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Building Reliable AI Agents with PydanticAI: Result Validators Masterclass. Welcome to the PydanticAI Masterclass, where we explore how to build robust and reliable AI agents!

In this module, we’ll dive deep into the result validator functions, a powerful PydanticAI feature that ensures your AI agents produce validated and high-quality outputs. Validators add an extra layer of reliability by analyzing model responses before passing them downstream, making your agentic workflows more robust.

💡 What You’ll Learn:
1️⃣ How to define result validator functions for validating AI outputs.
2️⃣ How to use tools to dynamically inject context and dependencies at runtime.
3️⃣ How to leverage retry mechanisms for handling invalid outputs.
4️⃣ Step-by-step implementation of an AI agent that provides detailed information about capital cities.

⚙️ Key Features of PydanticAI:
Post-LLM Validation: Ensure structured and valid responses from your AI models
Dynamic Tools: Add runtime context to improve agent responses
Retry Mechanisms: Automatically re-prompt for corrections when validation fails
Python-First Framework: Fully type-safe, model-agnostic, and developer-friendly

Masterclass Series:
▶️ Part 1:    • PydanticAI: The Best AI Agent Framework Ha...  
▶️ Part 2:    • From Chaos to Clarity: LLM Tracing with Lo...  
▶️ Part 3:    • 100% Reliable LLM Outputs with Structured ...  
▶️ Part 4:    • Dramatic Improvement! Design Better Agents...  
▶️ Part 5:    • Design Better AI Agents With Function Calling  
▶️ Part 6:    • Transform You Agents with Result Validator...  
▶️ Part 7:    • Improve Agent Scalability with Dependency ...  
▶️ Part 8:    • Build More Reliable Agents with Retries an...  
▶️ Part 9:    • Better Context Retention with Agent Memory...  
▶️ Part 10:    • Building Resilient Agents: Self-Reflection...  
▶️ Part 11:    • Better User Experience with Streaming Outp...  
▶️ Part 12:    • Hidden Model Settings That Will Transform ...  
▶️ Part 13: Multi-Model Agents in PydanticAI: Unlocking Next-Gen AI Capabilities
▶️ Part 14: Mastering RAG in PydanticAI: Better AI Agents with Real-Time Data
▶️ Part 15: Masterclass Final Project: AI Resume Writing with Multiple Agents

🎯 Whether you're building a chatbot, an AI agent, or any other LLM-powered system, this tutorial provides practical examples to elevate your application’s ability to get better outputs from AI.

What agents are you building? Join the conversation at   / discord  

🔗 Links & Resources:
Skool: https://www.skool.com/ai-software-dev...
Code the Revolution: Newsletter - https://aidev9.substack.com/
Discord server:   / discord  
PydanticAI: https://ai.pydantic.dev

Timecodes:
00:00 - Welcome to PydanticAI Masterclass
00:05 - Introduction to PydanticAI Masterclass
00:30 - Result validator functions
00:42 - Why validate results?
01:02 - GitHub repo
01:14 - Discord server
01:40 - Coding tutorial
02:26 - Hello, World!
05:00 - Validators with context
07:22 - Validators with result type
11:02 - Multiple validators
14:36 - SQL code validation
20:18 - Python code validation
24:42 - Summary

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