Creating a github repo about creating effective agents in PydanticAI, this is the using tools scenario for raw OpenAI SDK vs PydanticAI. Shortens the LOC more than 2x while also having minimal abstractions. Well done
MongoDB just released a repo with AI Agent and RAG code examples. Includes self-reflecting agents, multi-agent systems, chunking strategies, and vector embedding examples. Uses LangChain, PydanticAI, OpenAI, and all major frameworks and LLMs. 100% free and opensource.
Personal AI Agent Mind-Map. This is a Multi-agent. Tech Stack:.- Python's (Langchain and PydanticAI).- Supabase as DB for RAG and Memory. I am building this for my Sem-end-Project.
Build production-grade Agentic AI apps in pure Python!. PydanticAI is a Python agent framework designed to simplify building production-grade Agentic applications. 100% Open Source
PydanticAI. A new Python-based agent framework to build production-grade LLM-powered applications. - Built by the team behind Pydantic.- Model-agnostic.- Type-sage.- Structured response validation with Pydantic.- Streamed responses (including validation) with Pydantic.- Tools
I’ve loved PydanticAI’s elegant approach to building agents and now using @pydantic with @heroku ‘s openAI compatible chat completion endpoint is simple.
Finally had some time to publish a simple vibecoded tool I (and Claude Code) built to explore PydanticAI, Arbitron. Replicates a contest where jurors evaluate candidates in pairwise comparisons that get turned into a leaderboard.
PydanticAI, A Python agent framework to build production grade apps with Generative AI. >>> Type safe, structured outputs.>>> Stream + validate model responses.>>> Works with OpenAI, Gemini & more.>>> Write agent logic in plain Python.>>> Built-in Logfire for debugging.>>> Easy