two version of R2R are hereHEADmaster

1 files changed, 41 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/nebius.py b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/nebius.py
new file mode 100644
index 00000000..d6b37356
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/nebius.py
@@ -0,0 +1,41 @@
+import base64
+from typing import Any, Dict, Optional, Union
+
+from huggingface_hub.inference._common import _as_dict
+from huggingface_hub.inference._providers._common import (
+    BaseConversationalTask,
+    BaseTextGenerationTask,
+    TaskProviderHelper,
+    filter_none,
+)
+
+
+class NebiusTextGenerationTask(BaseTextGenerationTask):
+    def __init__(self):
+        super().__init__(provider="nebius", base_url="https://api.studio.nebius.ai")
+
+
+class NebiusConversationalTask(BaseConversationalTask):
+    def __init__(self):
+        super().__init__(provider="nebius", base_url="https://api.studio.nebius.ai")
+
+
+class NebiusTextToImageTask(TaskProviderHelper):
+    def __init__(self):
+        super().__init__(task="text-to-image", provider="nebius", base_url="https://api.studio.nebius.ai")
+
+    def _prepare_route(self, mapped_model: str) -> str:
+        return "/v1/images/generations"
+
+    def _prepare_payload_as_dict(self, inputs: Any, parameters: Dict, mapped_model: str) -> Optional[Dict]:
+        parameters = filter_none(parameters)
+        if "guidance_scale" in parameters:
+            parameters.pop("guidance_scale")
+        if parameters.get("response_format") not in ("b64_json", "url"):
+            parameters["response_format"] = "b64_json"
+
+        return {"prompt": inputs, **parameters, "model": mapped_model}
+
+    def get_response(self, response: Union[bytes, Dict]) -> Any:
+        response_dict = _as_dict(response)
+        return base64.b64decode(response_dict["data"][0]["b64_json"])