aiq-deploy

# AIQ Deploy Skill ## Purpose Use this skill to get a local or self-hosted NVIDIA AI-Q Blueprint server running and verified for use by `aiq-research`. This skill owns setup, deployment, operational checks, troubleshooting, and shutdown. It does not run deep research itself. After deployment is healthy, hand off the verified server URL to `aiq-research`. The workflow stays explicit so deployment validation and handoff are repeatable across supported agent clients. ## Prerequisites Users need: - Access to clone or update `https://github.com/NVIDIA-AI-Blueprints/aiq`. - Git available in the shell. - One deployment runtime: - Docker Engine with Docker Compose v2 for the default durable local deployment. - Python 3.11+ and `uv` for local process or CLI mode. - Node.js 20+ and `npm` for local browser UI development mode. - `kubectl` 1.28+, Helm 3.12+, and access to a Kubernetes cluster for Helm mode. - Network access to GitHub, NVIDIA-hosted model endpoints, and any selected search provider. - Credentials stored outside chat. Hosted-model usage requires `NVIDIA_API_KEY`; web research requires at least one supported search provider key such as `TAVILY_API_KEY`, `SERPER_API_KEY`, or `EXA_API_KEY`. - System capacity for the selected runtime. Docker Compose mode starts the AI-Q backend and PostgreSQL by default; browser UI mode also uses frontend port `3000`. Self-hosted model or RAG deployments may require GPU resources. Before writing secrets, verify `deploy/.env`...