#python #agent #ai #data_visualization #database #llm #rag #sql #text_to_sql

Vanna is a tool that helps you generate SQL queries easily. Here’s how it works: you train a model with your database information, and then you can ask questions to get the corresponding SQL queries. This process is simple and doesn't require you to know the technical details underneath. The benefits include high accuracy, security since your data stays local, and the ability to use it with any SQL database. You can also customize the interface to suit your needs, such as using Jupyter Notebooks, Slack, or web apps. This makes it easier and faster to work with your database without writing complex SQL queries manually.

https://github.com/vanna-ai/vanna

#typescript #agent #bigquery #charts #duckdb #genbi #gpt #llm #openai #postgresql #rag #reporting #spreadsheets #sql #sqlai #text_to_sql #text2sql

Wren AI is a free, open-source tool that helps you get insights from your data easily. You can ask questions in any language, and it will generate the necessary SQL queries to get the answers. It integrates well with tools like Excel and Google Sheets, making it easy to analyze and visualize your data. Wren AI also suggests follow-up questions to help you dig deeper into your data without needing to write code. This makes it simpler for anyone, regardless of their technical skills, to understand and use their data effectively.

https://github.com/Canner/WrenAI

#python #ai #csv #data #data_analysis #data_science #data_visualization #database #datalake #gpt_4 #llm #pandas #sql #text_to_sql

PandaAI is a tool that lets you ask questions about your data using natural language. It's helpful for both non-technical and technical users. Non-technical users can interact with data more easily, while technical users can save time and effort. You can load your data, save it as a dataframe, and then ask questions like "Which are the top 5 countries by sales?" or "What is the total sales for the top 3 countries?" PandaAI also allows you to visualize charts and work with multiple datasets. It's easy to install using pip or poetry and can be used in Jupyter notebooks, Streamlit apps, or even a secure Docker sandbox. This makes it simpler and more efficient to analyze your data.

https://github.com/sinaptik-ai/pandas-ai

#python #chatbi #deepseek #llm #nl2sql #rag #sqlbot #text_to_sql #text2sql

SQLBot is an easy-to-use intelligent system that turns natural language questions into SQL queries using advanced AI models and retrieval-augmented generation (RAG). You just need to set up your AI model and data source to start asking questions about your data. It integrates smoothly with other business systems and AI platforms, making it simple to add smart data querying to your apps. It also ensures data security with workspace-based resource isolation and fine-grained access control. You can quickly deploy it on a Linux server using Docker, enabling fast, secure, and intelligent data interaction without needing deep SQL knowledge. This saves you time and improves data accessibility.

https://github.com/dataease/SQLBot