Model service documentation

[Jurgee]

This PR adds and polishes MkDocs documentation for the model-service. Changes:

• Add/iterate MkDocs documentation (docs/): quick start, architecture overview, deployment guide, configuration reference, adding models, troubleshooting.
• Align README with the current Ray Serve + KubeRay RayService setup
• Add docs dependency group in pyproject.toml ([dependency-groups].docs: mkdocs, mkdocs-material, pymdown-extensions).
• Add GitLab CI job for docs build: .gitlab-ci.yml → docs:build runs mkdocs build --strict.
• Update mkdocs.yml as needed for the docs site.

Summary by CodeRabbit

• Documentation

  • Added a full docs site with architecture, request lifecycle, batching, queues/backpressure, quick start, deployment, model integration, configuration reference, and troubleshooting.
  • Rewrote the README with Kubernetes quick-start, deploy/access steps, prerequisites, a reference model test example (compressed binary payloads), autoscaling, resource sizing, and operational guidance.

• Chores

  • Added docs tooling/configuration, docs dependency group, and an automated documentation build workflow.

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📝 Walkthrough

Walkthrough

Replaces the template README with a Ray Serve–focused README, adds a MkDocs site and config, ten new documentation pages (architecture, guides, quick-start, troubleshooting), a docs dependency group, a GitHub Actions docs-build workflow, and minor non-functional edits to two model files.

Changes

Cohort / File(s)	Summary
Top-level docs & manifest README.md, ray-service.yaml	Replace generic template README with a Ray Serve / Kubernetes–focused README referencing the RayService manifest, quick start, testing, support, and license details.
MkDocs site & tooling mkdocs.yml, pyproject.toml	Add MkDocs Material site configuration and a docs dependency group (mkdocs, mkdocs-material, pymdown-extensions).
Docs CI workflow .github/workflows/build-docs.yml	Add GitHub Actions workflow that triggers on docs changes and delegates to a reusable mkdocs-build workflow.
Docs home & quick start docs/index.md, docs/get-started/quick-start.md	Add documentation homepage and a Kubernetes quick-start with prerequisites, kubectl apply/port-forward steps, and verification guidance.
Architecture pages docs/architecture/overview.md, docs/architecture/request-lifecycle.md, docs/architecture/queues-and-backpressure.md, docs/architecture/batching.md	Add four architecture pages covering system overview, end-to-end request lifecycle, multi-level queuing/backpressure semantics, and replica-local batching behavior and tuning.
Guides & operations docs/guides/adding-models.md, docs/guides/deployment-guide.md, docs/guides/configuration-reference.md, docs/guides/troubleshooting.md	Add guides for adding models, production deployment, RayService YAML configuration reference (fields, autoscaling, resources), and troubleshooting/playbook.
Model minor edits models/binary_classifier.py, models/semantic_segmentation.py	Small formatting/comment adjustments in trt_options entries (removed inline type-ignore comments / minor punctuation); no runtime behavior changes.

Sequence Diagram(s)

(omitted)

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~12 minutes

Poem

🐰 I hopped through docs to polish each part,
New pages stacked neat — a rabbitly art.
Manifests, guides, and a quick-start quest,
Models whisper ready, servers dressed.
MkDocs lights the trail — now onward, best! 🥕📚

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'Model service documentation' accurately and directly describes the primary change: comprehensive documentation additions for the model service project.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch docs/model-service

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[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the Model Service's discoverability and usability by introducing a comprehensive, structured documentation portal. The new documentation, built with MkDocs, covers essential aspects from quick deployment to detailed architectural insights and troubleshooting, making it easier for users to understand, deploy, and manage machine learning models. Accompanying these changes are updates to the main README, CI/CD pipelines for documentation validation, and proper dependency management for the documentation tools.

Highlights

• Comprehensive Documentation: Introduced a new MkDocs-based documentation site covering quick start, architecture, deployment, configuration, adding models, and troubleshooting for the model service.
• README Update: Rewrote the README.md to align with the current Ray Serve + KubeRay setup and provide a high-level overview and links to the new documentation.
• CI/CD Integration: Added a GitLab CI job to build and validate the MkDocs documentation, ensuring its integrity.
• Dependency Management: Introduced a dedicated docs dependency group in pyproject.toml for documentation-related tools.
• MkDocs Configuration: Configured mkdocs.yml to define the documentation site structure, theme, and navigation.

Changelog

• .gitlab-ci.yml
  • Included the MkDocs.gitlab-ci.yml template.
  • Added a deploy stage to the CI pipeline.
• README.md
  • Rewrote the entire content to provide a modern, focused overview of the Model Service.
  • Added sections for documentation links, quick start instructions for Kubernetes, testing the reference model, and repository structure.
  • Removed generic GitLab-generated boilerplate.
• docs/architecture/batching.md
  • Added a new document explaining Ray Serve's batching mechanism, including its API, internal workings, and tuning.
• docs/architecture/overview.md
  • Added a new document providing a high-level architectural overview of the Model Service, covering system components, scaling, and fault tolerance.
• docs/architecture/queues-and-backpressure.md
  • Added a new document detailing Ray Serve's queueing and backpressure mechanisms, explaining proxy-side and replica-side queues.
• docs/architecture/request-lifecycle.md
  • Added a new document tracing the detailed request lifecycle through the Model Service stack, from client to model execution.
• docs/get-started/quick-start.md
  • Added a new quick start guide for deploying a sample model on Kubernetes.
• docs/guides/adding-models.md
  • Added a new guide on how to implement, configure, and deploy new machine learning models.
• docs/guides/configuration-reference.md
  • Added a new reference document explaining key configuration parameters for RayService, applications, and deployments.
• docs/guides/deployment-guide.md
  • Added a new comprehensive guide for deploying models to production, including resource planning and best practices.
• docs/guides/troubleshooting.md
  • Added a new troubleshooting guide addressing common deployment and runtime issues.
• docs/index.md
  • Added the main landing page for the Model Service documentation, outlining its purpose, features, and content structure.
• mkdocs.yml
  • Added the MkDocs configuration file, defining the site name, description, repository, theme, navigation structure, and Markdown extensions.
• pyproject.toml
  • Added a docs dependency group including mkdocs, mkdocs-material, and pymdown-extensions.

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[gemini-code-assist]

Code Review

The pull request introduces a comprehensive documentation site for the Model Service, covering its architecture, deployment guides, model integration, configuration, and troubleshooting, while also integrating the documentation build process into the CI pipeline. Review comments suggest improving clarity in the README.md regarding kubectl namespace placeholders, completing a placeholder URL in the configuration reference, addressing a potential LaTeX rendering issue in the configuration-reference.md by suggesting a pymdownx.arithmatex extension, resolving a missing JSON curl example in deployment-guide.md, and adding a final newline character to mkdocs.yml for consistency.

[Copilot]

Pull request overview

This PR adds an MkDocs documentation site for the model-service and updates repository metadata/CI to build the docs alongside the existing Ray Serve + KubeRay RayService setup.

Changes:

• Adds a new MkDocs site (mkdocs.yml) and a full set of docs pages under docs/ (quick start, guides, architecture).
• Updates README.md to match the current Ray Serve + KubeRay deployment model and reference model payload format.
• Adds a docs dependency group to pyproject.toml and updates .gitlab-ci.yml to include the docs build template.

Reviewed changes

Copilot reviewed 14 out of 14 changed files in this pull request and generated 8 comments.

Show a summary per file

File	Description
pyproject.toml	Adds a docs dependency group for MkDocs tooling.
mkdocs.yml	Introduces MkDocs Material configuration, nav, and Markdown extensions.
docs/index.md	Adds the documentation landing page content and navigation pointers.
docs/get-started/quick-start.md	Adds a Kubernetes quick start for deploying the RayService.
docs/guides/deployment-guide.md	Adds a detailed production deployment guide and ops considerations.
docs/guides/configuration-reference.md	Adds a reference for RayService / Serve knobs (autoscaling, backpressure, etc.).
docs/guides/adding-models.md	Adds guidance and examples for implementing and integrating models.
docs/guides/troubleshooting.md	Adds common failure modes and triage steps for RayService/Serve on K8s.
docs/architecture/overview.md	Adds a high-level architecture overview of the stack and scaling model.
docs/architecture/request-lifecycle.md	Documents end-to-end request flow and queueing points.
docs/architecture/queues-and-backpressure.md	Explains queueing controls (max_queued_requests, max_ongoing_requests).
docs/architecture/batching.md	Explains Ray Serve batching behavior and tuning considerations.
README.md	Replaces the GitLab template README with repo-specific usage and payload details.
.gitlab-ci.yml	Includes the MkDocs CI template and adds a deploy stage for docs build.

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[Copilot]

Pull request overview

Copilot reviewed 14 out of 15 changed files in this pull request and generated 3 comments.

Comments suppressed due to low confidence (1)

.github/workflows/build-docs.yml:24

• PR description mentions adding a GitLab CI docs build job (updating .gitlab-ci.yml), but this PR only adds a GitHub Actions workflow and there is no .gitlab-ci.yml change in the repo. Please either update the PR description to match, or add the intended GitLab CI job/file in this PR.

name: Build Documentation

on:
  push:
    branches: ["main"]
    paths:
      - "docs/**"
      - "mkdocs.yml"
      - "pyproject.toml"
      - "uv.lock"
      - ".github/workflows/build-docs.yml"
  pull_request:
    branches: ["main"]
    paths:
      - "docs/**"
      - "mkdocs.yml"
      - "pyproject.toml"
      - "uv.lock"
      - ".github/workflows/build-docs.yml"

jobs:
  run:
    uses: RationAI/.github/.github/workflows/mkdocs-build.yml@main

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[matejpekar]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces a comprehensive documentation suite for the Model Service, including architecture overviews, deployment guides, and a configuration reference using MkDocs. It also overhauls the README and adds a documentation dependency group to the project configuration. Feedback was provided to improve the readability of memory values in the configuration reference by adding human-readable comments.

[Copilot]

Pull request overview

Copilot reviewed 16 out of 17 changed files in this pull request and generated 4 comments.

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