Upload externalmod.py

externalmod.py

@@ -9,7 +9,7 @@ import re
 import tempfile
 import warnings
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable
+from typing import TYPE_CHECKING, Callable, Literal
 
 import httpx
 import huggingface_hub
@@ -41,7 +41,7 @@ server_timeout = 600
 def load(
     name: str,
     src: str | None = None,
-    hf_token: str | None = None,
+    hf_token: str | Literal[False] | None = None,
     alias: str | None = None,
     **kwargs,
 ) -> Blocks:
@@ -52,7 +52,7 @@ def load(
     Parameters:
         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`)
-        hf_token: optional access token for loading private Hugging Face Hub models or spaces. Find your token here: https://huggingface.co/settings/tokens.  Warning: only provide this if you are loading a trusted private Space as it can be read by the Space you are loading.
+        hf_token: optional access token for loading private Hugging Face Hub models or spaces. Will default to the locally saved token if not provided. Pass `token=False` if you don't want to send your token to the server. Find your token here: https://huggingface.co/settings/tokens.  Warning: only provide a token if you are loading a trusted private Space as it can be read by the Space you are loading.
         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 Blocks object for the given model
@@ -69,7 +69,7 @@ def load(
 def load_blocks_from_repo(
     name: str,
     src: str | None = None,
-    hf_token: str | None = None,
+    hf_token: str | Literal[False] | None = None,
     alias: str | None = None,
     **kwargs,
 ) -> Blocks:
@@ -93,7 +93,7 @@ def load_blocks_from_repo(
     if src.lower() not in factory_methods:
         raise ValueError(f"parameter: src must be one of {factory_methods.keys()}")
 
-    if hf_token is not None:
+    if hf_token is not None and hf_token is not False:
         if Context.hf_token is not None and Context.hf_token != hf_token:
             warnings.warn(
                 """You are loading a model/Space with a different access token than the one you used to load a previous model/Space. This is not recommended, as it may cause unexpected behavior."""
@@ -104,12 +104,16 @@ def load_blocks_from_repo(
     return blocks
 
 
-def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwargs):
+def from_model(
+    model_name: str, hf_token: str | Literal[False] | None, alias: str | None, **kwargs
+):
     model_url = f"https://huggingface.co/{model_name}"
     api_url = f"https://api-inference.huggingface.co/models/{model_name}"
     print(f"Fetching model from: {model_url}")
 
-    headers = {"Authorization": f"Bearer {hf_token}"} if hf_token is not None else {}
+    headers = (
+        {} if hf_token in [False, None] else {"Authorization": f"Bearer {hf_token}"}
+    )
     response = httpx.request("GET", api_url, headers=headers)
     if response.status_code != 200:
         raise ModelNotFoundError(
@@ -372,7 +376,11 @@ def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwarg
     def query_huggingface_inference_endpoints(*data, **kwargs):
         if preprocess is not None:
             data = preprocess(*data)
-        data = fn(*data, **kwargs)  # type: ignore
+        try:
+            data = fn(*data, **kwargs)  # type: ignore
+        except huggingface_hub.utils.HfHubHTTPError as e:
+            if "429" in str(e):
+                raise TooManyRequestsError() from e
         if postprocess is not None:
             data = postprocess(data)  # type: ignore
         return data
@@ -384,7 +392,7 @@ def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwarg
         "inputs": inputs,
         "outputs": outputs,
         "title": model_name,
-    #    "examples": examples,
+        #"examples": examples,
     }
 
     kwargs = dict(interface_info, **kwargs)
@@ -395,19 +403,12 @@ def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwarg
 def from_spaces(
     space_name: str, hf_token: str | None, alias: str | None, **kwargs
 ) -> Blocks:
-    client = Client(
-        space_name,
-        hf_token=hf_token,
-        download_files=False,
-        _skip_components=False,
-    )
-
     space_url = f"https://huggingface.co/spaces/{space_name}"
 
     print(f"Fetching Space from: {space_url}")
 
     headers = {}
-    if hf_token is not None:
+    if hf_token not in [False, None]:
         headers["Authorization"] = f"Bearer {hf_token}"
 
     iframe_url = (
@@ -444,8 +445,7 @@ def from_spaces(
                 "Blocks or Interface locally. You may find this Guide helpful: "
                 "https://gradio.app/using_blocks_like_functions/"
             )
-        if client.app_version < version.Version("4.0.0b14"):
-            return from_spaces_blocks(space=space_name, hf_token=hf_token)
+        return from_spaces_blocks(space=space_name, hf_token=hf_token)
 
 
 def from_spaces_blocks(space: str, hf_token: str | None) -> Blocks:
@@ -490,7 +490,7 @@ def from_spaces_interface(
     config = external_utils.streamline_spaces_interface(config)
     api_url = f"{iframe_url}/api/predict/"
     headers = {"Content-Type": "application/json"}
-    if hf_token is not None:
+    if hf_token not in [False, None]:
         headers["Authorization"] = f"Bearer {hf_token}"
 
     # The function should call the API with preprocessed data
@@ -530,7 +530,7 @@ def gr_Interface_load(
     src: str | None = None,
     hf_token: str | None = None,
     alias: str | None = None,
-    **kwargs,
+    **kwargs, # ignore
 ) -> Blocks:
     try:
         return load_blocks_from_repo(name, src, hf_token, alias)