NeMo Flow Deep Agents Integration

Use the nemo_flow.integrations.deepagents package to add NeMo Flow observability to Deep Agents applications through the LangChain and LangGraph integration surfaces that Deep Agents builds on.

Setup

Install the Deep Agents integration extra in your application environment.

uv

uv add "nemo-flow[deepagents]"

pip

pip install "nemo-flow[deepagents]"

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

uv

uv add "nemo-flow[deepagents,langchain-nvidia]"

pip

pip install "nemo-flow[deepagents,langchain-nvidia]"

Usage Example

import nemo_flow
from deepagents import create_deep_agent
from nemo_flow.integrations.deepagents import (
    NemoFlowDeepAgentsCallbackHandler,
    add_nemo_flow_integration,
)

agent = create_deep_agent(
    **add_nemo_flow_integration(
        model="nvidia:nvidia/nemotron-3-nano-30b-a3b",
        tools=[],
        skills=["/skills/research/"],
        name="main-agent",
    )
)

input_payload = {
    "messages": [
        {
            "role": "user",
            "content": "Research recent GPU news",
        }
    ]
}

with nemo_flow.scope.scope("deepagents-request", nemo_flow.ScopeType.Agent):
    result = agent.invoke(
        input_payload,
        config={"callbacks": [NemoFlowDeepAgentsCallbackHandler()]},
    )

final_message = result["messages"][-1]
print(f"Final response: {final_message.content}")

Observability

The integration composes the existing NeMo Flow LangChain and LangGraph hooks, then emits Deep Agents-specific marks for configured skills, subagents, and human-in-the-loop lifecycle events.

It captures:

• LangChain model and tool calls through NeMo Flow managed execution.

• LangGraph run scopes through callbacks.

• Human-in-the-loop interrupt and resume marks.

• Configured skills and subagent summaries at agent-run start.

• In-process dictionary-style subagents with the same NeMo Flow middleware, so their model and tool calls are captured when Deep Agents invokes them.

Remote graphs or processes still need NeMo Flow instrumentation in that graph or process to capture their internal model and tool calls.

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