diff --git a/README.md b/README.md
index 511d6e307205..fffd119c9aab 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
⚡ Building applications with LLMs through composability ⚡
-[](https://github.com/langchain-ai/langchainjs/actions/workflows/ci.yml)  [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai) [](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchainjs)
+  [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai) [](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchainjs)
[
](https://codespaces.new/langchain-ai/langchainjs)
Looking for the Python version? Check out [LangChain](https://github.com/langchain-ai/langchain).
@@ -43,15 +43,13 @@ This framework consists of several parts.
The LangChain libraries themselves are made up of several different packages.
-- **[`@langchain/core`](https://github.com/langchain-ai/langchainjs/blob/main/langchain-core)**: Base abstractions and LangChain Expression Language.
+- **[`@langchain/core`](https://github.com/langchain-ai/langchainjs/blob/main/langchain-core)**: Base abstractions.
- **[`@langchain/community`](https://github.com/langchain-ai/langchainjs/blob/main/libs/langchain-community)**: Third party integrations.
- **[`langchain`](https://github.com/langchain-ai/langchainjs/blob/main/langchain)**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
- **[LangGraph.js](https://langchain-ai.github.io/langgraphjs/)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. 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.
Integrations may also be split into their own compatible packages.
-
-
This library aims to assist in the development of those types of applications. Common examples of these applications include:
**❓Question Answering over specific documents**
diff --git a/langchain-core/README.md b/langchain-core/README.md
index 40ea1f730e47..d63669067142 100644
--- a/langchain-core/README.md
+++ b/langchain-core/README.md
@@ -1,6 +1,6 @@
# 🦜🍎️ @langchain/core
-[](https://github.com/langchain-ai/langchainjs/actions/workflows/ci.yml)  [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai)
+ [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai)
`@langchain/core` contains the core abstractions and schemas of LangChain.js, including base classes for language models,
chat models, vectorstores, retrievers, and runnables.
@@ -8,7 +8,7 @@ chat models, vectorstores, retrievers, and runnables.
## 💾 Quick Install
```bash
-$ yarn add @langchain/core
+yarn add @langchain/core
```
## 🤔 What is this?
@@ -21,7 +21,7 @@ The benefit of having these abstractions is that any provider can implement the
For example, you can install other provider-specific packages like this:
```bash
-$ yarn add @langchain/openai
+yarn add @langchain/openai
```
And use them as follows:
@@ -72,22 +72,6 @@ leigh
Note that for compatibility, all used LangChain packages (including the base LangChain package, which itself depends on core!) must share the same version of `@langchain/core`.
This means that you may need to install/resolve a specific version of `@langchain/core` that matches the dependencies of your used packages.
-## 🔗 What is LangChain Expression Language?
-
-LangChain Core also contains LangChain Expression Language, or LCEL, a runtime that allows users to compose arbitrary sequences together and get several benefits that are important when building LLM applications.
-We call these sequences “runnables”.
-
-All runnables expose the same interface with single-invocation, batch, streaming and async methods.
-This design is useful because it is not enough to have a single sync interface when building an LLM application.
-Batch is needed for efficient processing of many inputs.
-Streaming (and streaming of intermediate steps) is needed to show the user that progress is being made.
-Async interfaces are nice when moving into production.
-Rather than having to write multiple implementations for all of those, LCEL allows you to write a runnable once and invoke it in many different ways.
-
-For more check out the [LCEL docs](https://js.langchain.com/docs/concepts/lcel).
-
-
-
## 📕 Releases & Versioning
`@langchain/core` is currently on version `0.3.x`.
diff --git a/langchain/README.md b/langchain/README.md
index 511d6e307205..f0e1d4867e28 100644
--- a/langchain/README.md
+++ b/langchain/README.md
@@ -2,7 +2,7 @@
⚡ Building applications with LLMs through composability ⚡
-[](https://github.com/langchain-ai/langchainjs/actions/workflows/ci.yml)  [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai) [](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchainjs)
+[](https://opensource.org/licenses/MIT)  [](https://twitter.com/langchainai) [](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchainjs)
[
](https://codespaces.new/langchain-ai/langchainjs)
Looking for the Python version? Check out [LangChain](https://github.com/langchain-ai/langchain).
@@ -43,15 +43,13 @@ This framework consists of several parts.
The LangChain libraries themselves are made up of several different packages.
-- **[`@langchain/core`](https://github.com/langchain-ai/langchainjs/blob/main/langchain-core)**: Base abstractions and LangChain Expression Language.
+- **[`@langchain/core`](https://github.com/langchain-ai/langchainjs/blob/main/langchain-core)**: Base abstractions.
- **[`@langchain/community`](https://github.com/langchain-ai/langchainjs/blob/main/libs/langchain-community)**: Third party integrations.
- **[`langchain`](https://github.com/langchain-ai/langchainjs/blob/main/langchain)**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
- **[LangGraph.js](https://langchain-ai.github.io/langgraphjs/)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. 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.
Integrations may also be split into their own compatible packages.
-
-
This library aims to assist in the development of those types of applications. Common examples of these applications include:
**❓Question Answering over specific documents**