Add support for loading Private Spaces using HF Token

CHANGELOG.md

@@ -88,7 +88,8 @@ No changes to highlight.
 No changes to highlight.
 
 ## Full Changelog:
-No changes to highlight.
+* Allows loading private Spaces by passing an an `api_key` to `gr.Interface.load()`
+by [@abidlabs](https://github.com/abidlabs) in [PR 2568](https://github.com/gradio-app/gradio/pull/2568)
 
 ## Contributors Shoutout:
 No changes to highlight.

gradio/blocks.py

@@ -1054,10 +1054,10 @@ def load(
 
         Instance method: adds event that runs as soon as the demo loads in the browser. Example usage below.
         Parameters:
-            name: Class Method - the name of the model (e.g. "gpt2"), can include the `src` as prefix (e.g. "models/gpt2")
-            src: Class Method - the source of the model: `models` or `spaces` (or empty if source is provided as a prefix in `name`)
-            api_key: Class Method - optional api key for use with Hugging Face Hub
-            alias: Class Method - optional string used as the name of the loaded model instead of the default name
+            name: Class Method - the name of the model (e.g. "gpt2" or "facebook/bart-base") or space (e.g. "flax-community/spanish-gpt2"), can include the `src` as prefix (e.g. "models/facebook/bart-base")
+            src: Class Method - the source of the model: `models` or `spaces` (or leave empty if source is provided as a prefix in `name`)
+            api_key: Class Method - optional access token for loading private Hugging Face Hub models or spaces. Find your token here: https://huggingface.co/settings/tokens
+            alias: Class Method - optional string used as the name of the loaded model instead of the default name (only applies if loading a Space running Gradio 2.x)
             fn: Instance Method - Callable function
             inputs: Instance Method - input list
             outputs: Instance Method - output list

gradio/exceptions.py

@@ -1,4 +1,12 @@
 class DuplicateBlockError(ValueError):
+    """Raised when a Blocks contains more than one Block with the same id"""
+
+    pass
+
+
+class TooManyRequestsError(Exception):
+    """Raised when the Hugging Face API returns a 429 status code."""
+
     pass
 
 

gradio/external.py

@@ -21,19 +21,18 @@
 
 import gradio
 from gradio import components, exceptions, utils
+from gradio.exceptions import TooManyRequestsError
 from gradio.processing_utils import to_binary
 
 if TYPE_CHECKING:
+    from gradio.blocks import Blocks
     from gradio.components import DataframeData
+    from gradio.interface import Interface
 
 
-class TooManyRequestsError(Exception):
-    """Raised when the Hugging Face API returns a 429 status code."""
-
-    pass
-
-
-def load_blocks_from_repo(name, src=None, api_key=None, alias=None, **kwargs):
+def load_blocks_from_repo(
+    name: str, src: str = None, api_key: str = None, alias: str = None, **kwargs
+) -> Blocks:
     """Creates and returns a Blocks instance from several kinds of Hugging Face repos:
     1) A model repo
     2) A Spaces repo running Gradio 2.x
@@ -55,7 +54,7 @@ def load_blocks_from_repo(name, src=None, api_key=None, alias=None, **kwargs):
     return blocks
 
 
-def get_tabular_examples(model_name) -> Dict[str, List[float]]:
+def get_tabular_examples(model_name: str) -> Dict[str, List[float]]:
     readme = requests.get(f"https://huggingface.co/{model_name}/resolve/main/README.md")
     if readme.status_code != 200:
         warnings.warn(f"Cannot load examples from README for {model_name}", UserWarning)
@@ -107,7 +106,7 @@ def rows_to_cols(
     return {"inputs": {"data": data_column_wise}}
 
 
-def get_models_interface(model_name, api_key, alias, **kwargs):
+def get_models_interface(model_name: str, api_key: str | None, alias: str, **kwargs):
     model_url = "https://huggingface.co/{}".format(model_name)
     api_url = "https://api-inference.huggingface.co/models/{}".format(model_name)
     print("Fetching model from: {}".format(model_url))
@@ -394,23 +393,37 @@ def query_huggingface_api(*params):
     return interface
 
 
-def get_spaces(model_name, api_key, alias, **kwargs):
-    space_url = "https://huggingface.co/spaces/{}".format(model_name)
-    print("Fetching interface from: {}".format(space_url))
-    iframe_url = "https://hf.space/embed/{}/+".format(model_name)
+def get_spaces(space_name: str, api_key: str | None, alias: str, **kwargs) -> Blocks:
+    space_url = "https://huggingface.co/spaces/{}".format(space_name)
+    print("Fetching Space from: {}".format(space_url))
+
+    headers = {}
+    if api_key is not None:
+        headers["Authorization"] = f"Bearer {api_key}"
+
+    iframe_url = (
+        requests.get(
+            f"https://huggingface.co/api/spaces/{space_name}/host", headers=headers
+        )
+        .json()
+        .get("host")
+    )
+
+    r = requests.get(iframe_url, headers=headers)
 
-    r = requests.get(iframe_url)
     result = re.search(
         r"window.gradio_config = (.*?);[\s]*</script>", r.text
     )  # some basic regex to extract the config
     try:
         config = json.loads(result.group(1))
     except AttributeError:
-        raise ValueError("Could not load the Space: {}".format(model_name))
+        raise ValueError("Could not load the Space: {}".format(space_name))
     if "allow_flagging" in config:  # Create an Interface for Gradio 2.x Spaces
-        return get_spaces_interface(model_name, config, alias, **kwargs)
+        return get_spaces_interface(
+            space_name, config, alias, api_key, iframe_url, **kwargs
+        )
     else:  # Create a Blocks for Gradio 3.x Spaces
-        return get_spaces_blocks(model_name, config)
+        return get_spaces_blocks(space_name, config, api_key, iframe_url)
 
 
 async def get_pred_from_ws(
@@ -447,7 +460,9 @@ def use_websocket(config, dependency):
     return queue_enabled and queue_uses_websocket and dependency_uses_queue
 
 
-def get_spaces_blocks(model_name, config):
+def get_spaces_blocks(
+    model_name: str, config: Dict, api_key: str | None, iframe_url: str
+) -> Blocks:
     def streamline_config(config: dict) -> dict:
         """Streamlines the blocks config dictionary to fix components that don't render correctly."""
         # TODO(abidlabs): Need a better way to fix relative paths in dataset component
@@ -457,8 +472,10 @@ def streamline_config(config: dict) -> dict:
         return config
 
     config = streamline_config(config)
-    api_url = "https://hf.space/embed/{}/api/predict/".format(model_name)
+    api_url = "{}/api/predict/".format(iframe_url)
     headers = {"Content-Type": "application/json"}
+    if api_key is not None:
+        headers["Authorization"] = f"Bearer {api_key}"
     ws_url = "wss://spaces.huggingface.tech/{}/queue/join".format(model_name)
 
     ws_fn = get_ws_fn(ws_url)
@@ -504,8 +521,15 @@ def fn(*data):
     return gradio.Blocks.from_config(config, fns)
 
 
-def get_spaces_interface(model_name, config, alias, **kwargs):
-    def streamline_config(config: dict) -> dict:
+def get_spaces_interface(
+    model_name: str,
+    config: Dict,
+    alias: str,
+    api_key: str | None,
+    iframe_url: str,
+    **kwargs,
+) -> Interface:
+    def streamline_config(config: Dict) -> Dict:
         """Streamlines the interface config dictionary to remove unnecessary keys."""
         config["inputs"] = [
             components.get_component_instance(component)
@@ -528,8 +552,10 @@ def streamline_config(config: dict) -> dict:
         return config
 
     config = streamline_config(config)
-    api_url = "https://hf.space/embed/{}/api/predict/".format(model_name)
+    api_url = "{}/api/predict/".format(iframe_url)
     headers = {"Content-Type": "application/json"}
+    if api_key is not None:
+        headers["Authorization"] = f"Bearer {api_key}"
 
     # The function should call the API with preprocessed data
     def fn(*data):
@@ -571,7 +597,7 @@ def fn(*data):
 }
 
 
-def load_from_pipeline(pipeline):
+def load_from_pipeline(pipeline) -> Dict:
     """
     Gets the appropriate Interface kwargs for a given Hugging Face transformers.Pipeline.
     pipeline (transformers.Pipeline): the transformers.Pipeline from which to create an interface

gradio/interface.py

@@ -92,10 +92,10 @@ def load(
         model repos (if src is "models") or Space repos (if src is "spaces"). The input
         and output components are automatically loaded from the repo.
         Parameters:
-            name: the name of the model (e.g. "gpt2"), can include the `src` as prefix (e.g. "models/gpt2")
-            src: the source of the model: `models` or `spaces` (or empty if source is provided as a prefix in `name`)
-            api_key: optional api key for use with Hugging Face Hub
-            alias: optional string used as the name of the loaded model instead of the default name
+            name: the name of the model (e.g. "gpt2" or "facebook/bart-base") or space (e.g. "flax-community/spanish-gpt2"), can include the `src` as prefix (e.g. "models/facebook/bart-base")
+            src: the source of the model: `models` or `spaces` (or leave empty if source is provided as a prefix in `name`)
+            api_key: optional access token for loading private Hugging Face Hub models or spaces. Find your token here: https://huggingface.co/settings/tokens
+            alias: optional string used as the name of the loaded model instead of the default name (only applies if loading a Space running Gradio 2.x)
         Returns:
             a Gradio Interface object for the given model
         Example:

test/test_external.py

@@ -234,6 +234,17 @@ def test_text_to_image_model(self):
         except TooManyRequestsError:
             pass
 
+    def test_private_space(self):
+        api_key = "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"  # Intentionally revealing this key for testing purposes
+        io = gr.Interface.load(
+            "spaces/gradio-tests/not-actually-private-space", api_key=api_key
+        )
+        try:
+            output = io("abc")
+            self.assertEqual(output, "abc")
+        except TooManyRequestsError:
+            pass
+
 
 class TestLoadFromPipeline(unittest.TestCase):
     def test_text_to_text_model_from_pipeline(self):

website/homepage/restart_demos.py

@@ -1,9 +1,11 @@
+import requests
 from upload_demos import demos, upload_demo_to_space, AUTH_TOKEN, gradio_version
 from gradio.networking import url_ok
 
 
 for demo in demos:
     space_id = "gradio/" + demo
-    if not url_ok(f"https://hf.space/embed/{space_id}/+"):
+    space_url = requests.get(f"https://huggingface.co/api/spaces/{space_id}/host").json().get("host")
+    if not url_ok(space_url):
         print(f"{space_id} was down, restarting")
         upload_demo_to_space(demo_name=demo, space_id=space_id, hf_token=AUTH_TOKEN, gradio_version=gradio_version)