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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"])
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