Background Jobs
Some tasks take time—like processing a 100-page PDF or analyzing a video. Background jobs let you start these tasks and check back later.
How It Works
Think of it like ordering food delivery: you place the order (start a job), get a tracking number (job ID), and check the status whenever you want. You don't have to wait around—just check back when convenient!
What Runs in the Background?
Document Processing
Upload large PDFs, Word docs, or presentations. Hebbrix extracts the text, breaks it into memories, and makes it searchable.
Media Analysis
Process videos and audio files. Hebbrix transcribes speech, identifies key moments, and creates searchable memories from your media.
Batch Operations
Update or delete thousands of memories at once. Instead of doing them one-by-one, batch jobs handle large-scale operations efficiently.
Memory Consolidation
Compress old memories to save space while keeping important information. This runs periodically in the background.
Job Statuses
Every job goes through these stages:
Job is queued, waiting to start
Job is currently being processed
Job finished successfully! Results are ready
Something went wrong. Check the error message
Endpoints
Code Examples
Start a Document Processing Job
from hebbrix import Hebbrix
client = Hebbrix()
# Start processing a large document
job = client.jobs.create(
type="document_processing",
file_url="https://example.com/large-document.pdf",
collection_id="col_abc123"
)
print(f"Job started!")
print(f"Job ID: {job['id']}")
print(f"Status: {job['status']}") # "pending" initially
# Save the job ID - you'll need it to check status later
job_id = job['id']Check Job Status
# Check job status
status = client.jobs.get(job_id)
print(f"Status: {status['status']}")
print(f"Progress: {status['progress']}%")
if status['status'] == 'completed':
print("Job finished!")
print(f"Result: {status['result']}")
elif status['status'] == 'failed':
print("Job failed")
print(f"Error: {status['error_message']}")Wait for Completion (Polling)
import time
def wait_for_job(job_id, max_wait=300):
"""Wait for job to complete (up to max_wait seconds)"""
start_time = time.time()
while True:
status = client.jobs.get(job_id)
if status['status'] == 'completed':
print("Job completed successfully!")
return status['result']
elif status['status'] == 'failed':
print(f"Job failed: {status['error_message']}")
return None
# Check if we've waited too long
if time.time() - start_time > max_wait:
print("Timeout waiting for job")
return None
# Wait 5 seconds before checking again
print(f"Status: {status['status']} ({status['progress']}%)")
time.sleep(5)
# Use it
result = wait_for_job(job_id)
if result:
print(f"Processed {result['memories_created']} memories!")Pro Tips
- Save job IDs! You need them to check status later
- Don't poll too frequently—check every 5-10 seconds is enough
- Jobs older than 30 days are automatically deleted (but results are saved)
- You can have multiple jobs running at once