Suleyman Ekmekci created SOLR-17117:
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Summary: Proposing to add Generative Search (RAG) to Solr
Key: SOLR-17117
URL: https://issues.apache.org/jira/browse/SOLR-17117
Project: Solr
Issue Type: New Feature
Security Level: Public (Default Security Level. Issues are Public)
Reporter: Suleyman Ekmekci
Retrieval Augmented Generation (RAG) is the technique of optimizing the output
of a Large Language Model (LLM), so it references an authoritative knowledge
base outside of its training data sources before generating a response. RAG has
recently become critical for enhancing the accuracy and reliability of
generative AI models.
Currently, RAG isn't supported natively by Solr. There might be different
approaches to make this happen. I had the opportunity to experiment generative
search with the Solr streaming expressions. Logic will be simple: as an input,
Solr results and user prompt will be given to a configured LLM. LLM will
receive the results and based on the prompt and the results, it will generate
human-like response. Giving the search results from Solr will help LLM to not
hallucinate.
Here is one example:
- Solr query: filtering by director (Christopher Nolan)
- Receiving Solr response: Titles and summaries of relevant movies
- LLM Interaction: "Write a comprehensive overview of Christopher Nolan's
filmmaking style, referencing his films"
- Expected outcome: Summary, comparisons and film details
Another example:
- Solr query: documentaries about space exploration
- Receiving Solr response: Titles and summaries of relevant documentaries
- LLM Interaction: "Create a viewer's guide that highlights the key themes and
facts presented in space exploration documentaries. Include a brief description
and critical analysis for each"
- Expected outcome: A well-structured guide that's both informative and
engaging, closely tied to the data provided by Solr
I would like to hear about your opinions, ideas and possible solutions to
discuss about the feature.
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