v2.0.0

[2.0.0] - 2025-03-18

This release adds support for multimodal documents using Nvidia Ingest including support for parsing PDFs, Word and PowerPoint documents. It also significantly improves accuracy and perf considerations by refactoring the APIs, architecture as well as adds a new developer friendly UI.

Added

• Integration with Nvingest for ingestion pipeline, the unstructured.io based pipeline is now deprecated.
• OTEL compatible observability and telemetry support.
• API refactoring. Updated schemas here.
  • Support runtime configuration of all common parameters. 
  • Multimodal citation support.
  • New dedicated endpoints for deleting collection, creating collections and reingestion of documents
• New react + nodeJS based UI showcasing runtime configurations
• Added optional features to improve accuracy and reliability of the pipeline, turned off by default. Best practices here
  • Self reflection support
  • NeMo Guardrails support
  • Hybrid search support using Milvus
• Brev dev compatible notebook
• Security enhancements and stability improvements

Changed

• • In RAG v1.0.0, a single server managed both ingestion and retrieval/generation APIs. In RAG v2.0.0, the architecture has evolved to utilize two separate microservices.
• Helm charts are now modularized, seperate helm charts are provided for each distinct microservice.
• Default settings configured to achieve a balance between accuracy and perf.
  • Default flow uses on-prem models with option to switch to API catalog endpoints for docker based flow.
  • Query rewriting uses a smaller llama3.1-8b-instruct and is turned off by default.
  • Support to use conversation history during retrieval for low-latency  multiturn support.

Known Issues

• The rag-playground container needs to be rebuild if the APP_LLM_MODELNAME, APP_EMBEDDINGS_MODELNAME or APP_RANKING_MODELNAME environment variable values are changed.
• Optional features reflection, nemoguardrails and image captioning are not available in helm based deployment.
• Uploading large files with .txt extension may fail during ingestion, we recommend splitting such files into smaller parts, to avoid this issue.

A detailed guide is available here for easing developers experience, while migrating from older versions.