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Sydney RunkleandGitHub
228a08b966
* Migrate to `uv` * Format `pyproject.toml` files properly * Remove upper bounds on dependencies, and bounds on dev dependencies (we should be using latest) * Move to hatch for packaing In the future we should: * Set up dependabot / automate lockfile updates and tests * Add tests for min compatible versions (I'll do this right after merge) * Use dynamic versioning * Bump `pydantic` to v2.11.4 in the lockfile, we have some tests failing
LangGraph Python SDK
This repository contains the Python SDK for interacting with the LangGraph Platform 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)