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# Created by .ignore support plugin (hsz.mobi)
### Python template
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# Custom
model_small/
# C extensions
*.so
# Distribution / packaging
.Python
env/
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
*.egg-info/
.installed.cfg
*.egg
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*,cover
.hypothesis/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
target/
# IPython Notebook
.ipynb_checkpoints
# pyenv
.python-version
# celery beat schedule file
celerybeat-schedule
# dotenv
.env
# virtualenv
venv/
ENV/
# Spyder project settings
.spyderproject
# Rope project settings
.ropeproject
### VirtualEnv template
# Virtualenv
# http://iamzed.com/2009/05/07/a-primer-on-virtualenv/
[Bb]in
[Ii]nclude
[Ll]ib
[Ll]ib64
[Ll]ocal
[Ss]cripts
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### JetBrains template
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# Generated files
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# Sensitive or high-churn files
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.idea/**/dataSources.ids
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### JetBrains template
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.idea/**/aws.xml
# Generated files
.idea/**/contentModel.xml
# Sensitive or high-churn files
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.idea/**/dataSources.ids
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# Gradle
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# Gradle and Maven with auto-import
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# .idea/*.iml
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# *.iml
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# CMake
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# Mongo Explorer plugin
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### PyCharm template
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# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
# User-specific stuff
.idea/**/workspace.xml
.idea/**/tasks.xml
.idea/**/usage.statistics.xml
.idea/**/dictionaries
.idea/**/shelf
# AWS User-specific
.idea/**/aws.xml
# Generated files
.idea/**/contentModel.xml
# Sensitive or high-churn files
.idea/**/dataSources/
.idea/**/dataSources.ids
.idea/**/dataSources.local.xml
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.idea/**/uiDesigner.xml
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# Gradle
.idea/**/gradle.xml
.idea/**/libraries
# Gradle and Maven with auto-import
# When using Gradle or Maven with auto-import, you should exclude module files,
# since they will be recreated, and may cause churn. Uncomment if using
# auto-import.
# .idea/artifacts
# .idea/compiler.xml
# .idea/jarRepositories.xml
# .idea/modules.xml
# .idea/*.iml
# .idea/modules
# *.iml
# *.ipr
# CMake
cmake-build-*/
# Mongo Explorer plugin
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# File-based project format
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# IntelliJ
out/
# mpeltonen/sbt-idea plugin
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# JIRA plugin
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### Python template
# Byte-compiled / optimized / DLL files
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*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
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# PyInstaller
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
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# commonly ignored for libraries.
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.pyre/
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# PyCharm
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
### PyCharm+all template
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# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
# User-specific stuff
.idea/**/workspace.xml
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.idea/**/usage.statistics.xml
.idea/**/dictionaries
.idea/**/shelf
# AWS User-specific
.idea/**/aws.xml
# Generated files
.idea/**/contentModel.xml
# Sensitive or high-churn files
.idea/**/dataSources/
.idea/**/dataSources.ids
.idea/**/dataSources.local.xml
.idea/**/sqlDataSources.xml
.idea/**/dynamic.xml
.idea/**/uiDesigner.xml
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# Gradle
.idea/**/gradle.xml
.idea/**/libraries
# Gradle and Maven with auto-import
# When using Gradle or Maven with auto-import, you should exclude module files,
# since they will be recreated, and may cause churn. Uncomment if using
# auto-import.
# .idea/artifacts
# .idea/compiler.xml
# .idea/jarRepositories.xml
# .idea/modules.xml
# .idea/*.iml
# .idea/modules
# *.iml
# *.ipr
# CMake
cmake-build-*/
# Mongo Explorer plugin
.idea/**/mongoSettings.xml
# File-based project format
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# IntelliJ
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# mpeltonen/sbt-idea plugin
.idea_modules/
# JIRA plugin
atlassian-ide-plugin.xml
# Cursive Clojure plugin
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# Crashlytics plugin (for Android Studio and IntelliJ)
com_crashlytics_export_strings.xml
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fabric.properties
# Editor-based Rest Client
.idea/httpRequests
# Android studio 3.1+ serialized cache file
.idea/caches/build_file_checksums.ser
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import json
import os
import struct
import time
import pvporcupine
import vosk
import yaml
from fuzzywuzzy import fuzz
from pvrecorder import PvRecorder
import config
from utils import execute_cmd, play
class Jarvis:
def __init__(self):
self.recorder = None
self.CDIR = os.getcwd()
self.VA_CMD_LIST = yaml.safe_load(open('commands.yaml', 'rt', encoding='utf8'))
self.porcupine = pvporcupine.create(
access_key=config.PICOVOICE_TOKEN,
keywords=['jarvis'],
sensitivities=[1]
)
self.kaldi_rec = vosk.KaldiRecognizer(vosk.Model("model_small"), 32000)
def main(self):
self.recorder = PvRecorder(
device_index=config.MICROPHONE_INDEX,
frame_length=self.porcupine.frame_length
)
self.recorder.start()
self.play("run")
time.sleep(0.5)
ltc = time.time() - 1000
while True:
try:
pcm = self.recorder.read()
if self.porcupine.process(pcm) >= 0:
self.recorder.stop()
self.play("greet", True)
self.recorder.start()
ltc = time.time()
while time.time() - ltc <= 10:
pcm = self.recorder.read()
sp = struct.pack("h" * len(pcm), *pcm)
if self.kaldi_rec.AcceptWaveform(sp):
if self.va_respond(json.loads(self.kaldi_rec.Result())["text"]):
ltc = time.time()
break
except Exception as err:
print(f"Unexpected {err=}, {type(err)=}")
raise
def va_respond(self, voice: str):
print(f"Распознано: {voice}")
for x in config.VA_ALIAS + config.VA_TBR:
voice = voice.replace(x, "").strip()
rc = {'cmd': '', 'percent': 0}
for c, v in self.VA_CMD_LIST.items():
for x in v:
vrt = fuzz.partial_ratio(voice.lower(), x.lower())
if vrt > rc['percent']:
rc['cmd'] = c
rc['percent'] = vrt
if len(rc['cmd'].strip()) <= 0:
return False
elif rc['percent'] < 70 or rc['cmd'] not in self.VA_CMD_LIST.keys():
self.play("not_found")
time.sleep(1)
return False
else:
execute_cmd.execute_cmd(self, rc['cmd'])
return True
def play(self, phrase, wait_done=True):
play.play(self, phrase, wait_done)
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'off':
- выключись
- вырубись
- завершить работу
- закройся
- отключись
- заверши свою работу
- на сегодня хватит
- выгрузи себя из памяти
- ты мне надоел
- пора спать
stupid:
- ты дурак
- ты дебил
- ты глупый
- ты тупой
thanks:
- спасибо
- молодец
- респект
- ты супер
- отличная работа
- ты крут
- ты большой молодец
- ты реально крут
- ты афигенный
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VA_ALIAS = ('джарвис',)
VA_TBR = ('скажи', 'покажи', 'ответь', 'произнеси', 'расскажи', 'сколько', 'слушай')
MICROPHONE_INDEX = -1
PICOVOICE_TOKEN = "4xbwaZwZmSHeTiowFl5Rgqsc8CR4FKGV8YueJUlR4Zt2e1kB64IDcA=="
OPENAI_TOKEN = "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"
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from Jarvis import Jarvis
def main():
jarvis = Jarvis()
jarvis.main()
if __name__ == '__main__':
main()
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[tool.poetry]
name = "djarvis-2-0"
version = "0.1.0"
description = ""
authors = ["dmitrium12 <belicdima8@gmail.com>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
vosk = "^0.3.45"
pvporcupine = "^3.0.1"
pvrecorder = "^1.2.1"
omegaconf = "^2.3.0"
numpy = "^1.26.2"
simpleaudio = "^1.0.4"
rich = "^13.7.0"
fuzzywuzzy = "^0.18.0"
python-levenshtein = "^0.23.0"
comtypes = "^1.2.0"
pycam = "^0.6.4"
sounddevice = "^0.4.6"
pyyaml = "^6.0.1"
python-dotenv = "^1.0.0"
pycaw = "^20230407"
torch = "^2.1.1+cpu"
torchaudio = "^2.1.1+cpu"
[[tool.poetry.source]]
name = "torch"
url = "https://download.pytorch.org/whl/cpu"
priority = "supplemental"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
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def execute_cmd(self, cmd: str):
if cmd == 'thanks':
self.play("thanks")
elif cmd == 'stupid':
self.play("stupid")
elif cmd == 'off':
self.play("off", True)
self.porcupine.delete()
exit(0)
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import random
import simpleaudio as sa
def play(self, phrase, wait_done=True):
filename = None
file_array = ["not_found", "thanks", "run", "stupid", "ready", "off"]
if phrase == "greet":
filename = f"greet{random.choice([1, 2, 3])}.wav"
elif phrase == "ok":
filename = f"ok{random.choice([1, 2, 3])}.wav"
elif phrase in file_array:
filename = f"{phrase}.wav"
if wait_done:
self.recorder.stop()
if filename:
wave_obj = sa.WaveObject.from_wave_file(f"{self.CDIR}/sound/{filename}")
play_obj = wave_obj.play()
if wait_done:
play_obj.wait_done()
self.recorder.start()
else:
print("tts")
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import time
import sounddevice as sd
import torch
language = 'ru'
model_id = 'ru_v3'
sample_rate = 48000 # 48000
speaker = 'aidar' # aidar, baya, kseniya, xenia, random
put_accent = True
put_yo = True
device = torch.device('cpu') # cpu или gpu
text = "Хауди Хо, друзья!!!"
model, _ = torch.hub.load(repo_or_dir='snakers4/silero-models',
model='silero_tts',
language=language,
speaker=model_id)
model.to(device)
def va_speak(what: str):
audio = model.apply_tts(text=what + "..",
speaker=speaker,
sample_rate=sample_rate,
put_accent=put_accent,
put_yo=put_yo)
sd.play(audio, sample_rate * 1.05)
time.sleep((len(audio) / sample_rate) + 0.5)
sd.stop()