[API] Update user agent for torchtune (#237)

Enable tracking of torchtune models via kagglehub api. This is the
change for kagglehub part. PR for midtier change is
http://go/kaggle-pr/34437

Fix = [b/381021004](https://buganizer.corp.google.com/issues/381021004)

Note: To test this change without midtier changes in production, you
need to have a midtier running locally and add breakpoint to review the
value for `userAgent` in `ProtoHttpRuleController.ApiV1.cs.` With that:

- Creating a python virtual environment

- Import this kagglehub version `pip install
git+https://github.com/Kaggle/kagglehub.git@nan_torch`

- Import torchtune and its required dependencies

- set environment variables 
export KAGGLE_USERNAME=[your_user_name]
export KAGGLE_KEY=local_api_token

- in virtual environment, run command `tune download
"google/bert/tensorFlow2/answer-equivalence-bem" --source "kaggle"`

- verify user agent has torchtune and its associated version 
<img width="650" alt="Screenshot 2025-03-30 at 12 18 49 PM"
src="https://github.com/user-attachments/assets/3993667f-489c-415a-9446-073bc926089c"
/>

Author: nl917

CHANGELOG.md

@@ -4,6 +4,10 @@
 
 *
 
+## v0.3.11 (April 1, 2025)
+
+* Add `torchtune` as user-agent ([#237](https://github.com/Kaggle/kagglehub/pull/237))
+
 ## v0.3.10 (February 25, 2025)
 
 * Fix Colab environment detection logic ([#230](https://github.com/Kaggle/kagglehub/pull/230))

src/kagglehub/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.3.10"
+__version__ = "0.3.11"
 
 import kagglehub.logger  # configures the library logger.
 from kagglehub import colab_cache_resolver, http_resolver, kaggle_cache_resolver, registry

src/kagglehub/clients.py

@@ -73,11 +73,10 @@ def get_user_agent() -> str:
         str: user agent information.
     """
     user_agents = [f"kagglehub/{kagglehub.__version__}"]
-
-    for keras_lib in ("keras_hub", "keras_nlp", "keras_cv", "keras"):
-        keras_info = search_lib_in_call_stack(keras_lib)
-        if keras_info is not None:
-            user_agents.append(keras_info)
+    for lib in ("keras_hub", "keras_nlp", "keras_cv", "keras", "torchtune"):
+        lib_info = search_lib_in_call_stack(lib)
+        if lib_info is not None:
+            user_agents.append(lib_info)
             break
 
     # Add an appropriate data loader user agent for kagglehub.dataset_load calls

tests/test_kaggle_api_client.py

@@ -138,3 +138,21 @@ def test_get_user_agent_keras_hub(
         mock_is_module.return_value = True
         mock_version.return_value = "0.17.0"
         self.assertEqual(clients.get_user_agent(), f"kagglehub/{kagglehub.__version__} keras_hub/0.17.0")
+
+    @patch("importlib.metadata.version")
+    @patch("inspect.ismodule")
+    @patch("inspect.stack")
+    def test_get_user_agent_torch_tune(
+        self, mock_stack: MagicMock, mock_is_module: MagicMock, mock_version: MagicMock
+    ) -> None:
+        # Mock the call stack and version information.
+        mock_stack.return_value = [
+            MagicMock(frame=MagicMock(__name__="kagglehub.clients")),
+            MagicMock(frame=MagicMock(__name__="kagglehub.models_helpers")),
+            MagicMock(frame=MagicMock(__name__="kagglehub.models")),
+            MagicMock(frame=MagicMock(__name__="torchtune.src.utils.preset_utils")),
+            MagicMock(frame=MagicMock(None)),
+        ]
+        mock_is_module.return_value = True
+        mock_version.return_value = "0.18.0"
+        self.assertEqual(clients.get_user_agent(), f"kagglehub/{kagglehub.__version__} torchtune/0.18.0")