Pipeline: simple API for assisted generation (#34504)

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

tests/pipelines/test_pipelines_automatic_speech_recognition.py

@@ -1933,6 +1933,20 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase):
             },
         )
 
+    @require_torch
+    def test_pipeline_assisted_generation(self):
+        """Tests that we can run assisted generation in the pipeline"""
+        model = "openai/whisper-tiny"
+        pipe = pipeline("automatic-speech-recognition", model=model, assistant_model=model)
+
+        # We can run the pipeline
+        prompt = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation[:1]")["audio"]
+        _ = pipe(prompt)
+
+        # It is running assisted generation under the hood (e.g. flags incompatible with assisted gen will crash)
+        with self.assertRaises(ValueError):
+            _ = pipe(prompt, generate_kwargs={"num_beams": 2})
+
 
 def require_ffmpeg(test_case):
     """

tests/pipelines/test_pipelines_text_generation.py

@@ -653,3 +653,17 @@ class TextGenerationPipelineTests(unittest.TestCase):
         with CaptureLogger(logger) as cl:
             _ = text_generator(prompt, max_length=10)
         self.assertNotIn(logger_msg, cl.out)
+
+    @require_torch
+    def test_pipeline_assisted_generation(self):
+        """Tests that we can run assisted generation in the pipeline"""
+        model = "hf-internal-testing/tiny-random-MistralForCausalLM"
+        pipe = pipeline("text-generation", model=model, assistant_model=model)
+
+        # We can run the pipeline
+        prompt = "Hello world"
+        _ = pipe(prompt)
+
+        # It is running assisted generation under the hood (e.g. flags incompatible with assisted gen will crash)
+        with self.assertRaises(ValueError):
+            _ = pipe(prompt, generate_kwargs={"num_beams": 2})