add acreate_fine_tuning_job

litellm/llms/openai_fine_tuning/openai.py

@@ -0,0 +1,96 @@
+from typing import Any, Coroutine, Optional, Union
+
+import httpx
+from openai import AsyncOpenAI, OpenAI
+from openai.types.fine_tuning import FineTuningJob
+
+from litellm._logging import verbose_logger
+from litellm.llms.base import BaseLLM
+from litellm.types.llms.openai import FineTuningJobCreate
+
+
+class OpenAIFineTuningAPI(BaseLLM):
+    """
+    OpenAI methods to support for batches
+    """
+
+    def __init__(self) -> None:
+        super().__init__()
+
+    def get_openai_client(
+        self,
+        api_key: Optional[str],
+        api_base: Optional[str],
+        timeout: Union[float, httpx.Timeout],
+        max_retries: Optional[int],
+        organization: Optional[str],
+        client: Optional[Union[OpenAI, AsyncOpenAI]] = None,
+        _is_async: bool = False,
+    ) -> Optional[Union[OpenAI, AsyncOpenAI]]:
+        received_args = locals()
+        openai_client: Optional[Union[OpenAI, AsyncOpenAI]] = None
+        if client is None:
+            data = {}
+            for k, v in received_args.items():
+                if k == "self" or k == "client" or k == "_is_async":
+                    pass
+                elif k == "api_base" and v is not None:
+                    data["base_url"] = v
+                elif v is not None:
+                    data[k] = v
+            if _is_async is True:
+                openai_client = AsyncOpenAI(**data)
+            else:
+                openai_client = OpenAI(**data)  # type: ignore
+        else:
+            openai_client = client
+
+        return openai_client
+
+    async def acreate_fine_tuning_job(
+        self,
+        create_fine_tuning_job_data: FineTuningJobCreate,
+        openai_client: AsyncOpenAI,
+    ) -> FineTuningJob:
+        response = await openai_client.batches.create(**create_fine_tuning_job_data)
+        return response
+
+    def create_fine_tuning_job(
+        self,
+        _is_async: bool,
+        create_fine_tuning_job_data: FineTuningJobCreate,
+        api_key: Optional[str],
+        api_base: Optional[str],
+        timeout: Union[float, httpx.Timeout],
+        max_retries: Optional[int],
+        organization: Optional[str],
+        client: Optional[Union[OpenAI, AsyncOpenAI]] = None,
+    ) -> Union[Coroutine[Any, Any, FineTuningJob]]:
+        openai_client: Optional[Union[OpenAI, AsyncOpenAI]] = self.get_openai_client(
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            max_retries=max_retries,
+            organization=organization,
+            client=client,
+            _is_async=_is_async,
+        )
+        if openai_client is None:
+            raise ValueError(
+                "OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
+            )
+
+        if _is_async is True:
+            if not isinstance(openai_client, AsyncOpenAI):
+                raise ValueError(
+                    "OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
+                )
+            return self.acreate_fine_tuning_job(  # type: ignore
+                create_fine_tuning_job_data=create_fine_tuning_job_data,
+                openai_client=openai_client,
+            )
+        verbose_logger.debug(
+            "creating fine tuning job, args= %s", create_fine_tuning_job_data
+        )
+        response = openai_client.fine_tuning.jobs.create(**create_fine_tuning_job_data)
+        return response