wehub-resource-sync
218 lines
8.1 KiB
YAML
218 lines
8.1 KiB
YAML
name: Bug Report (Use "UI Bug Report" for UI bugs)
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description: Create a report to help us reproduce and correct the bug
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labels: "bug"
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title: "[BUG]"
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body:
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- type: markdown
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attributes:
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value: |
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> [!WARNING]
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> Before submitting a PR, please make sure that:
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> - A maintainer has triaged this issue and applied the `ready` label
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> - This issue has no assignee
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> - No duplicate PR exists
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>
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> PRs not meeting these requirements may be automatically closed.
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- type: markdown
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attributes:
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value: |
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Thank you for submitting an issue. Please refer to our [issue policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md) for additional information about bug reports. For help with debugging your code, please refer to [Stack Overflow](https://stackoverflow.com/questions/tagged/mlflow).
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#### Please fill in this bug report template to ensure a timely and thorough response.
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- type: checkboxes
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attributes:
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label: Issues Policy acknowledgement
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description: |
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I understand that failure to adhere to the issues guidance may result in my issue being closed without warning or response.
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options:
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- label: I have read and agree to submit bug reports in accordance with the [issues policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md)
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required: true
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- type: dropdown
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attributes:
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label: Where did you encounter this bug?
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options:
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- Local machine
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- Databricks
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- Azure Machine Learning
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- Other
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validations:
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required: true
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- type: textarea
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validations:
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required: true
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attributes:
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label: MLflow version
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description: MLflow version (run `mlflow --version`) or commit SHA if you have MLflow installed from source (run `pip freeze | grep mlflow`). The tracking server version is required if `mlflow server` is used.
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value: |
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- Client: 1.x.y
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- Tracking server: 1.x.y
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- type: textarea
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attributes:
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label: System information
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description: |
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Describe the system where you encountered the bug.
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value: |
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- **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**:
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- **Python version**:
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validations:
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required: true
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- type: textarea
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attributes:
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label: Describe the problem
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description: |
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Describe the problem clearly here. Include descriptions of the expected behavior and the actual behavior.
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validations:
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required: true
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- type: textarea
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attributes:
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label: Tracking information
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description: |
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For bugs related to the tracking features (e.g. mlflow should log a run in my database but it doesn't), please insert the following code in your python script / notebook where you encountered the bug and run it:
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```python
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# MLflow < 2.0
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print("MLflow version:", mlflow.__version__)
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print("Tracking URI:", mlflow.get_tracking_uri())
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print("Artifact URI:", mlflow.get_artifact_uri())
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# MLflow >= 2.0
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mlflow.doctor()
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```
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Then, make sure the printed out information matches what you expect and paste it (with sensitive information masked) in the box below. If you know the command that was used to launch your tracking server (e.g. `mlflow server -h 0.0.0.0 -p 5000`), please provide it.
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value: |
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<!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
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```shell
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REPLACE_ME
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```
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validations:
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required: false
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- type: textarea
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attributes:
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label: Code to reproduce issue
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description: |
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Provide a reproducible test case that is the bare minimum necessary to generate the problem.
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### Bad
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Requires modifications (e.g., adding missing import statements) to run.
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```python
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with mlflow.start_run(): # `mlflow` is not imported
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mlflow.sklearn.log_model(model, "model") # `model` is undefined
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```
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### Good
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Does not require any modifications to run.
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```python
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from sklearn.datasets import load_iris
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from sklearn.linear_model import LogisticRegression
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import mlflow
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X, y = load_iris(return_X_y=True)
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model = LogisticRegression().fit(X, y)
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with mlflow.start_run():
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mlflow.sklearn.log_model(model, "model")
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```
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value: |
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<!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
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```
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REPLACE_ME
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```
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validations:
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required: true
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- type: textarea
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attributes:
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label: Stack trace
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description: |
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Provide a **full** stack trace.
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### Bad
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```python
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TypeError: expected string or bytes-like object
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```
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### Good
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```python
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Traceback (most recent call last):
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File "a.py", line 3, in <module>
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mlflow.log_param(1, 2)
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File "/home/user/mlflow/mlflow/tracking/fluent.py", line 541, in log_param
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return MlflowClient().log_param(run_id, key, value)
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File "/home/user/mlflow/mlflow/tracking/client.py", line 742, in log_param
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self._tracking_client.log_param(run_id, key, value)
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File "/home/user/mlflow/mlflow/tracking/_tracking_service/client.py", line 295, in log_param
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self.store.log_param(run_id, param)
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File "/home/user/mlflow/mlflow/store/tracking/file_store.py", line 917, in log_param
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_validate_param(param.key, param.value)
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File "/home/user/mlflow/mlflow/utils/validation.py", line 150, in _validate_param
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_validate_param_name(key)
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File "/home/user/mlflow/mlflow/utils/validation.py", line 217, in _validate_param_name
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if not _VALID_PARAM_AND_METRIC_NAMES.match(name):
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TypeError: expected string or bytes-like object
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```
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value: |
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<!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
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```
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REPLACE_ME
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```
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validations:
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required: true
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- type: textarea
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attributes:
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label: Other info / logs
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description: |
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Include any logs or source code that would be helpful to diagnose the problem. Large logs and files should be attached.
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### Example
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```
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# Tracking server logs
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[2022-08-01 16:03:02 +0900] [222636] [INFO] Starting gunicorn 20.1.0
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[2022-08-01 16:03:02 +0900] [222636] [INFO] Listening at: http://127.0.0.1:5000 (222636)
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[2022-08-01 16:03:02 +0900] [222636] [INFO] Using worker: sync
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[2022-08-01 16:03:02 +0900] [222639] [INFO] Booting worker with pid: 222639
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```
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value: |
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<!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
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```
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REPLACE_ME
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```
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validations:
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required: false
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- type: checkboxes
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id: component
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attributes:
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label: What component(s) does this bug affect?
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description: Please choose one or more components below.
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options:
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- label: "`area/tracking`: Tracking Service, tracking client APIs, autologging"
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required: false
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- label: "`area/model-registry`: Model Registry service, APIs, and the fluent client calls for Model Registry"
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required: false
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- label: "`area/scoring`: MLflow model serving, deployment tools, Spark UDFs"
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required: false
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- label: "`area/evaluation`: MLflow model evaluation features, evaluation metrics, and evaluation workflows"
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required: false
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- label: "`area/prompt`: MLflow prompt engineering features, prompt templates, and prompt management"
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required: false
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- label: "`area/tracing`: MLflow Tracing features, tracing APIs, and LLM tracing functionality"
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required: false
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- label: "`area/gateway`: MLflow AI Gateway client APIs, server, and third-party integrations"
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required: false
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- label: "`area/projects`: MLproject format, project running backends"
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required: false
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- label: "`area/uiux`: Front-end, user experience, plotting"
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required: false
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- label: "`area/docs`: MLflow documentation pages"
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required: false
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