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+import ThemedImage from '@theme/ThemedImage';
+import useBaseUrl from '@docusaurus/useBaseUrl';
+
+In this section, you'll find explanations of the key concepts, providing a deeper understanding of core principles.
+
+The conceptual guide will not cover step-by-step instructions or specific implementation details — those are found in the [How-To Guides](/docs/how_to/) and [Tutorials](/docs/tutorials) sections. For detailed reference material, please visit the [API Reference](https://python.langchain.com/api_reference/).
+
+## Architecture
+
+LangChain as a framework consists of a number of packages.
+
+### `langchain-core`
+This package contains base abstractions of different components and ways to compose them together.
+The interfaces for core components like LLMs, vector stores, retrievers and more are defined here.
+No third party integrations are defined here.
+The dependencies are kept purposefully very lightweight.
+
+### `langchain`
+
+The main `langchain` package contains chains, agents, and retrieval strategies that make up an application's cognitive architecture.
+These are NOT third party integrations.
+All chains, agents, and retrieval strategies here are NOT specific to any one integration, but rather generic across all integrations.
+
+### `langchain-community`
+
+This package contains third party integrations that are maintained by the LangChain community.
+Key partner packages are separated out (see below).
+This contains all integrations for various components (LLMs, vector stores, retrievers).
+All dependencies in this package are optional to keep the package as lightweight as possible.
+
+### Partner packages
+
+While the long tail of integrations is in `langchain-community`, we split popular integrations into their own packages (e.g. `langchain-openai`, `langchain-anthropic`, etc).
+This was done in order to improve support for these important integrations.
+
+### [`langgraph`](https://langchain-ai.github.io/langgraph)
+
+`langgraph` is an extension of `langchain` aimed at
+building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
+
+LangGraph exposes high level interfaces for creating common types of agents, as well as a low-level API for composing custom flows.
+
+### [`langserve`](/docs/langserve)
+
+A package to deploy LangChain chains as REST APIs. Makes it easy to get a production ready API up and running.
+
+### [LangSmith](https://docs.smith.langchain.com)
+
+A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
+
+
diff --git a/docs/docs/concepts/index.mdx b/docs/docs/concepts/index.mdx
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# Conceptual guide
-import ThemedImage from '@theme/ThemedImage';
-import useBaseUrl from '@docusaurus/useBaseUrl';
-
In this section, you'll find explanations of the key concepts, providing a deeper understanding of core principles.
The conceptual guide will not cover step-by-step instructions or specific implementation details — those are found in the [How-To Guides](/docs/how_to/) and [Tutorials](/docs/tutorials) sections. For detailed reference material, please visit the [API Reference](https://python.langchain.com/api_reference/).
## Architecture
-LangChain as a framework consists of a number of packages.
-
-### `langchain-core`
-This package contains base abstractions of different components and ways to compose them together.
-The interfaces for core components like LLMs, vector stores, retrievers and more are defined here.
-No third party integrations are defined here.
-The dependencies are kept purposefully very lightweight.
-
-### `langchain`
-
-The main `langchain` package contains chains, agents, and retrieval strategies that make up an application's cognitive architecture.
-These are NOT third party integrations.
-All chains, agents, and retrieval strategies here are NOT specific to any one integration, but rather generic across all integrations.
-
-### `langchain-community`
-
-This package contains third party integrations that are maintained by the LangChain community.
-Key partner packages are separated out (see below).
-This contains all integrations for various components (LLMs, vector stores, retrievers).
-All dependencies in this package are optional to keep the package as lightweight as possible.
-
-### Partner packages
-
-While the long tail of integrations is in `langchain-community`, we split popular integrations into their own packages (e.g. `langchain-openai`, `langchain-anthropic`, etc).
-This was done in order to improve support for these important integrations.
-
-### [`langgraph`](https://langchain-ai.github.io/langgraph)
-
-`langgraph` is an extension of `langchain` aimed at
-building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
-
-LangGraph exposes high level interfaces for creating common types of agents, as well as a low-level API for composing custom flows.
-
-### [`langserve`](/docs/langserve)
-
-A package to deploy LangChain chains as REST APIs. Makes it easy to get a production ready API up and running.
-
-### [LangSmith](https://docs.smith.langchain.com)
-
-A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
-
-
+* Conceptual Guide: [LangChain Architecture](/docs/concepts/architecture)
## Runnable interface