Why Pydantic AI is the Future of AI Agents
https://github.com/samuelcolvin/…
https://github.com/samuelcolvin/boston-ae/blob/main/slides.md
AI Summary
Summary of Video Transcript
- Event Structure:
- Two talks scheduled.
- Breakout room sessions concentrated into one after the talks.
- Presentation by Samuel:
- Introduction to Pantic, started in 2017, became a company in 2023.
- Pantic V2 released last year, rewritten in Rust.
- Pantic’s usage: 300 million downloads a month, not just for Gen but for general Python development.
- Pantic’s role in validating structured responses, especially in API contexts.
- Pantic’s Functionality:
- Type coercion for data validation.
- JSON schema support for APIs, contributed by Sebastian Ramirez.
- Pantic’s increased relevance with the rise of tools like Gen.
- Introduction of Pan AI:
- Released two weeks prior to the talk.
- Wrapper for Pantic, providing additional features like reflection and dependency injection.
- Type safety and static analysis for error prevention.
- Example of using Pan AI to get weather information based on location.
- Live demo of Pan AI in action.
- Observability with Logfire:
- Importance of observability in understanding agent actions and performance.
- Logfire integration with Pan AI for detailed insights.
- Upcoming Features in Pantic AI:
- Agent handoff: allowing agents to call other agents.
- Tool sets: registering sets of tools for agents to use, including support for model context protocol.
- Model agnosticism: support for various models beyond OpenAI.
- Q&A Session:
- Customizing agent logic and tool behavior.
- Repository availability for the presentation code.
- Pantic AI as a potential replacement for other frameworks like llama index or Lang chain.
Detailed Instructions and URLs
No specific CLI commands, website URLs, or detailed instructions were provided in the transcript.