two version of R2R are here HEAD master

1 files changed, 210 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/openai/transcriptions/handler.py b/.venv/lib/python3.12/site-packages/litellm/llms/openai/transcriptions/handler.py
new file mode 100644
index 00000000..d9dd3c12
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/openai/transcriptions/handler.py
@@ -0,0 +1,210 @@
+from typing import Optional, Union
+
+import httpx
+from openai import AsyncOpenAI, OpenAI
+from pydantic import BaseModel
+
+import litellm
+from litellm.litellm_core_utils.audio_utils.utils import get_audio_file_name
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.types.utils import FileTypes
+from litellm.utils import (
+    TranscriptionResponse,
+    convert_to_model_response_object,
+    extract_duration_from_srt_or_vtt,
+)
+
+from ..openai import OpenAIChatCompletion
+
+
+class OpenAIAudioTranscription(OpenAIChatCompletion):
+    # Audio Transcriptions
+    async def make_openai_audio_transcriptions_request(
+        self,
+        openai_aclient: AsyncOpenAI,
+        data: dict,
+        timeout: Union[float, httpx.Timeout],
+    ):
+        """
+        Helper to:
+        - call openai_aclient.audio.transcriptions.with_raw_response when litellm.return_response_headers is True
+        - call openai_aclient.audio.transcriptions.create by default
+        """
+        try:
+            raw_response = (
+                await openai_aclient.audio.transcriptions.with_raw_response.create(
+                    **data, timeout=timeout
+                )
+            )  # type: ignore
+            headers = dict(raw_response.headers)
+            response = raw_response.parse()
+
+            return headers, response
+        except Exception as e:
+            raise e
+
+    def make_sync_openai_audio_transcriptions_request(
+        self,
+        openai_client: OpenAI,
+        data: dict,
+        timeout: Union[float, httpx.Timeout],
+    ):
+        """
+        Helper to:
+        - call openai_aclient.audio.transcriptions.with_raw_response when litellm.return_response_headers is True
+        - call openai_aclient.audio.transcriptions.create by default
+        """
+        try:
+            if litellm.return_response_headers is True:
+                raw_response = (
+                    openai_client.audio.transcriptions.with_raw_response.create(
+                        **data, timeout=timeout
+                    )
+                )  # type: ignore
+                headers = dict(raw_response.headers)
+                response = raw_response.parse()
+                return headers, response
+            else:
+                response = openai_client.audio.transcriptions.create(**data, timeout=timeout)  # type: ignore
+                return None, response
+        except Exception as e:
+            raise e
+
+    def audio_transcriptions(
+        self,
+        model: str,
+        audio_file: FileTypes,
+        optional_params: dict,
+        model_response: TranscriptionResponse,
+        timeout: float,
+        max_retries: int,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str],
+        api_base: Optional[str],
+        client=None,
+        atranscription: bool = False,
+    ) -> TranscriptionResponse:
+        data = {"model": model, "file": audio_file, **optional_params}
+
+        if "response_format" not in data or (
+            data["response_format"] == "text" or data["response_format"] == "json"
+        ):
+            data["response_format"] = (
+                "verbose_json"  # ensures 'duration' is received - used for cost calculation
+            )
+
+        if atranscription is True:
+            return self.async_audio_transcriptions(  # type: ignore
+                audio_file=audio_file,
+                data=data,
+                model_response=model_response,
+                timeout=timeout,
+                api_key=api_key,
+                api_base=api_base,
+                client=client,
+                max_retries=max_retries,
+                logging_obj=logging_obj,
+            )
+
+        openai_client: OpenAI = self._get_openai_client(  # type: ignore
+            is_async=False,
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            max_retries=max_retries,
+            client=client,
+        )
+
+        ## LOGGING
+        logging_obj.pre_call(
+            input=None,
+            api_key=openai_client.api_key,
+            additional_args={
+                "api_base": openai_client._base_url._uri_reference,
+                "atranscription": True,
+                "complete_input_dict": data,
+            },
+        )
+        _, response = self.make_sync_openai_audio_transcriptions_request(
+            openai_client=openai_client,
+            data=data,
+            timeout=timeout,
+        )
+
+        if isinstance(response, BaseModel):
+            stringified_response = response.model_dump()
+        else:
+            stringified_response = TranscriptionResponse(text=response).model_dump()
+
+        ## LOGGING
+        logging_obj.post_call(
+            input=get_audio_file_name(audio_file),
+            api_key=api_key,
+            additional_args={"complete_input_dict": data},
+            original_response=stringified_response,
+        )
+        hidden_params = {"model": "whisper-1", "custom_llm_provider": "openai"}
+        final_response: TranscriptionResponse = convert_to_model_response_object(response_object=stringified_response, model_response_object=model_response, hidden_params=hidden_params, response_type="audio_transcription")  # type: ignore
+        return final_response
+
+    async def async_audio_transcriptions(
+        self,
+        audio_file: FileTypes,
+        data: dict,
+        model_response: TranscriptionResponse,
+        timeout: float,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        client=None,
+        max_retries=None,
+    ):
+        try:
+            openai_aclient: AsyncOpenAI = self._get_openai_client(  # type: ignore
+                is_async=True,
+                api_key=api_key,
+                api_base=api_base,
+                timeout=timeout,
+                max_retries=max_retries,
+                client=client,
+            )
+
+            ## LOGGING
+            logging_obj.pre_call(
+                input=None,
+                api_key=openai_aclient.api_key,
+                additional_args={
+                    "api_base": openai_aclient._base_url._uri_reference,
+                    "atranscription": True,
+                    "complete_input_dict": data,
+                },
+            )
+            headers, response = await self.make_openai_audio_transcriptions_request(
+                openai_aclient=openai_aclient,
+                data=data,
+                timeout=timeout,
+            )
+            logging_obj.model_call_details["response_headers"] = headers
+            if isinstance(response, BaseModel):
+                stringified_response = response.model_dump()
+            else:
+                duration = extract_duration_from_srt_or_vtt(response)
+                stringified_response = TranscriptionResponse(text=response).model_dump()
+                stringified_response["duration"] = duration
+            ## LOGGING
+            logging_obj.post_call(
+                input=get_audio_file_name(audio_file),
+                api_key=api_key,
+                additional_args={"complete_input_dict": data},
+                original_response=stringified_response,
+            )
+            hidden_params = {"model": "whisper-1", "custom_llm_provider": "openai"}
+            return convert_to_model_response_object(response_object=stringified_response, model_response_object=model_response, hidden_params=hidden_params, response_type="audio_transcription")  # type: ignore
+        except Exception as e:
+            ## LOGGING
+            logging_obj.post_call(
+                input=input,
+                api_key=api_key,
+                original_response=str(e),
+            )
+            raise e