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@mdrxy mdrxy commented Oct 31, 2025

Closes #437

@github-actions github-actions bot added langchain For docs changes to LangChain oss labels Oct 31, 2025
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Mintlify preview ID generated: preview-mdrxyc-1761937494-5301a39

@mdrxy mdrxy marked this pull request as ready for review November 3, 2025 22:07
Copilot AI review requested due to automatic review settings November 3, 2025 22:07
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Pull Request Overview

This PR adds a new conceptual documentation page explaining LangChain's component architecture with visual diagrams. The page helps users understand how different LangChain components (models, tools, agents, memory, retrievers, etc.) work together to build AI applications.

  • Introduces a visual component ecosystem diagram showing input processing, embedding & storage, retrieval, generation, and orchestration layers
  • Adds a component categories table with links to detailed guides
  • Includes example diagrams for common patterns: RAG, agent with tools, and multi-agent systems

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File Description
src/oss/langchain/component-architecture.mdx New documentation page with Mermaid diagrams explaining component relationships and common architecture patterns
src/docs.json Adds navigation entries for the new component architecture page in both Python and JavaScript documentation sections

Comment on lines +1 to +3
---
title: Component architecture
---
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The frontmatter is missing a required description field. According to the documentation guidelines, all MDX files must include both title and description in their frontmatter. Add a concise description that will be used for SEO and navigation purposes.

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nits

title: Component architecture
---

LangChain's power comes from how its components work together to create sophisticated AI applications. This page provides visual diagrams showing the relationships between different components, helping you understand how they fit together.
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Suggested change
LangChain's power comes from how its components work together to create sophisticated AI applications. This page provides visual diagrams showing the relationships between different components, helping you understand how they fit together.
LangChain's power comes from how its components work together to create sophisticated AI applications. This page provides visual diagrams showing the relationships between different components.

B --> F[Coordinated Response]
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## Next steps
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DOC: Add diagram(s) showing components relationships (specialization, usage, dependency...)?

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