Adds a script to create jobs.

scripts/create_job.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env -S uv run --script
+# /// script
+# requires-python = ">=3.13"
+# dependencies = [
+#   "requests>=2.32"
+# ]
+# ///
+
+import argparse, csv, json, os, requests
+from pathlib import Path
+
+# SERVICE_URL is the url where the AI service is running. It is the endpoint used to create jobs.
+SERVICE_URL = os.getenv('SERVICE_URL', 'https://example.com')
+# API_KEY is the authentication token necessary to use the service. This will error is it is not set.
+API_KEY= os.getenv('API_KEY', None)
+# REPO_BUCKET is the URI for the bucket (and folder) containing images already ingested into our repository.
+REPO_BUCKET = os.getenv('REPO_BUCKET', 's3://REPO/')
+# INGEST_BUCKET is the base URI for the bucket containing images not yet ingested into our repository.
+# The images in this bucket are expected to live in folders with the same name as the job being enqueued.
+INGEST_BUCKET = os.getenv('INGEST_BUCKET', 's3://INGEST/')
+
+parser = argparse.ArgumentParser(description='Creates bias and metadata jobs for AI processing')
+parser.add_argument('--name', '-n', help='Job Name. If this is not supplied, the CSV filename will be used.')
+parser.add_argument('type', choices=['bias', 'metadata'], help='Job Type')
+parser.add_argument('csv', type=Path, help='Ingest CSV file')
+parser.add_argument('--context', '-c', help='Context URI')
+parser.add_argument('--metadata', '-m', help='Metadata URI')
+parser.add_argument('--dryrun', '-d', action='store_true', help='Print the job metadata, but do not create the job.')
+args = parser.parse_args()
+
+if API_KEY is None:
+    print("Please set an environment variable for the API_KEY.")
+    exit(10)
+
+if args.name is None:
+    # The name is optional for this utility, but required for creating jobs. Use the CSV filename if no name is supplied.
+    args.name = args.csv.stem
+
+works = {}
+
+with args.csv.open() as csv_file:
+    csv_reader = csv.DictReader(csv_file)
+    for row in csv_reader:
+        image_uri = ''
+        if row['file_set_id']:
+            # If there's a fileset ID, the work has been ingested, so the image is in the repository bucket.
+            image_uri = "{}{}".format(REPO_BUCKET, row['page_sha1'])
+        else:
+            # No fileset, so the image is in the ingest bucket.
+            image_uri = "{}{}".format(INGEST_BUCKET, row['page_sha1'])
+
+        if row['work_id'] in works:
+            # Work ID already in works
+            works[row['work_id']]['image_s3_uris'].append(image_uri)
+        else:
+            # First time setup for a new work id
+            work = {'work_id': row['work_id'], 'image_s3_uris': [image_uri]}
+            if args.context is not None:
+                work['context_s3_uri'] = args.context
+            if args.metadata is not None:
+                work['original_metadata_s3_uri'] = args.metadata
+            works[row['work_id']] = work
+
+job_data = {'job_name': args.name, 'job_type': args.type, 'works': list(works.values())}
+
+if not args.dryrun:
+    response = requests.post(SERVICE_URL, headers={'X-Api-Key': API_KEY}, json=job_data, timeout=30)
+    response.raise_for_status()
+    print(response.text)
+else:
+    print(json.dumps(job_data, indent=2))