aws-samples/tabular-column-semantic-search
Code accompanying AWS blog post "Build a Semantic Search Engine for Tabular Columns with Transformers and Amazon OpenSearch Service"
This solution helps data engineers or analysts quickly build a search engine for tabular data. You upload CSV files containing various columns, and it automatically processes them to create a searchable index. The output is a web application where you can enter a query and find the most relevant columns across your uploaded datasets, making it easier to discover and reuse data.
No commits in the last 6 months.
Use this if you need to build a semantic search capability for your internal CSV datasets and want to quickly find relevant data columns based on natural language queries.
Not ideal if you are looking for an off-the-shelf product with no development or infrastructure setup, or if your data is not in CSV format.
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Language
Python
License
Apache-2.0
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Last pushed
Nov 09, 2023
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