schema-description-agent 0.1.1

LLM-driven agent for describing data tables based on domain schemas

Schema Description Agent

The Schema Description Agent is a Python-based tool that automatically generates descriptions for tables and their columns. It analyzes the structure and content of a data file, and then uses a Large Language Model (LLM) to produce accurate and concise documentation.

Features

• Statistical Analysis: Automatically calculates key statistics for each column, such as row count, column count, duplicate rows, missing cells, and more.
• AI-Powered Descriptions: Leverages LLMs to generate human-readable descriptions for tables and columns based on the statistical analysis.
• Configurable: Easily configure the AI provider, model, and other parameters.
• Extensible: Built on a modular framework (sfn_blueprint) that allows for easy extension and integration.

Installation

Prerequisites

• uv – package & environment manager
  Please refer to the official installation guide for the most up-to-date instructions.
  For quick setup on macOS/Linux, you can currently use:

  curl -LsSf https://astral.sh/uv/install.sh | sh
  

• Git

Steps

1. Clone the repository:

   git clone https://github.com/stepfnAI/schema_description_agent.git
   cd schema_description_agent
   git switch dev
   

2. Create virtual environment and install dependencies:

   uv sync --extra dev
   source .venv/bin/activate
   

3. Clone and install the blueprint dependency: The agent requires the sfn_blueprint library. Clone it into a sibling directory.

   cd ../
   git clone https://github.com/stepfnAI/sfn_blueprint.git
   cd sfn_blueprint
   git switch dev
   uv pip install -e .
   

4. Return to the agent directory:

   cd ../schema_description_agent
   

5. ** set environment variables:**

   export OPENAI_API_KEY='your_openai_api_key'
   

Testing

To run the tests, use the following command from the root of the schema_description_agent directory:

# Run all tests
pytest tests/ -s

# test agent    
pytest tests/test_agent.py -s

# test agent with sample data
pytest tests/test_agent_with_data.py -s

Usage

Here is a simple example of how to use the agent:

python examples/basic_usage.py

Configuration

The agent can be configured via the SchemaDescriptionConfig class. You can modify the default configuration by passing a SchemaDescriptionConfig object to the SchemaDescriptionAgent constructor.

Default Configuration:

• ai_provider: "openai"
• model_name: "gpt-4o"
• temperature: 0.3
• max_tokens: 4000

Example of custom configuration:

from schema_description_agent import SchemaDescriptionAgent, SchemaDescriptionConfig

# Create a custom configuration
config = SchemaDescriptionConfig(
    ai_provider="anthropic",
    model_name="claude-3-opus-20240229",
    temperature=0.5
)

# Create an instance of the agent with the custom configuration
agent = SchemaDescriptionAgent(config=config)