd ≥ 1.25.4 with the azure.ai.agents extension, a Foundry project, a container registry the project can pull from, and an OpenAI-compatible endpoint + model + API key.

SKILL=path/to/open-foundry/.agents/skills/open-foundry
IMAGE=ghcr.io/1openwindow/pi-foundry-runtime:0.1   # swap for the harness you want

node $SKILL/scripts/bootstrap.mjs     --agent-name <name> --runtime-image $IMAGE
node $SKILL/scripts/configure-env.mjs --env-name <env> --agent-name <name> --model <model> --base-url <url> --api-key-env OF_OPENAI_API_KEY \
                                      --acr <acr>.azurecr.io --foundry-project-endpoint <url> --azure-subscription-id <sub> --azure-location <region>
azd deploy
node $SKILL/scripts/verify.mjs

Notes:

• Deploy with azd deploy, not azd up — this is a thin layout with no infra/ to provision.
• The Pi runtime also supports keyless auth via OF_MODEL_AUTH=managed-identity; the others are API-key only.
• The skill ships no model, ACR, or endpoint defaults — you provide those per deployment.

Sample agent repos

Ready-made repos to try a deploy end-to-end:

• of-pi-agent — Pi
• of-ghcp-agent — GitHub Copilot
• of-codex-agent — OpenAI Codex
• of-opencode-agent — OpenCode

Runtime contract

The runtime image owns these environment variables (source of truth: src/contract.mjs):

Variable	Required when	Notes
OF_OPENAI_API_KEY / OF_OPENAI_BASE_URL / OF_OPENAI_MODEL	live (OF_MOCK!=1)	OpenAI-compatible triple
OF_MOCK	optional	1 = run without a real model (smoke test)
OF_MODEL_AUTH	optional	apikey (default) or managed-identity (Pi only)
HARNESS	baked into the image	do not set in azd env

Reserved (Foundry-owned, do not redefine): AGENT_*, FOUNDRY_* (except FOUNDRY_PROJECT_ENDPOINT). If the live triple is missing and OF_MOCK is unset, the runtime fails fast at startup. Inside the container, run open-foundry contract or open-foundry doctor.

Local development

npm test                                       # unit + SSE integration, no Docker
OF_MOCK=1 npm run start:backend                # local mock backend
npm run runtime:build && npm run runtime:smoke # build + smoke image (Docker)
npm run emit:contract                          # refresh skill's contract.json

Docs

• SKILL.md — skill behavior (canonical UX doc)
• DEPLOY.md — manual deploy primitives, verify, monitor, common failures
• docs/runtime-image.md — build / publish the runtime image
• docs/http-api.md — raw HTTP shape for direct callers