We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Store pipeline tasks in the index, and update Taskcluster URLs in scripts
The scripts are still using the old URLs from releng-services.
Store pipeline tasks in the index, and update Taskcluster URLs in scripts
The scripts are still using the old URLs from releng-services.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `scripts/trainer.py`
Content:
```
1 # -*- coding: utf-8 -*-
2 
3 import argparse
4 import lzma
5 import os
6 import shutil
7 from logging import INFO, basicConfig, getLogger
8 from urllib.request import urlretrieve
9 
10 from bugbug.models.component import ComponentModel
11 from bugbug.models.defect_enhancement_task import DefectEnhancementTaskModel
12 from bugbug.models.regression import RegressionModel
13 from bugbug.models.tracking import TrackingModel
14 
15 basicConfig(level=INFO)
16 logger = getLogger(__name__)
17 
18 BASE_URL = "https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_data.latest/artifacts/public"
19 
20 
21 class Trainer(object):
22     def decompress_file(self, path):
23         with lzma.open(f"{path}.xz", "rb") as input_f:
24             with open(path, "wb") as output_f:
25                 shutil.copyfileobj(input_f, output_f)
26 
27     def compress_file(self, path):
28         with open(path, "rb") as input_f:
29             with lzma.open(f"{path}.xz", "wb") as output_f:
30                 shutil.copyfileobj(input_f, output_f)
31 
32     def train_defect_enhancement_task(self):
33         logger.info("Training *defect vs enhancement vs task* model")
34         model = DefectEnhancementTaskModel()
35         model.train()
36         self.compress_file("defectenhancementtaskmodel")
37 
38     def train_component(self):
39         logger.info("Training *component* model")
40         model = ComponentModel()
41         model.train()
42         self.compress_file("componentmodel")
43 
44     def train_regression(self):
45         logger.info("Training *regression vs non-regression* model")
46         model = RegressionModel()
47         model.train()
48         self.compress_file("regressionmodel")
49 
50     def train_tracking(self):
51         logger.info("Training *tracking* model")
52         model = TrackingModel()
53         model.train()
54         self.compress_file("trackingmodel")
55 
56     def go(self, model):
57         # TODO: Stop hard-coding them
58         valid_models = ["defect", "component", "regression", "tracking"]
59 
60         if model not in valid_models:
61             exception = (
62                 f"Invalid model {model!r} name, use one of {valid_models!r} instead"
63             )
64             raise ValueError(exception)
65 
66         # Download datasets that were built by bugbug_data.
67         os.makedirs("data", exist_ok=True)
68 
69         # Bugs.json
70         logger.info("Downloading bugs database")
71         urlretrieve(f"{BASE_URL}/bugs.json.xz", "data/bugs.json.xz")
72         logger.info("Decompressing bugs database")
73         self.decompress_file("data/bugs.json")
74 
75         # Commits.json
76         logger.info("Downloading commits database")
77         urlretrieve(f"{BASE_URL}/commits.json.xz", "data/commits.json.xz")
78         logger.info("Decompressing commits database")
79         self.decompress_file("data/commits.json")
80 
81         if model == "defect":
82             # Train classifier for defect-vs-enhancement-vs-task.
83             self.train_defect_enhancement_task()
84         elif model == "component":
85             # Train classifier for the component of a bug.
86             self.train_component()
87         elif model == "regression":
88             # Train classifier for regression-vs-nonregression.
89             self.train_regression()
90         elif model == "tracking":
91             # Train classifier for tracking bugs.
92             self.train_tracking()
93         else:
94             # We shouldn't be here
95             raise Exception("valid_models is likely not up-to-date anymore")
96 
97 
98 def main():
99     description = "Train the models"
100     parser = argparse.ArgumentParser(description=description)
101 
102     parser.add_argument("model", help="Which model to train.")
103 
104     args = parser.parse_args()
105 
106     retriever = Trainer()
107     retriever.go(args.model)
108
```

Path: `http_service/download_models.py`
Content:
```
1 # -*- coding: utf-8 -*-
2 # This Source Code Form is subject to the terms of the Mozilla Public
3 # License, v. 2.0. If a copy of the MPL was not distributed with this file,
4 # You can obtain one at http://mozilla.org/MPL/2.0/.
5 
6 import logging
7 import lzma
8 import os
9 import shutil
10 from urllib.request import urlretrieve
11 
12 import requests
13 
14 logging.basicConfig(level=logging.INFO)
15 LOGGER = logging.getLogger()
16 
17 BASE_URL = "https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_train.latest/artifacts/public"
18 
19 MODELS_NAMES = ("defectenhancementtask", "component", "regression")
20 MODELS_DIR = os.path.join(os.path.dirname(__file__), "models")
21 
22 
23 def retrieve_model(name):
24     os.makedirs(MODELS_DIR, exist_ok=True)
25 
26     file_name = f"{name}model"
27     file_path = os.path.join(MODELS_DIR, file_name)
28 
29     model_url = f"{BASE_URL}/{file_name}.xz"
30     LOGGER.info(f"Checking ETAG of {model_url}")
31     r = requests.head(model_url, allow_redirects=True)
32     r.raise_for_status()
33     new_etag = r.headers["ETag"]
34 
35     try:
36         with open(f"{file_path}.etag", "r") as f:
37             old_etag = f.read()
38     except IOError:
39         old_etag = None
40 
41     if old_etag != new_etag:
42         LOGGER.info(f"Downloading the model from {model_url}")
43         urlretrieve(model_url, f"{file_path}.xz")
44 
45         with lzma.open(f"{file_path}.xz", "rb") as input_f:
46             with open(file_path, "wb") as output_f:
47                 shutil.copyfileobj(input_f, output_f)
48                 LOGGER.info(f"Written model in {file_path}")
49 
50         with open(f"{file_path}.etag", "w") as f:
51             f.write(new_etag)
52     else:
53         LOGGER.info(f"ETAG for {model_url} is ok")
54 
55     return file_path
56 
57 
58 def preload_models():
59     for model_name in MODELS_NAMES:
60         retrieve_model(model_name)
61 
62 
63 if __name__ == "__main__":
64     preload_models()
65
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/http_service/download_models.py b/http_service/download_models.py
--- a/http_service/download_models.py
+++ b/http_service/download_models.py
@@ -14,7 +14,7 @@
 logging.basicConfig(level=logging.INFO)
 LOGGER = logging.getLogger()
 
-BASE_URL = "https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_train.latest/artifacts/public"
+BASE_URL = "https://index.taskcluster.net/v1/task/project.relman.bugbug.train_{}.latest/artifacts/public"
 
 MODELS_NAMES = ("defectenhancementtask", "component", "regression")
 MODELS_DIR = os.path.join(os.path.dirname(__file__), "models")
@@ -26,7 +26,8 @@
     file_name = f"{name}model"
     file_path = os.path.join(MODELS_DIR, file_name)
 
-    model_url = f"{BASE_URL}/{file_name}.xz"
+    base_model_url = BASE_URL.format(name)
+    model_url = f"{base_model_url}/{file_name}.xz"
     LOGGER.info(f"Checking ETAG of {model_url}")
     r = requests.head(model_url, allow_redirects=True)
     r.raise_for_status()
diff --git a/scripts/trainer.py b/scripts/trainer.py
--- a/scripts/trainer.py
+++ b/scripts/trainer.py
@@ -15,7 +15,7 @@
 basicConfig(level=INFO)
 logger = getLogger(__name__)
 
-BASE_URL = "https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_data.latest/artifacts/public"
+BASE_URL = "https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.latest/artifacts/public"
 
 
 class Trainer(object):
@@ -68,13 +68,15 @@
 
         # Bugs.json
         logger.info("Downloading bugs database")
-        urlretrieve(f"{BASE_URL}/bugs.json.xz", "data/bugs.json.xz")
+        bugs_url = BASE_URL.format("bugs")
+        urlretrieve(f"{bugs_url}/bugs.json.xz", "data/bugs.json.xz")
         logger.info("Decompressing bugs database")
         self.decompress_file("data/bugs.json")
 
         # Commits.json
         logger.info("Downloading commits database")
-        urlretrieve(f"{BASE_URL}/commits.json.xz", "data/commits.json.xz")
+        commits_url = BASE_URL.format("commits")
+        urlretrieve(f"{commits_url}/commits.json.xz", "data/commits.json.xz")
         logger.info("Decompressing commits database")
         self.decompress_file("data/commits.json")

{"golden_diff": "diff --git a/http_service/download_models.py b/http_service/download_models.py\n--- a/http_service/download_models.py\n+++ b/http_service/download_models.py\n@@ -14,7 +14,7 @@\n logging.basicConfig(level=logging.INFO)\n LOGGER = logging.getLogger()\n \n-BASE_URL = \"https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_train.latest/artifacts/public\"\n+BASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.train_{}.latest/artifacts/public\"\n \n MODELS_NAMES = (\"defectenhancementtask\", \"component\", \"regression\")\n MODELS_DIR = os.path.join(os.path.dirname(__file__), \"models\")\n@@ -26,7 +26,8 @@\n     file_name = f\"{name}model\"\n     file_path = os.path.join(MODELS_DIR, file_name)\n \n-    model_url = f\"{BASE_URL}/{file_name}.xz\"\n+    base_model_url = BASE_URL.format(name)\n+    model_url = f\"{base_model_url}/{file_name}.xz\"\n     LOGGER.info(f\"Checking ETAG of {model_url}\")\n     r = requests.head(model_url, allow_redirects=True)\n     r.raise_for_status()\ndiff --git a/scripts/trainer.py b/scripts/trainer.py\n--- a/scripts/trainer.py\n+++ b/scripts/trainer.py\n@@ -15,7 +15,7 @@\n basicConfig(level=INFO)\n logger = getLogger(__name__)\n \n-BASE_URL = \"https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_data.latest/artifacts/public\"\n+BASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.latest/artifacts/public\"\n \n \n class Trainer(object):\n@@ -68,13 +68,15 @@\n \n         # Bugs.json\n         logger.info(\"Downloading bugs database\")\n-        urlretrieve(f\"{BASE_URL}/bugs.json.xz\", \"data/bugs.json.xz\")\n+        bugs_url = BASE_URL.format(\"bugs\")\n+        urlretrieve(f\"{bugs_url}/bugs.json.xz\", \"data/bugs.json.xz\")\n         logger.info(\"Decompressing bugs database\")\n         self.decompress_file(\"data/bugs.json\")\n \n         # Commits.json\n         logger.info(\"Downloading commits database\")\n-        urlretrieve(f\"{BASE_URL}/commits.json.xz\", \"data/commits.json.xz\")\n+        commits_url = BASE_URL.format(\"commits\")\n+        urlretrieve(f\"{commits_url}/commits.json.xz\", \"data/commits.json.xz\")\n         logger.info(\"Decompressing commits database\")\n         self.decompress_file(\"data/commits.json\")\n", "issue": "Store pipeline tasks in the index, and update Taskcluster URLs in scripts\nThe scripts are still using the old URLs from releng-services.\nStore pipeline tasks in the index, and update Taskcluster URLs in scripts\nThe scripts are still using the old URLs from releng-services.\n", "before_files": [{"content": "# -*- coding: utf-8 -*-\n\nimport argparse\nimport lzma\nimport os\nimport shutil\nfrom logging import INFO, basicConfig, getLogger\nfrom urllib.request import urlretrieve\n\nfrom bugbug.models.component import ComponentModel\nfrom bugbug.models.defect_enhancement_task import DefectEnhancementTaskModel\nfrom bugbug.models.regression import RegressionModel\nfrom bugbug.models.tracking import TrackingModel\n\nbasicConfig(level=INFO)\nlogger = getLogger(__name__)\n\nBASE_URL = \"https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_data.latest/artifacts/public\"\n\n\nclass Trainer(object):\n    def decompress_file(self, path):\n        with lzma.open(f\"{path}.xz\", \"rb\") as input_f:\n            with open(path, \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n\n    def compress_file(self, path):\n        with open(path, \"rb\") as input_f:\n            with lzma.open(f\"{path}.xz\", \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n\n    def train_defect_enhancement_task(self):\n        logger.info(\"Training *defect vs enhancement vs task* model\")\n        model = DefectEnhancementTaskModel()\n        model.train()\n        self.compress_file(\"defectenhancementtaskmodel\")\n\n    def train_component(self):\n        logger.info(\"Training *component* model\")\n        model = ComponentModel()\n        model.train()\n        self.compress_file(\"componentmodel\")\n\n    def train_regression(self):\n        logger.info(\"Training *regression vs non-regression* model\")\n        model = RegressionModel()\n        model.train()\n        self.compress_file(\"regressionmodel\")\n\n    def train_tracking(self):\n        logger.info(\"Training *tracking* model\")\n        model = TrackingModel()\n        model.train()\n        self.compress_file(\"trackingmodel\")\n\n    def go(self, model):\n        # TODO: Stop hard-coding them\n        valid_models = [\"defect\", \"component\", \"regression\", \"tracking\"]\n\n        if model not in valid_models:\n            exception = (\n                f\"Invalid model {model!r} name, use one of {valid_models!r} instead\"\n            )\n            raise ValueError(exception)\n\n        # Download datasets that were built by bugbug_data.\n        os.makedirs(\"data\", exist_ok=True)\n\n        # Bugs.json\n        logger.info(\"Downloading bugs database\")\n        urlretrieve(f\"{BASE_URL}/bugs.json.xz\", \"data/bugs.json.xz\")\n        logger.info(\"Decompressing bugs database\")\n        self.decompress_file(\"data/bugs.json\")\n\n        # Commits.json\n        logger.info(\"Downloading commits database\")\n        urlretrieve(f\"{BASE_URL}/commits.json.xz\", \"data/commits.json.xz\")\n        logger.info(\"Decompressing commits database\")\n        self.decompress_file(\"data/commits.json\")\n\n        if model == \"defect\":\n            # Train classifier for defect-vs-enhancement-vs-task.\n            self.train_defect_enhancement_task()\n        elif model == \"component\":\n            # Train classifier for the component of a bug.\n            self.train_component()\n        elif model == \"regression\":\n            # Train classifier for regression-vs-nonregression.\n            self.train_regression()\n        elif model == \"tracking\":\n            # Train classifier for tracking bugs.\n            self.train_tracking()\n        else:\n            # We shouldn't be here\n            raise Exception(\"valid_models is likely not up-to-date anymore\")\n\n\ndef main():\n    description = \"Train the models\"\n    parser = argparse.ArgumentParser(description=description)\n\n    parser.add_argument(\"model\", help=\"Which model to train.\")\n\n    args = parser.parse_args()\n\n    retriever = Trainer()\n    retriever.go(args.model)\n", "path": "scripts/trainer.py"}, {"content": "# -*- coding: utf-8 -*-\n# This Source Code Form is subject to the terms of the Mozilla Public\n# License, v. 2.0. If a copy of the MPL was not distributed with this file,\n# You can obtain one at http://mozilla.org/MPL/2.0/.\n\nimport logging\nimport lzma\nimport os\nimport shutil\nfrom urllib.request import urlretrieve\n\nimport requests\n\nlogging.basicConfig(level=logging.INFO)\nLOGGER = logging.getLogger()\n\nBASE_URL = \"https://index.taskcluster.net/v1/task/project.releng.services.project.testing.bugbug_train.latest/artifacts/public\"\n\nMODELS_NAMES = (\"defectenhancementtask\", \"component\", \"regression\")\nMODELS_DIR = os.path.join(os.path.dirname(__file__), \"models\")\n\n\ndef retrieve_model(name):\n    os.makedirs(MODELS_DIR, exist_ok=True)\n\n    file_name = f\"{name}model\"\n    file_path = os.path.join(MODELS_DIR, file_name)\n\n    model_url = f\"{BASE_URL}/{file_name}.xz\"\n    LOGGER.info(f\"Checking ETAG of {model_url}\")\n    r = requests.head(model_url, allow_redirects=True)\n    r.raise_for_status()\n    new_etag = r.headers[\"ETag\"]\n\n    try:\n        with open(f\"{file_path}.etag\", \"r\") as f:\n            old_etag = f.read()\n    except IOError:\n        old_etag = None\n\n    if old_etag != new_etag:\n        LOGGER.info(f\"Downloading the model from {model_url}\")\n        urlretrieve(model_url, f\"{file_path}.xz\")\n\n        with lzma.open(f\"{file_path}.xz\", \"rb\") as input_f:\n            with open(file_path, \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n                LOGGER.info(f\"Written model in {file_path}\")\n\n        with open(f\"{file_path}.etag\", \"w\") as f:\n            f.write(new_etag)\n    else:\n        LOGGER.info(f\"ETAG for {model_url} is ok\")\n\n    return file_path\n\n\ndef preload_models():\n    for model_name in MODELS_NAMES:\n        retrieve_model(model_name)\n\n\nif __name__ == \"__main__\":\n    preload_models()\n", "path": "http_service/download_models.py"}], "after_files": [{"content": "# -*- coding: utf-8 -*-\n\nimport argparse\nimport lzma\nimport os\nimport shutil\nfrom logging import INFO, basicConfig, getLogger\nfrom urllib.request import urlretrieve\n\nfrom bugbug.models.component import ComponentModel\nfrom bugbug.models.defect_enhancement_task import DefectEnhancementTaskModel\nfrom bugbug.models.regression import RegressionModel\nfrom bugbug.models.tracking import TrackingModel\n\nbasicConfig(level=INFO)\nlogger = getLogger(__name__)\n\nBASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.data_{}.latest/artifacts/public\"\n\n\nclass Trainer(object):\n    def decompress_file(self, path):\n        with lzma.open(f\"{path}.xz\", \"rb\") as input_f:\n            with open(path, \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n\n    def compress_file(self, path):\n        with open(path, \"rb\") as input_f:\n            with lzma.open(f\"{path}.xz\", \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n\n    def train_defect_enhancement_task(self):\n        logger.info(\"Training *defect vs enhancement vs task* model\")\n        model = DefectEnhancementTaskModel()\n        model.train()\n        self.compress_file(\"defectenhancementtaskmodel\")\n\n    def train_component(self):\n        logger.info(\"Training *component* model\")\n        model = ComponentModel()\n        model.train()\n        self.compress_file(\"componentmodel\")\n\n    def train_regression(self):\n        logger.info(\"Training *regression vs non-regression* model\")\n        model = RegressionModel()\n        model.train()\n        self.compress_file(\"regressionmodel\")\n\n    def train_tracking(self):\n        logger.info(\"Training *tracking* model\")\n        model = TrackingModel()\n        model.train()\n        self.compress_file(\"trackingmodel\")\n\n    def go(self, model):\n        # TODO: Stop hard-coding them\n        valid_models = [\"defect\", \"component\", \"regression\", \"tracking\"]\n\n        if model not in valid_models:\n            exception = (\n                f\"Invalid model {model!r} name, use one of {valid_models!r} instead\"\n            )\n            raise ValueError(exception)\n\n        # Download datasets that were built by bugbug_data.\n        os.makedirs(\"data\", exist_ok=True)\n\n        # Bugs.json\n        logger.info(\"Downloading bugs database\")\n        bugs_url = BASE_URL.format(\"bugs\")\n        urlretrieve(f\"{bugs_url}/bugs.json.xz\", \"data/bugs.json.xz\")\n        logger.info(\"Decompressing bugs database\")\n        self.decompress_file(\"data/bugs.json\")\n\n        # Commits.json\n        logger.info(\"Downloading commits database\")\n        commits_url = BASE_URL.format(\"commits\")\n        urlretrieve(f\"{commits_url}/commits.json.xz\", \"data/commits.json.xz\")\n        logger.info(\"Decompressing commits database\")\n        self.decompress_file(\"data/commits.json\")\n\n        if model == \"defect\":\n            # Train classifier for defect-vs-enhancement-vs-task.\n            self.train_defect_enhancement_task()\n        elif model == \"component\":\n            # Train classifier for the component of a bug.\n            self.train_component()\n        elif model == \"regression\":\n            # Train classifier for regression-vs-nonregression.\n            self.train_regression()\n        elif model == \"tracking\":\n            # Train classifier for tracking bugs.\n            self.train_tracking()\n        else:\n            # We shouldn't be here\n            raise Exception(\"valid_models is likely not up-to-date anymore\")\n\n\ndef main():\n    description = \"Train the models\"\n    parser = argparse.ArgumentParser(description=description)\n\n    parser.add_argument(\"model\", help=\"Which model to train.\")\n\n    args = parser.parse_args()\n\n    retriever = Trainer()\n    retriever.go(args.model)\n", "path": "scripts/trainer.py"}, {"content": "# -*- coding: utf-8 -*-\n# This Source Code Form is subject to the terms of the Mozilla Public\n# License, v. 2.0. If a copy of the MPL was not distributed with this file,\n# You can obtain one at http://mozilla.org/MPL/2.0/.\n\nimport logging\nimport lzma\nimport os\nimport shutil\nfrom urllib.request import urlretrieve\n\nimport requests\n\nlogging.basicConfig(level=logging.INFO)\nLOGGER = logging.getLogger()\n\nBASE_URL = \"https://index.taskcluster.net/v1/task/project.relman.bugbug.train_{}.latest/artifacts/public\"\n\nMODELS_NAMES = (\"defectenhancementtask\", \"component\", \"regression\")\nMODELS_DIR = os.path.join(os.path.dirname(__file__), \"models\")\n\n\ndef retrieve_model(name):\n    os.makedirs(MODELS_DIR, exist_ok=True)\n\n    file_name = f\"{name}model\"\n    file_path = os.path.join(MODELS_DIR, file_name)\n\n    base_model_url = BASE_URL.format(name)\n    model_url = f\"{base_model_url}/{file_name}.xz\"\n    LOGGER.info(f\"Checking ETAG of {model_url}\")\n    r = requests.head(model_url, allow_redirects=True)\n    r.raise_for_status()\n    new_etag = r.headers[\"ETag\"]\n\n    try:\n        with open(f\"{file_path}.etag\", \"r\") as f:\n            old_etag = f.read()\n    except IOError:\n        old_etag = None\n\n    if old_etag != new_etag:\n        LOGGER.info(f\"Downloading the model from {model_url}\")\n        urlretrieve(model_url, f\"{file_path}.xz\")\n\n        with lzma.open(f\"{file_path}.xz\", \"rb\") as input_f:\n            with open(file_path, \"wb\") as output_f:\n                shutil.copyfileobj(input_f, output_f)\n                LOGGER.info(f\"Written model in {file_path}\")\n\n        with open(f\"{file_path}.etag\", \"w\") as f:\n            f.write(new_etag)\n    else:\n        LOGGER.info(f\"ETAG for {model_url} is ok\")\n\n    return file_path\n\n\ndef preload_models():\n    for model_name in MODELS_NAMES:\n        retrieve_model(model_name)\n\n\nif __name__ == \"__main__\":\n    preload_models()\n", "path": "http_service/download_models.py"}]}