WEBDIENSTE/langgraph
1
0
Fork 0
mirror of https://github.com/langchain-ai/langgraph.git synced 2026-09-21 17:18:09 +02:00
Code Issues Packages Projects Releases Wiki Activity

[docs]: minor changes for testing locally (#1029)

Browse Source 
* small changes

* harrison comments

* Update docs/docs/cloud/deployment/test_locally.md

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Isaac Francisco
2024-07-16 10:43:03 -07:00
committed by GitHub
co-authored by Harrison Chase
parent 6fd1dc5697
commit 924cd1f2d8
2 changed files with 10 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docs/docs/cloud/deployment/test_locally.md
+6
View File
@@ -10,6 +10,12 @@ Install the proper packages:
pip install langgraph-cli
```
Ensure you have an API key, which you can create from the LangSmith UI (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
```python
LANGCHAIN_API_KEY = *********
```
## Start the API server
Once you have downloaded the CLI, you can run the following command to start the API server for local testing:
docs/docs/cloud/how-tos/index.md
+4 -1
View File
@@ -11,10 +11,13 @@ Welcome to the LangGraph Cloud how-to guides! These guides provide practical, st
LangGraph Cloud gives you best in class observability, testing, and hosting services. Read more about them in these how to guides:
- [How to set up app for deployment](../deployment/setup.md)
- [How to set up app for deployment (requirements.txt)](../deployment/setup.md)
- [How to set up app for deployment (pyproject.toml)](../deployment/setup_pyproject.md)
- [How to test locally](../deployment/test_locally.md)
- [How to deploy to LangGraph cloud](../deployment/cloud.md)
- [How to self-host](../deployment/self_hosted.md)
## Streaming
Streaming the results of your LLM application is vital for ensuring a good user experience, especially when your graph may call multiple models and take a long time to fully complete a run. Read about how to stream values from your graph in these how to guides: