edits to transcribe agent
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@ -22,18 +22,20 @@
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# if __name__ == "__main__":
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# main()
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import os
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from groq import Groq
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import pyaudio
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import wave
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import pyautogui
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import requests
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import keyboard
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# Constants
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API_URL = "https://api.openai.com/v1/whisper"
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API_KEY = "your_openai_api_key"
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API_KEY = "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" # Make sure to use your actual API key
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BUTTON = 'ctrl' # The button to listen for
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# Initialize the Groq client
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client = Groq(api_key=API_KEY)
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def record_audio(filename):
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# Setup audio recording
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audio = pyaudio.PyAudio()
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@ -42,8 +44,8 @@ def record_audio(filename):
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frames = []
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print("Recording...")
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# Record while button is pressed
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while keyboard.is_pressed(BUTTON):
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# Record while button or mouse is pressed
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while keyboard.is_pressed(BUTTON) or mouse.is_pressed(button='left'):
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data = stream.read(1024)
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frames.append(data)
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@ -61,14 +63,17 @@ def record_audio(filename):
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wave_file.close()
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def transcribe_audio(filename):
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# Transcribe audio using Whisper API
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with open(filename, 'rb') as audio_file:
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response = requests.post(
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API_URL,
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headers={"Authorization": f"Bearer {API_KEY}"},
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files={"file": audio_file}
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# Open the audio file
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with open(filename, "rb") as file:
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# Create a transcription of the audio file
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transcription = client.audio.transcriptions.create(
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file=(filename, file.read()), # Required audio file
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model="distil-whisper-large-v3-en", # Required model to use for transcription
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prompt="Specify context or spelling", # Optional
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response_format="json", # Optional
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temperature=0.0 # Optional
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)
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return response.json().get('text', '')
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return transcription['text']
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def simulate_keypress(text):
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# Simulate keypress for each character in text
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