The Tool Desk
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Keep the run open, preserve its resumable state, show the pending action or question to an authorized human, and continue that same run after a decision. An approval pause is an unfinished workflow—not a completed answer and not a reason to silently replay the user’s request as a new turn.
What a pause means
A human-review pause is an expected workflow state. In an approval flow, the agent has reached an action that requires a decision; the gated tool should not execute until the decision is made. OpenAI’s documentation describes this as an approval interruption, distinct from runtime, validation, guardrail, or run-limit failures. See Guardrails and human review and Running agents.
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Do not treat every stopped run as a human-input pause. Classify the runtime’s result first: an expected interruption can be resumed after input, while a failure may require error handling rather than approval.
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- Detect and classify the pause. Inspect the result using the runtime’s documented interface. Identify whether it is an approval interruption or another kind of failure; do not infer approval from a generic stopped status.
- Preserve the pending item and resumable state. Keep the exact pending action or question with the state needed to continue. The OpenAI Agents SDK represents approval interruptions in a resumable
RunStateand supports serializing that state when review will happen later. See Human-in-the-loop. - Present the decision to the right reviewer. Show the pending operation or question with enough context to judge it. The framework documentation establishes the approval and rejection lifecycle, but does not dictate a general review-screen layout.
- Apply the reviewer’s decision to the interruption. Resolve the pending item through the framework’s API; do not execute the gated tool yourself before approval.
- Resume the existing run. Continue from its saved state so the runtime retains the workflow and conversation context. OpenAI’s guide explicitly says to resolve interruptions and resume from state rather than begin a fresh user turn.
- Keep session-backed history connected. If the application uses SDK sessions, resume with the same session, or another session configured with the same ID and backing store, so the continued turn appends to the stored conversation. See Sessions.
How the continuation pattern differs by runtime
The principle is consistent—preserve the interrupted workflow and continue it with human input—but the APIs are framework-specific. Do not mix their state objects or resume calls.
OpenAI Agents SDK
Approval interruptions are attached to a resumable run state. Resolve the pending interruption and pass the state back to the SDK to continue. The Python SDK documents serializable state for delayed review; the JavaScript SDK documents its own interruption and resume flow. See the Python human-in-the-loop guide and the JavaScript human-in-the-loop guide.
LangGraph
LangGraph documents a workflow-interrupt pattern in which execution pauses for human input and resumes with a Command containing the response. That is a different interface from the OpenAI SDK’s approval interruption and RunState. Follow the relevant framework’s documented resume mechanism. See LangGraph Human-in-the-loop.
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If the run was streamed
Do not inspect for interruptions or resume while the stream is still producing its result. The JavaScript SDK guidance is to let the stream complete, inspect its interruptions, resolve them, and continue from the stream’s state. If further output is needed, continue streaming from that saved state. See Human-in-the-loop.
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- State ownership: Decide whether your application carries the transcript, relies on server-managed continuation, or stores framework-managed resumable state. OpenAI’s running-agent guide describes different conversation-continuation strategies; the JavaScript results guide explains interruption state and continuation context. See Running agents and Results.
- Pause representation: An approval interruption for a specific tool call is not the same abstraction as a workflow interrupt awaiting arbitrary human input. Choose the runtime whose pause model fits the operation.
- Review boundary: Confirm that the action is held before execution and that the reviewer or policy can approve or reject the exact pending operation. OpenAI’s documented approval lifecycle provides this boundary for configured tools.
- Continuity: For delayed reviews, verify how resumable state is persisted and how session-backed history is reattached when continuation occurs.
- Streaming: Ensure your application can determine when a stream has settled before it inspects interruptions and resumes.
Production decisions your framework does not make for you
The documented pause-and-resume mechanics do not establish a universal policy for approval expiration, reviewer identity and authorization, durable storage guarantees, retries, idempotency, or a crash during resumption. Set those policies around your runtime and the side effects your application permits. For sensitive actions, define who may review them and keep the approval boundary in the application; framework support for an interruption does not by itself settle those security and reliability choices. OpenAI discusses review boundaries in Guardrails and human review.
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