Fix bug with primitive types parsing in Worklfows

docs/workflows/blocks.md

@@ -64,6 +64,7 @@ hide:
 <p class="card block-card" data-url="lmm" data-name="LMM" data-desc="Run a large multimodal model such as ChatGPT-4v or CogVLM." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="lmm_for_classification" data-name="LMM For Classification" data-desc="Run a large multimodal model such as ChatGPT-4v or CogVLM for classification." data-labels="MODEL, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="label_visualization" data-name="Label Visualization" data-desc="Draws labels on an image at specific coordinates based on provided detections." data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>
+<p class="card block-card" data-url="classification_label_visualization" data-name="Classification Label Visualization" data-desc="Visualizes both single-label and multi-label classification predictions with customizable display options." data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="line_counter" data-name="Line Counter" data-desc="Count detections passing line" data-labels="ANALYTICS, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="line_counter_visualization" data-name="Line Counter Visualization" data-desc="Paints a mask over line zone in an image." data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>
 <p class="card block-card" data-url="mask_visualization" data-name="Mask Visualization" data-desc="Paints a mask over detected objects in an image." data-labels="VISUALIZATION, APACHE-2.0" data-author="dummy"></p>

docs/workflows/kinds.md

@@ -68,37 +68,38 @@ providing compile-time verification of Workflows definitions.
 
 ## Kinds declared in Roboflow plugins
 <!--- AUTOGENERATED_KINDS_LIST -->
-* [`image`](/workflows/kinds/image): Image in workflows
+* [`object_detection_prediction`](/workflows/kinds/object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object
 * [`float`](/workflows/kinds/float): Float value
-* [`numpy_array`](/workflows/kinds/numpy_array): Numpy array
-* [`prediction_type`](/workflows/kinds/prediction_type): String value with type of prediction
-* [`language_model_output`](/workflows/kinds/language_model_output): LLM / VLM output
 * [`image_metadata`](/workflows/kinds/image_metadata): Dictionary with image metadata required by supervision
-* [`keypoint_detection_prediction`](/workflows/kinds/keypoint_detection_prediction): Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object
-* [`top_class`](/workflows/kinds/top_class): String value representing top class predicted by classification model
+* [`prediction_type`](/workflows/kinds/prediction_type): String value with type of prediction
+* [`*`](/workflows/kinds/*): Equivalent of any element
+* [`dictionary`](/workflows/kinds/dictionary): Dictionary
+* [`roboflow_api_key`](/workflows/kinds/roboflow_api_key): Roboflow API key
+* [`classification_prediction`](/workflows/kinds/classification_prediction): Predictions from classifier
 * [`video_metadata`](/workflows/kinds/video_metadata): Video image metadata
+* [`detection`](/workflows/kinds/detection): Single element of detections-based prediction (like `object_detection_prediction`)
+* [`boolean`](/workflows/kinds/boolean): Boolean flag
+* [`bytes`](/workflows/kinds/bytes): This kind represent bytes
 * [`qr_code_detection`](/workflows/kinds/qr_code_detection): Prediction with QR code detection
 * [`contours`](/workflows/kinds/contours): List of numpy arrays where each array represents contour points
-* [`roboflow_model_id`](/workflows/kinds/roboflow_model_id): Roboflow model id
-* [`object_detection_prediction`](/workflows/kinds/object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object
+* [`language_model_output`](/workflows/kinds/language_model_output): LLM / VLM output
+* [`inference_id`](/workflows/kinds/inference_id): Inference identifier
+* [`serialised_payloads`](/workflows/kinds/serialised_payloads): Serialised element that is usually accepted by sink
+* [`string`](/workflows/kinds/string): String value
+* [`float_zero_to_one`](/workflows/kinds/float_zero_to_one): `float` value in range `[0.0, 1.0]`
+* [`rgb_color`](/workflows/kinds/rgb_color): RGB color
+* [`image`](/workflows/kinds/image): Image in workflows
 * [`roboflow_project`](/workflows/kinds/roboflow_project): Roboflow project name
+* [`top_class`](/workflows/kinds/top_class): String value representing top class predicted by classification model
 * [`image_keypoints`](/workflows/kinds/image_keypoints): Image keypoints detected by classical Computer Vision method
 * [`list_of_values`](/workflows/kinds/list_of_values): List of values of any type
-* [`float_zero_to_one`](/workflows/kinds/float_zero_to_one): `float` value in range `[0.0, 1.0]`
 * [`instance_segmentation_prediction`](/workflows/kinds/instance_segmentation_prediction): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object
-* [`rgb_color`](/workflows/kinds/rgb_color): RGB color
-* [`boolean`](/workflows/kinds/boolean): Boolean flag
+* [`keypoint_detection_prediction`](/workflows/kinds/keypoint_detection_prediction): Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object
+* [`numpy_array`](/workflows/kinds/numpy_array): Numpy array
 * [`bar_code_detection`](/workflows/kinds/bar_code_detection): Prediction with barcode detection
-* [`classification_prediction`](/workflows/kinds/classification_prediction): Predictions from classifier
-* [`string`](/workflows/kinds/string): String value
+* [`roboflow_model_id`](/workflows/kinds/roboflow_model_id): Roboflow model id
+* [`integer`](/workflows/kinds/integer): Integer value
 * [`parent_id`](/workflows/kinds/parent_id): Identifier of parent for step output
 * [`point`](/workflows/kinds/point): Single point in 2D
-* [`bytes`](/workflows/kinds/bytes): This kind represent bytes
-* [`serialised_payloads`](/workflows/kinds/serialised_payloads): Serialised element that is usually accepted by sink
-* [`dictionary`](/workflows/kinds/dictionary): Dictionary
-* [`*`](/workflows/kinds/*): Equivalent of any element
-* [`detection`](/workflows/kinds/detection): Single element of detections-based prediction (like `object_detection_prediction`)
-* [`integer`](/workflows/kinds/integer): Integer value
 * [`zone`](/workflows/kinds/zone): Definition of polygon zone
-* [`roboflow_api_key`](/workflows/kinds/roboflow_api_key): Roboflow API key
 <!--- AUTOGENERATED_KINDS_LIST -->

inference/core/workflows/execution_engine/introspection/schema_parser.py

@@ -40,6 +40,7 @@
 
 ITEMS_KEY = "items"
 UNIQUE_ITEMS_KEY = "uniqueItems"
+TUPLE_ITEMS_KEY = "prefixItems"
 TYPE_KEY = "type"
 REF_KEY = "$ref"
 ADDITIONAL_PROPERTIES_KEY = "additionalProperties"
@@ -134,6 +135,21 @@ def retrieve_primitive_type_from_property(
         return replace(
             result, type_annotation=f"{high_level_type}[{result.type_annotation}]"
         )
+    if TUPLE_ITEMS_KEY in property_definition:
+        nested_annotations = [
+            retrieve_primitive_type_from_property(
+                property_name=property_name,
+                property_description=property_description,
+                property_definition=nested_definition,
+            )
+            for nested_definition in property_definition[TUPLE_ITEMS_KEY]
+        ]
+        inner_types = ", ".join(a.type_annotation for a in nested_annotations)
+        return PrimitiveTypeDefinition(
+            property_name=property_name,
+            property_description=property_description,
+            type_annotation=f"Tuple[{inner_types}]",
+        )
     if property_definition.get(TYPE_KEY) in TYPE_MAPPING:
         type_name = TYPE_MAPPING[property_definition[TYPE_KEY]]
         return PrimitiveTypeDefinition(