fix(openai.py): fix openai response for /audio/speech endpoint

litellm/main.py

@@ -91,12 +91,7 @@ import tiktoken
 from concurrent.futures import ThreadPoolExecutor
 from typing import Callable, List, Optional, Dict, Union, Mapping
 from .caching import enable_cache, disable_cache, update_cache
-from .types.llms.openai import (
-    StreamedBinaryAPIResponse,
-    ResponseContextManager,
-    AsyncResponseContextManager,
-    AsyncStreamedBinaryAPIResponse,
-)
+from .types.llms.openai import HttpxBinaryResponseContent
 
 encoding = tiktoken.get_encoding("cl100k_base")
 from litellm.utils import (
@@ -4169,9 +4164,7 @@ def transcription(
     return response
 
 
-def aspeech(
-    *args, **kwargs
-) -> AsyncResponseContextManager[AsyncStreamedBinaryAPIResponse]:
+async def aspeech(*args, **kwargs) -> HttpxBinaryResponseContent:
     """
     Calls openai tts endpoints.
     """
@@ -4181,25 +4174,25 @@ def aspeech(
     kwargs["aspeech"] = True
     custom_llm_provider = kwargs.get("custom_llm_provider", None)
     try:
-        # # Use a partial function to pass your keyword arguments
-        # func = partial(speech, *args, **kwargs)
+        # Use a partial function to pass your keyword arguments
+        func = partial(speech, *args, **kwargs)
 
-        # # Add the context to the function
-        # ctx = contextvars.copy_context()
-        # func_with_context = partial(ctx.run, func)
+        # Add the context to the function
+        ctx = contextvars.copy_context()
+        func_with_context = partial(ctx.run, func)
 
-        # _, custom_llm_provider, _, _ = get_llm_provider(
-        #     model=model, api_base=kwargs.get("api_base", None)
-        # )
+        _, custom_llm_provider, _, _ = get_llm_provider(
+            model=model, api_base=kwargs.get("api_base", None)
+        )
 
-        # # Await normally
-        # init_response = await loop.run_in_executor(None, func_with_context)
-        # if asyncio.iscoroutine(init_response):
-        #     response = await init_response
-        # else:
-        #     # Call the synchronous function using run_in_executor
-        #     response = await loop.run_in_executor(None, func_with_context)
-        return speech(*args, **kwargs)  # type: ignore
+        # Await normally
+        init_response = await loop.run_in_executor(None, func_with_context)
+        if asyncio.iscoroutine(init_response):
+            response = await init_response
+        else:
+            # Call the synchronous function using run_in_executor
+            response = await loop.run_in_executor(None, func_with_context)
+        return response  # type: ignore
     except Exception as e:
         custom_llm_provider = custom_llm_provider or "openai"
         raise exception_type(
@@ -4215,12 +4208,12 @@ def speech(
     model: str,
     input: str,
     voice: str,
-    optional_params: dict,
-    api_key: Optional[str],
-    api_base: Optional[str],
-    organization: Optional[str],
-    project: Optional[str],
-    max_retries: int,
+    api_key: Optional[str] = None,
+    api_base: Optional[str] = None,
+    organization: Optional[str] = None,
+    project: Optional[str] = None,
+    max_retries: Optional[int] = None,
+    metadata: Optional[dict] = None,
     timeout: Optional[Union[float, httpx.Timeout]] = None,
     response_format: Optional[str] = None,
     speed: Optional[int] = None,
@@ -4228,7 +4221,8 @@ def speech(
     headers: Optional[dict] = None,
     custom_llm_provider: Optional[str] = None,
     aspeech: Optional[bool] = None,
-) -> ResponseContextManager[StreamedBinaryAPIResponse]:
+    **kwargs,
+) -> HttpxBinaryResponseContent:
 
     model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider(model=model, custom_llm_provider=custom_llm_provider, api_base=api_base)  # type: ignore
 
@@ -4236,12 +4230,14 @@ def speech(
     if response_format is not None:
         optional_params["response_format"] = response_format
     if speed is not None:
-        optional_params["speed"] = speed
+        optional_params["speed"] = speed  # type: ignore
 
     if timeout is None:
         timeout = litellm.request_timeout
 
-    response: Optional[ResponseContextManager[StreamedBinaryAPIResponse]] = None
+    if max_retries is None:
+        max_retries = litellm.num_retries or openai.DEFAULT_MAX_RETRIES
+    response: Optional[HttpxBinaryResponseContent] = None
     if custom_llm_provider == "openai":
         api_base = (
             api_base  # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there