Working with OpenAI Agents SDK

Trace OpenAI Agents SDK workflows end-to-end with LangDB—monitor model calls, tool invocations, and runner sessions via one-line init().

LangDB helps you add full tracing and observability to your OpenAI Agents SDK workflows—without changing your core logic. With a one-line initialization, LangDB captures model calls, tool invocations, and intermediate steps, giving you a complete view of how your agent operates.

Checkout: https://app.langdb.ai/sharing/threads/53b87631-de7f-431a-a049-48556f899b4d

Installation

Enable end-to-end tracing for your OpenAI Agents SDK agents by installing the pylangdb client with the openai feature flag:

pip install pylangdb[openai]

Quick Start

Export Environment Variables

Set your LangDB credentials:

export LANGDB_API_KEY="<your_langdb_api_key>"
export LANGDB_PROJECT_ID="<your_langdb_project_id>"

Initialize Tracing

Import and run the initialize before configuring your OpenAI client:

from pylangdb.openai import init
# Initialise LangDB
init()

Configure OpenAI Client and Agent Runner

# Agent SDK imports
from agents import (
    Agent,
    Runner,
    set_default_openai_client,
    RunConfig,
    ModelProvider,
    Model,
    OpenAIChatCompletionsModel
)
from openai import AsyncOpenAI

# Configure the OpenAI client with LangDB headers
client = AsyncOpenAI(
    api_key=os.environ["LANGDB_API_KEY"],
    base_url=os.environ["LANGDB_API_BASE_URL"],
    default_headers={"x-project-id": os.environ["LANGDB_PROJECT_ID"]}
)
set_default_openai_client(client)

# Create a custom model provider for advanced routing
class CustomModelProvider(ModelProvider):
    def get_model(self, model_name: str | None) -> Model:
        return OpenAIChatCompletionsModel(model=model_name, openai_client=client)

# Register your custom model provider to route model calls through LangDB
CUSTOM_MODEL_PROVIDER = CustomModelProvider()

# Assign a unique group_id to link all steps in this session trace
group_id = str(uuid.uuid4())
response = await Runner.run(
    agent,
    input="Hello, world!",
    run_config=RunConfig(
        model_provider=CUSTOM_MODEL_PROVIDER,  # Inject custom model provider
        group_id=group_id                      # Link all steps to the same trace
    )
)

Once executed, LangDB links all steps—model calls, intermediate tool usage, and runner orchestration—into a single session trace.