chore: import upstream snapshot with attribution

.github/workflows/triage.md

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+# Synthetic triage dataset
+
+Each issue is separated by `---`. Expected result is noted in the header.
+
+---
+
+## Issue 1 — UI bug, no screenshot (expect comment)
+
+**Title:** Sidebar overlaps main content on narrow screens
+
+**Body:**
+When I resize the browser window to less than 1000px, the left sidebar overlaps
+with the experiment table. The columns become unreadable and I can't click on
+any runs.
+
+---
+
+## Issue 2 — UI bug with screenshot (expect no comment)
+
+**Title:** Run name truncated in experiment list
+
+**Body:**
+The run name gets cut off when it's longer than 30 characters. See below:
+
+![truncated run name](https://user-images.githubusercontent.com/12345/screenshot.png)
+
+MLflow 2.17.0, Python 3.11, macOS 14.
+
+Steps:
+
+1. Create a run with a long name
+2. Open the experiment page
+3. Observe the truncated name
+
+---
+
+## Issue 3 — Bug, no repro steps, no env info (expect comment)
+
+**Title:** `mlflow.log_metric` silently drops NaN values
+
+**Body:**
+I noticed that when I log NaN as a metric value, it just disappears. No error,
+no warning, nothing in the UI. This is really confusing because I thought my
+training was going fine but the metrics were just not being recorded.
+
+---
+
+## Issue 4 — Bug with repro steps and env info (expect no comment)
+
+**Title:** `mlflow server` crashes on startup with SQLite backend
+
+**Body:**
+**Environment:**
+
+- OS: Ubuntu 22.04
+- Python: 3.10.12
+- MLflow: 2.18.0
+
+**Steps to reproduce:**
+
+1. Install mlflow 2.18.0
+2. Run `mlflow server --backend-store-uri sqlite:///mlflow.db`
+3. Server crashes with `OperationalError: database is locked`
+
+**Traceback:**
+
+```
+Traceback (most recent call last):
+  File "/home/user/.local/lib/python3.10/site-packages/mlflow/server/__init__.py", line 42, in _run_server
+    store = _get_store(backend_store_uri)
+  File "/home/user/.local/lib/python3.10/site-packages/mlflow/store/tracking/__init__.py", line 75, in _get_store
+    return _tracking_store_registry.get_store(store_uri)
+  File "/home/user/.local/lib/python3.10/site-packages/mlflow/store/tracking/sqlalchemy_store.py", line 112, in __init__
+    self._setup_db()
+sqlite3.OperationalError: database is locked
+```
+
+---
+
+## Issue 5 — Feature request (expect no comment)
+
+**Title:** Add support for grouping runs by tag in the UI
+
+**Body:**
+It would be great to be able to group runs in the experiment view by a specific
+tag value. For example, I tag my runs with `model_type=cnn` or
+`model_type=transformer` and I'd love to see them grouped in the table.
+
+This is similar to how you can group by "dataset" in Weights & Biases.
+
+---
+
+## Issue 6 — Bug with repro steps but no env info (expect comment)
+
+**Title:** Autologging fails with PyTorch Lightning 2.5
+
+**Body:**
+When I enable autologging with PyTorch Lightning 2.5, I get an AttributeError.
+
+```python
+import mlflow
+
+mlflow.pytorch.autolog()
+
+trainer = pl.Trainer(max_epochs=5)
+trainer.fit(model, dataloader)
+```
+
+```
+AttributeError: module 'pytorch_lightning' has no attribute 'callbacks'
+```
+
+---
+
+## Issue 7 — Bug with env info but no repro steps (expect comment)
+
+**Title:** Model serving returns 500 on valid input
+
+**Body:**
+I deployed a model using `mlflow models serve` and it returns 500 errors
+on inputs that used to work fine. This started happening after I upgraded
+MLflow.
+
+Environment: Python 3.11, MLflow 2.18.0, macOS Sonoma.
+
+---
+
+## Issue 8 — UI bug, has env and repro but no screenshot (expect comment)
+
+**Title:** Chart tooltip shows wrong metric value
+
+**Body:**
+The tooltip on the metric chart shows a different value than what's actually
+plotted. The line is at ~0.95 but the tooltip says 0.42.
+
+**Environment:** MLflow 2.17.0, Python 3.10, Chrome 130, Ubuntu 22.04
+
+**Steps:**
+
+1. Log 100 metric values for "accuracy"
+2. Open the run page
+3. Hover over the chart line near the end
+4. Tooltip shows an incorrect value
+
+---
+
+## Issue 9 — Documentation issue (expect no comment)
+
+**Title:** Typo in quickstart guide
+
+**Body:**
+In the quickstart guide, the command `mlflow server --port 500` should be
+`mlflow server --port 5000`. The wrong port causes a "permission denied" error
+on Linux.
+
+---
+
+## Issue 10 — Bug, detailed report with everything (expect no comment)
+
+**Title:** `mlflow.evaluate()` fails with custom metrics on Spark DataFrame
+
+**Body:**
+**Environment:**
+
+- OS: CentOS 7
+- Python: 3.10.8
+- MLflow: 2.17.2
+- PySpark: 3.5.0
+
+**Description:**
+When passing a Spark DataFrame to `mlflow.evaluate()` with a custom metric
+function, the evaluation fails with a serialization error.
+
+**Steps to reproduce:**
+
+1. Create a Spark DataFrame with columns `prediction` and `target`
+2. Define a custom metric: `def rmse(eval_df, _): return np.sqrt(np.mean(...))`
+3. Call `mlflow.evaluate(model, data=spark_df, extra_metrics=[rmse])`
+
+**Error:**
+
+```
+pickle.PicklingError: Could not serialize object
+```
+
+**Expected behavior:**
+The evaluation should work with Spark DataFrames just like it does with
+Pandas DataFrames.
+
+---
+
+## Issue 11 — Security Vulnerability (expect no comment - filtered by triage.py)
+
+**Title:** Security Vulnerability: XSS in MLflow UI allows script injection
+
+**Body:**
+I discovered a cross-site scripting vulnerability in the MLflow UI that allows
+an attacker to inject malicious JavaScript code through experiment names.
+
+This is a serious security issue that needs immediate attention.
+
+---
+
+## Issue 12 — security vulnerability lowercase (expect no comment - filtered by triage.py)
+
+**Title:** security vulnerability in authentication module
+
+**Body:**
+Found a security issue in the authentication flow that allows bypassing login.