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UppuluriKalyani / ML-Nexus

ML Nexus is an open-source collection of machine learning projects, covering topics like neural networks, computer vision, and NLP. Whether you're a beginner or expert, contribute, collaborate, and grow together in the world of AI. Join us to shape the future of machine learning!
https://ml-nexus.vercel.app/
MIT License
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Feature request: Natural Language to SQL Query Conversion (Text2SQL) #567

Closed pranavvb03 closed 1 month ago

pranavvb03 commented 1 month ago

The Text2SQL project focuses on creating an AI-driven system that converts natural language queries into SQL commands. The goal is to enable non-technical users to interact with databases using plain English, simplifying complex data retrieval processes without needing SQL knowledge. This system can be particularly useful for business analysts, data teams, and anyone who needs quick access to insights from databases but lacks SQL expertise.

Technologies Used:

  1. Pytorch
  2. NLP Tools: SpaCy, Transformers
  3. Machine Learning Models: Sequence-to-Sequence models, Transformers
  4. SQL Query LLM : Hugging Face Defog's SQLCoder for query generation and execution
  5. Database Management Systems (DBMS): MySQL
  6. Frameworks: Streamlit for interactive UI

Key Features:

  1. Natural Language Interface: Users can input queries in plain language without needing to know SQL syntax, making database access more user-friendly for non-technical stakeholders.
  2. SQL Generation: Defog SQLCoder processes the input and converts it into accurate SQL queries, ensuring that even complex multi-join and nested queries are generated.
  3. Context-Aware Responses: The model understands the schema of the database, including table relationships and constraints, to generate queries that are syntactically and contextually correct.

Additional context Add any other context or screenshots about the feature request here.

github-actions[bot] commented 1 month ago

Thanks for creating the issue in ML-Nexus!🎉 Before you start working on your PR, please make sure to:

github-actions[bot] commented 1 month ago

Thanks for raising this issue! However, we believe a similar issue already exists. Kindly go through all the open issues and ask to be assigned to that issue.

Abhilove-Goyal commented 1 month ago

I really liked the project idea , it unique and is well suited for the current world, i will love to suggest some additional features 1.Caching Frequent Queries: Implement a caching system to store the results of frequently asked queries, reducing response time for repetitive requests. 2.Schema Adaptability: The system could dynamically adapt to different database schemas, allowing it to work across various industries and applications (e.g., finance, healthcare, retail) without manual reconfiguration.

UppuluriKalyani commented 1 month ago

I really liked the project idea , it unique and is well suited for the current world, i will love to suggest some additional features 1.Caching Frequent Queries: Implement a caching system to store the results of frequently asked queries, reducing response time for repetitive requests. 2.Schema Adaptability: The system could dynamically adapt to different database schemas, allowing it to work across various industries and applications (e.g., finance, healthcare, retail) without manual reconfiguration.

Yes proceed

github-actions[bot] commented 1 month ago

Hello @pranavvb03! Your issue #567 has been closed. Thank you for your contribution!