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Nuno CamposandGitHub
eeadeb282e
## Summary - ensure both async and sync HTTP clients flush the SSE decoder after streaming - add regression tests covering trailing SSE events without a terminating blank line ## Testing - make format - make lint - make test ------ https://chatgpt.com/codex/tasks/task_e_68c9727ca9f8832d9f207323c5e02a72
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)