We are using Elasticsearch database. We are planning to provide global search with lot of filters. Our data is mostly structured and there are built in relationships. Having many filters on global search can create usability problems.
Is it possible to perform NLP tasks like question/answer or chat bot on structured data? I believe this will help us to get rid of filters and user will be able to search through questions.
Thank you for your question! There is ongoing development in the (tech-preview) inference API, which will probably have more task types added in the future. There's also built-in NLP support, which also supports question answering models. Does this help?
I was wondering if it is possible to do following:
User will ask questions like in UI -
How many students are suffering from covid 19?
My index doesn't store values in vector form but I would still like to convert above question into proper elastic query and return result to user.
we have some examples of how you would do this within LangChain.
In this example notebook, you provide a schema for your index and it will transform the question into an BM25 only query.
Behind the scenes, LangChain is providing a prompt to transform the query into a structured query, based on the schema and then translating that structured query into a BM25 query. You could do this process manually, without LangChain.