Description:
In this video, we dive deep into PromptTemplate, StrOutputParser, and the concept of chaining in LangChain — three core tools for building structured and controllable multi-step AI workflows.
We’ll start by designing reusable prompts using PromptTemplate, ensuring consistent and dynamic instructions for the AI. Then we’ll clean and standardize outputs with StrOutputParser, making them reliable for downstream tasks. Finally, we’ll connect everything through chaining, where the output of one step becomes the input to another, enabling complex, layered reasoning like report generation and summarization.
By the end of this session, you’ll understand how to combine these tools to create predictable, modular, and production-ready AI pipelines for tasks like content generation, summarization, and report automation.
Complete Playlist: https://www.youtube.com/playlist?list=PL9myac9mW283Xg9_h_u33PALLDxvXsqPq
Generative AI Playlist: https://www.youtube.com/playlist?list=PL9myac9mW283KgBetbmX0RM9gfiSmKR9v
LangGrpah Playlist: https://www.youtube.com/playlist?list=PL9myac9mW281TroFMRjBiJjcM3sAlhRMb
Hands on ML with PyTorch Playlist: https://www.youtube.com/playlist?list=PL9myac9mW280ozHIipsJiae0ygfH932sB
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