python3Packages.gradio: 6.5.1 -> 6.8.0

  nodejs = nodejs_24;

  pnpm = pnpm_10.override { inherit nodejs; };

in

buildPythonPackage rec {

buildPythonPackage (finalAttrs: {

  pname = "gradio";

  version = "6.5.1";

  version = "6.8.0";

  pyproject = true;

  src = fetchFromGitHub {

    owner = "gradio-app";

    repo = "gradio";

    tag = "gradio@${version}";

    hash = "sha256-pIcliKcb1eVVMk0ARzWcZGXc6pmI8mGVAvCJZ0JHXUw=";

    tag = "gradio@${finalAttrs.version}";

    hash = "sha256-ZHglnRs0AXCu9HlVoSO0h5p6SE4al/OLPn0jwZgKVR8=";

  };

  patches = [

    ./fix-transformers-pipelines-imports.patch

  ];

  pnpmDeps = fetchPnpmDeps {

    inherit

    inherit (finalAttrs)

      pname

      pnpm

      version

      src

      ;

    inherit pnpm;

    fetcherVersion = 3;

    hash = "sha256-6Cx0hdVd0srhArvck2Kn9U2fT7aKtTZjgV5b/Usrnoo=";

  };

  pythonRelaxDeps = [

    "aiofiles"

    "gradio-client"

    "markupsafe"

    "pydantic" # Requests >=2.11.10,<=2.12.4. Staging has it, master doesn't.

  ];

  pythonRemoveDeps = [

    # this isn't a real runtime dependency

    "ruff"

  ];

  nativeBuildInputs = [

    zip

    nodejs

    hatch-fancy-pypi-readme

  ];

  pythonRelaxDeps = [

    "aiofiles"

    "tomlkit"

  ];

  dependencies = [

    aiofiles

    anyio

    # mock calls to `shutil.which(...)`

    (writeShellScriptBin "npm" "false")

  ]

  ++ optional-dependencies.oauth

  ++ finalAttrs.passthru.optional-dependencies.oauth

  ++ pydantic.optional-dependencies.email;

  preBuild = ''

    # requires network, it caught our xfail exception

    "test_error_analytics_successful"

    "TestSnippetExecution"

    # Flaky, tries to pin dependency behaviour. Sensitive to dep versions

    # These error only affect downstream use of the check dependencies.

  meta = {

    homepage = "https://www.gradio.app/";

    changelog = "https://github.com/gradio-app/gradio/releases/tag/gradio@${version}";

    changelog = "https://github.com/gradio-app/gradio/releases/tag/${finalAttrs.src.tag}";

    description = "Python library for easily interacting with trained machine learning models";

    license = lib.licenses.asl20;

    maintainers = with lib.maintainers; [ pbsds ];

  };

}

})

diff --git a/test/test_pipelines.py b/test/test_pipelines.py

index 1903f758f..c40e6d3b1 100644

--- a/test/test_pipelines.py

+++ b/test/test_pipelines.py

@@ -3,20 +3,6 @@ from unittest.mock import MagicMock

 import pytest

 import transformers

-from transformers import (

-    AudioClassificationPipeline,

-    AutomaticSpeechRecognitionPipeline,

-    DocumentQuestionAnsweringPipeline,

-    FeatureExtractionPipeline,

-    FillMaskPipeline,

-    ImageClassificationPipeline,

-    ObjectDetectionPipeline,

-    QuestionAnsweringPipeline,

-    TextClassificationPipeline,

-    TextGenerationPipeline,

-    VisualQuestionAnsweringPipeline,

-    ZeroShotClassificationPipeline,

-)

 import gradio as gr

 from gradio.pipelines_utils import (

@@ -24,6 +10,14 @@ from gradio.pipelines_utils import (

 )

+def _get_pipeline_cls(name: str):

+    """Resolve a pipeline class by name from transformers, returning None if it

+    was removed in the installed version."""

+    return getattr(transformers, name, None) or getattr(

+        transformers.pipelines, name, None

+    )

+

+

 @pytest.mark.flaky

 def test_interface_in_blocks():

     pipe1 = transformers.pipeline(model="deepset/roberta-base-squad2")  # type: ignore

@@ -50,50 +44,66 @@ def test_transformers_load_from_pipeline():

 class TestHandleTransformersPipelines(unittest.TestCase):

+    def _require(self, name: str):

+        """Return the pipeline class or skip the test if it was removed."""

+        cls = _get_pipeline_cls(name)

+        if cls is None:

+            self.skipTest(

+                f"{name} not available in transformers {transformers.__version__}"

+            )

+        return cls

+

     def test_audio_classification_pipeline(self):

-        pipe = MagicMock(spec=AudioClassificationPipeline)

+        cls = self._require("AudioClassificationPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Class"

     def test_automatic_speech_recognition_pipeline(self):

-        pipe = MagicMock(spec=AutomaticSpeechRecognitionPipeline)

+        cls = self._require("AutomaticSpeechRecognitionPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Output"

     def test_object_detection_pipeline(self):

-        pipe = MagicMock(spec=ObjectDetectionPipeline)

+        cls = self._require("ObjectDetectionPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input Image"

         assert pipeline_info["outputs"].label == "Objects Detected"

     def test_feature_extraction_pipeline(self):

-        pipe = MagicMock(spec=FeatureExtractionPipeline)

+        cls = self._require("FeatureExtractionPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Output"

     def test_fill_mask_pipeline(self):

-        pipe = MagicMock(spec=FillMaskPipeline)

+        cls = self._require("FillMaskPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Classification"

     def test_image_classification_pipeline(self):

-        pipe = MagicMock(spec=ImageClassificationPipeline)

+        cls = self._require("ImageClassificationPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input Image"

         assert pipeline_info["outputs"].label == "Classification"

     def test_question_answering_pipeline(self):

-        pipe = MagicMock(spec=QuestionAnsweringPipeline)

+        cls = self._require("QuestionAnsweringPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"][0].label == "Context"

@@ -102,21 +112,24 @@ class TestHandleTransformersPipelines(unittest.TestCase):

         assert pipeline_info["outputs"][1].label == "Score"

     def test_text_classification_pipeline(self):

-        pipe = MagicMock(spec=TextClassificationPipeline)

+        cls = self._require("TextClassificationPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Classification"

     def test_text_generation_pipeline(self):

-        pipe = MagicMock(spec=TextGenerationPipeline)

+        cls = self._require("TextGenerationPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"].label == "Input"

         assert pipeline_info["outputs"].label == "Output"

     def test_zero_shot_classification_pipeline(self):

-        pipe = MagicMock(spec=ZeroShotClassificationPipeline)

+        cls = self._require("ZeroShotClassificationPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"][0].label == "Input"

@@ -127,7 +140,8 @@ class TestHandleTransformersPipelines(unittest.TestCase):

         assert pipeline_info["outputs"].label == "Classification"

     def test_document_question_answering_pipeline(self):

-        pipe = MagicMock(spec=DocumentQuestionAnsweringPipeline)

+        cls = self._require("DocumentQuestionAnsweringPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"][0].label == "Input Document"

@@ -135,7 +149,8 @@ class TestHandleTransformersPipelines(unittest.TestCase):

         assert pipeline_info["outputs"].label == "Label"

     def test_visual_question_answering_pipeline(self):

-        pipe = MagicMock(spec=VisualQuestionAnsweringPipeline)

+        cls = self._require("VisualQuestionAnsweringPipeline")

+        pipe = MagicMock(spec=cls)

         pipeline_info = handle_transformers_pipeline(pipe)

         assert pipeline_info is not None

         assert pipeline_info["inputs"][0].label == "Input Image"