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# main.py (python example)
import os
from dotenv import load_dotenv
from deepgram import (
DeepgramClient,
PrerecordedOptions,
FileSource,
)
load_dotenv()
# Path to the audio file
AUDIO_FILE = r".\media\recorded.mp3"
API_KEY = os.getenv("DG_API_KEY")
def speech_to_text():
try:
# STEP 1 Create a Deepgram client using the API key
deepgram = DeepgramClient(API_KEY)
with open(AUDIO_FILE, "rb") as file:
buffer_data = file.read()
payload: FileSource = {
"buffer": buffer_data,
}
#STEP 2: Configure Deepgram options for audio analysis
options = PrerecordedOptions(
model="nova-2",
smart_format=True,
)
# STEP 3: Call the transcribe_file method with the text payload and options
response = deepgram.listen.prerecorded.v("1").transcribe_file(payload, options)
# STEP 4: Print the response
#print(response.to_json(indent=4))
#print(response["results"]["channels"][0]["alternatives"][0]["transcript"])
return str(response["results"]["channels"][0]["alternatives"][0]["transcript"])
except Exception as e:
print(f"Exception: {e}")
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