dapr-agents/quickstarts/02_llm_call_open_ai/audio_translation.py

37 lines
1.0 KiB
Python

from dapr_agents.types.llm import AudioTranslationRequest
from dapr_agents import OpenAIAudioClient
from dotenv import load_dotenv
load_dotenv()
client = OpenAIAudioClient()
# Specify the audio file to translate
audio_file_path = "speech_spanish.mp3"
# Create a translation request
translation_request = AudioTranslationRequest(
model="whisper-1",
file=audio_file_path,
prompt="The user will provide an audio file in Spanish. Translate the audio to English and transcribe the english text, word for word.",
)
# Generate translation
translation_response = client.create_translation(request=translation_request)
# Display the transcription result
if not len(translation_response.text) > 0:
exit(1)
print("Translation:", translation_response)
words = ["dapr", "agents", "open", "source", "framework", "researchers", "developers"]
normalized_text = translation_response.text.lower()
count = 0
for word in words:
if word in normalized_text:
count += 1
if count >= 5:
print("Success! The transcription contains at least 5 out of 7 words.")