Wandbify skills by ngrayluna · Pull Request #647 · wandb/examples

ngrayluna · 2026-08-26T23:35:19Z

Summary

Adds tooling (Python scripts) for converting Colab/Jupyter notebooks to marimo and consolidates marimo conversion guidance into a focused W&B-specific skill.

How this works

convert -> inspect diagnostics -> clean up with an agent -> verify

scripts/convert-colab-to-marimo.py converts individual .ipynb notebooks or a batch list to marimo .py files. It runs marimo convert and an initial marimo check. Records and saves diagnostics as JSON and/or .txt files.

Outputs are written under marimo/convert/:

marimo/convert/
  <example-name>/
    <example_name>.py
    .logs/
      result.json
      marimo-*.log
  convert-summary.txt

Converted notebooks may still need cleanup before they can run successfully on molab. An agent uses the generated output files (.json) to identify blockers, then use the marimo notebook skill to fix reactive-graph issues (i.e. marimo idioms) and preserve tutorial intent (i.e. preserve teaching qualities of the notebook).

Skill updates

Replaces the previous general marimo/Jupyter conversion guidance with one repo-specific skill:

SKILL.md
references/
  convert-cleanup.md
  marimo-idioms.md
  tutorial-notebook-objectives.md
  wandb-patterns.md

Key changes:

SKILL.md: defines the conversion and cleanup workflow.
convert-cleanup.md: covers conversion diagnostics and cleanup.
marimo-idioms.md: contains marimo mechanics and reactive-notebook conventions.
tutorial-notebook-objectives.md: covers tutorial narrative, purpose
wandb-patterns.md: contains W&B SDK conventions
scripts/convert-colab-to-marimo.py handles mechanical conversion and initial validation; agents rerun marimo check during cleanup and final verification.

The previous marimo skills were too broad, generic for wandb/examples. It also removed the teaching quality with strict rules about helper functions.

Scripts added

scripts/colab_sources/make_list.py: converts the source CSV into a deduplicated notebook path list.
scripts/colab_sources/notebook_paths.txt: batch input for conversion.
scripts/convert-colab-to-marimo.py: converts notebooks, runs the initial check, and records diagnostics.

github-actions · 2026-08-26T23:35:33Z

▶️ Run the marimo notebook(s) in this PR

molab launches any public marimo notebook on GitHub in a hosted environment — no local setup required.

Notebook	molab
`marimo/convert/alphafold-with-w-b-align-fold-log/alphafold_with_w_b_align_fold_log.py`
`marimo/convert/configs-in-w-b/configs_in_w_b.py`
`marimo/convert/custom-progress-callback/custom_progress_callback.py`
`marimo/convert/huggingface-wandb/huggingface_wandb.py`
`marimo/convert/hyperparameter-optimization-in-tensorflow-using-w-b-sweeps/hyperparameter_optimization_in_tensorflow_using_w_b_sweeps.py`
`marimo/convert/intro-to-weights-biases-keras/intro_to_weights_biases_keras.py`
`marimo/convert/intro-to-weights-biases/intro_to_weights_biases.py`
`marimo/convert/lcm-diffusers/lcm_diffusers.py`
`marimo/convert/log-a-confusion-matrix-with-w-b/log_a_confusion_matrix_with_w_b.py`
`marimo/convert/log-almost-anything-with-w-b-media/log_almost_anything_with_w_b_media.py`
`marimo/convert/openai-api-autologger-quickstart/openai_api_autologger_quickstart.py`
`marimo/convert/optimize-hugging-face-models-with-weights-biases/optimize_hugging_face_models_with_weights_biases.py`
`marimo/convert/optimize-pytorch-lightning-models-with-weights-biases/optimize_pytorch_lightning_models_with_weights_biases.py`
`marimo/convert/organizing-hyperparameter-sweeps-in-pytorch-with-w-b/organizing_hyperparameter_sweeps_in_pytorch_with_w_b.py`
`marimo/convert/pipeline-versioning-with-w-b-artifacts/pipeline_versioning_with_w_b_artifacts.py`
`marimo/convert/plot-roc-curves-with-w-b/plot_roc_curves_with_w_b.py`
`marimo/convert/report-api-quickstart/report_api_quickstart.py`
`marimo/convert/simple-pytorch-integration/simple_pytorch_integration.py`
`marimo/convert/torchtune-and-wandb/torchtune_and_wandb.py`
`marimo/convert/train-and-debug-yolov5-models-with-weights-biases/train_and_debug_yolov5_models_with_weights_biases.py`
`marimo/convert/use-wandbevalcallback-in-your-keras-workflow/use_wandbevalcallback_in_your_keras_workflow.py`
`marimo/convert/use-wandbmetriclogger-in-your-keras-workflow/use_wandbmetriclogger_in_your_keras_workflow.py`
`marimo/convert/use-wandbmodelcheckpoint-in-your-keras-workflow/use_wandbmodelcheckpoint_in_your_keras_workflow.py`
`marimo/convert/using-w-b-sweeps-with-xgboost/using_w_b_sweeps_with_xgboost.py`
`marimo/convert/w-b-tables-quickstart/w_b_tables_quickstart.py`
`marimo/convert/wandb-artifacts-time-to-live-ttl-walkthrough/wandb_artifacts_time_to_live_ttl_walkthrough.py`
`marimo/convert/zoo-wandb/zoo_wandb.py`

Links track the head of wandbify_skills.

+    with wandb.init(project="visualize-predictions", name="html") as run:
+        # Log HTML from file
+        path_to_html = "examples/data/some_html.html"
+        run.log({"custom_file": wandb.Html(open(path_to_html))})


+    # Initialize a new run
+    with wandb.init(project="visualize-predictions", name="3d_objects") as run:
+        path_to_obj = "examples/data/wolf.obj"
+        run.log({"3d_object": wandb.Object3D(open(path_to_obj))})


+            model_runner = model.RunModel(cfg, params)
+            processed_feature_dict = model_runner.process_features(feature_dict, random_seed=0)
+            prediction_result = model_runner.predict(processed_feature_dict)
+            mean_plddt = prediction_result['plddt'].mean()


+        x_train, x_test = (x_train / 255.0, x_test / 255.0)
+        x_train, y_train = (x_train[::5], y_train[::5])
+        x_test, y_test = (x_test[::20], y_test[::20])
+        labels = [str(digit) for digit in range(np.max(y_train) + 1)]


+    autolog(init=dict(project="diffusers_logging"))
+
+    # call the pipeline to generate the images
+    images = pipeline(


+                    "optimizer": "Adam"}
+
+    entity = wandb_entity.value.strip() or None
+    model = train_and_log(train_config, entity=entity)


Copilot

Pull request overview

Adds a repo-specific “marimo ↔️ W&B examples” agent skill plus conversion tooling and artifacts to support batch conversion of Colab/Jupyter notebooks (.ipynb) into marimo notebooks (.py) with saved diagnostics under marimo/convert/.

Changes:

Added scripts/convert-colab-to-marimo.py for single/batch conversion + marimo check + structured diagnostics output.
Added scripts/colab_sources/* inputs and a small helper script (make_list.py) to build normalized conversion path lists.
Replaced prior generic/vendored marimo skills with a consolidated repo-specific skill (marimo-wandb-notebooks) and committed initial conversion outputs/logs under marimo/convert/.

Reviewed changes

Copilot reviewed 83 out of 107 changed files in this pull request and generated 10 comments.

Show a summary per file

File	Description
scripts/convert-colab-to-marimo.py	Conversion runner that invokes `marimo convert/check` and writes `.logs/` + batch summary.
scripts/colab_sources/make_list.py	Builds a normalized, deduped path list from the CSV “Path” column.
scripts/colab_sources/notebook_paths.txt	Batch input list for conversions.
scripts/colab_sources/Notebook_mentions_Exported_wandb_docs_models_list.csv	Source CSV of doc references/paths used to derive conversion targets.
marimo/convert/convert-summary.txt	Human-readable batch conversion summary.
marimo/convert/zoo-wandb/.logs/result.json	Per-notebook structured conversion/check result.
marimo/convert/zoo-wandb/.logs/marimo-convert.log	Captured `marimo convert` transcript.
marimo/convert/zoo-wandb/.logs/marimo-check.log	Captured `marimo check` transcript.
marimo/convert/torchtune-and-wandb/torchtune_and_wandb.py	Converted marimo notebook output (currently with check blockers).
marimo/convert/torchtune-and-wandb/.logs/result.json	Diagnostics for torchtune conversion/check.
marimo/convert/torchtune-and-wandb/.logs/marimo-convert.log	`marimo convert` transcript for torchtune.
marimo/convert/torchtune-and-wandb/.logs/marimo-check.log	`marimo check` transcript for torchtune.
marimo/convert/lcm-diffusers/lcm_diffusers.py	Converted marimo notebook output for diffusers example.
marimo/convert/lcm-diffusers/.logs/result.json	Diagnostics for lcm-diffusers conversion/check.
marimo/convert/openai-api-autologger-quickstart/openai_api_autologger_quickstart.py	Converted marimo notebook output for OpenAI autologger tutorial.
marimo/convert/openai-api-autologger-quickstart/.logs/result.json	Diagnostics for OpenAI autologger conversion/check.
marimo/convert/huggingface-wandb/huggingface_wandb.py	Converted marimo notebook output for Hugging Face integration tutorial.
marimo/convert/huggingface-wandb/.logs/result.json	Diagnostics for huggingface-wandb conversion/check.
marimo/convert/plot-roc-curves-with-w-b/plot_roc_curves_with_w_b.py	Converted marimo notebook output for ROC curve plotting tutorial.
marimo/convert/plot-roc-curves-with-w-b/.logs/result.json	Diagnostics for plot-roc conversion/check.
marimo/convert/log-a-confusion-matrix-with-w-b/log_a_confusion_matrix_with_w_b.py	Converted marimo notebook output for confusion matrix tutorial.
marimo/convert/log-a-confusion-matrix-with-w-b/.logs/result.json	Diagnostics for confusion-matrix conversion/check.
marimo/convert/configs-in-w-b/configs_in_w_b.py	Converted marimo notebook output for configs tutorial.
marimo/convert/configs-in-w-b/.logs/result.json	Diagnostics for configs conversion/check.
marimo/convert/use-wandbmodelcheckpoint-in-your-keras-workflow/use_wandbmodelcheckpoint_in_your_keras_workflow.py	Converted marimo notebook output for Keras ModelCheckpoint tutorial.
marimo/convert/use-wandbmodelcheckpoint-in-your-keras-workflow/.logs/result.json	Diagnostics for that conversion/check.
marimo/convert/use-wandbmetriclogger-in-your-keras-workflow/use_wandbmetriclogger_in_your_keras_workflow.py	Converted marimo notebook output for Keras MetricsLogger tutorial.
marimo/convert/use-wandbmetriclogger-in-your-keras-workflow/.logs/result.json	Diagnostics for that conversion/check.
marimo/convert/use-wandbevalcallback-in-your-keras-workflow/.logs/result.json	Diagnostics for EvalCallback conversion/check.
marimo/convert/credit-scorecards-with-xgboost-and-w-b/.logs/result.json	Diagnostics for credit-scorecards conversion/check.
marimo/convert/using-w-b-sweeps-with-xgboost/.logs/result.json	Diagnostics for XGBoost sweeps conversion/check.
marimo/convert/w-b-tables-quickstart/.logs/result.json	Diagnostics for tables quickstart conversion/check.
marimo/convert/report-api-quickstart/.logs/result.json	Diagnostics for report API conversion/check.
marimo/convert/simple-pytorch-integration/.logs/result.json	Diagnostics for PyTorch integration conversion/check.
marimo/convert/organizing-hyperparameter-sweeps-in-pytorch-with-w-b/.logs/result.json	Diagnostics for sweeps notebook conversion/check.
marimo/convert/organizing-hyperparameter-sweeps-in-pytorch-with-w-b/.logs/marimo-convert.log	`marimo convert` transcript for sweeps notebook.
marimo/convert/organizing-hyperparameter-sweeps-in-pytorch-with-w-b/.logs/marimo-check.log	`marimo check` transcript for sweeps notebook.
marimo/convert/pipeline-versioning-with-w-b-artifacts/.logs/result.json	Diagnostics for artifacts pipeline conversion/check.
marimo/convert/pipeline-versioning-with-w-b-artifacts/.logs/marimo-convert.log	`marimo convert` transcript for artifacts pipeline.
marimo/convert/pipeline-versioning-with-w-b-artifacts/.logs/marimo-check.log	`marimo check` transcript for artifacts pipeline.
marimo/convert/alphafold-with-w-b-align-fold-log/.logs/result.json	Diagnostics for AlphaFold conversion/check.
marimo/convert/alphafold-with-w-b-align-fold-log/.logs/marimo-convert.log	`marimo convert` transcript for AlphaFold.
marimo/convert/alphafold-with-w-b-align-fold-log/.logs/marimo-check.log	`marimo check` transcript for AlphaFold.
marimo/convert/train-and-debug-yolov5-models-with-weights-biases/.logs/result.json	Diagnostics for YOLOv5 conversion/check.
marimo/convert/optimize-pytorch-lightning-models-with-weights-biases/.logs/result.json	Diagnostics for PyTorch Lightning conversion/check.
marimo/convert/optimize-hugging-face-models-with-weights-biases/.logs/result.json	Diagnostics for HF optimization conversion/check.
marimo/convert/hyperparameter-optimization-in-tensorflow-using-w-b-sweeps/.logs/result.json	Diagnostics for TF sweeps conversion/check.
marimo/convert/intro-to-weights-biases-keras/intro_to_weights_biases_keras.py	Converted marimo notebook output for Keras intro tutorial.
marimo/convert/intro-to-weights-biases-keras/.logs/result.json	Diagnostics for Keras intro conversion/check.
marimo/convert/intro-to-weights-biases/.logs/result.json	Diagnostics for intro conversion/check.
marimo/convert/log-almost-anything-with-w-b-media/.logs/result.json	Diagnostics for “log media” conversion/check.
marimo/convert/wandb-artifacts-time-to-live-ttl-walkthrough/.logs/result.json	Diagnostics for TTL walkthrough conversion/check.
marimo/convert/custom-progress-callback/.logs/result.json	Diagnostics for custom callback conversion/check.
marimo/convert/log-almost-anything-with-w-b-media/.logs/result.json	Diagnostics for media logging conversion/check.
.agents/skills/README.md	Updates skill index to point to consolidated repo-specific skill + conversion script.
.agents/skills/marimo-wandb-notebooks/SKILL.md	New consolidated skill definition + workflow guidance.
.agents/skills/marimo-wandb-notebooks/references/convert-cleanup.md	Reference: how to interpret/act on conversion logs.
.agents/skills/marimo-wandb-notebooks/references/marimo-idioms.md	Reference: marimo structure/idioms for this repo.
.agents/skills/marimo-wandb-notebooks/references/tutorial-notebook-objectives.md	Reference: preserve tutorial narrative/teaching surface.
.agents/skills/marimo-wandb-notebooks/references/wandb-patterns.md	Reference: W&B SDK usage patterns for tutorials.
.agents/skills/marimo-notebook/SKILL.md	Removed vendored generic skill content.
.agents/skills/marimo-notebook/references/WATCHING.md	Removed (vendored references cleanup).
.agents/skills/marimo-notebook/references/UI.md	Removed.
.agents/skills/marimo-notebook/references/TOP-LEVEL-IMPORTS.md	Removed.
.agents/skills/marimo-notebook/references/STATE.md	Removed.
.agents/skills/marimo-notebook/references/SQL.md	Removed.
.agents/skills/marimo-notebook/references/REACTIVITY.md	Removed.
.agents/skills/marimo-notebook/references/PYTEST.md	Removed.
.agents/skills/marimo-notebook/references/EXPORTS.md	Removed.
.agents/skills/marimo-notebook/references/EXPENSIVE.md	Removed.
.agents/skills/marimo-notebook/references/DEPLOYMENT.md	Removed.
.agents/skills/marimo-notebook/references/CONFIGURATION.md	Removed.
.agents/skills/marimo-notebook/references/COLUMNS.md	Removed.
.agents/skills/marimo-notebook/references/ANYWIDGET.md	Removed.
.agents/skills/marimo-notebook/LICENSE	Removed.
.agents/skills/marimo-example-notebook/SKILL.md	Removed (superseded by consolidated skill).
.agents/skills/jupyter-to-marimo/SKILL.md	Removed (superseded by consolidated skill).
.agents/skills/jupyter-to-marimo/references/widgets.md	Removed.
.agents/skills/jupyter-to-marimo/references/latex.md	Removed.
.agents/skills/jupyter-to-marimo/LICENSE	Removed.
.gitignore	Ignores conversion scratch dirs under `examples/marimo/*/.conversion/` and a CSV path.

💡 Add a code-review agent skill or configure MCP servers for context-aware, tailored reviews. Learn more in the docs.

+    print(f"Converting {display_path(source, repo_root)}...", flush=True)
+    commands["convert"] = run_command(
+        ["uvx", "marimo", "convert", str(source), "-o", str(target)],
+        cwd=repo_root,
+    )
+
+    if commands["convert"].returncode != 0:
+        status = "convert_failed"
+        failed_stage = "convert"
+    else:
+        print(f"Checking {display_path(target, repo_root)}...", flush=True)
+        commands["check"] = run_command(
+            ["uvx", "marimo", "check", str(target)],
+            cwd=repo_root,
+        )
+        failed_stage = "check" if commands["check"].returncode != 0 else None
+        status = "check_failed" if failed_stage else "ok"


+    with open(args.input_file, newline="", encoding="utf-8") as f:
+        paths = {
+            normalize_path(row["Path"])
+            for row in csv.DictReader(f)
+            if row.get("Path")
+        }


+colabs/intro/Intro_to_Weights_&_Biases_keras.ipynb
+colabs/intro/Report_API_Quickstart.ipynb
+colabs/intro/run_quickstart.ipynb
+colabs/keras/Keras_pipeline_with_Weights_and_Biases.ipynb


+examples/boosting-algorithms/xgboost-housing/train.py
+examples/keras/keras-cnn-fashion/train.py
+examples/pytorch/pytorch-cnn-fashion/fashion_data.py
+examples/pytorch/pytorch-ddp/log-ddp.py
+examples/tensorflow/tf-cnn-fashion/train.py
+examples/tensorflow/tf-estimator-mnist/mnist.py
+examples/wandb-sweeps/sweeps-xgboost/xgboost_tune.py


+@app.cell
+def _(openai):
+    # pass your OpenAI key
+    openai.api_key = 'sk-foo'
+    return


+@app.cell
+def _(os, subprocess):
+    os.environ['WANDB_PROJECT'] = 'huggingface-demo'
+    os.environ['TASK_NAME'] = 'MRPC'
+    #! python run_glue.py --model_name_or_path bert-base-uncased --task_name $TASK_NAME --do_train --do_eval --max_seq_length 256 --per_device_train_batch_size 32 --learning_rate 2e-4 --num_train_epochs 3 --output_dir /tmp/$TASK_NAME/ --overwrite_output_dir --logging_steps 50
+    subprocess.call(['python', 'run_glue.py', '--model_name_or_path', 'bert-base-uncased', '--task_name', '$TASK_NAME', '--do_train', '--do_eval', '--max_seq_length', '256', '--per_device_train_batch_size', '32', '--learning_rate', '2e-4', '--num_train_epochs', '3', '--output_dir', '/tmp/$TASK_NAME/', '--overwrite_output_dir', '--logging_steps', '50'])
+    return


+    - Manage image generation experiments using [Weights & Biases](http://wandb.ai/site).
+    - Log the prompts, generated images and experiment configs to [Weigts & Biases](http://wandb.ai/site) for visalization.
+
+    ![](./assets/diffusers-autolog-4.gif)


+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""
+    # Getting Started with torchtune and Weigths & Biases
+
+    In this notebook you will learn how to use [torchtune](https://github.com/pytorch/torchtune) with [Weights & Biases](https://wandb.ai) to monitor your training runs.
+    """)
+    return
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""
+    > You need to select a machine a GPU, go to Runtime > Change runtime type > select a GPU (L40, A100 ideally)
+    """)
+    return


+    # this determines the name of your wandb project, where all your
+    # runs will be loggeed


+      "command": [
+        "uvx",
+        "marimo",
+        "check",
+        "/Users/noahluna/Desktop/examples_group/examples/marimo/convert/zoo-wandb/zoo_wandb.py"
+      ],
+      "exit_code": 1,
+      "log": "marimo/convert/zoo-wandb/.logs/marimo-check.log"
+    },
+    "convert": {
+      "command": [
+        "uvx",
+        "marimo",
+        "convert",
+        "/Users/noahluna/Desktop/examples_group/examples/colabs/wandb_registry/zoo_wandb.ipynb",
+        "-o",
+        "/Users/noahluna/Desktop/examples_group/examples/marimo/convert/zoo-wandb/zoo_wandb.py"
+      ],


ngrayluna and others added 30 commits August 11, 2026 12:37

wip

c5313cf

remove vendor skill

7eeb511

wip

35d85f4

prepare-marimo-ex.sh updates

336fdc4

added table for logic

50435ea

wip

4b49b5f

clean up

86442bf

remove CSV file

0b38cef

rename

a4b689d

change script name

ed3786e

update docstrings

32cd72e

correct docstring

2f90e39

update .md

80be87a

renamed files

eb7d639

add convert txt file

e79afce

change naming

515ece0

add rough convert-cleanup.md

bba53f8

update SKILL.md so it checks logs first

755acf9

wip

e77e895

organize skills

b9642ac

add tutorial skill

8e371c2

more editing

1dd3fd8

update wb and marimo references

0457daf

add reference links as backup

29935fb

remove duplicate rule

a13a53b

wip

f07ad53

wip

d0e683b

not confuse app vs function decorator cells

3198575

add converted marimo scripts

4e60132

Run marimo-wandb-notebooks skill on file

b98df1f

Copilot AI lite review requested due to automatic review settings August 26, 2026 23:35

Copilot started reviewing on behalf of ngrayluna August 26, 2026 23:35 View session

github-code-quality Bot found potential problems Aug 26, 2026

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Wandbify skills - #647

Wandbify skills#647
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		# this determines the name of your wandb project, where all your
		# runs will be loggeed

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ngrayluna commented Aug 26, 2026

Summary

How this works

Skill updates

Scripts added

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github-actions Bot commented Aug 26, 2026

▶️ Run the marimo notebook(s) in this PR

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