Add support for inference providers in gr.load() (#10496)

* changes

* add changeset

* format

* changes

---------

Co-authored-by: gradio-pr-bot <[email protected]>

.changeset/lucky-cars-follow.md

@@ -0,0 +1,5 @@
+---
+"gradio": minor
+---
+
+feat:Add support for inference `providers` in `gr.load()`

gradio/external.py

@@ -31,6 +31,8 @@
 from gradio.processing_utils import save_base64_to_cache, to_binary
 
 if TYPE_CHECKING:
+    from huggingface_hub.inference._providers import PROVIDER_T
+
     from gradio.blocks import Blocks
     from gradio.chat_interface import ChatInterface
     from gradio.components.chatbot import MessageDict
@@ -46,6 +48,7 @@ def load(
     token: str | None = None,
     hf_token: str | None = None,
     accept_token: bool = False,
+    provider: PROVIDER_T | None = None,
     **kwargs,
 ) -> Blocks:
     """
@@ -56,6 +59,7 @@ def load(
         token: optional token that is passed as the second parameter to the `src` function. If not explicitly provided, will use the HF_TOKEN environment variable or fallback to the locally-saved HF token when loading models but not Spaces (when loading Spaces, only provide a token if you are loading a trusted private Space as the token can be read by the Space you are loading). Find your HF tokens here: https://huggingface.co/settings/tokens.
         accept_token: if True, a Textbox component is first rendered to allow the user to provide a token, which will be used instead of the `token` parameter when calling the loaded model or Space.
         kwargs: additional keyword parameters to pass into the `src` function. If `src` is "models" or "Spaces", these parameters are passed into the `gr.Interface` or `gr.ChatInterface` constructor.
+        provider: the name of the third-party (non-Hugging Face) providers to use for model inference (e.g. "replicate", "sambanova", "fal-ai", etc). Should be one of the providers supported by `huggingface_hub.InferenceClient`. This parameter is only used when `src` is "models"
     Returns:
         a Gradio Blocks app for the given model
     Example:
@@ -93,7 +97,7 @@ def load(
         if isinstance(src, Callable):
             return src(name, token, **kwargs)
         return load_blocks_from_huggingface(
-            name=name, src=src, hf_token=token, **kwargs
+            name=name, src=src, hf_token=token, provider=provider, **kwargs
         )
     else:
         import gradio as gr
@@ -150,6 +154,7 @@ def load_blocks_from_huggingface(
     src: str,
     hf_token: str | Literal[False] | None = None,
     alias: str | None = None,
+    provider: PROVIDER_T | None = None,
     **kwargs,
 ) -> Blocks:
     """Creates and returns a Blocks instance from a Hugging Face model or Space repo."""
@@ -168,18 +173,24 @@ def load_blocks_from_huggingface(
 
     if src == "spaces" and hf_token is None:
         hf_token = False  # Since Spaces can read the token, we don't want to pass it in unless the user explicitly provides it
-    blocks: gradio.Blocks = factory_methods[src](name, hf_token, alias, **kwargs)
+    blocks: gradio.Blocks = factory_methods[src](
+        name, hf_token=hf_token, alias=alias, provider=provider, **kwargs
+    )
     return blocks
 
 
 def from_model(
-    model_name: str, hf_token: str | Literal[False] | None, alias: str | None, **kwargs
+    model_name: str,
+    hf_token: str | Literal[False] | None,
+    alias: str | None,
+    provider: PROVIDER_T | None = None,
+    **kwargs,
 ) -> Blocks:
     headers = {"X-Wait-For-Model": "true"}
     if hf_token is False:
         hf_token = None
     client = huggingface_hub.InferenceClient(
-        model=model_name, headers=headers, token=hf_token
+        model=model_name, headers=headers, token=hf_token, provider=provider
     )
     p, tags = external_utils.get_model_info(model_name, hf_token)
 
@@ -458,8 +469,17 @@ def query_huggingface_inference_endpoints(*data):
 
 
 def from_spaces(
-    space_name: str, hf_token: str | None | Literal[False], alias: str | None, **kwargs
+    space_name: str,
+    hf_token: str | None | Literal[False],
+    alias: str | None,
+    provider: PROVIDER_T | None = None,
+    **kwargs,
 ) -> Blocks:
+    if provider is not None:
+        warnings.warn(
+            "The `provider` parameter is not supported when loading Spaces. It will be ignored."
+        )
+
     space_url = f"https://huggingface.co/spaces/{space_name}"
 
     print(f"Fetching Space from: {space_url}")

requirements.txt

@@ -5,7 +5,7 @@ fastapi>=0.115.2,<1.0
 ffmpy
 gradio_client==1.7.0
 httpx>=0.24.1
-huggingface_hub>=0.25.1
+huggingface_hub>=0.28.1
 Jinja2<4.0
 markupsafe~=2.0
 numpy>=1.0,<3.0