[BUG] .ipynb notebook artifacts are served as application/octet-stream instead of text/plain

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Issues Policy acknowledgement

• I have read and agree to submit bug reports in accordance with the issues policy

Where did you encounter this bug?

Local machine

MLflow version

• Client: 3.x.y
• Tracking server: 3.x.y

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 22.04 / Windows 11 (reproducible on any OS)
• Python version: 3.10+

Describe the problem

Jupyter notebook (.ipynb) files logged as MLflow artifacts are always served with Content-Type: application/octet-stream, even though .ipynb files are plain-text JSON. This forces the browser to download the file instead of allowing the tracking server UI (or any client relying on the artifact's mime type) to preview/render it inline like other text-based artifacts (.py, .json, .md, .yaml, etc.).

Root cause: mlflow/utils/mime_type_utils.py's _guess_mime_type() first checks a hardcoded get_text_extensions() allowlist, then falls back to Python's stdlib mimetypes.guess_type(). Neither path recognizes .ipynb:

.ipynb is not present in get_text_extensions(). mimetypes.guess_type("notebook.ipynb") returns (None, None) since .ipynb is not a registered MIME type in the stdlib.

As a result, _guess_mime_type() falls through to the binary fallback and returns application/octet-stream.

Expected behavior: .ipynb files should be detected as text/plain (or application/x-ipynb+json) and be viewable in the artifact browser, consistent with how .py, .json, and .md files are handled.

Actual behavior: .ipynb files are always treated as opaque binary and force a download in the UI / artifact viewer instead of rendering inline.

Tracking information

Not applicable - this is a static mime-type detection bug, not run-specific.

Code to reproduce issue

from mlflow.utils.mime_type_utils import _guess_mime_type

print(_guess_mime_type("notebook.ipynb"))

Actual: application/octet-stream

Expected: text/plain

Stack trace

N/A - this is a behavioral/logic bug, not a crash. No exception is raised.

Other info / logs

import mlflow

with mlflow.start_run(): mlflow.log_artifact("notebook.ipynb")

Willingness to contribute

Yes. I can contribute a fix for this bug independently.

What component(s) does this bug affect?

• area/tracking: Tracking Service, tracking client APIs, autologging
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/scoring: MLflow model serving, deployment tools, Spark UDFs
• area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
• area/prompt: MLflow prompt engineering features, prompt templates, and prompt management
• area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
• area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
• area/projects: MLproject format, project running backends
• area/uiux: Front-end, user experience, plotting
• area/docs: MLflow documentation pages