diff --git a/README.md b/README.md
index 01c6773370aed..27448baea9a8c 100644
--- a/README.md
+++ b/README.md
@@ -38,24 +38,25 @@ conda install langchain -c conda-forge
For these applications, LangChain simplifies the entire application lifecycle:
-- **Open-source libraries**: Build your applications using LangChain's [modular building blocks](https://python.langchain.com/v0.2/docs/concepts/#langchain-expression-language-lcel) and [components](https://python.langchain.com/v0.2/docs/concepts/#components). Integrate with hundreds of [third-party providers](https://python.langchain.com/v0.2/docs/integrations/platforms/).
+- **Open-source libraries**: Build your applications using LangChain's open-source [building blocks](https://python.langchain.com/v0.2/docs/concepts#langchain-expression-language-lcel), [components](https://python.langchain.com/v0.2/docs/concepts), and [third-party integrations](https://python.langchain.com/v0.2/docs/integrations/platforms/).
+Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support.
- **Productionization**: Inspect, monitor, and evaluate your apps with [LangSmith](https://docs.smith.langchain.com/) so that you can constantly optimize and deploy with confidence.
-- **Deployment**: Turn any chain into a REST API with [LangServe](https://python.langchain.com/v0.2/docs/langserve/).
+- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/).
### Open-source libraries
- **`langchain-core`**: Base abstractions and LangChain Expression Language.
- **`langchain-community`**: Third party integrations.
- Some integrations have been further split into **partner packages** that only rely on **`langchain-core`**. Examples include **`langchain_openai`** and **`langchain_anthropic`**.
- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
-- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
+- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
### Productionization:
- **[LangSmith](https://docs.smith.langchain.com/)**: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.
### Deployment:
-- **[LangServe](https://python.langchain.com/v0.2/docs/langserve/)**: A library for deploying LangChain chains as REST APIs.
+- **[LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants.
-
+
## 𧱠What can you build with LangChain?
@@ -106,7 +107,7 @@ Retrieval Augmented Generation involves [loading data](https://python.langchain.
**π€ Agents**
-Agents allow an LLM autonomy over how a task is accomplished. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. LangChain provides a [standard interface for agents](https://python.langchain.com/v0.2/docs/concepts/#agents) along with the [LangGraph](https://github.com/langchain-ai/langgraph) extension for building custom agents.
+Agents allow an LLM autonomy over how a task is accomplished. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. LangChain provides a [standard interface for agents](https://python.langchain.com/v0.2/docs/concepts/#agents), along with [LangGraph](https://github.com/langchain-ai/langgraph) for building custom agents.
## π Documentation
@@ -120,10 +121,9 @@ Please see [here](https://python.langchain.com) for full documentation, which in
## π Ecosystem
-- [π¦π οΈ LangSmith](https://docs.smith.langchain.com/): Tracing and evaluating your language model applications and intelligent agents to help you move from prototype to production.
-- [π¦πΈοΈ LangGraph](https://langchain-ai.github.io/langgraph/): Creating stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives.
-- [π¦π LangServe](https://python.langchain.com/docs/langserve): Deploying LangChain runnables and chains as REST APIs.
-- [LangChain Templates](https://python.langchain.com/v0.2/docs/templates/): Example applications hosted with LangServe.
+- [π¦π οΈ LangSmith](https://docs.smith.langchain.com/): Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
+- [π¦πΈοΈ LangGraph](https://langchain-ai.github.io/langgraph/): Create stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
+- [π¦π LangServe](https://python.langchain.com/docs/langserve): Deploy LangChain runnables and chains as REST APIs.
## π Contributing
diff --git a/docs/docs/concepts.mdx b/docs/docs/concepts.mdx
index 410bca3938faa..d811e7054a6ec 100644
--- a/docs/docs/concepts.mdx
+++ b/docs/docs/concepts.mdx
@@ -51,8 +51,8 @@ A developer platform that lets you debug, test, evaluate, and monitor LLM applic
diff --git a/docs/docs/how_to/installation.mdx b/docs/docs/how_to/installation.mdx
index 95c8028b458e5..29614d306c147 100644
--- a/docs/docs/how_to/installation.mdx
+++ b/docs/docs/how_to/installation.mdx
@@ -72,7 +72,7 @@ pip install langchain-experimental
```
### LangGraph
-`langgraph` is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain.
+`langgraph` is a library for building stateful, multi-actor applications with LLM. It integrates smoothly with LangChain, but can be used without it.
Install with:
```bash
diff --git a/docs/docs/introduction.mdx b/docs/docs/introduction.mdx
index c66f195db2057..0b143fcb8ff72 100644
--- a/docs/docs/introduction.mdx
+++ b/docs/docs/introduction.mdx
@@ -8,9 +8,10 @@ sidebar_class_name: hidden
**LangChain** is a framework for developing applications powered by large language models (LLMs).
LangChain simplifies every stage of the LLM application lifecycle:
-- **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts#langchain-expression-language-lcel) and [components](/docs/concepts). Hit the ground running using [third-party integrations](/docs/integrations/platforms/) and [Templates](/docs/templates).
+- **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts#langchain-expression-language-lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/platforms/).
+Use [LangGraph](/docs/concepts/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support.
- **Productionization**: Use [LangSmith](https://docs.smith.langchain.com/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.
-- **Deployment**: Turn any chain into an API with [LangServe](/docs/langserve).
+- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/).
import ThemedImage from '@theme/ThemedImage';
import useBaseUrl from '@docusaurus/useBaseUrl';
@@ -18,8 +19,8 @@ import useBaseUrl from '@docusaurus/useBaseUrl';
@@ -30,7 +31,7 @@ Concretely, the framework consists of the following open-source libraries:
- **`langchain-community`**: Third party integrations.
- Partner packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Some integrations have been further split into their own lightweight packages that only depend on **`langchain-core`**.
- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
-- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
+- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
- **[LangServe](/docs/langserve)**: Deploy LangChain chains as REST APIs.
- **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications.
@@ -43,15 +44,17 @@ These docs focus on the Python LangChain library. [Head here](https://js.langcha
## [Tutorials](/docs/tutorials)
-If you're looking to build something specific or are more of a hands-on learner, check out our [tutorials](/docs/tutorials).
+If you're looking to build something specific or are more of a hands-on learner, check out our [tutorials section](/docs/tutorials).
This is the best place to get started.
These are the best ones to get started with:
+
- [Build a Simple LLM Application](/docs/tutorials/llm_chain)
- [Build a Chatbot](/docs/tutorials/chatbot)
- [Build an Agent](/docs/tutorials/agents)
+- [Introduction to LangGraph](https://langchain-ai.github.io/langgraph/tutorials/introduction/)
-Explore the full list of tutorials [here](/docs/tutorials).
+Explore the full list of LangChain tutorials [here](/docs/tutorials), and check out other [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/).
## [How-to guides](/docs/how_to)
@@ -60,10 +63,14 @@ Explore the full list of tutorials [here](/docs/tutorials).
These how-to guides donβt cover topics in depth β youβll find that material in the [Tutorials](/docs/tutorials) and the [API Reference](https://api.python.langchain.com/en/latest/).
However, these guides will help you quickly accomplish common tasks.
+Check out [LangGraph-specific how-tos here](https://langchain-ai.github.io/langgraph/how-tos/).
+
## [Conceptual guide](/docs/concepts)
Introductions to all the key parts of LangChain youβll need to know! [Here](/docs/concepts) you'll find high level explanations of all LangChain concepts.
+For a deeper dive into LangGraph concepts, check out [this page](https://langchain-ai.github.io/langgraph/concepts/).
+
## [API reference](https://api.python.langchain.com)
Head to the reference section for full documentation of all classes and methods in the LangChain Python packages.
@@ -73,10 +80,7 @@ Head to the reference section for full documentation of all classes and methods
Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
### [π¦πΈοΈ LangGraph](https://langchain-ai.github.io/langgraph)
-Build stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain primitives.
-
-### [π¦π LangServe](/docs/langserve)
-Deploy LangChain runnables and chains as REST APIs.
+Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
## Additional resources
diff --git a/docs/static/img/langchain_stack.png b/docs/static/img/langchain_stack.png
index 48c2772cbceaf..4d2f1a3767bce 100644
Binary files a/docs/static/img/langchain_stack.png and b/docs/static/img/langchain_stack.png differ
diff --git a/docs/static/svg/langchain_stack_june_2024.svg b/docs/static/svg/langchain_stack_june_2024.svg
new file mode 100644
index 0000000000000..84b7181f46460
--- /dev/null
+++ b/docs/static/svg/langchain_stack_june_2024.svg
@@ -0,0 +1,47 @@
+
diff --git a/docs/static/svg/langchain_stack_june_2024_dark.svg b/docs/static/svg/langchain_stack_june_2024_dark.svg
new file mode 100644
index 0000000000000..f9249bf80c7b9
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+++ b/docs/static/svg/langchain_stack_june_2024_dark.svg
@@ -0,0 +1,47 @@
+
diff --git a/libs/community/README.md b/libs/community/README.md
index be0ffef29a3c7..1087c6d5efd2d 100644
--- a/libs/community/README.md
+++ b/libs/community/README.md
@@ -15,7 +15,7 @@ LangChain Community contains third-party integrations that implement the base in
For full documentation see the [API reference](https://api.python.langchain.com/en/stable/community_api_reference.html).
-
+
## π Releases & Versioning
@@ -27,4 +27,4 @@ All changes will be accompanied by a patch version increase.
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
-For detailed information on how to contribute, see the [Contributing Guide](https://python.langchain.com/docs/contributing/).
\ No newline at end of file
+For detailed information on how to contribute, see the [Contributing Guide](https://python.langchain.com/docs/contributing/).
diff --git a/libs/core/README.md b/libs/core/README.md
index 7de5b5a7f1b66..129f6536d5108 100644
--- a/libs/core/README.md
+++ b/libs/core/README.md
@@ -53,7 +53,7 @@ LangChain Core compiles LCEL sequences to an _optimized execution plan_, with au
For more check out the [LCEL docs](https://python.langchain.com/docs/expression_language/).
-
+
For more advanced use cases, also check out [LangGraph](https://github.com/langchain-ai/langgraph), which is a graph-based runner for cyclic and recursive LLM workflows.