Alessandro Benedetti – End-to-End Semantic Search with Apache Solr 9.8 LLM Module #bbuzz

More: https://2025.berlinbuzzwords.de/sessi... Speaker: Alessandro Benedetti Apache Solr 9.8 introduces the LLM module opening the doors of end-to-end natural language query support through vector-backed semantic search (K Nearest Neighbors). This talk explores the open source contribution from both the indexing and query angles and what’s coming next for Solr in terms of integrations with Large Language Models. Dense vector search was introduced in Apache Solr 9.0 in 2022 and since then it has received substantial adoption from the community. Text vectorisation had to happen outside Solr, as there was no support to encode text to vector within the search engine transparently. Apache Solr 9.8 changes this, introducing a module that allows interaction with well-known large language model providers such as OpenAI, Cohere, HuggingFace and Mistral AI via the open-source library LangChain4j. Expect to learn how to configure Solr to access external text vectorisation services and use them to encode and run your queries through the 'knn_text_to_vector' query parser and vectorise your documents’ textual fields through the 'Text To Vector Update Request Processor'. This is a foundational enabler that speeds up the design and development of end-to-end semantic search solutions. The talk wraps up with future directions and how the introduction of the LLM module opens the doors for exciting new integrations. Join us as we dive into the AI future of Apache Solr! ### Follow us on Social Media and join the Community! Mastodon: https://floss.social/@BerlinBuzzwords LinkedIn:   / berlin-buzzwords   Website: https://berlinbuzzwords.de Mail: [email protected] Berlin Buzzwords is an event by Plain Schwarz – https://plainschwarz.com