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https://github.com/madhanmohanreddy2301/chat-with-sql_db
This project demonstrates how to use the Vanna AI library to connect to a SQLite database and query for the top 10 albums by sales from the Chinook database. Additionally, a Flask application is created to run the Vanna AI interface.
https://github.com/madhanmohanreddy2301/chat-with-sql_db
flask-sqlalchemy gpt35turbo llm sqlite streamlit vanna
Last synced: 2 days ago
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This project demonstrates how to use the Vanna AI library to connect to a SQLite database and query for the top 10 albums by sales from the Chinook database. Additionally, a Flask application is created to run the Vanna AI interface.
- Host: GitHub
- URL: https://github.com/madhanmohanreddy2301/chat-with-sql_db
- Owner: MadhanMohanReddy2301
- License: gpl-3.0
- Created: 2024-06-30T11:36:23.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-06-30T11:40:06.000Z (5 months ago)
- Last Synced: 2024-07-02T09:49:48.773Z (5 months ago)
- Topics: flask-sqlalchemy, gpt35turbo, llm, sqlite, streamlit, vanna
- Language: Jupyter Notebook
- Homepage:
- Size: 575 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Vanna AI SQL Querying Application
This project demonstrates how to use the Vanna AI library to connect to a SQLite database and query for the top 10 albums by sales from the Chinook database. Additionally, a Flask application is created to run the Vanna AI interface.
## Table of Contents
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Project Structure](#project-structure)
- [License](#license)
## Prerequisites
Before you begin, ensure you have met the following requirements:
- Python 3.6 or later installed on your machine.
- The required Python packages installed (listed in the `requirements.txt`).
## Installation
1. Clone this repository to your local machine:
```sh
git clone https://github.com/your-username/vanna-ai-sql-query.git
cd vanna-ai-sql-query
```
2. Install the required Python packages:
```sh
pip install -r requirements.txt
```
3. Ensure you have the Chinook SQLite database file (`Chinook.sqlite`) in the `vannaAi` directory. You can download it from [here](https://github.com/lerocha/chinook-database).
## Usage
1. Set your Vanna API key by replacing `[email protected]` with your email address:
```python
vn = VannaDefault(model='chinook', api_key=vanna.get_api_key('[email protected]'))
```
2. Ensure the path to your SQLite database is correct in the `connect_to_sqlite` method:
```python
vn.connect_to_sqlite('vannaAi/Chinook.sqlite') # Adjust the path if necessary
```
3. Run the application:
```sh
python app.py
```
This will start a Flask server running the Vanna AI interface.
4. Access the application in your web browser at `http://127.0.0.1:5000`.
## Code Overview
Here is the main code used in the application:
```python
import vanna
from vanna.remote import VannaDefault
from vanna.flask import VannaFlaskApp
# Initialize VannaDefault with the specified model and API key
vn = VannaDefault(model='chinook', api_key=vanna.get_api_key('[email protected]'))
# Connect to the SQLite database
vn.connect_to_sqlite('vannaAi/Chinook.sqlite') # Path to your SQLite database
# Ask a query to Vanna
vn.ask("What are the top 10 albums by sales?")
# Create and run the Flask app
VannaFlaskApp(vn).run()