two version of R2R are hereHEADmaster

1 files changed, 59 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/together.py b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/together.py
new file mode 100644
index 00000000..6e2c1eb4
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/huggingface_hub/inference/_providers/together.py
@@ -0,0 +1,59 @@
+import base64
+from abc import ABC
+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,
+)
+
+
+_PROVIDER = "together"
+_BASE_URL = "https://api.together.xyz"
+
+
+class TogetherTask(TaskProviderHelper, ABC):
+    """Base class for Together API tasks."""
+
+    def __init__(self, task: str):
+        super().__init__(provider=_PROVIDER, base_url=_BASE_URL, task=task)
+
+    def _prepare_route(self, mapped_model: str) -> str:
+        if self.task == "text-to-image":
+            return "/v1/images/generations"
+        elif self.task == "conversational":
+            return "/v1/chat/completions"
+        elif self.task == "text-generation":
+            return "/v1/completions"
+        raise ValueError(f"Unsupported task '{self.task}' for Together API.")
+
+
+class TogetherTextGenerationTask(BaseTextGenerationTask):
+    def __init__(self):
+        super().__init__(provider=_PROVIDER, base_url=_BASE_URL)
+
+
+class TogetherConversationalTask(BaseConversationalTask):
+    def __init__(self):
+        super().__init__(provider=_PROVIDER, base_url=_BASE_URL)
+
+
+class TogetherTextToImageTask(TogetherTask):
+    def __init__(self):
+        super().__init__("text-to-image")
+
+    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["guidance"] = parameters.pop("guidance_scale")
+
+        return {"prompt": inputs, "response_format": "base64", **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"])