Distinguish _bytes_to_dict and _bytes_to_list + fix issues

src/huggingface_hub/inference/_client.py

@@ -62,6 +62,7 @@
     _b64_to_image,
     _bytes_to_dict,
     _bytes_to_image,
+    _bytes_to_list,
     _get_recommended_model,
     _import_numpy,
     _is_tgi_server,
@@ -284,7 +285,7 @@ def audio_classification(
         ```
         """
         response = self.post(data=audio, model=model, task="audio-classification")
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     def automatic_speech_recognition(
         self,
@@ -381,7 +382,7 @@ def conversational(
         if parameters is not None:
             payload["parameters"] = parameters
         response = self.post(json=payload, model=model, task="conversational")
-        return _bytes_to_dict(response)
+        return _bytes_to_dict(response)  # type: ignore
 
     def feature_extraction(self, text: str, *, model: Optional[str] = None) -> "np.ndarray":
         """
@@ -453,7 +454,7 @@ def image_classification(
         ```
         """
         response = self.post(data=image, model=model, task="image-classification")
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     def image_segmentation(
         self,
@@ -719,7 +720,7 @@ def sentence_similarity(
             model=model,
             task="sentence-similarity",
         )
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     def summarization(
         self,
@@ -1285,7 +1286,7 @@ def zero_shot_image_classification(
             model=model,
             task="zero-shot-image-classification",
         )
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     def _resolve_url(self, model: Optional[str] = None, task: Optional[str] = None) -> str:
         model = model or self.model

src/huggingface_hub/inference/_common.py

@@ -226,10 +226,24 @@ def _b64_to_image(encoded_image: str) -> "Image":
     return Image.open(io.BytesIO(base64.b64decode(encoded_image)))
 
 
-def _bytes_to_dict(content: bytes) -> "Image":
+def _bytes_to_list(content: bytes) -> List:
+    """Parse bytes from a Response object into a Python list.
+
+    Expects the response body to be JSON-encoded data.
+
+    NOTE: This is exactly the same implementation as `_bytes_to_dict` and will not complain if the returned data is a
+    dictionary. The only advantage of having both is to help the user (and mypy) understand what kind of data to expect.
+    """
+    return json.loads(content.decode())
+
+
+def _bytes_to_dict(content: bytes) -> Dict:
     """Parse bytes from a Response object into a Python dictionary.
 
-    Expects the response body to be encoded-JSON data.
+    Expects the response body to be JSON-encoded data.
+
+    NOTE: This is exactly the same implementation as `_bytes_to_list` and will not complain if the returned data is a
+    list. The only advantage of having both is to help the user (and mypy) understand what kind of data to expect.
     """
     return json.loads(content.decode())
 

src/huggingface_hub/inference/_generated/_async_client.py

@@ -47,6 +47,7 @@
     _b64_to_image,
     _bytes_to_dict,
     _bytes_to_image,
+    _bytes_to_list,
     _get_recommended_model,
     _import_numpy,
     _is_tgi_server,
@@ -281,7 +282,7 @@ async def audio_classification(
         ```
         """
         response = await self.post(data=audio, model=model, task="audio-classification")
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     async def automatic_speech_recognition(
         self,
@@ -380,7 +381,7 @@ async def conversational(
         if parameters is not None:
             payload["parameters"] = parameters
         response = await self.post(json=payload, model=model, task="conversational")
-        return _bytes_to_dict(response)
+        return _bytes_to_dict(response)  # type: ignore
 
     async def feature_extraction(self, text: str, *, model: Optional[str] = None) -> "np.ndarray":
         """
@@ -454,7 +455,7 @@ async def image_classification(
         ```
         """
         response = await self.post(data=image, model=model, task="image-classification")
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     async def image_segmentation(
         self,
@@ -725,7 +726,7 @@ async def sentence_similarity(
             model=model,
             task="sentence-similarity",
         )
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     async def summarization(
         self,
@@ -1297,7 +1298,7 @@ async def zero_shot_image_classification(
             model=model,
             task="zero-shot-image-classification",
         )
-        return _bytes_to_dict(response)
+        return _bytes_to_list(response)
 
     def _resolve_url(self, model: Optional[str] = None, task: Optional[str] = None) -> str:
         model = model or self.model