This release adds new dedicated notebooks showcasing usage of cloud based NVIDIA AI Foundation models, upgraded milvus container version to enable GPU accelerated vector search and added support for FAISS vector database. Detailed changes are listed below:

Added

• New dedicated notebooks showcasing usage of cloud based Nvidia AI Foundation 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.

Changed

• 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

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