knnlabs/Conduit

AI Summary: Implement a lightweight content preprocessor and enhance ReactMarkdown rendering in a React application to improve the visual presentation of structured AI responses containing XML-like tags. This involves converting common tags (e.g., `<thinking>`, `<warning>`) into Markdown equivalents for better formatting and adding collapsible sections and alert boxes for enhanced user experience. The task will be implemented in TypeScript and will focus on core tags initially, with extended tag support planned for future enhancements.

AI Summary: This task requires modifying the backend DTO `ModelProviderMappingDto` to include a `ProviderName` property and updating the `ToDto()` method to populate it. The frontend should then be updated to use this new property instead of the numeric ID for displaying provider names in the Model Mappings table. Additionally, it's recommended to clean up redundant provider name conversion logic in other frontend components.

AI Summary: Add integration tests to the ConduitLLM Admin and Http API projects to verify the successful generation of Swagger documentation. The tests should check for a 200 OK response, valid JSON, and the presence of key OpenAPI properties. This will prevent runtime Swagger failures and ensure API documentation remains available.

AI Summary: The task involves updating the Node.js SDK for ConduitLLM to use a new, faster health check endpoint ('/health/ready') while maintaining backward compatibility with the existing endpoint ('/health'). This includes adding a new method to the SDK, updating documentation, and ensuring the WebUI utilizes the improved endpoint. Unit and integration tests are required to verify functionality and backward compatibility.

AI Summary: This task requires implementing the ability to rename model mappings within a Large Language Model (LLM) API gateway. This involves adding a rename functionality to both the Admin SDK (potentially using a delete-and-recreate approach if direct renaming isn't supported by the API) and the WebUI, including validation to prevent duplicate model aliases. Thorough testing is crucial to ensure data integrity and a smooth user experience.

AI Summary: This task requires updating the `ModelProviderMappingDto` in the ConduitLLM project to include a `providerName` field. This involves modifying the DTO itself, updating the data mapping logic in the backend to populate this new field, adjusting the TypeScript definitions in the Admin SDK and WebUI, and finally simplifying the WebUI's `ModelMappingsTable` component to directly use the new `providerName` field instead of making an extra API call. The goal is to improve performance and reduce complexity in the WebUI by eliminating an unnecessary API call.

AI Summary: Migrate three React modal components (`CreateModelMappingModal`, `CreateProviderModal`, `CreateSecurityEventModal`) to use a common base component (`FormModal`), removing duplicate code and ensuring consistency. This involves updating the component code, preserving existing functionality (form validation, submission logic, etc.), and thorough testing.