Build an Agent | 🦜️🔗 LangChain
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By themselves, language models can't take actions - they just output text.
RAG with Deep Agents - Docs by LangChain Documentation Index Fetch the complete documentation index at: /llms.txt Use this file to discover all available pages before exploring further. Skip to main content One of the most powerful LLM-based applications are sophisticated question-answering (Q&A) chatbots which augment LLMs by providing it with inference-time access to a set of data. This might be private data, recent data, or data that is not part of the training data the LLM is trained on. These applications use a technique known as Retrieval Augmented Generation, or RAG . Deep Agents gives
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