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Techsplainers by IBM · July 30 · 6 min

What is LangChain?

This episode of Techsplainers explores LangChain, an open-source framework that's revolutionizing how developers build applications powered by large language models. Created by Harrison Chase in 2022, LangChain provides modular components that help connect AI models to external data sources, tools, and reasoning capabilities. We break down LangChain's key components—models, prompts, memory, chains, agents, and tools—explaining how they work together to overcome the inherent limitations of language models. The discussion highlights popular applications, including retrieval-augmented generation systems that connect AI to private data, conversational agents that can use external tools, document analysis solutions, and personal assistants. While emphasizing LangChain's flexibility and growing ecosystem, we also address its limitations and alternatives like Haystack, LlamaIndex, and Semantic Kernel. Whether you're a developer looking to build AI applications or simply interested in how modern AI systems work, this episode provides a comprehensive introduction to one of the most important frameworks in today's AI development landscape. Find more information at https://www.ibm.com/think/topics/langchain Find more episodes https://www.ibm.biz/techsplainers-podcast Narrated by Amanda Downie

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This episode of Techsplainers explores LangChain, an open-source framework that's revolutionizing how developers build applications powered by large language models. Created by Harrison Chase in 2022, LangChain provides modular components that help connect AI models to external data sources, tools, and reasoning capabilities. We break down LangChain's key components—models, prompts, memory, chains, agents, and tools—explaining how they work together to overcome the inherent limitations of language models. The discussion highlights popular applications, including retrieval-augmented generation systems that connect AI to private data, conversational agents that can use external tools, document analysis solutions, and personal assistants. While emphasizing LangChain's flexibility and growing ecosystem, we also address its limitations and alternatives like Haystack, LlamaIndex, and Semantic Kernel. Whether you're a developer looking to build AI applications or simply interested in how modern AI systems work, this episode provides a comprehensive introduction to one of the most important frameworks in today's AI development landscape.

Find more information at https://www.ibm.com/think/topics/langchain Find more episodes https://www.ibm.biz/techsplainers-podcast

Narrated by Amanda Downie
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