refactor: use async image and transcription handling

This commit is contained in:
Igor Ilic 2025-12-16 16:27:13 +01:00
parent d92d6b9d8f
commit f2cb68dd5e

View file

@ -27,7 +27,9 @@ from tenacity import (
before_sleep_log, before_sleep_log,
) )
from ..types import TranscriptionReturnType from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.types import (
TranscriptionReturnType,
)
logger = get_logger() logger = get_logger()
observe = get_observe() observe = get_observe()
@ -216,7 +218,7 @@ class GenericAPIAdapter(LLMInterface):
raise ValueError( raise ValueError(
f"Could not determine MIME type for audio file: {input}. Is the extension correct?" f"Could not determine MIME type for audio file: {input}. Is the extension correct?"
) )
response = litellm.completion( response = await litellm.acompletion(
model=self.transcription_model, model=self.transcription_model,
messages=[ messages=[
{ {
@ -270,7 +272,7 @@ class GenericAPIAdapter(LLMInterface):
raise ValueError( raise ValueError(
f"Could not determine MIME type for image file: {input}. Is the extension correct?" f"Could not determine MIME type for image file: {input}. Is the extension correct?"
) )
return litellm.completion( response = await litellm.acompletion(
model=self.image_transcribe_model, model=self.image_transcribe_model,
messages=[ messages=[
{ {
@ -295,3 +297,4 @@ class GenericAPIAdapter(LLMInterface):
max_completion_tokens=300, max_completion_tokens=300,
max_retries=self.MAX_RETRIES, max_retries=self.MAX_RETRIES,
) )
return response