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oss: slight rfc on quickstart #1636

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39 changes: 2 additions & 37 deletions src/oss/langchain/overview.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -29,47 +29,11 @@ We recommend you use LangChain if you want to quickly build agents and autonomou

LangChain [agents](/oss/langchain/agents) are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. You do not need to know LangGraph for basic LangChain agent usage.

## <Icon icon="download" size={20} /> Install

:::python
<CodeGroup>
```bash pip
pip install -U langchain
# Requires Python 3.10+
```

```bash uv
uv add langchain
# Requires Python 3.10+
```
</CodeGroup>
:::
:::js
<CodeGroup>
```bash npm
npm install langchain @langchain/core
```

```bash pnpm
pnpm add langchain @langchain/core
```

```bash yarn
yarn add langchain @langchain/core
```

```bash bun
bun add langchain @langchain/core
```
</CodeGroup>
:::

## <Icon icon="wand-magic-sparkles" /> Create an agent

:::python
```python
# pip install -qU "langchain[anthropic]" to call the model

# pip install -qU langchain "langchain[anthropic]"
from langchain.agents import create_agent

def get_weather(city: str) -> str:
Expand Down Expand Up @@ -119,6 +83,7 @@ console.log(
```
:::

See the [Installation instructions](/oss/langchain/install) and [Quickstart guide](/oss/langchain/quickstart) to get started building your own agents and applications with LangChain.

## <Icon icon="star" size={20} /> Core benefits

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22 changes: 17 additions & 5 deletions src/oss/langchain/quickstart.mdx
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Expand Up @@ -4,14 +4,24 @@ title: Quickstart

This quickstart takes you from a simple setup to a fully functional AI agent in just a few minutes.

## Requirements

For these examples, you will need to:

* [Install](/oss/langchain/install) the LangChain package
* Set up a [Claude (Anthropic)](https://www.anthropic.com/) account and get an API key
* Set the `ANTHROPIC_API_KEY` environment variable in your terminal

<Tip>
**LangChain Docs MCP server**

If you're using an AI coding assistant, you should install the [LangChain Docs MCP server](/use-these-docs) to get the most out of it. This ensures your agent has access to the latest documentation and examples.
</Tip>

## Build a basic agent

Start by creating a simple agent that can answer questions and call tools. The agent will use Claude Sonnet 4.5 as its language model, a basic weather function as a tool, and a simple prompt to guide its behavior.

<Info>
For this example, you will need to set up a [Claude (Anthropic)](https://www.anthropic.com/) account and get an API key. Then, set the `ANTHROPIC_API_KEY` environment variable in your terminal.
</Info>

:::python
```python
from langchain.agents import create_agent
Expand Down Expand Up @@ -205,7 +215,7 @@ Let's walk through each step:
:::
</Step>
<Step title="Configure your model">
Set up your [language model](/oss/langchain/models) with the right [parameters](/oss/langchain/models#parameters) for your use case:
Set up your [language model](/oss/langchain/models) with the right parameters for your use case:

:::python

Expand All @@ -232,6 +242,8 @@ Let's walk through each step:
);
```
:::

Depending on the model and provider chosen, initialization parameters may vary; refer to their reference pages for details.
</Step>
<Step title="Define response format">
:::python
Expand Down