Fix Image import handling and update MlxLLM initialisation (#1102)

Co-authored-by: Gabriel Martín Blázquez <gmartinbdev@gmail.com>

Author: davidberenstein1957

Diff for: pyproject.toml

@@ -38,6 +38,7 @@ dependencies = [
     "orjson >= 3.10.0",
     "universal_pathlib >= 0.2.2",
     "portalocker >= 2.8.2",
+    "setuptools",
 ]
 dynamic = ["version"]
 
@@ -90,9 +91,7 @@ ray = ["ray[default] >= 2.31.0"]
 vertexai = ["google-cloud-aiplatform >= 1.38.0"]
 vllm = [
     "vllm >= 0.5.3",
-    "filelock >= 3.13.4",
-    # `setuptools` is needed to be installed if installed with `uv pip install distilabel[vllm]`
-    "setuptools",
+    "filelock >= 3.13.4"
 ]
 sentence-transformers = ["sentence-transformers >= 3.0.0"]
 faiss-cpu = ["faiss-cpu >= 1.8.0"]

Diff for: src/distilabel/models/image_generation/huggingface/inference_endpoints.py

@@ -20,7 +20,6 @@
     InferenceEndpointsBaseClient,
 )
 from distilabel.models.image_generation.base import AsyncImageGenerationModel
-from distilabel.models.image_generation.utils import image_to_str
 
 if TYPE_CHECKING:
     from PIL.Image import Image
@@ -60,10 +59,14 @@ class InferenceEndpointsImageGeneration(  # type: ignore
     """
 
     def load(self) -> None:
+        from distilabel.models.image_generation.utils import image_to_str
+
         # Sets the logger and calls the load method of the BaseClient
         AsyncImageGenerationModel.load(self)
         InferenceEndpointsBaseClient.load(self)
 
+        self._image_to_str = image_to_str
+
     @validate_call
     async def agenerate(  # type: ignore
         self,
@@ -101,6 +104,6 @@ async def agenerate(  # type: ignore
             num_inference_steps=num_inference_steps,
             guidance_scale=guidance_scale,
         )
-        img_str = image_to_str(image, image_format="JPEG")
+        img_str = self._image_to_str(image, image_format="JPEG")
 
         return [{"images": [img_str]}]

Diff for: src/distilabel/models/image_generation/utils.py

@@ -18,14 +18,14 @@
 from PIL import Image
 
 
-def image_to_str(image: Image.Image, image_format: str = "JPEG") -> str:
+def image_to_str(image: "Image.Image", image_format: str = "JPEG") -> str:
     """Converts a PIL Image to a base64 encoded string."""
     buffered = io.BytesIO()
     image.save(buffered, format=image_format)
     return base64.b64encode(buffered.getvalue()).decode("utf-8")
 
 
-def image_from_str(image_str: str) -> Image.Image:
+def image_from_str(image_str: str) -> "Image.Image":
     """Converts a base64 encoded string to a PIL Image."""
     image_bytes = base64.b64decode(image_str)
     return Image.open(io.BytesIO(image_bytes))

Diff for: src/distilabel/models/llms/mlx.py

@@ -60,7 +60,7 @@ class MlxLLM(LLM, MagpieChatTemplateMixin):
         ```python
         from distilabel.models.llms import MlxLLM
 
-        llm = MlxLLM(model="mlx-community/Meta-Llama-3.1-8B-Instruct-4bit")
+        llm = MlxLLM(path_or_hf_repo="mlx-community/Meta-Llama-3.1-8B-Instruct-4bit")
 
         llm.load()
 

Diff for: src/distilabel/steps/tasks/image_generation.py

@@ -15,7 +15,6 @@
 import hashlib
 from typing import TYPE_CHECKING
 
-from distilabel.models.image_generation.utils import image_from_str
 from distilabel.steps.base import StepInput
 from distilabel.steps.tasks.base import ImageTask
 
@@ -117,6 +116,13 @@ class ImageGeneration(ImageTask):
     save_artifacts: bool = False
     image_format: str = "JPEG"
 
+    def load(self) -> None:
+        from distilabel.models.image_generation.utils import image_from_str
+
+        super().load()
+
+        self._image_from_str = image_from_str
+
     @property
     def inputs(self) -> "StepColumns":
         return ["prompt"]
@@ -166,7 +172,7 @@ def process(self, inputs: StepInput) -> "StepOutput":
                     # use prompt as filename
                     prompt_hash = hashlib.md5(input["prompt"].encode()).hexdigest()
                     # Build PIL image to save it
-                    image = image_from_str(image)
+                    image = self._image_from_str(image)
 
                     self.save_artifact(
                         name="images",

Diff for: src/distilabel/steps/tasks/structured_outputs/outlines.py

@@ -28,7 +28,6 @@
     get_args,
 )
 
-import pkg_resources
 from pydantic import BaseModel
 
 from distilabel.errors import DistilabelUserError
@@ -50,6 +49,8 @@ def _is_outlines_version_below_0_1_0() -> bool:
     Returns:
         bool: True if outlines is not installed or version is below 0.1.0
     """
+    import pkg_resources
+
     if not importlib.util.find_spec("outlines"):
         raise ImportError(
             "Outlines is not installed. Please install it using `pip install outlines`."

Diff for: src/distilabel/steps/tasks/text_generation_with_image.py

@@ -15,7 +15,6 @@
 from typing import TYPE_CHECKING, Any, Literal, Union
 
 from jinja2 import Template
-from PIL import Image
 from pydantic import Field
 
 from distilabel.steps.tasks.base import Task

Diff for: src/distilabel/utils/image.py

@@ -14,12 +14,13 @@
 
 import base64
 import io
+from typing import TYPE_CHECKING
 
-from PIL import Image
+if TYPE_CHECKING:
+    from PIL import Image
 
 
-# TODO: Once we merge the image generation, this function can be reused
-def image_to_str(image: Image.Image, image_format: str = "JPEG") -> str:
+def image_to_str(image: "Image.Image", image_format: str = "JPEG") -> str:
     """Converts a PIL Image to a base64 encoded string."""
     buffered = io.BytesIO()
     image.save(buffered, format=image_format)