All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

• New dedicated notebooks showcasing usage of cloud based Nvidia AI Playground based models using Langchain connectors as well as local model deployment using Huggingface.
• Upgraded milvus container version to enable GPU accelerated vector search.
• Added support to interact with models behind NeMo Inference Microservices using new model engines nemo-embed and nemo-infer.
• Added support to provide example specific collection name for vector databases using an environment variable named COLLECTION_NAME.
• Added faiss as a generic vector database solution behind utils.py.

• Upgraded and changed base containers for all components to pytorch 23.12-py3.
• Added langchain specific vector database connector in utils.py.
• Changed speech support to use single channel for Riva ASR and TTS.
• Changed get_llm utility in utils.py to return Langchain wrapper instead of Llmaindex wrappers.

• Fixed a bug causing empty rating in evaluation notebook
• Fixed document search implementation of query decomposition example.

• New dedicated example showcasing Nvidia AI Playground based models using Langchain connectors.
• New example demonstrating query decomposition.
• Support for using PG Vector as a vector database in the developer rag canonical example.
• Support for using Speech-in Speech-out interface in the sample frontend leveraging RIVA Skills.
• New tool showcasing RAG observability support.
• Support for on-prem deployment of TRTLLM based nemotron models.

• Upgraded Langchain and llamaindex dependencies for all container.
• Restructured README files for better intuitiveness.
• Added provision to plug in multiple examples using a common base class.
• Changed minio service's port to 9010from 9000 in docker based deployment.
• Moved evaluation directory from top level to under tools and created a dedicated compose file.
• Added an experimental directory for plugging in experimental features.
• Modified notebooks to use TRTLLM and Nvidia AI foundation based connectors from langchain.
• Changed ai-playground model engine name to nv-ai-foundation in configurations.

• Fixed issue #19

• Support for using Nvidia AI Playground based LLM models
• Support for using Nvidia AI Playground based embedding models
• Support for deploying and using quantized LLM models
• Support for Kubernetes deployment support using helm charts
• Support for evaluating RAG pipeline

• Repository restructing to allow better open source contributions
• Upgraded dependencies for chain server container
• Upgraded NeMo Inference Framework container version, no seperate sign up needed for access.
• Main README now provides more details.
• Documentation improvements.
• Better error handling and reporting mechanism for corner cases
• Renamed triton-inference-server container to llm-inference-server

• Fixed issue #13 of pipeline not able to answer questions unrelated to knowledge base
• Fixed issue #12 typechecking while uploading PDF files