Add support for semantic search with the dense vector #355
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Intention
Current chatbot-rag-app is set up with only SparseVectorStrategy. I'd like to add DenseVectorStrategy because for those who speak non-English languages, DenseVectorStrategy with E5 models is good option.
I know this doesn't work for the data ingestion part, but it's great to have a dense vector option in the RAG example.
Changes
This pull request introduces several enhancements to the
example-apps/chatbot-rag-appto support both sparse and dense vector strategies for Elasticsearch. The changes include updates to the environment configuration, the main chat API, and logging improvements.Support for multiple vector strategies:
example-apps/chatbot-rag-app/api/chat.py: Added support forDenseVectorStrategyalongside the existingSparseVectorStrategy. Introduced new environment variables to configure the strategy type, model ID, vector field, and query field. [1] [2]Environment configuration updates:
example-apps/chatbot-rag-app/env.example: Updated the example environment file to include configurations for both sparse and dense vector strategies, allowing users to easily switch between them.Logging improvements:
example-apps/chatbot-rag-app/api/chat.py: Improved logging in theask_questionfunction to ensure that document metadata is logged only if the "name" field is present.