Swiss AI Hub v0.310.3

Added

• ✨ Introduced RAG Figure Inlining: Implemented a new mechanism to inline RAG figures (images) as Base64 directly at
  the LiteLLM gateway, ensuring compatibility with LLM providers that cannot directly access internal S3 storage.
• 🖼️ Configurable Image Inlining: Added new environment variables (RAG_IMAGE_INLINE_ENABLED,
  RAG_IMAGE_INLINE_MAX_BYTES) to control RAG image inlining behavior and define a maximum size, allowing for flexible
  deployment configurations and cost management.
• 🔗 Dedicated Internal S3 Endpoint: Introduced S3_STORAGE_INTERNAL_ENDPOINT for signing presigned URLs
  specifically for in-cluster services like the LiteLLM gateway, enhancing secure and efficient internal data transfer.
• 📄 Architectural Decision Record: Added a new ADR outlining the rationale, design, and consequences of the RAG
  figure inlining solution.

Changed

• 🔄 Refined S3 Presigned URL Generation: Updated the S3 anonymous file access service to support generating
  presigned URLs tailored for either public or internal (in-cluster) access based on the RAG image inlining setting.
• 🔌 LiteLLM Gateway Integration: Configured the LiteLLM gateway to utilize a new custom callback, which
  intelligently fetches RAG figures from internal storage and inlines them as Base64 into LLM prompts.
• 🎛️ RAG Agent Image Handling: Modified RAG agents to sign image URLs against the new internal S3 endpoint when
  inlining is enabled, ensuring figures are correctly prepared for the LiteLLM gateway.
• ⚙️ Deployment Configuration: Updated Docker Compose and deployment scripts to include the new LiteLLM custom
  callback and propagate relevant environment variables to the LiteLLM and RAG agent services.
• 📚 Documentation: Expanded the environment variables documentation to include details on
  RAG_IMAGE_INLINE_ENABLED, RAG_IMAGE_INLINE_MAX_BYTES, and S3_STORAGE_INTERNAL_ENDPOINT.