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Extract Property Features

This guide walks through analyzing property photos using computer vision to generate descriptions, identify room types, and extract searchable features.

Before You Start

Section titled “Before You Start”
  1. Ensure Ollama server is running and accessible
  2. Verify the vision model is installed (ollama pull qwen2-vl)
  3. Check system status on the Vision Extraction page

Starting an Extraction Job

Section titled “Starting an Extraction Job”

Navigate to Admin Dashboard → Vision and follow these steps:

  1. Review the Unindexed Alert to see how many properties need processing
  2. Click Start Extraction
  3. Configure job options:
    • Limit — Process only a specific number of properties (leave empty for all)
    • Skip visual embeddings — Faster processing using description-based search only
  4. Click Start Job

Monitoring Job Progress

Section titled “Monitoring Job Progress”

While a job is running, you’ll see a progress card displaying:

  • Status badge — Current job state (pending, running, completed, failed)
  • Progress bar — Visual completion indicator
  • Image count — Processed vs. total images
  • Start time — When the job began
  • Cancel button — Stop the job if needed

The page updates automatically every 5 seconds.

Testing with Small Batches

Section titled “Testing with Small Batches”

For initial setup or troubleshooting:

  1. Start with a small limit (10-20 properties)
  2. Monitor the job to completion
  3. Review extraction history for any failures
  4. Verify descriptions appear in property images
  5. Gradually increase batch size

Ongoing Maintenance

Section titled “Ongoing Maintenance”

Regular Extraction Schedule

Section titled “Regular Extraction Schedule”
  1. Schedule extraction jobs after MLS data syncs
  2. Monitor coverage percentage on the dashboard
  3. Aim for 100% coverage to ensure all photos are searchable
  4. Run during off-peak hours to avoid impacting user searches

Reviewing Job History

Section titled “Reviewing Job History”

Check the Extraction History table regularly:

  • Identify recurring failures that need attention
  • Track processing trends over time
  • Monitor average duration per job
  • Review which users triggered jobs

Troubleshooting

Section titled “Troubleshooting”

Job Fails Immediately

Section titled “Job Fails Immediately”

Symptoms: Job shows “failed” status within seconds

Solutions:

  • Check Ollama server connectivity at the configured URL
  • Verify the vision model is installed (ollama list)
  • Review server logs for error details
  • Test Ollama API manually: curl http://ollama-server:11434/api/version

Slow Processing

Section titled “Slow Processing”

Symptoms: Job takes hours for small batches

Solutions:

  • Reduce VISION_CONCURRENCY if server is overloaded
  • Process in smaller batches (limit to 50-100 properties)
  • Consider GPU acceleration for Ollama
  • Check Ollama server resource usage (CPU, RAM, GPU)

Low Coverage Despite Completed Jobs

Section titled “Low Coverage Despite Completed Jobs”

Symptoms: Coverage percentage stays low even after successful jobs

Solutions:

  • Check failed image count in job history
  • Some images may be corrupted or have inaccessible URLs
  • Re-run extraction for specific properties with failures
  • Review server logs for HTTP errors when fetching images
Section titled “Features Not Appearing in Search”

Symptoms: Extracted features don’t show up in semantic search

Solutions:

  • Wait for embedding generation to complete fully
  • Verify the search index has been updated
  • Check that semantic search is enabled for the brokerage
  • Test with explicit feature queries like “granite countertops”

Performance Tips

Section titled “Performance Tips”

Skip Visual Embeddings

Use description-only mode for faster initial indexing

Use Limits

Process in manageable batches (100-500 properties)

Off-Peak Processing

Run large jobs during low-traffic hours

Monitor Resources

Watch Ollama server CPU/GPU usage during jobs

Section titled “Related Documentation”