* Adds document intelligence model configuration
Enables the configuration of the Document Intelligence model to be used by the RAG pipeline.
This allows users to specify the model they want to use for document processing, providing flexibility and control over the extraction process.
* Added Titel to Document Intelligence Model Config
Added Titel to Document Intelligence Model Config
Removes the unused `/litellm/config` endpoint, the corresponding `downloadLiteLLMConfig` frontend API function, and the unused import from the `Database.svelte` component. This code was identified as dead code as it was not being used in the UI.
This refactors the model import functionality to improve performance and user experience by centralizing the logic on the backend.
Previously, the frontend would parse an imported JSON file and send an individual API request for each model, which was slow and inefficient.
This change introduces a new backend endpoint, `/api/v1/models/import`, that accepts a list of model objects. The frontend now reads the selected JSON file, parses it, and sends the entire payload to the backend in a single request. The backend then processes this list, creating or updating models as necessary.
This commit also includes the following fixes:
- Handles cases where the imported JSON contains models without `meta` or `params` fields by providing default empty values.
This moves the JSON model import functionality to the backend. Instead of the frontend parsing the JSON file and sending multiple requests, it now uploads the file to a new endpoint (/api/v1/models/import), which processes the file and imports the models. This improves efficiency and provides better user feedback.
The previous implementation for unarchiving all chats in `ArchivedChatsModal.svelte` was inefficient, as it sent a separate request for each chat, which could potentially overload the server.
This commit introduces a new backend endpoint, `/chats/unarchive/all`, to handle the bulk unarchiving of all chats for a user with a single API call.
The frontend has been updated to use this new endpoint, resolving the performance issue by minimizing the number of requests to the server.
