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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →To pause a long-running Microsoft Foundry hosted agent for human approval, model the work as a persistent multi-turn task: return an approval request on the first turn, then start another turn with the same task_id after a person decides. The original turn ends rather than holding an HTTP request open. Microsoft’s guide says the suspended task can wait arbitrarily long and survive container restarts, but the feature is in preview and its API may change.
How the approval pause works
A Foundry multi-turn task suspends its chain under a task ID when it returns an approval request. The application can show that request to a person and let the turn finish. Once the person approves or rejects, the application invokes the task again with the same task ID and supplies the decision as new input. The handler resumes in a resumed mode and continues along the appropriate branch. Microsoft describes this wait as arbitrarily long and says it survives container restarts; those claims apply to the long-running hosted-agent preview documented in its approval guide, not to every related session or framework.
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Implement the approval as a multi-turn task
- Define the task and context. Use
@multi_turn_taskand a typed task context for the approval workflow. - Prepare the action on the first turn. Gather what is needed to make the decision, save only small references such as an expense ID or watermark in
ctx.metadata, and return a concise approval summary and a status such asawaiting_approval. - Present the request and end the turn. Show the summary to the approver. Do not keep the original request open while waiting; the chain is suspended under its task ID.
- Resume with the decision. After the person responds, invoke the same task with that same
task_idand input containing the approval or rejection. In the resumed call, readctx.inputand continue the corresponding branch. - Persist the substantial state elsewhere. Keep full request payloads, conversation history, and generated artifacts in application storage or a framework checkpoint rather than relying on task metadata for large state.
Microsoft’s example uses an expense: the first turn stores expense.id in task metadata and returns an awaiting-approval status with a summary; a later turn submits the expense if approved or returns a rejected result. It is a documentation example, not an independently verified implementation.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsPreserve state across framework interrupts
If approval pauses a framework workflow over a background response, use the framework’s interrupt or approval mechanism, enable resilient_background=True, persist its checkpoint at the interrupt, and rebuild state from that checkpoint when resuming. This is a separate state-management layer from the Foundry task ID: the task ID identifies the suspended multi-turn chain, while the checkpoint or application store holds the full workflow state.
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Do not confuse an indefinite wait with session retention
“Arbitrarily long” describes the suspended wait in the Foundry long-running hosted-agent approval guide. The separately documented Durable Task extension for Microsoft Agent Framework has an idle session TTL: its default is 14 days, it can be configured globally or per agent, and an agent can be configured with no TTL. When an idle session expires, its entire state is deleted; a later message creates a fresh session. Microsoft says TTL configuration is currently available in .NET only. The same documentation gives a 5-minute minimum TTL deletion delay, and notes a 1 MB maximum entity state size for Durable Task Scheduler, which can matter when long conversations include large tool outputs and may require manual compaction. See Microsoft’s Durable Task extension documentation.
These TTL details concern Durable Task agent sessions, not the Foundry preview task’s documented suspended wait. Likewise, the Durable Task for AI agents overview lists stateful Logic Apps workflows as lasting up to 90 days in its comparison of Azure options; that is a Logic Apps service-option limit, not a Foundry task limit.
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Choose the orchestration model that fits the workflow
Human approval can be implemented through several Microsoft options. They differ in how control flow is expressed, where the workflow runs and stores state, and how the system resumes after a pause or failure.
| Option | Control flow and resume | Fit and retention considerations |
|---|---|---|
| Foundry long-running hosted-agent multi-turn task | The agent returns an approval request, suspends under a task ID, and resumes when called again with that ID and the person’s decision. | Use when the agent itself needs a durable suspended task. The feature is preview; the approval guide describes an arbitrarily long wait that survives container restarts. |
| Microsoft Agent Framework workflow with Durable Task extension | Pause at a workflow point such as .NET RequestPort or Python ctx.request_info(); the documented durable workflow exposes run, status, and respond HTTP endpoints, with the response endpoint resuming execution. |
Consider its session TTL and storage limits. The default idle session TTL is 14 days, configurable including no TTL; expired state is deleted. Microsoft says TTL configuration is currently .NET-only. |
| Azure Logic Apps with Foundry | A managed, declarative workflow can combine agent steps, connectors, webhooks, human approvals, and external events; Microsoft shows approvals waiting for a manager response. | Useful when orchestration should be declarative and integrate with managed connectors or events. Microsoft describes workflows as durably running for the process duration; its options comparison lists stateful Logic Apps workflows up to 90 days. |
| Durable Task programming model | A code-first durable-execution model with checkpointing and recovery after infrastructure failures. | Consider when a code-first orchestration model, multiple language options, and framework flexibility suit the application; compare hosting and state-storage choices for the intended deployment. |
Microsoft’s Azure options comparison also distinguishes the options by language support, hosting, state storage, long-running limits, and failure recovery. Azure Logic Apps approval behavior is described in Microsoft’s agentic process automation documentation.
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Design the approval boundary deliberately
- Make the request actionable. Include the information a person needs to approve or reject, while keeping the persisted task metadata small.
- Separate durable identity from durable content. Keep the task ID for resumption and store the full payload and artifacts in an appropriate application store or checkpoint.
- Define both outcomes. Resume into explicit approved and rejected branches so rejection does not accidentally proceed with the action.
- Check the retention model you actually use. An indefinite suspended wait in the Foundry preview does not disable a separate session TTL or guarantee retention by every external state store.
- Plan for preview changes. Confirm current package and API details against Microsoft documentation before relying on specific signatures or availability.
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