Content based document search - KNIME Locall LLMs

This workflow creates a content-based document search on a contracts dataset.

First, we generate a summary of the contract using Local Llama, then extract the embedding vectors and store them in the Chroma vector database. After that, we can use vector store retrieval to retrieve documents related to a user query.