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7f5d221c56
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b47e9cddbd
4 changed files with 31 additions and 64 deletions
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@ -36,8 +36,3 @@ Press the hotkey (default is Home) and then talk to jarvis
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- "hey jarvis, thats a clip"
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Checkout the code to see specific keywords/phrases as all NLP is regex/string based, not generative AI
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### Resource Usage
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With the `distil-small.en` model, on my system it uses about 500mb of VRAM
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16
config.py
16
config.py
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@ -1,16 +0,0 @@
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model = "distil-small.en"
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replacements = {"gigi": "gg", "heels": "heals", "heeling": "healing", "heel": "heal"}
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maximum_pulse = [
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"maximum",
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"pulse",
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"ball",
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"remove",
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"eliminate",
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"murder",
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"goon",
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"obliterate",
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"delete",
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"piss",
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]
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54
main.py
54
main.py
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@ -1,51 +1,35 @@
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import pyautogui as pg
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from pynput import keyboard
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import speech_recognition as sr
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from faster_whisper import WhisperModel
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from string import punctuation
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import config
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from slang import replacements
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import re
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import subprocess
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from time import sleep
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from mss import mss
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import numpy as np
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from io import BytesIO
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import sounddevice # turns off alsa error logging
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r = sr.Recognizer()
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r.pause_threshold = 2
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model = WhisperModel(config.model, device="cuda", compute_type="int8_float16")
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print("Testing Sound")
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with sr.Microphone() as source:
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r.adjust_for_ambient_noise(source, duration=3)
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print("ready!")
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def recognize_text() -> str:
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with sr.Microphone() as source:
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print("Say something!")
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audio = r.listen(source)
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results, _ = model.transcribe(
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BytesIO(audio.get_wav_data()),
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beam_size=5,
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language="en",
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condition_on_previous_text=False,
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)
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return " ".join([segment.text for segment in results])
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result = r.recognize_faster_whisper(audio, model="distil-small.en", beam_size=5, language="en", condition_on_previous_text=False)
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return result
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def chat_type():
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screen = mss() #! bad for performance but necessary
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screenshot = np.array(
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screen.grab({"top": 1090, "left": 1110, "width": 100, "height": 100})
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)
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screenshot = np.array(screen.grab({"top": 1090, "left": 1110, "width": 100, "height": 100}))
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try:
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pg.locate("ui/team-chat.png", screenshot, confidence=0.9)
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return "team"
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@ -60,34 +44,29 @@ def chat_type():
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return None
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def on_press(key):
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if key is not keyboard.Key.home:
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return
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print("Listening...")
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print("triggered!")
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command = recognize_text()
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print(f"Heard: {command}")
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# cleanup command
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command = command.lower().strip()
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command = command.lower()
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for char in punctuation:
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command = command.replace(char, "")
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command = command.replace(char, '')
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for original, new in config.replacements.items():
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for original, new in replacements.items():
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command = command.replace(original, new)
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print(f"Cleaned up command: {command}")
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if any(keyword in command for keyword in ["type", "say", "write"]):
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message = (
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re.search(r"(type|say|write) (.+?)(and |in |\n|$)", command)
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.groups(0)[1]
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.strip()
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)
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print(f"Typing: {message} in chat")
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if "chat" in command:
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message = re.search(r"type (.+?)(and |in |\n|$)", command).groups(0)[0].strip()
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print(f"Typing: {message} in team chat")
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pg.keyDown("enter")
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sleep(0.041)
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@ -95,7 +74,7 @@ def on_press(key):
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sleep(0.94)
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current_chat = chat_type()
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if current_chat == None or current_chat in command:
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if current_chat in command:
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pass # no change needed
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elif "match" in command or "team" in command:
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pg.keyDown("tab")
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@ -107,7 +86,7 @@ def on_press(key):
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# sleep(0.074)
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# pg.keyUp("enter")
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elif any(keyword in command for keyword in config.maximum_pulse):
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elif any(keyword in command for keyword in ["maximum", "pulse", "balls", "remove", "eliminate", "murder", "goon"]):
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print("MAXIMUM PULSE!!!!")
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pg.keyDown("q")
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sleep(0.032)
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@ -117,6 +96,9 @@ def on_press(key):
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subprocess.run("/home/ultrablob/Videos/Clips/save_clip.sh")
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# Collect events until released
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with keyboard.Listener(on_press=on_press, on_release=lambda event: None) as listener:
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with keyboard.Listener(
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on_press=on_press,
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on_release=lambda event: None) as listener:
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listener.join()
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6
slang.py
Normal file
6
slang.py
Normal file
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@ -0,0 +1,6 @@
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replacements = {
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"gigi": "gg",
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"heels": "heals",
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"heeling": "healing",
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"heel": "heal"
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}
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