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docs: get started with langgraph platform (#2469)
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Eugene Yurtsev
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# Quick Start: Launch Local LangGraph Server
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This is a quick start guide to help you get a LangGraph app up and running locally.
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!!! info "Requirements"
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- [LangGraph CLI](https://langchain-ai.github.io/langgraph/cloud/reference/cli/): Requires langchain-cli[inmem] >= 0.1.58
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## Install the LangGraph CLI
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```bash
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pip install "langgraph-cli[inmem]==0.1.58" python-dot-env
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```
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## 🌱 Create a LangGraph App
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Create a new app from the `react-agent` template. This template is a simple agent that can be flexibly extended to many tools.
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=== "Python Server"
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```shell
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langgraph new path/to/your/app --template react-agent-python
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```
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=== "Node Server"
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```shell
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langgraph new path/to/your/app --template react-agent-js
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```
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!!! tip "Additional Templates"
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If you use `langgraph new` without specifying a template, you will be presented with an interactive menu that will allow you to choose from a list of available templates.
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## Create a `.env` file
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You will find a `.env.example` in the root of your new LangGraph app. Create
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a `.env` file in the root of your new LangGraph app and copy the contents of the `.env.example` file into it, filling in the necessary API keys:
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```bash
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LANGSMITH_API_KEY=lsv2...
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TAVILY_API_KEY=tvly-...
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ANTHROPIC_API_KEY=sk-
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OPENAI_API_KEY=sk-...
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```
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<details><summary>Get API Keys</summary>
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<ul>
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<li> <b>LANGSMITH_API_KEY</b>: Go to the <a href="https://smith.langchain.com/settings">LangSmith Settings page</a>. Then clck <b>Create API Key</b>.
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</li>
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<li>
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<b>ANTHROPIC_API_KEY</b>: Get an API key from <a href="https://console.anthropic.com/">Anthropic</a>.
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</li>
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<li>
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<b>OPENAI_API_KEY</b>: Get an API key from <a href="https://openai.com/">OpenAI</a>.
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</li>
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<li>
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<b>TAVILY_API_KEY</b>: Get an API key on the <a href="https://app.tavily.com/">Tavily website</a>.
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</li>
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</ul>
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</details>
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## 🚀 Launch LangGraph Server
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```shell
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langgraph dev
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```
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This will start up the LangGraph API server locally. If this runs successfully, you should see something like:
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> Ready!
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>
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> - API: [http://localhost:8123](http://localhost:8123/)
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>
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> - Docs: http://localhost:8123/docs
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>
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> - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:8123
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!!! note "In-Memory Mode"
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The `langgraph dev` command starts LangGraph Server in an in-memory mode. This mode is suitable for development and testing purposes. For production use, you should deploy LangGraph Server with access to a persistent storage backend.
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If you want to test your application with a persistent storage backend, you can use the `langgraph up` command instead of `langgraph dev`. You will
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need to have `docker` installed on your machine to use this command.
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## LangGraph Studio Web UI
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Test your graph in the LangGraph Studio Web UI by visiting the URL provided in the output of the `langgraph up` command.
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> - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:8123
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!!! warning "Safari Compatibility"
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Currently, LangGraph Studio Web does not support Safari when running a server locally.
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## Test the API
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=== "Python SDK (Async)"
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**Install the LangGraph Python SDK**
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```shell
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pip install langgraph-sdk
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```
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**Send a message to the assistant (threadless run)**
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```python
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from langgraph_sdk import get_client
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client = get_client(url="http://localhost:8123")
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async for chunk in client.runs.stream(
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None, # Threadless run
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"agent", # Name of assistant. Defined in langgraph.json.
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input={
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"messages": [{
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"role": "human",
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"content": "What is LangGraph?",
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}],
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},
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stream_mode="updates",
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):
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print(f"Receiving new event of type: {chunk.event}...")
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print(chunk.data)
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print("\n\n")
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```
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=== "Python SDK (Sync)"
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**Install the LangGraph Python SDK**
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```shell
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pip install langgraph-sdk
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```
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**Send a message to the assistant (threadless run)**
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```python
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from langgraph_sdk import get_sync_client
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client = get_sync_client(url="http://localhost:8123")
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for chunk in client.runs.stream(
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None, # Threadless run
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"agent", # Name of assistant. Defined in langgraph.json.
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input={
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"messages": [{
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"role": "human",
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"content": "What is LangGraph?",
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}],
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},
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stream_mode="updates",
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):
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print(f"Receiving new event of type: {chunk.event}...")
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print(chunk.data)
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print("\n\n")
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```
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=== "Javascript SDK"
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**Install the LangGraph JS SDK**
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```shell
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npm install @langchain/langgraph-sdk
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```
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**Send a message to the assistant (threadless run)**
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```js
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const { Client } = await import("@langchain/langgraph-sdk");
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// only set the apiUrl if you changed the default port when calling langgraph up
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const client = new Client({ apiUrl: "http://localhost:8123"});
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const streamResponse = client.runs.stream(
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null, // Threadless run
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"agent", // Assistant ID
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{
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input: {
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"messages": [
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{ "role": "user", "content": "What is LangGraph?"}
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]
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},
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streamMode: "messages",
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}
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);
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for await (const chunk of streamResponse) {
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console.log(`Receiving new event of type: ${chunk.event}...`);
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console.log(JSON.stringify(chunk.data));
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console.log("\n\n");
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}
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```
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=== "Rest API"
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```bash
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curl -s --request POST \
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--url "http://localhost:8123/runs/stream" \
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--header 'Content-Type: application/json' \
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--data "{
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\"assistant_id\": \"agent\",
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\"input\": {
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\"messages\": [
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{
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\"role\": \"human\",
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\"content\": \"What is LangGraph?\"
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}
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]
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},
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\"stream_mode\": \"updates\"
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}"
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```
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!!! tip "Auth"
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If you're connecting to a remote server, you will need to provide a LangSmith
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API Key for authorization. Please see the API Reference for the clients
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for more information.
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## Next Steps
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Now that you have a LangGraph app running locally, take your journey further by exploring deployment and advanced features:
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### 🌐 Deploy to LangGraph Cloud
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- **[LangGraph Cloud QuickStart](../../cloud/quick_start.md)**: Deploy your LangGraph app using LangGraph Cloud.
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### 📚 Learn More about LangGraph Platform
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Expand your knowledge with these resources:
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- **[LangGraph Platform Concepts](../../concepts/index.md#langgraph-platform)**: Understand the foundational concepts of the LangGraph Platform.
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- **[LangGraph Platform How-to Guides](../../how-tos/index.md#langgraph-platform)**: Discover step-by-step guides to build and deploy applications.
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### 🛠️ Developer References
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Access detailed documentation for development and API usage:
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- **[LangGraph Server API Reference](../../cloud/reference/api/api_ref.html)**: Explore the LangGraph Server API documentation.
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- **[Python SDK Reference](../../cloud/reference/sdk/python_sdk_ref.md)**: Explore the Python SDK API Reference.
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- **[JS/TS SDK Reference](../../cloud/reference/sdk/js_ts_sdk_ref.md)**: Explore the Python SDK API Reference.
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