Allow accepting user-provided-tokens in gr.load (#9807)

* load

* add changeset

* lint

* external

* lint

* changes

* format

* changes

* renamed

* external

---------

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

.changeset/shaggy-mirrors-nail.md

@@ -0,0 +1,5 @@
+---
+"gradio": minor
+---
+
+feat:Allow accepting user-provided-tokens in `gr.load`

gradio/external.py

@@ -41,6 +41,7 @@ def load(
     | None = None,
     token: str | None = None,
     hf_token: str | None = None,
+    accept_token: bool = False,
     **kwargs,
 ) -> Blocks:
     """
@@ -49,6 +50,7 @@ def load(
         name: the name of the model (e.g. "google/vit-base-patch16-224") or Space (e.g. "flax-community/spanish-gpt2"). This is the first parameter passed into the `src` function. Can also be formatted as {src}/{repo name} (e.g. "models/google/vit-base-patch16-224") if `src` is not provided.
         src: function that accepts a string model `name` and a string or None `token` and returns a Gradio app. Alternatively, this parameter takes one of two strings for convenience: "models" (for loading a Hugging Face model through the Inference API) or "spaces" (for loading a Hugging Face Space). If None, uses the prefix of the `name` parameter to determine `src`.
         token: optional token that is passed as the second parameter to the `src` function. For Hugging Face repos, uses the local 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 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.
     Returns:
         a Gradio Blocks app for the given model
@@ -64,23 +66,44 @@ def load(
         )
     if src is None:
         # Separate the repo type (e.g. "model") from repo name (e.g. "google/vit-base-patch16-224")
-        tokens = name.split("/")
-        if len(tokens) <= 1:
+        parts = name.split("/")
+        if len(parts) <= 1:
             raise ValueError(
                 "Either `src` parameter must be provided, or `name` must be formatted as {src}/{repo name}"
             )
-        src = tokens[0]  # type: ignore
-        name = "/".join(tokens[1:])
-    if src in ["huggingface", "models", "spaces"]:
+        src = parts[0]  # type: ignore
+        name = "/".join(parts[1:])
+    assert src is not None  # noqa: S101
+    if not isinstance(src, Callable) and src not in ["models", "spaces", "huggingface"]:
+        raise ValueError(
+            "The `src` parameter must be one of 'huggingface', 'models', 'spaces', or a function that accepts a model name (and optionally, a token), and returns a Gradio app."
+        )
+
+    if not accept_token:
+        if isinstance(src, Callable):
+            return src(name, token, **kwargs)
         return load_blocks_from_huggingface(
             name=name, src=src, hf_token=token, **kwargs
         )
-    elif isinstance(src, Callable):
-        return src(name, token, **kwargs)
     else:
-        raise ValueError(
-            "The `src` parameter must be one of 'huggingface', 'models', 'spaces', or a function that accepts a model name (and optionally, a token), and returns a Gradio app."
-        )
+        import gradio as gr
+
+        with gr.Blocks(fill_height=True) as demo:
+            textbox = gr.Textbox(
+                type="password",
+                label="Token",
+                info="Enter your token and press enter.",
+            )
+
+            @gr.render(inputs=[textbox], triggers=[textbox.submit])
+            def create(token_value):
+                if isinstance(src, Callable):
+                    return src(name, token_value, **kwargs)
+                return load_blocks_from_huggingface(
+                    name=name, src=src, hf_token=token_value, **kwargs
+                )
+
+        return demo
 
 
 def load_blocks_from_huggingface(