🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.
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Updated
Jul 11, 2024 - Python
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.
Interact with your SQL database, Natural Language to SQL using LLMs
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL
Multiple paper open-source codes of the Microsoft Research Asia DKI group
[ACL 2021] This is the project containing source codes and pre-trained models about ACL2021 Long Paper ``LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations".
A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG
Code and trained model for Hybrid ranking network for text-to-SQL on WikiSQL
MindSQL: A Python Text-to-SQL RAG Library simplifying database interactions. Seamlessly integrates with PostgreSQL, MySQL, SQLite, Snowflake, and BigQuery. Powered by GPT-4 and Llama 2, it enables natural language queries. Supports ChromaDB and Faiss for context-aware responses.
[NeurIPS'22] EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records
sqlgpt-parser is a Python implementation of an SQL parser that effectively converts SQL statements into Abstract Syntax Trees (AST). By leveraging AST tree comparisons between two SQL queries, it becomes possible to achieve robust evaluation of text-to-SQL models.
This repo in the implementation of EMNLP'21 paper "SPARQLing Database Queries from Intermediate Question Decompositions" by Irina Saparina, Anton Osokin
Python package for managing OHDSI clinical data models. Includes support for LLM based plain text queries!
Make sense of it all. Semantic data modeling and analytics with a sprinkle of AI. https://totalhack.github.io/zillion/
[preprint'24] EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records
Code and data for the paper "DBCᴏᴘɪʟᴏᴛ: Scaling Natural Language Querying to Massive Databases"
The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question IntentionClassification Benchmark for Text-to-SQL"
Recognize English speech then convert it to text then generate a SQL query from it and then finally fetch data from database
Efficient, consistent and secure library for querying structured data with natural language
Code, data, and model of paper "Text-to-SQL Error Correction with Language Models of Code" (ACL'23)
A framework for converting natural language text inputs to corresponding Pandas, MongoDB, Kusto and Neo4j (Cypher) queries.
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