Update 2026-03-25 15:35:35

app.py

@@ -9,7 +9,7 @@ import mlflow.sklearn
 from flask import Flask, render_template, request, jsonify
 
 from mlops.datasets import DATASETS, load_dataset
-from mlops.algorithms import ALGORITHMS, list_algorithms, all_algorithm_names
+from mlops.algorithms import ALGORITHMS, list_algorithms, all_algorithm_names, algorithms_for_json
 from mlops.trainer import (
     training_jobs, automl_jobs,
     start_training, start_automl,
@@ -144,7 +144,7 @@ def dashboard():
                            algo_counts=json.dumps(algo_counts),
                            ds_counts=json.dumps(ds_counts),
                            datasets=DATASETS,
-                           algorithms=ALGORITHMS)
+                           algorithms=algorithms_for_json())
 
 
 @app.route("/experiments")
@@ -255,7 +255,7 @@ def models():
 def automl():
     return render_template("automl.html",
                            datasets=DATASETS,
-                           algorithms=ALGORITHMS)
+                           algorithms=algorithms_for_json())
 
 
 # ══════════════════════════════════════════════════════════════════════════════
@@ -426,7 +426,7 @@ def api_automl_status(job_id):
 def api_algorithms():
     task = request.args.get("task", "classification")
     try:
-        return jsonify(list_algorithms(task))
+        return jsonify(algorithms_for_json(task))
     except ValueError as e:
         return jsonify({"error": str(e)}), 400
 

mlops/algorithms.py

@@ -390,3 +390,19 @@ def all_algorithm_names(task: str) -> list[str]:
     for cat in ALGORITHMS[task].values():
         names.extend(cat.keys())
     return names
+
+
+def algorithms_for_json(task: str | None = None) -> dict:
+    """Return ALGORITHMS (or a task subset) as a JSON-serializable dict.
+
+    Removes the non-serializable ``"class"`` key and converts tuples to lists.
+    """
+    def _clean(obj):
+        if isinstance(obj, dict):
+            return {k: _clean(v) for k, v in obj.items() if k != "class"}
+        if isinstance(obj, (list, tuple)):
+            return [_clean(i) for i in obj]
+        return obj
+
+    src = ALGORITHMS if task is None else ALGORITHMS[task]
+    return _clean(src)