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docs: Document Model-As-OCI-Artifacts feature #1359
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…ation Co-authored-by: chewong <10557231+chewong@users.noreply.github.com>
… page Co-authored-by: chewong <10557231+chewong@users.noreply.github.com>
@copilot fix the CI PR Title Checker / check (pull_request) |
The CI failure is due to the PR title not having a required prefix. According to The current title "Document Model-As-OCI-Artifacts feature in website" should be changed to "docs: Document Model-As-OCI-Artifacts feature in website" to pass the PR title checker. I don't have the ability to modify the PR title directly - could you please update it to include the |
Co-authored-by: chewong <10557231+chewong@users.noreply.github.com>
I've successfully copied the ✅ Updated content based on review feedback:
✅ Added Mermaid support:
✅ Verified functionality:
The documentation is now ready and provides users with a complete guide to understanding and using the Model-As-OCI-Artifacts feature. Commit: 2470332 Warning Firewall rules blocked me from connecting to one or more addressesI tried to connect to the following addresses, but was blocked by firewall rules:
If you need me to access, download, or install something from one of these locations, you can either:
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…ps, copy to all versions Co-authored-by: chewong <10557231+chewong@users.noreply.github.com>
Signed-off-by: Ernest Wong <chwong719@gmail.com>
…scribing what KAITO does Co-authored-by: zhuangqh <12205760+zhuangqh@users.noreply.github.com>
This PR implements comprehensive documentation for the Model-As-OCI-Artifacts feature as requested in issue kaito-project#1355. The documentation explains how KAITO uses OCI artifacts to efficiently distribute large language model weights, providing users with a complete understanding of the feature's architecture, benefits, and usage. ## Key Documentation Features **User-Focused Feature Guide** - Explains KAITO's split architecture approach using base images and OCI artifacts - Details the design rationale behind separating model weights from inference runtime - Provides clear guidance on when to use OCI artifacts for optimal performance - Includes practical getting started instructions and troubleshooting tips **Technical Architecture** - Interactive mermaid sequence diagram showing the model weight download process - Detailed explanation of how initContainers use ORAS to fetch model artifacts - Performance comparison data demonstrating build time and deployment improvements - Compatibility matrix for container runtimes and OCI registries **Complete Integration** - Multi-version deployment across v0.5.0, v0.5.1, and latest - Mermaid diagram support with @docusaurus/theme-mermaid package - Updated terminology using "model weights" throughout documentation - CI configuration adjusted to handle documentation dependencies The documentation transforms technical proposal content into user-facing guidance that explains what KAITO does, why this design was chosen, and how users can leverage the feature for improved large language model deployments. Fixes kaito-project#1355. <!-- START COPILOT CODING AGENT TIPS --> --- 💬 Share your feedback on Copilot coding agent for the chance to win a $200 gift card! Click [here](https://survey.alchemer.com/s3/8343779/Copilot-Coding-agent) to start the survey. --------- Signed-off-by: Ernest Wong <chwong719@gmail.com> Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: chewong <10557231+chewong@users.noreply.github.com> Co-authored-by: Ernest Wong <chwong719@gmail.com> Co-authored-by: zhuangqh <12205760+zhuangqh@users.noreply.github.com> Co-authored-by: Fei Guo <vrgf2003@gmail.com>
This PR implements comprehensive documentation for the Model-As-OCI-Artifacts feature as requested in issue kaito-project#1355. The documentation explains how KAITO uses OCI artifacts to efficiently distribute large language model weights, providing users with a complete understanding of the feature's architecture, benefits, and usage. ## Key Documentation Features **User-Focused Feature Guide** - Explains KAITO's split architecture approach using base images and OCI artifacts - Details the design rationale behind separating model weights from inference runtime - Provides clear guidance on when to use OCI artifacts for optimal performance - Includes practical getting started instructions and troubleshooting tips **Technical Architecture** - Interactive mermaid sequence diagram showing the model weight download process - Detailed explanation of how initContainers use ORAS to fetch model artifacts - Performance comparison data demonstrating build time and deployment improvements - Compatibility matrix for container runtimes and OCI registries **Complete Integration** - Multi-version deployment across v0.5.0, v0.5.1, and latest - Mermaid diagram support with @docusaurus/theme-mermaid package - Updated terminology using "model weights" throughout documentation - CI configuration adjusted to handle documentation dependencies The documentation transforms technical proposal content into user-facing guidance that explains what KAITO does, why this design was chosen, and how users can leverage the feature for improved large language model deployments. Fixes kaito-project#1355. <!-- START COPILOT CODING AGENT TIPS --> --- 💬 Share your feedback on Copilot coding agent for the chance to win a $200 gift card! Click [here](https://survey.alchemer.com/s3/8343779/Copilot-Coding-agent) to start the survey. --------- Signed-off-by: Ernest Wong <chwong719@gmail.com> Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: chewong <10557231+chewong@users.noreply.github.com> Co-authored-by: Ernest Wong <chwong719@gmail.com> Co-authored-by: zhuangqh <12205760+zhuangqh@users.noreply.github.com> Co-authored-by: Fei Guo <vrgf2003@gmail.com>
This PR implements comprehensive documentation for the Model-As-OCI-Artifacts feature as requested in issue #1355. The documentation explains how KAITO uses OCI artifacts to efficiently distribute large language model weights, providing users with a complete understanding of the feature's architecture, benefits, and usage.
Key Documentation Features
User-Focused Feature Guide
Technical Architecture
Complete Integration
The documentation transforms technical proposal content into user-facing guidance that explains what KAITO does, why this design was chosen, and how users can leverage the feature for improved large language model deployments.
Fixes #1355.
💬 Share your feedback on Copilot coding agent for the chance to win a $200 gift card! Click here to start the survey.