[ML] Make eland_import_hub_model an installable script

bin/eland_import_hub_model

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 #  Licensed to Elasticsearch B.V. under one or more contributor
 #  license agreements. See the NOTICE file distributed with
 #  this work for additional information regarding copyright
@@ -35,7 +37,7 @@ MODEL_HUB_URL = "https://huggingface.co"
 
 
 def main():
-    parser = argparse.ArgumentParser(prog="upload_hub_model.py")
+    parser = argparse.ArgumentParser(prog="upload_hub_model")
     parser.add_argument(
         "--url",
         required=True,
@@ -59,7 +61,7 @@ def main():
         "--task-type",
         required=True,
         choices=SUPPORTED_TASK_TYPES,
-        help="The task type that the model will be used for.",
+        help="The task type for the model usage.",
     )
     parser.add_argument(
         "--quantize",
@@ -73,13 +75,19 @@ def main():
         default=False,
         help="Start the model deployment after uploading. Default: False",
     )
+    parser.add_argument(
+        "--clear-previous",
+        action="store_true",
+        default=False,
+        help="Should the model previously stored with `elasticsearch-model-id` be deleted"
+    )
     args = parser.parse_args()
 
     es = elasticsearch.Elasticsearch(args.url, timeout=300)  # 5 minute timeout
 
     # trace and save model, then upload it from temp file
     with tempfile.TemporaryDirectory() as tmp_dir:
-        print("Loading HuggingFace transformer tokenizer and model")
+        print(f"Loading HuggingFace transformer tokenizer and model {args.hub_model_id}")
         tm = TransformerModel(args.hub_model_id, args.task_type, args.quantize)
         model_path, config_path, vocab_path = tm.save(tmp_dir)
 
@@ -90,14 +98,16 @@ def main():
         )
 
         ptm = PyTorchModel(es, es_model_id)
-        ptm.stop()
-        ptm.delete()
+        if args.clear_previous:
+            print(f"Stopping previous deployment and deleting model: {ptm.model_id}")
+            ptm.stop()
+            ptm.delete()
         print(f"Importing model: {ptm.model_id}")
         ptm.import_model(model_path, config_path, vocab_path)
 
     # start the deployed model
     if args.start:
-        print("Starting model deployment")
+        print(f"Starting model deployment: {ptm.model_id}")
         ptm.start()
 
 

setup.py

@@ -76,6 +76,7 @@ setup(
         "matplotlib",
         "numpy",
     ],
+    scripts=["bin/eland_import_hub_model"],
     python_requires=">=3.7",
     package_data={"eland": ["py.typed"]},
     include_package_data=True,