open-edge-platform/skills

chatqna-docker-deploy

Deploy Chat Question-and-Answer Core with Docker Compose (OpenVINO CPU, OpenVINO GPU, or Ollama CPU), including env setup, profile selection, startup verification, health checks, and teardown. Use this skill when the user says "deploy chatqna core", "start chatqna container", "run compose", "openvino gpu deploy", or "ollama deploy". Canonical deploy sources are docker/compose.yaml (services and image names) and scripts/setup_env.sh (runtime profile export); Makefile is not the source of truth.

First seen Aug 19, 2026

Installation

$ npx skills add open-edge-platform/skills --skill chatqna-docker-deploy

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Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0
LicenseApache-2.0
More metadata
version
1.0.0
tags
chatqna deploy docker compose openvino ollama gpu cpu

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 11,789 B
  • docs SUMMARY.md 527 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 14 installs

SKILL.md

<!-- SPDX-FileCopyrightText: (C) 2026 Intel Corporation SPDX-License-Identifier: Apache-2.0 -->

ChatQnA Docker Deploy

Deploy the Chat Question and Answer Core sample application as containers using Docker Compose.

Environment setup (run first)

This skill operates on real ChatQnA source files, so the ChatQnA application must be present and commands must run from the app root. Do this before any deploy workflow, whether or not source is already in your workspace.

Run the bundled bootstrap. It searches for an existing ChatQnA checkout by walking up from the current directory and checking the enclosing git repo, then reuses it without re-cloning. Only when no checkout is found does it do a shallow, single-branch, sparse checkout of just sample-applications/chat-question-and-answer-core from main.

It prints the resolved app root on stdout:

# SKILL_DIR is this skill directory. In-repo it is:
# .github/skills/chatqna-docker-deploy
SKILL_DIR=".github/skills/chatqna-docker-deploy"
APP_ROOT="$(bash "$SKILL_DIR/scripts/chatqna-bootstrap.sh")"
cd "$APP_ROOT"

Every command below assumes the working directory is this APP_ROOT.

To use a fork/branch or a specific clone path, override these before running the bootstrap script:

  • CHATQNAREPOURL
  • CHATQNAREPOBRANCH
  • CHATQNACLONEDIR
  • CHATQNAFORCECLONE (set to 1 to force clone)

Codebase root: sample-applications/chat-question-and-answer-core/

What This Skill Produces

  • A running ChatQnA Core deployment on one backend profile:

- OpenVINO CPU (OPENVINO) - OpenVINO GPU (OPENVINO-GPU) - Ollama CPU (OLLAMA)

  • A verified startup state using container status, logs, and health endpoint.
  • A concise deployment report containing:

- runtime profile selected - image source used (prebuilt tags or locally built) - whether pinned default tags or user-provided tags were used - access URL and API docs URL - any warnings (token/model/device constraints)

When to Use

  • "Deploy chat question and answer core"
  • "Start chatqna containers"
  • "Run docker compose for chatqna"
  • "Deploy OpenVINO GPU profile"
  • "Deploy ollama backend"

Inputs To Confirm

Before running commands, confirm or infer these values:

  1. Backend/runtime: openvino or ollama
  2. Device: cpu or gpu (GPU valid only for OpenVINO)
  3. Image source:

- prebuilt registry images (REGISTRY, BACKENDTAG, UITAG), or - local source builds (tags usually latest)

  1. Optional model config path: MODELCONFIGPATH
  2. Optional Hugging Face token for private/gated models: HUGGINGFACEHUBAPITOKEN

If runtime/device values are missing, default to openvino + cpu, proceed directly with OpenVINO CPU using source scripts/setup_env.sh.

If prebuilt images are used and tags are not specified by the user, default to pinned release tags.

Use Docker Compose commands only for deployment actions in this skill. Always use the repository compose file path docker/compose.yaml. Do not substitute docker-compose.yml and do not use placeholders such as <compose-file>.

Defaulting Rule (Mandatory)

For prompts like "Deploy chatqna core with docker compose" where runtime or device is omitted:

  1. Assume backend=openvino and device=cpu.
  2. Run the standard preflight checks.
  3. Select profile with source scripts/setup_env.sh.
  4. Start with docker compose -f docker/compose.yaml up -d.
  5. Verify with docker compose -f docker/compose.yaml ps,

docker compose -f docker/compose.yaml logs --tail=150, and health check on /v1/chatqna/health.

Decision Logic

  • If backend is ollama:

- force CPU path - use source scripts/setup_env.sh -b ollama

  • If backend is openvino and device is gpu:

- use source scripts/setup_env.sh -d gpu - if /dev/dri/render* does not exist, warn and fall back to CPU path

  • Else:

- use source scripts/setup_env.sh (OpenVINO CPU)

Deployment Workflow

Run from sample-applications/chat-question-and-answer-core.

1. Preflight

docker --version
docker compose version

If prebuilt images are requested and the user did not provide tags, use the following as defaults:

export REGISTRY="intel/"
export BACKEND_TAG="core_2026.2.0-rc2"      # or core_gpu_2026.2.0-rc2 / core_ollama_2026.2.0-rc2
export UI_TAG="core_2026.2.0-rc2"

These variable names must match docker/compose.yaml exactly:

  • REGISTRY
  • BACKEND_TAG
  • UI_TAG

Do not use other variable names other than REGISTRY, BACKENDTAG, and UITAG for this workflow. Do not use a generic TAG variable for this workflow. Do not default to latest when tags are omitted.

If the user explicitly provides different tags or registry, use those values instead of the pinned defaults.

Optional model config override:

export MODEL_CONFIG_PATH="/absolute/path/to/config.yaml"

Optional gated/private model token:

export HUGGINGFACEHUB_API_TOKEN="<token>"

For gated/private models, use the variable name exactly as above. Do not replace it with HF_TOKEN in this skill.

2. Select Profile and Export Environment

Choose exactly one:

# OpenVINO CPU (default)
source scripts/setup_env.sh

# OpenVINO GPU
source scripts/setup_env.sh -d gpu

# Ollama CPU
source scripts/setup_env.sh -b ollama

3. Start Containers

Default startup mode is detached:

docker compose -f docker/compose.yaml up -d

4. Verify Deployment

docker compose -f docker/compose.yaml ps
docker compose -f docker/compose.yaml logs --tail=150
curl -sf "http://${HOST_IP:-127.0.0.1}:8102/v1/chatqna/health"
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "http://${HOST_IP:-127.0.0.1}:8102/v1/chatqna/health"

When handling a deploy request, include raw command output in the response as evidence:

  • docker compose -f docker/compose.yaml ps output showing expected services

as Up.

  • Health check output and HTTP status from:

curl -sS -w "\nHTTPSTATUS:%{httpcode}\n" "http://${HOST_IP:-127.0.0.1}:8102/v1/chatqna/health";

Expected readiness indicators:

  • backend container is running
  • UI container is running
  • nginx container for selected profile is running
  • health endpoint returns success

Access ChatQnA application:

  • To access the ChatQnA UI: http://<HOST_IP>:8102 or http://localhost:8102
  • To access the ChatQnA API docs: http://<HOST_IP>:8102/v1/chatqna/docs or http://localhost:8102/v1/chatqna/docs

5. Stop or Reset

# Stop and remove service containers
docker compose -f docker/compose.yaml down

# Evidence: show running containers after shutdown
docker ps

When handling a stop request, include the exact docker ps output in the response as evidence that containers are terminated.

Expected evidence for a fully stopped state:

CONTAINER ID   IMAGE     COMMAND   CREATED   STATUS    PORTS     NAMES

The deep cleanup command below (down -v --remove-orphans) exists only for requests that explicitly ask for volume/orphan removal or a full reset/teardown. For a plain stop request, leave it out of the response entirely — do not run it, print it, or add a note explaining that it was skipped; a plain stop only needs the down and docker ps commands above.

# Optional deep cleanup (only when explicitly requested)
docker compose -f docker/compose.yaml down -v --remove-orphans

Failure Handling

  • setup_env.sh returns unsupported backend/device:

- restrict backend to one of: openvino or ollama - restrict device to one of: cpu or gpu (GPU valid only for OpenVINO) - continue with at least one corrected invocation: - source scripts/setupenv.sh - source scripts/setupenv.sh -d gpu - source scripts/setup_env.sh -b ollama

  • GPU requested but no render node:

- continue with OpenVINO CPU and report fallback

  • container startup failure:

- collect docker compose -f docker/compose.yaml ps - collect docker compose -f docker/compose.yaml logs --tail=200 - identify and report the failing service name from compose status or logs - capture and report the first actionable error from logs

  • health check fails after startup:

- check backend container logs first, for example: docker compose -f docker/compose.yaml logs --tail=200 chatqna-backend-server - validate HOSTIP and selected runtime profile (openvino or ollama) - note that first startup can take longer due to model download or conversion - re-check health after stabilization: curl -sS -w "\nHTTPSTATUS:%{httpcode}\n" "http://${HOSTIP:-127.0.0.1}:8102/v1/chatqna/health"

Scenario-Specific Must-Include Commands

  • Deploy request with missing runtime/device:

- source scripts/setupenv.sh - docker compose -f docker/compose.yaml up -d - docker compose -f docker/compose.yaml ps - curl -sS -w "\nHTTPSTATUS:%{httpcode}\n" "http://${HOSTIP:-127.0.0.1}:8102/v1/chatqna/health"

  • OpenVINO GPU deploy request:

- source scripts/setupenv.sh -d gpu - check /dev/dri/render*; if missing, fall back to source scripts/setupenv.sh - docker compose -f docker/compose.yaml up -d

  • Ollama deploy request:

- state Ollama path is CPU-only in this skill - source scripts/setup_env.sh -b ollama - docker compose -f docker/compose.yaml up -d

  • Prebuilt image tags request without tags:

- must use these exact variable names (REGISTRY, BACKENDTAG, UITAG) to set pinned defaults, not alternate names: - export REGISTRY="intel/" - export BACKENDTAG="core2026.2.0-rc2" (or runtime-specific pinned backend tag) - export UITAG="core2026.2.0-rc2" - do not use latest as the default when tags are omitted - use only REGISTRY, BACKENDTAG, and UITAG; do not replace them with other variable names - if user provides registry/tags, they override these defaults

  • Custom model config + token request:

- export MODELCONFIGPATH="/absolute/path/to/config.yaml" - export HUGGINGFACEHUBAPITOKEN="<token>" - valid profile selection via setup_env.sh - docker compose -f docker/compose.yaml up -d

  • Readiness evidence request:

- include raw outputs for ps, logs --tail=150, and health with HTTP_STATUS

  • Stop request:

- docker compose -f docker/compose.yaml down - include raw docker ps output as termination evidence - do not mention, run, or reference down -v --remove-orphans unless the user explicitly asks for deep cleanup/volume removal

Completion Criteria

  1. Requested runtime profile is started successfully.
  2. docker compose ps shows expected services running.
  3. Health endpoint responds at /v1/chatqna/health.
  4. User gets access URL, API docs URL, exact stop command, and the image tags used.
  5. For deploy requests, response includes raw docker compose ps output and

raw health-check output with HTTP_STATUS:200 as readiness evidence.

  1. For stop requests, response includes raw docker ps output as termination

evidence, and a fully stopped state matches: CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES