Structured Output in LangChain | Generative AI using LangChain | Video 5 | CampusX

Code - https://github.com/campusx-official/langchain-structured-output In this video, we explore how to make LLMs interact with databases, APIs, and other systems using structured responses like JSON instead of unstructured text. 📌 What You’ll Learn: ✅ Difference between structured vs. unstructured output ✅ How structured output improves data processing and automation ✅ Real-world use cases for integrating LLMs with APIs and databases ============================ Did you like my teaching style? Check my affordable mentorship program at : https://learnwith.campusx.in DSMP FAQ: https://docs.google.com/document/d/1OsMe9jGHoZS67FH8TdIzcUaDWuu5RAbCbBKk2cNq6Dk/edit#heading=h.gvv0r2jo3vjw ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official Slide into our DMs: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] ⌚Time Stamps⌚ 00:00 - Intro 01:13 - Recap 02:09 - What is Structured Output? 05:17 - Why do we need structured output? 11:40 - Ways to get structured output 14:08 - with_structured_output function 15:33 - TypedDict 36:07 - Pydantic 01:02:32 - JSON 01:02:58 - When to use? 01:04:53 - Important Points 01:07:47 - Outro