From 4a52a71956a8d46fcb7294ac71734504bb09bcc2 Mon Sep 17 00:00:00 2001
From: S. Solomon Darnell
Date: Fri, 28 Mar 2025 21:52:21 -0500
Subject: two version of R2R are here

---
 .../inference/_providers/hyperbolic.py             | 43 ++++++++++++++++++++++
 1 file changed, 43 insertions(+)
 create mode 100644 .venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/hyperbolic.py

(limited to '.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/hyperbolic.py')

diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/hyperbolic.py b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/hyperbolic.py
new file mode 100644
index 00000000..919a3818
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/hyperbolic.py
@@ -0,0 +1,43 @@
+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, TaskProviderHelper, filter_none
+
+
+class HyperbolicTextToImageTask(TaskProviderHelper):
+    def __init__(self):
+        super().__init__(provider="hyperbolic", base_url="https://api.hyperbolic.xyz", task="text-to-image")
+
+    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 "num_inference_steps" in parameters:
+            parameters["steps"] = parameters.pop("num_inference_steps")
+        if "guidance_scale" in parameters:
+            parameters["cfg_scale"] = parameters.pop("guidance_scale")
+        # For Hyperbolic, the width and height are required parameters
+        if "width" not in parameters:
+            parameters["width"] = 512
+        if "height" not in parameters:
+            parameters["height"] = 512
+        return {"prompt": inputs, "model_name": mapped_model, **parameters}
+
+    def get_response(self, response: Union[bytes, Dict]) -> Any:
+        response_dict = _as_dict(response)
+        return base64.b64decode(response_dict["images"][0]["image"])
+
+
+class HyperbolicTextGenerationTask(BaseConversationalTask):
+    """
+    Special case for Hyperbolic, where text-generation task is handled as a conversational task.
+    """
+
+    def __init__(self, task: str):
+        super().__init__(
+            provider="hyperbolic",
+            base_url="https://api.hyperbolic.xyz",
+        )
+        self.task = task
-- 
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