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## Summary - Adds a `langsmith_tracing` parameter to `runs.create()`, `runs.stream()`, and `runs.wait()` on both async and sync SDK clients - Accepts a `LangSmithTracing` TypedDict with optional `project_name` and `example_id` fields - Maps to the server's existing `langsmith_tracer` payload key, enabling users to route traces to specific LangSmith projects or associate with dataset examples from the SDK ## Test plan - [x] Unit tests verify payload serialization (langsmith_tracing → langsmith_tracer mapping) - [x] Unit tests verify key is excluded when param not provided - [x] Unit tests verify partial configs (project_name only) work - [x] API parity tests pass (async/sync client signatures match) - [x] Full test suite passes (86 tests) - [x] Lint + type check pass Release Notes: Added `langsmith_tracing` parameter to `runs.create()`, `runs.stream()`, and `runs.wait()` in the Python SDK, allowing users to route traces to a specific LangSmith project or associate with a dataset example. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Will Fu-Hinthorn <will@langchain.dev> Co-authored-by: Claude Opus 4.6 (1M context) <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)