The OpenAI Agents SDK lets you build agentic applications powered by OpenAI models. Use LangSmith to trace OpenAI Agents SDK runs, including agent steps, model calls, tool calls, and handoffs.Documentation Index
Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
Use this file to discover all available pages before exploring further.
- Python
- JavaScript
Installation
Requires Python SDK version
langsmith>=0.3.15.pip install "langsmith[openai-agents]"
Environment configuration
Shell
export LANGSMITH_API_KEY=<your-api-key>
export OPENAI_API_KEY=<your-openai-api-key>
# Optional: set a project for your traces
export LANGSMITH_PROJECT=<your-project-name>
# For LangSmith API keys linked to multiple workspaces, set the LANGSMITH_WORKSPACE_ID environment variable to specify which workspace to use.
export LANGSMITH_WORKSPACE_ID=<your-workspace-id>
Quick start
Integrate LangSmith tracing with the OpenAI Agents SDK by using theOpenAIAgentsTracingProcessor class.import asyncio
from agents import Agent, Runner, set_trace_processors
from langsmith.integrations.openai_agents_sdk import OpenAIAgentsTracingProcessor
async def main():
agent = Agent(
name="Captain Obvious",
instructions="You are Captain Obvious, the world's most literal technical support agent.",
)
question = "Why is my code failing when I try to divide by zero? I keep getting this error message."
result = await Runner.run(agent, question)
print(result.final_output)
if __name__ == "__main__":
set_trace_processors([OpenAIAgentsTracingProcessor()])
asyncio.run(main())
Installation
Requires JS SDK version
langsmith>=0.5.25.npm install langsmith @openai/agents zod
Environment configuration
Shell
export LANGSMITH_API_KEY=<your-api-key>
export OPENAI_API_KEY=<your-openai-api-key>
# Optional: set a project for your traces
export LANGSMITH_PROJECT=<your-project-name>
# For LangSmith API keys linked to multiple workspaces, set the LANGSMITH_WORKSPACE_ID environment variable to specify which workspace to use.
export LANGSMITH_WORKSPACE_ID=<your-workspace-id>
Installing
OpenAIAgentsTracingProcessor is an explicit opt-in to tracing. The processor posts traces even when LANGSMITH_TRACING is not set, and nested traceable calls inside agent tools inherit the active trace context.Quick start
RegisterOpenAIAgentsTracingProcessor with the OpenAI Agents SDK before running agents.import { Agent, run, setTraceProcessors, tool } from "@openai/agents";
import { z } from "zod";
import { OpenAIAgentsTracingProcessor } from "langsmith/wrappers/openai_agents";
setTraceProcessors([new OpenAIAgentsTracingProcessor()]);
const getWeather = tool({
name: "get_weather",
description: "Get the current weather for a city",
parameters: z.object({
city: z.string().describe("The city to get weather for"),
}),
execute: async ({ city }: { city: string }) => {
return `The weather in ${city} is sunny.`;
},
});
const agent = new Agent({
name: "WeatherAgent",
instructions: "You are a helpful assistant. Use the get_weather tool when asked about weather.",
model: "gpt-5-nano",
tools: [getWeather],
});
const result = await run(agent, "What's the weather in San Francisco?");
console.log(result.finalOutput);
Configure the processor
Pass options to the processor to set a LangSmith client, project, tags, metadata, or root trace name.import { Agent, run, setTraceProcessors } from "@openai/agents";
import { Client } from "langsmith";
import { OpenAIAgentsTracingProcessor } from "langsmith/wrappers/openai_agents";
const client = new Client();
const processor = new OpenAIAgentsTracingProcessor({
client,
projectName: "openai-agents-demo",
name: "Support agent workflow",
tags: ["openai-agents"],
metadata: {
environment: "development",
},
});
setTraceProcessors([processor]);
const agent = new Agent({
name: "SupportAgent",
instructions: "You are a concise support agent.",
model: "gpt-5-nano",
});
const result = await run(agent, "Help me reset my password.");
console.log(result.finalOutput);
Nest traceable calls in tools
You can use traceable inside OpenAI Agents SDK tool handlers. LangSmith nests those runs under the active tool span.import { Agent, run, setTraceProcessors, tool } from "@openai/agents";
import { z } from "zod";
import { traceable } from "langsmith/traceable";
import { OpenAIAgentsTracingProcessor } from "langsmith/wrappers/openai_agents";
setTraceProcessors([new OpenAIAgentsTracingProcessor()]);
const lookupOrder = traceable(
async (orderId: string) => {
return { orderId, status: "shipped" };
},
{ name: "lookup_order" }
);
const orderStatus = tool({
name: "order_status",
description: "Look up the status of an order",
parameters: z.object({
orderId: z.string().describe("The order ID to look up"),
}),
execute: async ({ orderId }: { orderId: string }) => {
return JSON.stringify(await lookupOrder(orderId));
},
});
const agent = new Agent({
name: "OrdersAgent",
instructions: "Use the order_status tool to answer order questions.",
model: "gpt-5-nano",
tools: [orderStatus],
});
await run(agent, "Where is order 123?");
Flush traces in serverless environments
When tracing in serverless environments, flush pending traces before the process exits.import { Agent, run, setTraceProcessors } from "@openai/agents";
import { Client } from "langsmith";
import { OpenAIAgentsTracingProcessor } from "langsmith/wrappers/openai_agents";
const client = new Client();
const processor = new OpenAIAgentsTracingProcessor({ client });
setTraceProcessors([processor]);
try {
const agent = new Agent({
name: "SupportAgent",
instructions: "You are a concise support agent.",
model: "gpt-5-nano",
});
const result = await run(agent, "Help me reset my password.");
console.log(result.finalOutput);
} finally {
await processor.forceFlush();
}
Connect these docs to Claude, VSCode, and more via MCP for real-time answers.