diff --git a/docs/docs/cogstack-ce/tutorial/end-to-end-jupyterhub.md b/docs/docs/cogstack-ce/tutorial/end-to-end-jupyterhub.md index b5678db..35b3402 100644 --- a/docs/docs/cogstack-ce/tutorial/end-to-end-jupyterhub.md +++ b/docs/docs/cogstack-ce/tutorial/end-to-end-jupyterhub.md @@ -10,6 +10,11 @@ By the end, you will have completed an end-to-end user flow: 4. Run cells that call MedCAT and AnonCAT service APIs 5. Inspect the outputs +!!! tip + The following tutorial will use your CogStack CE installation and let you run real code against your environment. + + To see a non-interactive version of the tutorial notebook, refer to [the MedCAT Service Tutorial notebook](../../platform/cogstack-ai/medcat-service-tutorial.ipynb). + ## Before you start Make sure your CogStack CE release is installed and local port-forwarding is running. diff --git a/docs/docs/platform/deployment/helm/charts/cogstack-ce-helm.md b/docs/docs/platform/deployment/helm/charts/cogstack-ce-helm.md deleted file mode 100644 index 8d4d280..0000000 --- a/docs/docs/platform/deployment/helm/charts/cogstack-ce-helm.md +++ /dev/null @@ -1,134 +0,0 @@ -# CogStack CE Helm Chart - -This page documents the Helm chart for **CogStack Community Edition (CogStack CE)**. - -CogStack CE is an “umbrella” chart that deploys the full stack needed for the community edition: - -- MedCAT service -- AnonCAT (MedCAT in DeID mode) -- MedCAT Trainer (+ required supporting infrastructure) -- OpenSearch (+ dashboards) -- JupyterHub (with example notebooks) - -## Installation - -Install the chart (Helm release name: `cogstack`): - -```sh -helm install cogstack oci://registry-1.docker.io/cogstacksystems/cogstack-helm-ce --wait --timeout 10m0s -``` - -If you want to install into a dedicated namespace: - -```sh -helm install cogstack oci://registry-1.docker.io/cogstacksystems/cogstack-helm-ce \ - --namespace cogstack --create-namespace \ - --wait --timeout 10m0s -``` - -## Port-forwarding (local access) - -After installing, set up port-forwarding using the chart’s NOTES template: - -```sh -helm get notes cogstack | bash -``` - -This runs `kubectl port-forward` in the background and exposes: - -- MedCAT Service: `http://127.0.0.1:5000` -- AnonCAT: `http://127.0.0.1:5001` -- MedCAT Trainer: `http://127.0.0.1:8080` -- OpenSearch (if enabled): `http://127.0.0.1:9200` -- OpenSearch Dashboards (if enabled): `http://127.0.0.1:5601` -- JupyterHub (if enabled): `http://127.0.0.1:8000` - -Open the bundled notebook directly at: - -- http://127.0.0.1:8000/user/admin/notebooks/medcat-service-tutorial.ipynb - -## Configuration and customization - -You can customize the deployment by providing a `values.yaml` override file to `helm install` or `helm upgrade`. - -Typical example: - -```sh -helm upgrade cogstack oci://registry-1.docker.io/cogstacksystems/cogstack-helm-ce \ - --namespace cogstack \ - -f my-values.yaml -``` - -### Component enablement - -Use these boolean flags to enable/disable major components: - -- `medcat-service.enabled` -- `anoncat-service.enabled` -- `medcat-trainer.enabled` -- `opensearch.enabled` -- `opensearch-dashboards.enabled` -- `cogstack-jupyterhub.enabled` - -### MedCAT service (demo UI and replicas) - -Common values: - -- `medcat-service.replicasCount` -- `medcat-service.env.APP_ENABLE_DEMO_UI` (demo mode UI) -- `medcat-service.image.repository` -- `medcat-service.image.tag` - -### AnonCAT (DeID mode and replicas) - -Common values: - -- `anoncat-service.replicasCount` -- `anoncat-service.env.DEID_MODE` -- `anoncat-service.env.DEID_REDACT` -- `anoncat-service.image.repository` -- `anoncat-service.image.tag` - -### MedCAT Trainer (CSRF trusted origins) - -The Trainer frontend requires the correct CSRF trusted origins for your access pattern: - -- `medcat-trainer.env.CSRF_TRUSTED_ORIGINS` - -If you access Trainer via the standard local port-forward (`http://127.0.0.1:8080`), the chart default is usually suitable. If your port-forward differs, update this value accordingly. - -### JupyterHub (dummy authentication) - -By default, the community chart uses a dummy authenticator intended for local/non-production use: - -- `cogstack-jupyterhub.jupyterhub.hub.config.Authenticator.admin_users` (default: `["admin"]`) -- `cogstack-jupyterhub.jupyterhub.hub.config.DummyAuthenticator.password` (default: `SuperSecret`) - -Do not rely on these settings for production deployments. - -### OpenSearch initial credentials - -OpenSearch is deployed with an initial admin password set via: - -- `opensearch.extraEnvs` (contains `OPENSEARCH_INITIAL_ADMIN_PASSWORD`) - -Update this to something secure for non-demo environments. - -### Image pull secrets - -If you use private registries, configure: - -- `imagePullSecrets` - -## Uninstall - -```sh -helm uninstall cogstack --namespace cogstack -``` - -If you created the namespace only for this release: - -```sh -kubectl delete namespace cogstack -``` - diff --git a/docs/docs/platform/deployment/helm/charts/medcat-service-helm.md b/docs/docs/platform/deployment/helm/charts/medcat-service-helm.md deleted file mode 100644 index 9574261..0000000 --- a/docs/docs/platform/deployment/helm/charts/medcat-service-helm.md +++ /dev/null @@ -1,129 +0,0 @@ -# MedCAT Service Helm Chart - -This Helm chart deploys the MedCAT service to a Kubernetes cluster. - -## Installation - -```sh -helm install medcat-service-helm oci://registry-1.docker.io/cogstacksystems/medcat-service-helm -``` - -## Usage - -For local testing, by default you can port forward the service using this command: - -```sh -kubectl port-forward svc/medcat-service-helm 5000:5000 -``` - -Then navigate to http://localhost:5000 to try the service. You can also use http://localhost:5000/docs to view the REST APIs - -## Configuration - -To configure medcat service, create a values.yaml file and install with helm. - -### Model Pack - -You should specify a model pack to be used by the service. By default it will use a small bundled model, which can be used for testing - ---- - -#### Default: Use the demo model pack - -There is a model pack already bundled into medcat service, and is the default in this chart. - -This pack is only really used for testing, and has just a few concepts built in. - -#### Recommended: Download Model on Startup - -Enable MedCAT to download the model from a remote URL on container startup. - -Create a values file like `values-model-download.yaml` and set these values: - -```yaml -model: - downloadUrl: "http://localhost:9000/models/my-model.zip" - name: my-model.zip -``` - -Use this if you prefer dynamic loading of models at runtime. - -#### Advanced: Create a custom volume and load a model into it - -The service can use a model pack if you want to setup your own download flow. For example, setup an initContainer pattern that downloads to a volume, then mount the volume yourself. - -1. Create a persistent volume and PVC in kubernetes following the official documentation. Alternatively specifiy it in `values.extraManifests` and it will be created. - -2. Create a values file like the following, which mounts the volume, and defines a custom init container. - -```yaml -env: - APP_MEDCAT_MODEL_PACK: "/my/models/custom-model.zip" -volumeMounts: - name: model-volume - mountPath: /my/models - -volumes: - - name: model-volume - persistentVolumeClaim: - claimName: my-custom-pvc -extraInitContainers: - - name: model-downloader - image: busybox:1.28 - # In this command, you can write custom code required to download a file. For example you could configure authentication. - command: - ["sh", "-c", "wget -O /my/models/custom-model.zip http://example.com"] - volumeMounts: - - name: model-volume - mountPath: /my/models -``` - -### DeID Mode - -The service can perform DeID of EHRs by swithcing to the following values - -``` -env: - APP_MEDCAT_MODEL_PACK: "/cat/models/examples/example-deid-model-pack.zip" - DEID_MODE: "true" - DEID_REDACT: "true" -``` - -### GPU Support - -To run MedCAT Service with GPU acceleration, use the GPU-enabled image and set the pod runtime class accordingly. - -Note GPU support is only used for deidentification - -Create a values file like `values-gpu.yaml` with the following content: - -```yaml -image: - repository: ghcr.io/cogstack/medcat-service-gpu - -runtimeClassName: nvidia - -resources: - limits: - nvidia.com/gpu: 1 -env: - APP_CUDA_DEVICE_COUNT: 1 - APP_TORCH_THREADS: -1 - DEID_MODE: true -``` - -> To use GPU acceleration, your Kubernetes cluster should be configured with the NVIDIA GPU Operator or the following components: -> -> - [NVIDIA device plugin for Kubernetes](https://github.com/NVIDIA/k8s-device-plugin) -> - [NVIDIA GPU Feature Discovery](https://github.com/NVIDIA/gpu-feature-discovery) -> - The [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/) - -#### Test GPU support - -You can verify that the MedCAT Service pod has access to the GPU by executing `nvidia-smi` inside the pod. - -```sh -kubectl exec -it -- nvidia-smi -``` - -You should see the NVIDIA GPU device listing if the GPU is properly accessible. diff --git a/docs/docs/platform/deployment/helm/charts/medcat-trainer-helm.md b/docs/docs/platform/deployment/helm/charts/medcat-trainer-helm.md deleted file mode 100644 index e98760b..0000000 --- a/docs/docs/platform/deployment/helm/charts/medcat-trainer-helm.md +++ /dev/null @@ -1,50 +0,0 @@ -# MedCAT Trainer Helm Chart - -This Helm chart deploys MedCAT Trainer and infrastructure to a Kubernetes cluster. - -By default the chart will: - -- Run MedCAT Trainer Django server -- Run NGINX for static site hosting and routing -- Run a SOLR and Zookeeper cluster for the Concept DB -- Run a Postgres database for persistence - - -## Installation - -```sh -helm install my-medcat-trainer oci://registry-1.docker.io/cogstacksystems/medcat-trainer-helm -``` - -## Configuration - -See these values for common configurations to change: - -| Setting |description | -| -------- | -------- | -| `env` | Environment variables as defined in the [MedCAT Trainer docs](https://docs.cogstack.org/projects/medcat-trainer/en/latest/installation.html). | -|`medcatConfig`|MedCAT config file as described [here](https://github.com/CogStack/cogstack-nlp/blob/main/medcat-v2/medcat/config/config.py)| -| `env.CSRF_TRUSTED_ORIGINS` | The Host and Port to access the application on | - - -### Use Sqlite instead of Postgres - -Sqlite can be used for smaller single instance deployments - -Set these values: - -```yaml -DB_ENGINE: "sqlite3" - -postgresql: - enabled: false -``` - -## Missing features -These features are not yet existing but to be added in future: - -- Use a pre existing postgres db -- Use a pre existing SOLR instance -- Migrate from supervisord to standalone deployment for background tasks for better scaling -- Support SOLR authentication from medcat trainer -- Support passing DB OPTIONS to medcat trainer for use in cloud environments diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 03d954a..d24429b 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -45,6 +45,8 @@ nav: - Natural Language Processing: overview/Natural Language Processing.md - MedCAT: https://docs.cogstack.org/projects/nlp - MedCAT Trainer: https://docs.cogstack.org/projects/medcat-trainer/ + - Tutorials: + - Medcat Service Tutorial: platform/cogstack-ai/medcat-service-tutorial.ipynb - Data Engineering: - Data Engineering: data-engineering/index.md - Data pipelines: overview/Data pipelines.md @@ -66,8 +68,7 @@ nav: - Charts Overview: platform/deployment/helm/charts/_index.md - MedCAT Service Helm: platform/deployment/helm/charts/medcat-service-helm.md - MedCAT Trainer Helm: platform/deployment/helm/charts/medcat-trainer-helm.md - - CogStack CE: - - Cogstack CE Helm: platform/deployment/helm/charts/cogstack-ce-helm.md + - Cogstack CE Helm: platform/deployment/helm/charts/cogstack-helm-ce.md - Examples: - Examples: platform/deployment/examples/_index.md - AWS Kubernetes EKS: platform/deployment/examples/aws-kubernetes-eks.md @@ -99,7 +100,13 @@ nav: plugins: - search + - gen-files: + scripts: + - scripts/gen_helm_readme.py + - scripts/copy_files_from_repo.py - termynal + - mkdocs-jupyter: + ignore_h1_titles: True extra: analytics: diff --git a/docs/pyproject.toml b/docs/pyproject.toml index 9eb98e7..b1d5f5f 100644 --- a/docs/pyproject.toml +++ b/docs/pyproject.toml @@ -5,6 +5,8 @@ description = "CogStack Documentation" readme = "README.md" requires-python = ">=3.10" dependencies = [ + "mkdocs-gen-files>=0.6.1", + "mkdocs-jupyter>=0.26.1", "mkdocs-material>=9.7.0", "termynal>=0.13.1", ] diff --git a/docs/scripts/copy_files_from_repo.py b/docs/scripts/copy_files_from_repo.py new file mode 100644 index 0000000..014eb96 --- /dev/null +++ b/docs/scripts/copy_files_from_repo.py @@ -0,0 +1,49 @@ +from __future__ import annotations + +""" +mkdocs-gen-files generator for static CogStack AI assets. + +This script copies configured notebook files from the repository into the +MkDocs build output (relative to `docs_dir`). + +Configuration: +`COPY_SPECS` is a list of dicts with: +- `sourceFilePath`: path to the repo file to copy +- `outputFilePath`: path (relative to MkDocs' `docs_dir`) to write into +""" + +from pathlib import Path + +import mkdocs_gen_files # type: ignore[import-not-found] + + +REPO_ROOT = Path(__file__).resolve().parents[2] + +# Add more entries here to copy additional static files into documentation. +COPY_SPECS = [ + { + "sourceFilePath": "helm-charts/cogstack-helm-ce/charts/jupyterhub/examples/medcat-service-tutorial.ipynb", + "outputFilePath": "platform/cogstack-ai/medcat-service-tutorial.ipynb", + } +] + + +def main() -> None: + """Copy configured files into the MkDocs virtual filesystem.""" + for spec in COPY_SPECS: + source_rel = spec["sourceFilePath"] + output_rel = spec["outputFilePath"] + + source_path = REPO_ROOT / source_rel + if not source_path.is_file(): + raise FileNotFoundError(f"Source file not found: {source_path}") + + output_path = Path(output_rel) + + # Write bytes so formats like .ipynb are preserved exactly. + with mkdocs_gen_files.open(output_path.as_posix(), "wb") as f: + f.write(source_path.read_bytes()) + + +main() + diff --git a/docs/scripts/gen_helm_readme.py b/docs/scripts/gen_helm_readme.py new file mode 100644 index 0000000..0eb6bf5 --- /dev/null +++ b/docs/scripts/gen_helm_readme.py @@ -0,0 +1,47 @@ +from __future__ import annotations + +""" +mkdocs-gen-files generator. + +This script copies each Helm chart's `helm-charts//README.md` into the +MkDocs documentation build output so it can be referenced from `mkdocs.yml`. + +Output filename format: +`platform/deployment/helm/charts/.md` +""" + +from pathlib import Path + +import mkdocs_gen_files # type: ignore[import-not-found] + + +REPO_ROOT = Path(__file__).resolve().parents[2] +HELM_CHARTS_DIR = REPO_ROOT / "helm-charts" + +# Output path is relative to MkDocs' `docs_dir` (configured in docs/mkdocs.yml). +OUTPUT_DIR = Path("platform/deployment/helm/charts") + + +def main() -> None: + """Generate MkDocs markdown pages for all Helm charts found in `helm-charts/`.""" + for chart_dir in sorted(HELM_CHARTS_DIR.iterdir(), key=lambda p: p.name): + if not chart_dir.is_dir(): + continue + + readme_path = chart_dir / "README.md" + if not readme_path.is_file(): + continue + + output_path = OUTPUT_DIR / f"{chart_dir.name}.md" + + # Copy README.md content verbatim into the docs page. + with 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(de-identification).\n", @@ -338,4 +338,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +}