The document classification system uses advanced AI models to automatically categorize documents based on their content, structure, and visual elements. It provides accurate classification with confidence scores for single-page and multi-page documents.
Classification jobs are processed asynchronously. Submit a classification job and poll the status endpoint to retrieve results when complete.
from unsiloed_sdk import UnsiloedClient# Define categories with optional descriptionscategories = [ {"name": "Medical Record", "description": "Patient medical records and history"}, {"name": "Lab Report", "description": "Laboratory test results"}, {"name": "Prescription"} # Description is optional]with UnsiloedClient(api_key="your-api-key") as client: # Classify and wait for completion result = client.classify_and_wait( file="document.pdf", categories=categories ) print(f"Classification: {result.result['classification']}") print(f"Confidence: {result.result['confidence']:.2%}") # Check page-by-page results if available if 'page_results' in result.result: for page_result in result.result['page_results']: print(f"Page {page_result['page']}: {page_result['classification']}")
from unsiloed_sdk import UnsiloedClientdef check_classification_status(job_id: str, api_key: str): with UnsiloedClient(api_key=api_key) as client: # Get classification result job = client.get_classify_result(job_id) print(f"Status: {job.status}") print(f"Progress: {job.progress}") if job.status == "completed" and job.result: result = job.result print(f"\nClassification: {result['classification']}") print(f"Confidence: {result['confidence']:.2%}") print(f"Total Pages: {result.get('total_pages', 'N/A')}") if 'page_results' in result: for page_result in result['page_results']: print(f"Page {page_result['page']}: {page_result['classification']}") return job