PydanticOutputParser() Explained with Practical Examples in LangChain | Generative AI Tutorial
🚀 Welcome to the Generative AI Series!
In this video, we will learn LangChain's PydanticOutputParser with practical coding examples in Python.
📌 Topics Covered:
✅ What is PydanticOutputParser?
✅ Why do we need Structured Output in LLM Applications?
✅ Creating Pydantic Models
✅ Parsing JSON Output
✅ PydanticOutputParser.parse()
✅ PromptTemplate + PydanticOutputParser
✅ ChatOpenAI Integration
✅ LangChain Expression Language (LCEL)
✅ Building a Complete Parsing Chain
✅ Real-world Generative AI Use Cases
💻 Source Code Covered:
✔ Pydantic BaseModel
✔ Field Validation
✔ ChatOpenAI
✔ PromptTemplate
✔ LangChain Output Parsers
✔ Structured Output Generation
This tutorial is perfect for anyone learning:
• Generative AI
• LangChain
• Python
• Prompt Engineering
• LLM Application Development
• OpenAI API
• Structured Output
• AI Agents
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