mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-10-19 22:41:43 +02:00
@@ -38,6 +38,46 @@ Ready!
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We can now interact with the API server using the LangGraph SDK. First, we need to start our client, select our assistant (in this case a graph we called "agent", make sure to select the proper assistant you wish to test).
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You can either initialize by passing authentication or by setting an environment variable.
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#### Initialize with authentication
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=== "Python"
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```python
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from langgraph_sdk import get_client
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# only pass the url argument to get_client() if you changed the default port when calling langgraph up
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client = get_client(url=<DEPLOYMENT_URL>,api_key=<LANGCHAIN_API_KEY>)
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assistant_id = "agent"
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thread = await client.threads.create()
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```
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=== "Javascript"
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```js
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import { Client } from "@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: <DEPLOYMENT_URL>, apiKey: <LANGCHAIN_API_KEY> });
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const assistantId = "agent"
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const thread = await client.threads.create();
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```
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=== "CURL"
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```bash
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curl --request POST \
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--url <DEPLOYMENT_URL>/threads \
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--header 'Content-Type: application/json'
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--header 'x-api-key: <LANGCHAIN_API_KEY>'
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```
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#### Initialize with environment variables
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If you have a `LANGCHAIN_API_KEY` set in your environment, you do not need to explicitly pass authentication to the client
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=== "Python"
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```python
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@@ -60,6 +100,14 @@ We can now interact with the API server using the LangGraph SDK. First, we need
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const thread = await client.threads.create();
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```
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=== "CURL"
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```bash
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curl --request POST \
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--url <DEPLOYMENT_URL>/threads \
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--header 'Content-Type: application/json'
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```
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Now we can invoke our graph to ensure it is working. Make sure to change the input to match the proper schema for your graph.
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=== "Python"
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@@ -96,4 +144,39 @@ Now we can invoke our graph to ensure it is working. Make sure to change the inp
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}
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```
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=== "CURL"
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```bash
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curl --request POST \
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--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/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\": {\"messages\": [{\"role\": \"human\", \"content\": \"what's the weather in sf\"}]},
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\"stream_mode\": [
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\"events\"
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]
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}" | \
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sed 's/\r$//' | \
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awk '
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/^event:/ {
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if (data_content != "") {
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print data_content "\n"
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}
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sub(/^event: /, "Receiving event of type: ", $0)
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printf "%s...\n", $0
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data_content = ""
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}
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/^data:/ {
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sub(/^data: /, "", $0)
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data_content = $0
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}
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END {
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if (data_content != "") {
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print data_content "\n"
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}
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}
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'
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```
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If your graph works correctly, you should see your graph output displayed in the console. Of course, there are many more ways you might need to test your graph, for a full list of commands you can send with the SDK, see the [Python](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/python_sdk_ref/) and [JS/TS](https://langchain-ai.github.io/langgraph/cloud/reference/sdk/js_ts_sdk_ref/) references.
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