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**Description:** This PR adds the Python SDK types necessary for langgraph platform users to inject their own custom encryption-at-rest functions. See [docs PR](https://github.com/langchain-ai/docs/pull/1715) for more details. note: this PR adds a starlette dev dependency so that custom encryption can access BaseUser information. **Issue:** required for LSD-172 **Dependencies:** - [depended upon by associated langgraph-api changes](https://github.com/langchain-ai/langgraph-api/pull/1773)(this PR must merge before that one) - [docs PR](https://github.com/langchain-ai/docs/pull/1715) **TODO:** - [x] move docs to docs repo - [x] bump package versions before merge --------- Signed-off-by: Connor Braa <cwlbraa@langchain.dev> Co-authored-by: Claude <noreply@anthropic.com>
LangGraph Python SDK
This repository contains the Python SDK for interacting with the LangSmith Deployment REST API.
Quick Start
To get started with the Python SDK, install the package
pip install -U langgraph-sdk
You will need a running LangGraph API server. If you're running a server locally using langgraph-cli, SDK will automatically point at http://localhost:8123, otherwise
you would need to specify the server URL when creating a client.
from langgraph_sdk import get_client
# If you're using a remote server, initialize the client with `get_client(url=REMOTE_URL)`
client = get_client()
# List all assistants
assistants = await client.assistants.search()
# We auto-create an assistant for each graph you register in config.
agent = assistants[0]
# Start a new thread
thread = await client.threads.create()
# Start a streaming run
input = {"messages": [{"role": "human", "content": "what's the weather in la"}]}
async for chunk in client.runs.stream(thread['thread_id'], agent['assistant_id'], input=input):
print(chunk)