PydanticAI Examples

This repository contains practical examples of using PydanticAI for building LLM-powered applications. PydanticAI is a powerful framework that combines Pydantic's type safety with LLM capabilities.

Setup

1. Clone this repository:

git clone https://github.com/cloutprotocol/pydantic-ai.git
cd pydantic-ai

2. Install dependencies:

pip install -r requirements.txt

3. Set up your environment variables:

cp .env.example .env
# Edit .env with your OpenAI API key

Examples

1. Recipe Generator: Demonstrates using PydanticAI for structured recipe generation
2. Customer Support Agent: Shows how to build a support agent with structured responses
3. Data Analyzer: Example of using PydanticAI for structured data analysis

Each example is self-contained in its own directory under examples/.

Running the Examples

Each example can be run directly:

python examples/recipe_generator.py
python examples/customer_support.py
python examples/data_analyzer.py

Key Features Demonstrated

1. Type Safety: All examples use Pydantic models for type-safe inputs and outputs
2. Structured Outputs: Show how to get structured, predictable responses from LLMs
3. Error Handling: Examples include proper error handling and validation
4. Real-world Use Cases: Practical applications that can be adapted for production use

Documentation

For more information about PydanticAI, visit the official documentation.