Handle Long-Running Tasks

name: analysis-agent
runtime: python3
module: agent.py
entrypoint: handler

timeout: 1800  # 30 minutes (in seconds)
memory: 2048   # More memory for heavy processing

import time

def handler(input_data):
    documents = input_data.get('documents', [])

    results = []
    for i, doc in enumerate(documents):
        # Process each document (might take minutes)
        result = analyze_document(doc)
        results.append(result)

        # Progress is visible in logs
        print(f"Processed {i+1}/{len(documents)}")

    return {
        'results': results,
        'total': len(results)
    }

def analyze_document(doc):
    # Simulate heavy processing
    time.sleep(30)  # 30 seconds per doc
    return {'summary': f"Analyzed: {doc[:50]}..."}

# This might take 10+ minutes
orpheus run analysis-agent '{"documents": ["doc1", "doc2", "doc3"]}'

# See queue and worker status
orpheus stats analysis-agent

# View recent executions
orpheus execlog list analysis-agent

import json
import os

def handler(input_data):
    documents = input_data.get('documents', [])
    progress_file = '/workspace/progress.json'

    # Load previous progress
    if os.path.exists(progress_file):
        with open(progress_file) as f:
            progress = json.load(f)
    else:
        progress = {'completed': [], 'results': []}

    # Process remaining documents
    for doc in documents:
        if doc in progress['completed']:
            continue  # Skip already processed

        result = analyze_document(doc)
        progress['completed'].append(doc)
        progress['results'].append(result)

        # Save progress after each doc
        with open(progress_file, 'w') as f:
            json.dump(progress, f)

    return {'results': progress['results']}