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langchain
Knowledge Tutorial

A chapter-by-chapter walkthrough of langchain, generated from its source code and tutorial markdown.

7
Chapters
-
Subsystems
Rabbit Holes
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System Architecture

How the pieces fit

langchain is organized as connected concepts and components. Start broad, then drill down chapter by chapter.

⚙️
Language Models (Chat Models & LLMs)
Language Models (Chat Models & LLMs)
⚙️
Prompts & Messages
Prompts & Messages
⚙️
Runnables & Chains
Runnables & Chains
⚙️
Memory
Memory
⚙️
Retrieval (Documents & VectorStores)
Retrieval (Documents & VectorStores)
🔧
Agents & Tools
Agents & Tools
⚙️
Callbacks
Callbacks
langchain — bash
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Repository Overview

Intro and Architecture Diagram

LangChain is a framework for building applications powered by Language Models (LLMs and Chat Models). It provides a structure where Runnables & Chains orchestrate sequences of calls, Agents use models to decide on actions using Tools, and Memory persists conversational state. The framework also abstracts Retrieval for accessing external data and uses Callbacks for monitoring execution.

Source Repository: https://github.com/langchain-ai/langchain

flowchart TD A0["Runnables & Chains"] A1["Language Models (Chat Models & LLMs)"] A2["Prompts & Messages"] A3["Agents & Tools"] A4["Retrieval (Documents & VectorStores)"] A5["Memory"] A6["Callbacks"] A0 -->|"Invokes model"| A1 A0 -->|"Uses prompts"| A2 A0 -->|"Manages state"| A5 A3 -->|"Inherits from"| A0 A3 -->|"Uses for reasoning"| A1 A3 -->|"Executes tools"| A3 A1 -->|"Binds tools"| A3 A5 -->|"Stores messages"| A2 A1 -->|"Consumes messages"| A2 A4 -->|"Triggers events"| A6 A1 -->|"Triggers events"| A6
Tutorial Chapters

All 7 chapters

Follow sequentially or jump to any topic. Start with Language Models (Chat Models & LLMs).

About This Project

Generated by Code IQ

This tutorial was automatically generated by Code IQ and rendered with the shared tutorial site builder. It can be produced for any repository tutorial folder that follows the numbered markdown chapter layout.

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// → 7 chapters
// → source: langchain-ai/langchain