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Tasks

How do background tasks work in Tallyfy Answers?

Tallyfy Answers uses background task processing to handle long-running operations without blocking your API requests. This ensures that large batch imports and data processing jobs don’t cause timeouts or performance issues.

What are background tasks?

Background tasks in Tallyfy Answers handle:

  • Batch Document Imports - Processing large collections of documents for indexing
  • Data Processing Jobs - Converting and analyzing content for search optimization
  • Collection Updates - Making bulk changes to existing data
  • Maintenance Operations - System cleanup and optimization tasks

How do you monitor running tasks?

View all currently running background tasks:

Terminal window
GET /tasks

Example:

Terminal window
curl "https://answers.tallyfy.com/tasks" \
  -H "Authorization: Bearer your_api_key"

How do you cancel a running task?

Stop a specific background task by name:

Terminal window
DELETE /tasks/{task_name}

Example:

Terminal window
curl -X DELETE "https://answers.tallyfy.com/tasks/batch_import_docs" \
  -H "Authorization: Bearer your_api_key"

What task information is available?

When you list running tasks, you’ll see:

  • Task Name - Unique identifier for the background operation
  • Status - Current state of the task (running, queued, completed)
  • Progress - How much of the task has been completed
  • Start Time - When the task began processing
  • Estimated Completion - Predicted time remaining

When should you use task management?

Task management is useful for:

  1. Large Imports - Monitor progress of bulk document uploads
  2. System Maintenance - Check status of scheduled operations
  3. Troubleshooting - Cancel stuck or problematic tasks
  4. Resource Management - Prevent system overload by managing concurrent operations
  5. User Experience - Provide progress updates for long-running operations

What are best practices for task management?

  • Monitor Long Operations - Check task status for imports over 1000 documents1
  • Cancel Stuck Tasks - Remove tasks that appear frozen or taking too long
  • Plan Large Imports - Schedule big data loads during low-usage periods2
  • Regular Cleanup - Cancel completed or failed tasks to keep the queue clean

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Footnotes

  1. Processing time varies: ~5-10 mins per 1000 docs depending on content size and complexity ↩

  2. Typically weekends or 2-6 AM in your org’s primary timezone for optimal performance ↩

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