AIDBBot 0.1.1

AI-driven natural language queries for databases using AutoGen

DBBot

DBBot is an AI-driven Python library that converts natural language queries into SQL queries using OpenAI’s AutoGen, enabling seamless interaction with databases. It empowers developers and data analysts to retrieve and manipulate data effortlessly using plain English queries.

Features

• AI-Driven Query Generation: Converts natural language questions into valid SQL queries using AutoGen.
• Multi-Database Support: Works with PostgreSQL, MySQL, and MongoDB.
• Seamless Integration: Easily integrates with your existing Python projects.
• Flexible Setup: Users provide their own database and OpenAI credentials.
• Extensible: Allows adding support for more databases or customizing AI behavior.
• Logging & Debugging: Built-in features to help troubleshoot queries.

Installation

Install DBBot using pip:

pip install dbqna

Requirements

• Python 3.6 or higher
• Required database drivers:
  • psycopg2 for PostgreSQL
  • pymysql for MySQL
  • pymongo for MongoDB
• OpenAI API key (for using the GPT model)

Setup

Database Credentials

Provide the following details for database connection:

• Host
• Port
• Database Name
• User
• Password

OpenAI Credentials

You'll need an OpenAI API key and additional configurations:

• API Key
• Base URL
• API Version
• Deployment Name

You can set these as environment variables in a .env file or provide them directly in the code.

Usage

1. Initialize DBBot with OpenAI Credentials

from dbqna import DBQnA

db_bot = DBQnA(
    azure_api_key="your-azure-api-key",
    azure_api_base="your-azure-api-base",
    azure_api_version="your-api-version",
    azure_deployment_name="your-deployment-name"
)

2. Provide Database Credentials

from dbqna import DBHelper

db_helper = DBHelper(
    host="localhost",
    port="5432",
    database="your-database",
    user="postgres",
    password="your-password"
)

3. Query the Database Using Natural Language

query = "how many work orders are there for tenant 1289?"
result = await db_bot.query_database(query)
print(result)

4. Example Response

Result: 
[
    ('work_order_count', 35)
]

Contributing

We welcome contributions! Feel free to fork the repository, open issues, or submit pull requests to enhance DBBot.