This article discusses how to overcome limitations of retrieval-augmented generation (RAG) models by creating an AI assistant using advanced SQL vector queries. The author uses tools such as MyScaleDB, OpenAI, LangChain, Hugging Face and the HackerNews API to develop an application that enhances the accuracy and efficiency of data retrieval process.
Quadratic is a modern spreadsheet that combines the familiarity of a spreadsheet with the power of code, allowing you to work with data and code collaboratively in real-time. It supports popular programming languages like Python, SQL, and JavaScript, and offers features such as dynamic charts, APIs, multi-line formulas, and AI integration.
A prototype tool powered by Large Language Models to make querying your databases as easy as saying the word.
- Introduction to QueryGPT, a tool using Large Language Models (LLMs) for natural language database queries
- Focus on implementing a basic iteration of the system, with potential for significant enhancements
- Aim is to provide the LLM with the database schema and have it answer questions based on that context
- Discussion on prompt engineering, which is designing inputs for generative AI tools to produce optimal results
- Introduction to QueryGPT, a tool using Large Language Models (LLMs) for natural language database queries
- Focus on implementing a basic iteration of the system, with potential for significant enhancements
- Aim is to provide the LLM with the database schema and have it answer questions based on that context
- Discussion on prompt engineering, which is designing inputs for generative AI tools to produce optimal results
Tune a base LLama2 LLM to output SQL code. with Parameter Efficient Fine-Tuning techniques to optimise the process.
training GPT to query with few-shot prompting.
