Tao Chen
0df184e7dd
* Fix sub-workflow checkpoint restore to preserve sub-workflow state Add Runner.capture_checkpoint_object/restore_from_checkpoint_object (quiescent-only nested checkpoint) and embed a sub_workflow_checkpoint in WorkflowExecutor.on_checkpoint_save/on_checkpoint_restore so a resumed parent restores each sub-workflow's mid-progress state instead of only replaying pending request-info events. Keeps a backward-compat fallback when sub_workflow_checkpoint is absent. * Move checkpoint-object construction into the runner context Add RunnerContext.create_checkpoint_object alongside create_checkpoint (create_checkpoint now delegates to it and persists), so Runner.capture_checkpoint_object builds the snapshot via the context instead of a one-off get_messages peek primitive. In-flight messages are captured non-destructively (per-source lists copied). The checkpoint-less capturing contexts (azurefunctions, durabletask) raise NotImplementedError to match create_checkpoint. * Remove per-execution bookkeeping from WorkflowExecutor The sub-workflow is a single shared instance, so per-execution ExecutionContext/request routing never provided real isolation. Delegate request/response tracking to the sub-workflow itself: can_handle accepts targeted propagated responses, _handle_response validates against the sub-workflow's pending requests and forwards responses immediately, and on_checkpoint_save embeds only the sub-workflow checkpoint (on_checkpoint_restore keeps a legacy reader for older checkpoints). Also emit the fresh-message/checkpoint-while-pending warning from FunctionalWorkflow.run to match Workflow.run. * Drop redundant decode in WorkflowExecutor.on_checkpoint_restore The storage backend already materializes the full checkpoint on load (FileCheckpointStorage decodes recursively; InMemoryCheckpointStorage deep-copies), so the embedded sub_workflow_checkpoint (and legacy execution_contexts) arrive already decoded - like every other executor's on_checkpoint_restore state. Remove the no-op decode_checkpoint_value calls and the now-unused import. * Clean up * Do not allow checkpoint storage in sub workflow * Address comments * Fix syntax check * Add warning --------- Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Get Started with Microsoft Agent Framework Durable Functions
Please install this package via pip:
pip install agent-framework-azurefunctions --pre
Durable Agent Extension
The durable agent extension lets you host Microsoft Agent Framework agents on Azure Durable Functions so they can persist state, replay conversation history, and recover from failures automatically.
Basic Usage Example
See the durable functions integration sample in the repository to learn how to:
from agent_framework.azure import AgentFunctionApp
_app = AgentFunctionApp()
- Register agents with
AgentFunctionApp - Post messages using the generated
/api/agents/{agent_name}/runendpoint
For more details, review the Python README and the samples directory.