awslabs/gap-text2sql

GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

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This project helps convert natural language questions into executable SQL queries, making it easier to retrieve information from databases without needing to write complex code. You provide a question in plain English and a database schema, and it outputs a precise SQL query. This is useful for data analysts, business intelligence specialists, or anyone who needs to query databases using natural language.

109 stars. No commits in the last 6 months.

Use this if you need to transform plain English questions into exact SQL queries for structured databases, especially when dealing with varied phrasing and complex data relationships.

Not ideal if your primary goal is to answer questions using unstructured text or if you need to query databases that don't have a clear, well-defined schema.

data-analysis business-intelligence database-querying natural-language-processing information-retrieval
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

109

Forks

25

Language

Python

License

Apache-2.0

Last pushed

Mar 20, 2024

Commits (30d)

0

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