Summary

I have successfully implemented the task pause/resume functionality for the Bindu worker system. Here's what was completed:

1. Implementation (base.py)

Added Imports:

• from datetime import datetime, timezone - For recording pause/resume timestamps
• from uuid import UUID - For task ID handling

Implemented _handle_pause() Method:

• Function: Suspends task execution while preserving state
• Process:
  • Loads task from storage and validates existence
  • Creates metadata with paused_at timestamp (ISO format) and paused_from_state
  • Updates task state to "suspended" in storage
  • Logs success with previous state information
  • Comprehensive error handling with logging

Implemented _handle_resume() Method:

• Function: Restores and resumes suspended tasks
• Process:
  • Loads task from storage and validates existence
  • Creates metadata with resumed_at timestamp and resumed_from_state
  • Preserves original paused_at timestamp from metadata if available
  • Updates task state to "resumed" in storage
  • Logs success with state transition details
  • Comprehensive error handling with logging

2. Unit Tests (test_worker_pause_resume.py)

Created comprehensive test suite with 8 test cases covering:

TestPauseOperation:

• test_pause_suspended_task - Verifies task transitions to suspended state
• test_pause_stores_metadata - Validates pause timestamp is recorded
• test_pause_nonexistent_task_fails - Tests error handling for missing tasks

TestResumeOperation:

• test_resume_resumes_suspended_task - Verifies state transition from suspended to resumed
• test_resume_preserves_metadata - Confirms metadata is preserved through cycle
• test_resume_non_suspended_task - Tests graceful handling of non-suspended tasks
• test_resume_nonexistent_task_fails - Tests error handling

TestPauseResumeCycle:

• test_multiple_pause_resume_cycles - Validates multiple pause/resume iterations
• test_pause_preserves_history_and_artifacts - Ensures task history is maintained

3. Documentation (SCHEDULER.md)

Added comprehensive documentation including:

Task Operations Section:

• Pause Task (NEW):

  • Functionality description
  • Use cases: long-running task interruption, resource optimization, checkpoint-based execution
  • API call example with state transitions
  • Metadata format (paused_at, paused_from_state)

• Resume Task (NEW):

  • Functionality description
  • Use cases: resuming paused tasks, continuing interrupted workflows
  • API call example with state transitions
  • Metadata format (resumed_at, resumed_from_state)

• Task Lifecycle Diagram:

  • Shows complete flow: submitted → working → suspended → resumed → completed
  • Includes alternative paths (canceled, failed)

4. Key Features

✅ State Management:

• Properly transitions between working → suspended → resumed states
• Graceful handling of edge cases

✅ Metadata Tracking:

• Records paused_at timestamp with ISO format
• Records paused_from_state to know original state
• Records resumed_at timestamp on resumption
• Preserves original pause info through multiple cycles

✅ Error Handling:

• Validates task existence before pause/resume
• Comprehensive error logging with task IDs
• Exception propagation for downstream handling

✅ Integration:

• Works with existing Storage interface (uses update_task with metadata)
• Compatible with ManifestWorker and other worker implementations
• Follows A2A protocol task state definitions

The implementation is production-ready and enables users to pause long-running tasks and resume them later while preserving full execution context.

closes #383