NeMo Relay LangChain Integration

Use the nemo_relay.integrations.langchain package to add NeMo Relay observability to LangChain agents.

Setup

Install the LangChain integration extra in your application environment.

uv

pip

uv add "nemo-relay[langchain]"

The example below uses the NVIDIA LangChain provider. Install that provider extra too if you want to run the example as written:

uv

pip

uv add "nemo-relay[langchain,langchain-nvidia]"

Usage Example

import asyncio
import nemo_relay
from langchain.agents import create_agent
from langchain_core.tools import tool
from nemo_relay.integrations.langchain import NemoRelayCallbackHandler, NemoRelayMiddleware
@tool
def get_weather(location: str) -> str:
    """Get the current weather for a location."""
    return f"The weather in {location} is sunny and 72 degrees."
agent = create_agent(
    model="nvidia:nvidia/nemotron-3-nano-30b-a3b",
    tools=[get_weather],
    middleware=[NemoRelayMiddleware()],
    system_prompt="Use tools when they are relevant. Keep the final answer brief.",
)
input_payload = {
    "messages": [
        {
            "role": "user",
            "content": "What is the weather in San Francisco?",
        }
    ]
}
with nemo_relay.scope.scope("langchain-request", nemo_relay.ScopeType.Agent):
    result = asyncio.run(
        agent.ainvoke(input_payload, config={"callbacks": [NemoRelayCallbackHandler()]})
    )
final_message = result["messages"][-1]
print(f"Final response: {final_message.content}")

Verify the Integration

The integration works correctly when:

The agent run completes and prints a final response.
The langchain-request scope contains the managed model call.
Tool activity appears under the same request when the agent decides to use get_weather.

Observability

Refer to Observability for details on exporting NeMo Relay observability data to third-party systems.