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feat(proxy_server.py): working /audio/transcription endpoint

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This commit is contained in:
Krrish Dholakia 2024-03-08 18:20:27 -08:00
parent cc0294b2f2
commit 0fb7afe820
6 changed files with 95 additions and 54 deletions
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27
litellm/llms/azure.py
View file

@ -770,9 +770,8 @@ class AzureChatCompletion(BaseLLM):
api_version: Optional[str] = None,
client=None,
azure_ad_token: Optional[str] = None,
max_retries=None,
logging_obj=None,
atranscriptions: bool = False,
atranscription: bool = False,
):
data = {"model": model, "file": audio_file, **optional_params}
@ -781,9 +780,11 @@ class AzureChatCompletion(BaseLLM):
"api_version": api_version,
"azure_endpoint": api_base,
"azure_deployment": model,
"max_retries": max_retries,
"timeout": timeout,
}
max_retries = optional_params.pop("max_retries", None)
azure_client_params = select_azure_base_url_or_endpoint(
azure_client_params=azure_client_params
)
@ -792,7 +793,10 @@ class AzureChatCompletion(BaseLLM):
elif azure_ad_token is not None:
azure_client_params["azure_ad_token"] = azure_ad_token
if atranscriptions == True:
if max_retries is not None:
azure_client_params["max_retries"] = max_retries
if atranscription == True:
return self.async_audio_transcriptions(
audio_file=audio_file,
data=data,
@ -845,18 +849,29 @@ class AzureChatCompletion(BaseLLM):
)
else:
async_azure_client = client
response = await async_azure_client.audio.transcriptions.create(
**data, timeout=timeout
) # type: ignore
stringified_response = response.model_dump()
## LOGGING
logging_obj.post_call(
input=audio_file.name,
api_key=api_key,
additional_args={"complete_input_dict": data},
additional_args={
"headers": {
"Authorization": f"Bearer {async_azure_client.api_key}"
},
"api_base": async_azure_client._base_url._uri_reference,
"atranscription": True,
"complete_input_dict": data,
},
original_response=stringified_response,
)
return convert_to_model_response_object(response_object=stringified_response, model_response_object=model_response, response_type="image_generation") # type: ignore
response = convert_to_model_response_object(response_object=stringified_response, model_response_object=model_response, response_type="audio_transcription") # type: ignore
return response
except Exception as e:
## LOGGING
logging_obj.post_call(

4
litellm/llms/openai.py
View file

@ -779,10 +779,10 @@ class OpenAIChatCompletion(BaseLLM):
client=None,
max_retries=None,
logging_obj=None,
atranscriptions: bool = False,
atranscription: bool = False,
):
data = {"model": model, "file": audio_file, **optional_params}
if atranscriptions == True:
if atranscription == True:
return self.async_audio_transcriptions(
audio_file=audio_file,
data=data,

7
litellm/main.py
View file

@ -3385,7 +3385,7 @@ def transcription(
Allows router to load balance between them
"""
atranscriptions = kwargs.get("atranscriptions", False)
atranscription = kwargs.get("atranscription", False)
litellm_call_id = kwargs.get("litellm_call_id", None)
logger_fn = kwargs.get("logger_fn", None)
proxy_server_request = kwargs.get("proxy_server_request", None)
@ -3421,12 +3421,13 @@ def transcription(
or litellm.azure_key
or get_secret("AZURE_API_KEY")
)
response = azure_chat_completions.audio_transcriptions(
model=model,
audio_file=file,
optional_params=optional_params,
model_response=model_response,
atranscriptions=atranscriptions,
atranscription=atranscription,
timeout=timeout,
logging_obj=litellm_logging_obj,
api_base=api_base,
@ -3440,7 +3441,7 @@ def transcription(
audio_file=file,
optional_params=optional_params,
model_response=model_response,
atranscriptions=atranscriptions,
atranscription=atranscription,
timeout=timeout,
logging_obj=litellm_logging_obj,
)

95
litellm/proxy/proxy_server.py
View file

@ -120,6 +120,8 @@ from fastapi import (
Header,
Response,
Form,
UploadFile,
File,
)
from fastapi.routing import APIRouter
from fastapi.security import OAuth2PasswordBearer
@ -3216,17 +3218,16 @@ async def image_generation(
@router.post(
"/v1/audio/transcriptions",
dependencies=[Depends(user_api_key_auth)],
response_class=ORJSONResponse,
tags=["audio"],
)
@router.post(
"/audio/transcriptions",
dependencies=[Depends(user_api_key_auth)],
response_class=ORJSONResponse,
tags=["audio"],
)
async def audio_transcriptions(
request: Request,
file: UploadFile = File(...),
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
):
"""
@ -3237,11 +3238,11 @@ async def audio_transcriptions(
global proxy_logging_obj
try:
# Use orjson to parse JSON data, orjson speeds up requests significantly
body = await request.body()
data = orjson.loads(body)
form_data = await request.form()
data: Dict = {key: value for key, value in form_data.items() if key != "file"}
# Include original request and headers in the data
data["proxy_server_request"] = {
data["proxy_server_request"] = { # type: ignore
"url": str(request.url),
"method": request.method,
"headers": dict(request.headers),
@ -3298,44 +3299,60 @@ async def audio_transcriptions(
else []
)
### CALL HOOKS ### - modify incoming data / reject request before calling the model
data = await proxy_logging_obj.pre_call_hook(
user_api_key_dict=user_api_key_dict, data=data, call_type="moderation"
)
assert (
file.filename is not None
) # make sure filename passed in (needed for type)
start_time = time.time()
with open(file.filename, "wb+") as f:
f.write(await file.read())
try:
data["file"] = open(file.filename, "rb")
### CALL HOOKS ### - modify incoming data / reject request before calling the model
data = await proxy_logging_obj.pre_call_hook(
user_api_key_dict=user_api_key_dict,
data=data,
call_type="moderation",
)
## ROUTE TO CORRECT ENDPOINT ##
# skip router if user passed their key
if "api_key" in data:
response = await litellm.atranscription(**data)
elif (
llm_router is not None and data["model"] in router_model_names
): # model in router model list
response = await llm_router.atranscription(**data)
elif (
llm_router is not None and data["model"] in llm_router.deployment_names
): # model in router deployments, calling a specific deployment on the router
response = await llm_router.atranscription(**data, specific_deployment=True)
elif (
llm_router is not None
and llm_router.model_group_alias is not None
and data["model"] in llm_router.model_group_alias
): # model set in model_group_alias
response = await llm_router.atranscription(
**data
) # ensure this goes the llm_router, router will do the correct alias mapping
elif user_model is not None: # `litellm --model <your-model-name>`
response = await litellm.atranscription(**data)
else:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail={"error": "Invalid model name passed in"},
)
## ROUTE TO CORRECT ENDPOINT ##
# skip router if user passed their key
if "api_key" in data:
response = await litellm.atranscription(**data)
elif (
llm_router is not None and data["model"] in router_model_names
): # model in router model list
response = await llm_router.atranscription(**data)
elif (
llm_router is not None
and data["model"] in llm_router.deployment_names
): # model in router deployments, calling a specific deployment on the router
response = await llm_router.atranscription(
**data, specific_deployment=True
)
elif (
llm_router is not None
and llm_router.model_group_alias is not None
and data["model"] in llm_router.model_group_alias
): # model set in model_group_alias
response = await llm_router.atranscription(
**data
) # ensure this goes the llm_router, router will do the correct alias mapping
elif user_model is not None: # `litellm --model <your-model-name>`
response = await litellm.atranscription(**data)
else:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail={"error": "Invalid model name passed in"},
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
finally:
os.remove(file.filename) # Delete the saved file
### ALERTING ###
data["litellm_status"] = "success" # used for alerting
return response
except Exception as e:
await proxy_logging_obj.post_call_failure_hook(
@ -3344,7 +3361,7 @@ async def audio_transcriptions(
traceback.print_exc()
if isinstance(e, HTTPException):
raise ProxyException(
message=getattr(e, "message", str(e)),
message=getattr(e, "message", str(e.detail)),
type=getattr(e, "type", "None"),
param=getattr(e, "param", "None"),
code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),

14
litellm/utils.py
View file

@ -2309,7 +2309,7 @@ def client(original_function):
or call_type == CallTypes.transcription.value
):
_file_name: BinaryIO = args[1] if len(args) > 1 else kwargs["file"]
messages = _file_name.name
messages = "audio_file"
stream = True if "stream" in kwargs and kwargs["stream"] == True else False
logging_obj = Logging(
model=model,
@ -2607,6 +2607,8 @@ def client(original_function):
return result
elif "aimg_generation" in kwargs and kwargs["aimg_generation"] == True:
return result
elif "atranscription" in kwargs and kwargs["atranscription"] == True:
return result
### POST-CALL RULES ###
post_call_processing(original_response=result, model=model or None)
@ -7834,7 +7836,9 @@ def exception_type(
message=f"AzureException - {original_exception.message}",
llm_provider="azure",
model=model,
request=original_exception.request,
request=httpx.Request(
method="POST", url="https://openai.com/"
),
)
else:
# if no status code then it is an APIConnectionError: https://github.com/openai/openai-python#handling-errors
@ -7842,7 +7846,11 @@ def exception_type(
__cause__=original_exception.__cause__,
llm_provider="azure",
model=model,
request=original_exception.request,
request=getattr(
original_exception,
"request",
httpx.Request(method="POST", url="https://openai.com/"),
),
)
if (
"BadRequestError.__init__() missing 1 required positional argument: 'param'"

2
tests/test_whisper.py
View file

@ -98,7 +98,7 @@ async def test_transcription_on_router():
"model": "azure/azure-whisper",
"api_base": os.getenv("AZURE_EUROPE_API_BASE"),
"api_key": os.getenv("AZURE_EUROPE_API_KEY"),
"api_version": os.getenv("2024-02-15-preview"),
"api_version": "2024-02-15-preview",
},
},
]