This repository contains practice implementations of different LangChain chains. Each file demonstrates how to structure and execute various types of chains in LangChain for building flexible AI workflows
A collection of LangChain chain examples — Simple, Sequential, Parallel, and Conditional — showcasing how to build flexible, modular AI workflows. Includes runnable code to help you design efficient and dynamic LLM-powered applications.
"Advanced LangChain workflows utilizing Google Gemini, OpenAI, and Anthropic for structured AI-driven text processing. This repository includes examples of sequential, parallel, and conditional chains for generating structured outputs, sentiment analysis, summarization, and interactive AI workflows."
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