Pydantic AI: A Python Agent Framework for Generative AI

An overview of Pydantic AI, a new Python agent framework built on top of the popular Pydantic library, designed for building production-grade applications with generative AI.

Duration: 11 minutes
Level: Intermediate
6 Lessons
Agent Frameworks Prompt Engineering LLMs

Course Timeline

00:00

🎥 Introduction to Pydantic AI

Introduction to Pydantic AI and its features, highlighting its foundation in the popular Pydantic library and its focus on building production-ready applications with generative AI.

02:00

🚀 Pydantic AI's Advantages and Features

Details on Pydantic AI's key advantages, including model agnosticism, support for various LLMs, and features like streamed responses and structured validation. Built upon Pydantic's validation layer.

04:00

⚙️ Dependency Injection and Logfire Integration

Discussion on Pydantic AI's novel type-safe dependency injection system, useful for testing, and its integration with Logfire for debugging and monitoring.

05:35

💡 Simple Example: Synchronous Agent Execution

A simple example demonstrating the basic usage of Pydantic AI, including importing the agent, defining the LLM, and executing a synchronous agent.

06:15

🤖 Advanced Example: Customer Support Agent

A more advanced example showcasing a customer support agent built with Pydantic AI, highlighting the use of dynamic system prompts, structured results, and tools to interact with a database.

10:25

🤔 Conclusion and Future Outlook

Concluding thoughts on Pydantic AI's potential and its position in the market of agent frameworks, also discussion on its strengths and weaknesses.