Commit regenerated Python API files and bump version

site/releases/validmind-library-releases.qmd

@@ -1,7 +1,7 @@
 ---
 title: "{{< var validmind.developer >}} releases"
-subtitle: "Latest: `v2.9.5`"
-date: "October 7, 2025"
+subtitle: "Latest: `v2.10.0`"
+date: "October 16, 2025"
 listing:
   contents: ../releases/validmind-library/**/pr-*.qmd
   fields: [date, title, categories, description]

site/validmind/_sidebar.yml

@@ -10,7 +10,7 @@ website:
         - text: "---"
         - text: "Python API"
         # Root level items from validmind.qmd
-        - text: "<span class='version'>`2.8.25`</span>"
+        - text: "<span class='version'>`2.10.0`</span>"
           file: validmind/validmind.qmd#version__
         - text: "init<span class='suffix'></span>"
           file: validmind/validmind.qmd#init
@@ -40,6 +40,8 @@ website:
           file: validmind/validmind.qmd#tasks
         - text: "test<span class='suffix'></span>"
           file: validmind/validmind.qmd#test
+        - text: "scorer_decorator<span class='suffix'></span>"
+          file: validmind/validmind.qmd#scorer_decorator
         - text: "log_text<span class='suffix'></span>"
           file: validmind/validmind.qmd#log_text
         - text: "experimental_agent<span class='suffix'></span>"
@@ -75,6 +77,13 @@ website:
                   file: validmind/validmind/datasets/credit_risk/lending_club.qmd
                 - text: "lending_club_bias"
                   file: validmind/validmind/datasets/credit_risk/lending_club_bias.qmd
+            - text: "llm"
+              file: validmind/validmind/datasets/llm.qmd
+              contents:
+                - text: "rag"
+                  file: validmind/validmind/datasets/llm/rag.qmd
+                - text: "rfp"
+                  file: validmind/validmind/datasets/llm/rag/rfp.qmd
             - text: "nlp"
               file: validmind/validmind/datasets/nlp.qmd
               contents:
@@ -91,6 +100,8 @@ website:
                   file: validmind/validmind/datasets/regression/lending_club.qmd
         - text: "errors"
           file: validmind/validmind/errors.qmd
+        - text: "scorer"
+          file: validmind/validmind/scorer.qmd
         - text: "test_suites"
           file: validmind/validmind/test_suites.qmd
           contents:
@@ -407,6 +418,17 @@ website:
                   file: validmind/validmind/tests/model_validation/statsmodels.qmd
                 - text: "statsutils"
                   file: validmind/validmind/tests/model_validation/statsmodels/statsutils.qmd
+            - text: "plots"
+              file: validmind/validmind/tests/plots.qmd
+              contents:
+                - text: "BoxPlot"
+                  file: validmind/validmind/tests/plots/BoxPlot.qmd
+                - text: "CorrelationHeatmap"
+                  file: validmind/validmind/tests/plots/CorrelationHeatmap.qmd
+                - text: "HistogramPlot"
+                  file: validmind/validmind/tests/plots/HistogramPlot.qmd
+                - text: "ViolinPlot"
+                  file: validmind/validmind/tests/plots/ViolinPlot.qmd
             - text: "prompt_validation"
               file: validmind/validmind/tests/prompt_validation.qmd
               contents:
@@ -426,6 +448,17 @@ website:
                   file: validmind/validmind/tests/prompt_validation/Specificity.qmd
                 - text: "ai_powered_test"
                   file: validmind/validmind/tests/prompt_validation/ai_powered_test.qmd
+            - text: "stats"
+              file: validmind/validmind/tests/stats.qmd
+              contents:
+                - text: "CorrelationAnalysis"
+                  file: validmind/validmind/tests/stats/CorrelationAnalysis.qmd
+                - text: "DescriptiveStats"
+                  file: validmind/validmind/tests/stats/DescriptiveStats.qmd
+                - text: "NormalityTests"
+                  file: validmind/validmind/tests/stats/NormalityTests.qmd
+                - text: "OutlierDetection"
+                  file: validmind/validmind/tests/stats/OutlierDetection.qmd
         - text: "unit_metrics"
           file: validmind/validmind/unit_metrics.qmd
         - text: "vm_models"

site/validmind/validmind.qmd

@@ -27,7 +27,7 @@ To initialize the ValidMind Library, paste the code snippet with the model ident
 import validmind as vm
 
 vm.init(
-  api_host = "https://api.dev.vm.validmind.ai/api/v1/tracking/tracking",
+  api_host = "https://app.prod.validmind.ai/api/v1/tracking/tracking",
   api_key = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
   api_secret = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
   project = "<project-identifier>"
@@ -44,7 +44,7 @@ After you have pasted the code snippet into your development source code and exe
 
 ::: {.signature}
 
-<span class="name">2.8.25</span>
+<span class="name">2.10.0</span>
 
 :::
 
@@ -66,7 +66,7 @@ If the API key and secret are not provided, the client will attempt to retrieve
 
 **Arguments**
 
-- `project (str, optional)`: The project CUID. Alias for model. Defaults to None. \[DEPRECATED\]
+- `project (str, optional)`: The project CUID. Alias for model. Defaults to None. [DEPRECATED]
 - `model (str, optional)`: The model CUID. Defaults to None.
 - `api_key (str, optional)`: The API key. Defaults to None.
 - `api_secret (str, optional)`: The API secret. Defaults to None.
@@ -213,7 +213,7 @@ This function provides an interface to retrieve the TestSuite instance for the c
 
 ::: {.signature}
 
-<span class="kw">def</span><span class="name">log_metric</span>(<span class="params"><span class="n">key</span><span class="p">:</span><span class="nb">str</span><span class="muted">,</span></span><span class="params"><span class="n">value</span><span class="p">:</span><span class="nb">float</span><span class="muted">,</span></span><span class="params"><span class="n">inputs</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">List</span><span class="p">\[</span><span class="nb">str</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">params</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">Dict</span><span class="p">\[</span><span class="nb">str</span><span class="p">, </span><span class="n">Any</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">recorded_at</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="nb">str</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">thresholds</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">Dict</span><span class="p">\[</span><span class="nb">str</span><span class="p">, </span><span class="n">Any</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">passed</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="nb">bool</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span></span>):
+<span class="kw">def</span><span class="name">log_metric</span>(<span class="params"><span class="n">key</span><span class="p">:</span><span class="nb">str</span><span class="muted">,</span></span><span class="params"><span class="n">value</span><span class="p">:</span><span class="n">Union</span><span class="p">\[</span><span class="nb">int</span><span class="p">, </span><span class="nb">float</span><span class="p">\]</span><span class="muted">,</span></span><span class="params"><span class="n">inputs</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">List</span><span class="p">\[</span><span class="nb">str</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">params</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">Dict</span><span class="p">\[</span><span class="nb">str</span><span class="p">, </span><span class="n">Any</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">recorded_at</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="nb">str</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">thresholds</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="n">Dict</span><span class="p">\[</span><span class="nb">str</span><span class="p">, </span><span class="n">Any</span><span class="p">\]</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span><span class="muted">,</span></span><span class="params"><span class="n">passed</span><span class="p">:</span><span class="n">Optional</span><span class="p">\[</span><span class="nb">bool</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span></span>):
 
 :::
 
@@ -226,11 +226,12 @@ Unit metrics are key-value pairs where the key is the metric name and the value
 **Arguments**
 
 - `key (str)`: The metric key
-- `value (Union[int, float])`: The metric value
+- `value (Union[int, float])`: The metric value (scalar)
 - `inputs (List[str])`: List of input IDs
 - `params (Dict[str, Any])`: Parameters used to generate the metric
 - `recorded_at (str)`: Timestamp when the metric was recorded
 - `thresholds (Dict[str, Any])`: Thresholds for the metric
+- `passed (bool)`: Whether the metric passed validation thresholds
 
 ## preview_template<span class="suffix"></span>
 
@@ -422,6 +423,61 @@ The function may also include a docstring. This docstring will be used and logge
 
 - The decorated function.
 
+## scorer_decorator<span class="suffix"></span>
+
+<!-- signatures.jinja2 -->
+
+::: {.signature}
+
+<span class="kw">def</span><span class="name">scorer</span>(<span class="param"><span class="n">func_or_id</span><span class="p">:</span><span class="n">Union</span><span class="p">\[</span><span class="n">Callable</span><span class="p">\[</span><span class="n">...</span><span class="p">, </span><span class="n">Any</span><span class="p">\]</span><span class="p">, </span><span class="nb">str</span><span class="p">, </span><span class="n">None</span><span class="p">\]</span><span class="o">=</span><span class="kc">None</span></span>)<span class="p"> → </span><span class="return-annotation"><span class="n">Callable</span><span class="p">\[</span><span class="p">\[</span><a href="/validmind/validmind/vm_models.qmd#f">validmind.vm_models.F</a><span class="p">\]</span><span class="p">, </span><a href="/validmind/validmind/vm_models.qmd#f">validmind.vm_models.F</a><span class="p">\]</span></span>:
+
+:::
+
+<!-- docstring.jinja2 -->
+
+Decorator for creating and registering custom scorers
+
+This decorator registers the function it wraps as a scorer function within ValidMind under the provided ID. Once decorated, the function can be run using the `validmind.scorer.run_scorer` function.
+
+The scorer ID can be provided in three ways:
+
+1. Explicit ID: `@scorer("validmind.scorer.classification.BrierScore")`
+1. Auto-generated from path: `@scorer()` - automatically generates ID from file path
+1. Function name only: `@scorer` - uses function name with validmind.scorer prefix
+
+The function can take two different types of arguments:
+
+- Inputs: ValidMind model or dataset (or list of models/datasets). These arguments must use the following names: `model`, `models`, `dataset`, `datasets`.
+- Parameters: Any additional keyword arguments of any type (must have a default value) that can have any name.
+
+The function should return one of the following types:
+
+- Table: Either a list of dictionaries or a pandas DataFrame
+- Plot: Either a matplotlib figure or a plotly figure
+- Scalar: A single number (int or float)
+- Boolean: A single boolean value indicating whether the test passed or failed
+- List: A list of values (for row-level metrics) or a list of dictionaries with consistent keys
+- Any other type: The output will be stored as raw data for use by calling code
+
+When returning a list of dictionaries:
+
+- All dictionaries must have the same keys
+- The list length must match the number of rows in the dataset
+- Each dictionary key will become a separate column when using assign_scores
+- Column naming follows the pattern: {model_id}_{metric_name}_{dict_key}
+
+Note: Scorer outputs are not logged to the backend and are intended for use by other parts of the system (e.g., assign_scores method).
+
+The function may also include a docstring. This docstring will be used and logged as the scorer's description.
+
+**Arguments**
+
+- `func_or_id (Union[Callable[..., Any], str, None], optional)`: Either the function to decorate or the scorer ID. If None or empty string, the ID is auto-generated from the file path. Defaults to None.
+
+**Returns**
+
+- The decorated function.
+
 ## log_text<span class="suffix"></span>
 
 <!-- signatures.jinja2 -->

site/validmind/validmind/datasets.qmd

@@ -12,5 +12,6 @@ Example datasets that can be used with the ValidMind Library.
 
 - [classification](datasets/classification.qmd)
 - [credit_risk](datasets/credit_risk.qmd)
+- [llm](datasets/llm.qmd)
 - [nlp](datasets/nlp.qmd)
 - [regression](datasets/regression.qmd)