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Repository: WenJing95/SayKey
Branch: main
Commit: 8b76e04a2a82
Files: 58
Total size: 403.7 KB
Directory structure:
gitextract_j4dfeo4j/
├── .gitattributes
├── .gitignore
├── LICENSE.txt
├── backend/
│ ├── .gitignore
│ ├── CT-Transformer-punctuation/
│ │ ├── .flake8
│ │ ├── .gitignore
│ │ ├── LICENSE
│ │ ├── MANIFEST.in
│ │ ├── README.md
│ │ ├── cttPunctuator.py
│ │ ├── cttpunctuator/
│ │ │ ├── __init__.py
│ │ │ └── src/
│ │ │ ├── onnx/
│ │ │ │ └── configuration.json
│ │ │ ├── punctuator.py
│ │ │ └── utils/
│ │ │ ├── OrtInferSession.py
│ │ │ └── text_post_process.py
│ │ ├── setup.py
│ │ ├── test/
│ │ │ ├── test.py
│ │ │ └── test2.py
│ │ └── version.txt
│ ├── build_onefile.bat
│ ├── main.py
│ ├── punc-onnx/
│ │ ├── configuration.json
│ │ └── punc.onnx
│ ├── readme.md
│ ├── requirements.txt
│ ├── requirements_test.txt
│ ├── sherpa-onnx/
│ │ ├── model.int8.onnx
│ │ └── tokens.txt
│ └── test_api.py
├── frontend/
│ ├── .gitignore
│ ├── components.json
│ ├── index.html
│ ├── package.json
│ ├── postcss.config.js
│ ├── readme.md
│ ├── src/
│ │ ├── VoiceRecognitionIcon.tsx
│ │ ├── components/
│ │ │ └── ui/
│ │ │ ├── badge.tsx
│ │ │ ├── button.tsx
│ │ │ ├── card.tsx
│ │ │ ├── hover-card.tsx
│ │ │ ├── scroll-area.tsx
│ │ │ ├── tabs.tsx
│ │ │ └── tooltip.tsx
│ │ ├── favicon/
│ │ │ └── site.webmanifest
│ │ ├── globals.css
│ │ ├── i18n.ts
│ │ ├── index.html
│ │ ├── lib/
│ │ │ └── utils.ts
│ │ ├── log.html
│ │ ├── main.ts
│ │ ├── preload.ts
│ │ ├── renderer.tsx
│ │ └── styles.css
│ ├── tailwind.config.js
│ ├── tsconfig.json
│ └── webpack.config.js
├── readme.md
└── readme_zh.md
================================================
FILE CONTENTS
================================================
================================================
FILE: .gitattributes
================================================
backend/punc-onnx/punc.onnx filter=lfs diff=lfs merge=lfs -text
backend/sherpa-onnx/model.int8.onnx filter=lfs diff=lfs merge=lfs -text
================================================
FILE: .gitignore
================================================
.idea/
SayKey-v1.0.0
SayKey
SayKey-v1.0.0.zip
SayKey.zip
data
*.wav
================================================
FILE: LICENSE.txt
================================================
The MIT License (MIT)
Copyright (c) 2014-2017 Alexey Popravka
Copyright (c) 2021 Sean Stewart
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: backend/.gitignore
================================================
venv/
build/
dist/
*.spec
.idea/
data/
*.wav
================================================
FILE: backend/CT-Transformer-punctuation/.flake8
================================================
[flake8]
show-source=true
statistics=true
max-line-length = 108
per-file-ignores =
# line too long
runtime/src/utils/kaldifeat/feature.py : E501
runtime/src/utils/kaldifeat/ivector.py : E501
exclude =
.git,
**/data/**
**/onnx/**
ignore =
# E203 white space before ":"
E203,
# W503 line break before binary operator
W503,
# E226 missing whitespace around arithmetic operator
E226,
================================================
FILE: backend/CT-Transformer-punctuation/.gitignore
================================================
*.bin
*.onnx
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# 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/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# 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.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# 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/
================================================
FILE: backend/CT-Transformer-punctuation/LICENSE
================================================
The MIT License (MIT)
Copyright (c) 2014-2017 Alexey Popravka
Copyright (c) 2021 Sean Stewart
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: backend/CT-Transformer-punctuation/MANIFEST.in
================================================
include cttpunctuator/src/onnx/configuration.json
include cttpunctuator/src/onnx/punc.onnx
include cttpunctuator/src/onnx/punc.yaml
================================================
FILE: backend/CT-Transformer-punctuation/README.md
================================================
<br/>
<h2 align="center">Ctt punctuator</h2>
<br/>
A enterprise-grade Chinese-English code switch punctuator [funasr](https://github.com/alibaba-damo-academy/FunASR/).
<br/>
<h2 align="center">Key Features</h2>
<br/>
- **General**
ctt punctuator was trained on chinese-english code switch corpora.
- [x] offline punctuator
- [x] online punctuator
- [x] punctuator for chinese-english code switch
the onnx model file is 279M, you can download it from [here](https://github.com/lovemefan/CT-Transformer-punctuation/raw/main/cttpunctuator/src/onnx/punc.onnx)
- **Highly Portable**
ctt-punctuator reaps benefits from the rich ecosystems built around **ONNX** running everywhere where these runtimes are available.
## Installation
```bash
git clone https://github.com/lovemefan/CT-Transformer-punctuation.git
cd CT-Transformer-punctuation
# download onnx model from huggingface
wget "https://huggingface.co/lovemefan/ctt_punctuator/resolve/main/cttpunctuator/src/onnx/punc.onnx" -O cttpunctuator/src/onnx/punc.onnx
# you can also download with huggingface mirror
# wget "https://hf-mirror.com/lovemefan/ctt_punctuator/resolve/main/cttpunctuator/src/onnx/punc.onnx" -O cttpunctuator/src/onnx/punc.onnx
pip install -e .
```
## Usage
```python
from cttPunctuator import CttPunctuator
import logging
logging.basicConfig(
level=logging.INFO,
format="[%(asctime)s %(levelname)s] [%(filename)s:%(lineno)d %(module)s.%(funcName)s] %(message)s",
)
# offline mode
punc = CttPunctuator()
text = "据报道纽约时报使用ChatGPT创建了一个情人节消息生成器用户只需输入几个提示就可以得到一封自动生成的情书"
logging.info(punc.punctuate(text)[0])
# online mode
punc = CttPunctuator(online=True)
text_in = "跨境河流是养育沿岸|人民的生命之源长期以来为帮助下游地区防灾减灾中方技术人员|在上游地区极为恶劣的自然条件下克服巨大困难甚至冒着生命危险|向印方提供汛期水文资料处理紧急事件中方重视印方在跨境河流>问题上的关切|愿意进一步完善双方联合工作机制|凡是|中方能做的我们|都会去做而且会做得更好我请印度朋友们放心中国在上游的|任何开发利用都会经过科学|规划和论证兼顾上下游的利益"
vads = text_in.split("|")
rec_result_all = ""
param_dict = {"cache": []}
for vad in vads:
result = punc.punctuate(vad, param_dict=param_dict)
rec_result_all += result[0]
logging.info(f"Part: {rec_result_all}")
logging.info(f"Final: {rec_result_all}")
```
## Result
```bash
[2023-04-19 01:12:39,308 INFO] [ctt-punctuator.py:50 ctt-punctuator.__init__] Initializing punctuator model with offline mode.
[2023-04-19 01:12:55,854 INFO] [ctt-punctuator.py:52 ctt-punctuator.__init__] Offline model initialized.
[2023-04-19 01:12:55,854 INFO] [ctt-punctuator.py:55 ctt-punctuator.__init__] Model initialized.
[2023-04-19 01:12:55,868 INFO] [ctt-punctuator.py:67 ctt-punctuator.<module>] 据报道，纽约时报使用ChatGPT创建了一个情人节消息生成器，用户只需输入几个提示，就可以得到一封自动生成的情书。
[2023-04-19 01:12:55,868 INFO] [ctt-punctuator.py:40 ctt-punctuator.__init__] Initializing punctuator model with online mode.
[2023-04-19 01:13:12,499 INFO] [ctt-punctuator.py:43 ctt-punctuator.__init__] Online model initialized.
[2023-04-19 01:13:12,499 INFO] [ctt-punctuator.py:55 ctt-punctuator.__init__] Model initialized.
[2023-04-19 01:13:12,502 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸
[2023-04-19 01:13:12,508 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员
[2023-04-19 01:13:12,521 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险
[2023-04-19 01:13:12,547 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切
[2023-04-19 01:13:12,553 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制
[2023-04-19 01:13:12,559 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是
[2023-04-19 01:13:12,560 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是中方能做的，我们
[2023-04-19 01:13:12,567 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是中方能做的，我们都会去做，而且会做得更好。我请印度朋友们放心，中国在上游的
[2023-04-19 01:13:12,572 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是中方能做的，我们都会去做，而且会做得更好。我请印度朋友们放心，中国在上游的任何开发利用，都会经过科学
[2023-04-19 01:13:12,578 INFO] [ctt-punctuator.py:77 ctt-punctuator.<module>] Partial: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是中方能做的，我们都会去做，而且会做得更好。我请印度朋友们放心，中国在上游的任何开发利用，都会经过科学规划和论证，兼顾上下游的利益
[2023-04-19 01:13:12,578 INFO] [ctt-punctuator.py:79 ctt-punctuator.<module>] Final: 跨境河流是养育沿岸人民的生命之源。长期以来，为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难，甚至冒着生命危险，向印方提供汛期水文资料处理紧急事件。中方重视印方在跨境河流>问题上的关切，愿意进一步完善双方联合工作机制。凡是中方能做的，我们都会去做，而且会做得更好。我请印度朋友们放心，中国在上游的任何开发利用，都会经过科学规划和论证，兼顾上下游的利益
```
## Citation
```
@inproceedings{chen2020controllable,
title={Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection},
author={Chen, Qian and Chen, Mengzhe and Li, Bo and Wang, Wen},
booktitle={ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={8069--8073},
year={2020},
organization={IEEE}
}
```
```
@misc{FunASR,
author = {Speech Lab, Alibaba Group, China},
title = {FunASR: A Fundamental End-to-End Speech Recognition Toolkit},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/alibaba-damo-academy/FunASR/}},
}
```
================================================
FILE: backend/CT-Transformer-punctuation/cttPunctuator.py
================================================
# -*- coding:utf-8 -*-
# @FileName :ctt-punctuator.py
# @Time :2023/4/13 15:03
# @Author :lovemefan
# @Email :lovemefan@outlook.com
__author__ = "lovemefan"
__copyright__ = "Copyright (C) 2023 lovemefan"
__license__ = "MIT"
__version__ = "v0.0.1"
import logging
import threading
import os
from cttpunctuator.src.punctuator import CT_Transformer, CT_Transformer_VadRealtime
logging.basicConfig(
level=logging.WARN,
format="[%(asctime)s %(levelname)s] [%(filename)s:%(lineno)d %(module)s.%(funcName)s] %(message)s",
)
lock = threading.RLock()
class CttPunctuator:
_offline_model = None
_online_model = None
def __init__(self, online: bool = False, model_dir: str = None):
"""
punctuator with singleton pattern
:param online: whether to use online mode
:param model_dir: directory containing the model files
"""
self.online = online
self.model_dir = model_dir or os.path.join(os.path.dirname(__file__), "cttpunctuator", "src", "onnx")
if online:
if CttPunctuator._online_model is None:
with lock:
if CttPunctuator._online_model is None:
logging.info("Initializing punctuator model with online mode.")
CttPunctuator._online_model = CT_Transformer_VadRealtime(model_dir=self.model_dir)
self.param_dict = {"cache": []}
logging.info("Online model initialized.")
self.model = CttPunctuator._online_model
else:
if CttPunctuator._offline_model is None:
with lock:
if CttPunctuator._offline_model is None:
logging.info("Initializing punctuator model with offline mode.")
CttPunctuator._offline_model = CT_Transformer(model_dir=self.model_dir)
logging.info("Offline model initialized.")
self.model = CttPunctuator._offline_model
logging.info("Model initialized.")
def punctuate(self, text: str, param_dict=None):
if self.online:
param_dict = param_dict or self.param_dict
return self.model(text, self.param_dict)
else:
return self.model(text)
================================================
FILE: backend/CT-Transformer-punctuation/cttpunctuator/__init__.py
================================================
# -*- coding:utf-8 -*-
# @FileName :__init__.py.py
# @Time :2023/4/13 14:58
# @Author :lovemefan
# @Email :lovemefan@outlook.com
================================================
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/onnx/configuration.json
================================================
{
"framework": "onnx",
"task" : "punctuation",
"model" : {
"type" : "generic-punc",
"punc_model_name" : "punc.pb",
"punc_model_config" : {
"type": "pytorch",
"code_base": "funasr",
"mode": "punc",
"lang": "zh-cn",
"batch_size": 1,
"punc_config": "punc.yaml",
"model": "damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
}
},
"pipeline": {
"type":"punc-inference"
}
}
================================================
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/punctuator.py
================================================
import logging
import os.path
import pickle
from pathlib import Path
from typing import Tuple, Union
import numpy as np
from cttpunctuator.src.utils.OrtInferSession import ONNXRuntimeError, OrtInferSession
from cttpunctuator.src.utils.text_post_process import (
TokenIDConverter,
code_mix_split_words,
split_to_mini_sentence,
)
class CT_Transformer:
"""
Author: Speech Lab, Alibaba Group, China
CT-Transformer: Controllable time-delay transformer
for real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
def __init__(
self,
model_dir: Union[str, Path] = None,
batch_size: int = 1,
device_id: Union[str, int] = "-1",
quantize: bool = False,
intra_op_num_threads: int = 4,
):
model_dir = model_dir or os.path.join(os.path.dirname(__file__), "onnx")
if model_dir is None or not Path(model_dir).exists():
raise FileNotFoundError(f"{model_dir} does not exist.")
model_file = os.path.join(model_dir, "punc.onnx")
if quantize:
model_file = os.path.join(model_dir, "model_quant.onnx")
config_file = os.path.join(model_dir, "punc.bin")
with open(config_file, "rb") as file:
config = pickle.load(file)
self.converter = TokenIDConverter(config["token_list"])
self.ort_infer = OrtInferSession(
model_file, device_id, intra_op_num_threads=intra_op_num_threads
)
self.batch_size = 1
self.punc_list = config["punc_list"]
self.period = 0
for i in range(len(self.punc_list)):
if self.punc_list[i] == ",":
self.punc_list[i] = "，"
elif self.punc_list[i] == "?":
self.punc_list[i] = "？"
elif self.punc_list[i] == "。":
self.period = i
def __call__(self, text: Union[list, str], split_size=20):
split_text = code_mix_split_words(text)
split_text_id = self.converter.tokens2ids(split_text)
mini_sentences = split_to_mini_sentence(split_text, split_size)
mini_sentences_id = split_to_mini_sentence(split_text_id, split_size)
assert len(mini_sentences) == len(mini_sentences_id)
cache_sent = []
cache_sent_id = []
new_mini_sentence = ""
new_mini_sentence_punc = []
cache_pop_trigger_limit = 200
for mini_sentence_i in range(len(mini_sentences)):
mini_sentence = mini_sentences[mini_sentence_i]
mini_sentence_id = mini_sentences_id[mini_sentence_i]
mini_sentence = cache_sent + mini_sentence
mini_sentence_id = np.array(cache_sent_id + mini_sentence_id, dtype="int64")
text_lengths = np.array([len(mini_sentence)], dtype="int32")
data = {
"text": mini_sentence_id[None, :],
"text_lengths": text_lengths,
}
try:
outputs = self.infer(data["text"], data["text_lengths"])
y = outputs[0]
punctuations = np.argmax(y, axis=-1)[0]
assert punctuations.size == len(mini_sentence)
except ONNXRuntimeError as e:
logging.exception(e)
# Search for the last Period/QuestionMark as cache
if mini_sentence_i < len(mini_sentences) - 1:
sentenceEnd = -1
last_comma_index = -1
for i in range(len(punctuations) - 2, 1, -1):
if (
self.punc_list[punctuations[i]] == "。"
or self.punc_list[punctuations[i]] == "？"
):
sentenceEnd = i
break
if last_comma_index < 0 and self.punc_list[punctuations[i]] == "，":
last_comma_index = i
if (
sentenceEnd < 0
and len(mini_sentence) > cache_pop_trigger_limit
and last_comma_index >= 0
):
# The sentence it too long, cut off at a comma.
sentenceEnd = last_comma_index
punctuations[sentenceEnd] = self.period
cache_sent = mini_sentence[sentenceEnd + 1 :]
cache_sent_id = mini_sentence_id[sentenceEnd + 1 :].tolist()
mini_sentence = mini_sentence[0 : sentenceEnd + 1]
punctuations = punctuations[0 : sentenceEnd + 1]
new_mini_sentence_punc += [int(x) for x in punctuations]
words_with_punc = []
for i in range(len(mini_sentence)):
if i > 0:
if (
len(mini_sentence[i][0].encode()) == 1
and len(mini_sentence[i - 1][0].encode()) == 1
):
mini_sentence[i] = " " + mini_sentence[i]
words_with_punc.append(mini_sentence[i])
if self.punc_list[punctuations[i]] != "_":
words_with_punc.append(self.punc_list[punctuations[i]])
new_mini_sentence += "".join(words_with_punc)
# Add Period for the end of the sentence
new_mini_sentence_out = new_mini_sentence
new_mini_sentence_punc_out = new_mini_sentence_punc
if mini_sentence_i == len(mini_sentences) - 1:
if new_mini_sentence[-1] == "，" or new_mini_sentence[-1] == "、":
new_mini_sentence_out = new_mini_sentence[:-1] + "。"
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [
self.period
]
elif new_mini_sentence[-1] != "。" and new_mini_sentence[-1] != "？":
new_mini_sentence_out = new_mini_sentence + "。"
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [
self.period
]
return new_mini_sentence_out, new_mini_sentence_punc_out
def infer(
self, feats: np.ndarray, feats_len: np.ndarray
) -> Tuple[np.ndarray, np.ndarray]:
outputs = self.ort_infer([feats, feats_len])
return outputs
class CT_Transformer_VadRealtime(CT_Transformer):
"""
Author: Speech Lab, Alibaba Group, China
CT-Transformer: Controllable time-delay transformer for
real-time punctuation prediction and disfluency detection
https://arxiv.org/pdf/2003.01309.pdf
"""
def __init__(
self,
model_dir: Union[str, Path] = None,
batch_size: int = 1,
device_id: Union[str, int] = "-1",
quantize: bool = False,
intra_op_num_threads: int = 4,
):
super(CT_Transformer_VadRealtime, self).__init__(
model_dir, batch_size, device_id, quantize, intra_op_num_threads
)
def __call__(self, text: str, param_dict: map, split_size=20):
cache_key = "cache"
assert cache_key in param_dict
cache = param_dict[cache_key]
if cache is not None and len(cache) > 0:
precache = "".join(cache)
else:
precache = ""
cache = []
full_text = precache + text
split_text = code_mix_split_words(full_text)
split_text_id = self.converter.tokens2ids(split_text)
mini_sentences = split_to_mini_sentence(split_text, split_size)
mini_sentences_id = split_to_mini_sentence(split_text_id, split_size)
new_mini_sentence_punc = []
assert len(mini_sentences) == len(mini_sentences_id)
cache_sent = []
cache_sent_id = np.array([], dtype="int32")
sentence_punc_list = []
sentence_words_list = []
cache_pop_trigger_limit = 200
skip_num = 0
for mini_sentence_i in range(len(mini_sentences)):
mini_sentence = mini_sentences[mini_sentence_i]
mini_sentence_id = mini_sentences_id[mini_sentence_i]
mini_sentence = cache_sent + mini_sentence
mini_sentence_id = np.concatenate((cache_sent_id, mini_sentence_id), axis=0)
text_length = len(mini_sentence_id)
data = {
"input": np.array(mini_sentence_id[None, :], dtype="int64"),
"text_lengths": np.array([text_length], dtype="int32"),
"vad_mask": self.vad_mask(text_length, len(cache))[
None, None, :, :
].astype(np.float32),
"sub_masks": np.tril(
np.ones((text_length, text_length), dtype=np.float32)
)[None, None, :, :].astype(np.float32),
}
try:
outputs = self.infer(
data["input"],
data["text_lengths"],
data["vad_mask"],
data["sub_masks"],
)
y = outputs[0]
punctuations = np.argmax(y, axis=-1)[0]
assert punctuations.size == len(mini_sentence)
except ONNXRuntimeError as e:
logging.exception(e)
# Search for the last Period/QuestionMark as cache
if mini_sentence_i < len(mini_sentences) - 1:
sentenceEnd = -1
last_comma_index = -1
for i in range(len(punctuations) - 2, 1, -1):
if (
self.punc_list[punctuations[i]] == "。"
or self.punc_list[punctuations[i]] == "？"
):
sentenceEnd = i
break
if last_comma_index < 0 and self.punc_list[punctuations[i]] == "，":
last_comma_index = i
if (
sentenceEnd < 0
and len(mini_sentence) > cache_pop_trigger_limit
and last_comma_index >= 0
):
# The sentence it too long, cut off at a comma.
sentenceEnd = last_comma_index
punctuations[sentenceEnd] = self.period
cache_sent = mini_sentence[sentenceEnd + 1 :]
cache_sent_id = mini_sentence_id[sentenceEnd + 1 :]
mini_sentence = mini_sentence[0 : sentenceEnd + 1]
punctuations = punctuations[0 : sentenceEnd + 1]
punctuations_np = [int(x) for x in punctuations]
new_mini_sentence_punc += punctuations_np
sentence_punc_list += [self.punc_list[int(x)] for x in punctuations_np]
sentence_words_list += mini_sentence
assert len(sentence_punc_list) == len(sentence_words_list)
words_with_punc = []
sentence_punc_list_out = []
for i in range(0, len(sentence_words_list)):
if i > 0:
if (
len(sentence_words_list[i][0].encode()) == 1
and len(sentence_words_list[i - 1][-1].encode()) == 1
):
sentence_words_list[i] = " " + sentence_words_list[i]
if skip_num < len(cache):
skip_num += 1
else:
words_with_punc.append(sentence_words_list[i])
if skip_num >= len(cache):
sentence_punc_list_out.append(sentence_punc_list[i])
if sentence_punc_list[i] != "_":
words_with_punc.append(sentence_punc_list[i])
sentence_out = "".join(words_with_punc)
sentenceEnd = -1
for i in range(len(sentence_punc_list) - 2, 1, -1):
if sentence_punc_list[i] == "。" or sentence_punc_list[i] == "？":
sentenceEnd = i
break
cache_out = sentence_words_list[sentenceEnd + 1 :]
if sentence_out[-1] in self.punc_list:
sentence_out = sentence_out[:-1]
sentence_punc_list_out[-1] = "_"
param_dict[cache_key] = cache_out
return sentence_out, sentence_punc_list_out, cache_out
def vad_mask(self, size, vad_pos, dtype=np.bool_):
"""Create mask for decoder self-attention.
:param int size: size of mask
:param int vad_pos: index of vad index
:param torch.dtype dtype: result dtype
:rtype: torch.Tensor (B, Lmax, Lmax)
"""
ret = np.ones((size, size), dtype=dtype)
if vad_pos <= 0 or vad_pos >= size:
return ret
sub_corner = np.zeros((vad_pos - 1, size - vad_pos), dtype=dtype)
ret[0 : vad_pos - 1, vad_pos:] = sub_corner
return ret
def infer(
self,
feats: np.ndarray,
feats_len: np.ndarray,
vad_mask: np.ndarray,
sub_masks: np.ndarray,
) -> Tuple[np.ndarray, np.ndarray]:
outputs = self.ort_infer([feats, feats_len, vad_mask, sub_masks])
return outputs
================================================
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/utils/OrtInferSession.py
================================================
# -*- coding:utf-8 -*-
# @FileName :OrtInferSession.py
# @Time :2023/4/13 15:13
# @Author :lovemefan
# @Email :lovemefan@outlook.com
import logging
from pathlib import Path
from typing import List, Union
import numpy as np
from onnxruntime import (
GraphOptimizationLevel,
InferenceSession,
SessionOptions,
get_available_providers,
get_device,
)
class ONNXRuntimeError(Exception):
pass
class OrtInferSession:
def __init__(self, model_file, device_id=-1, intra_op_num_threads=4):
device_id = str(device_id)
sess_opt = SessionOptions()
sess_opt.intra_op_num_threads = intra_op_num_threads
sess_opt.log_severity_level = 4
sess_opt.enable_cpu_mem_arena = False
sess_opt.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_ALL
cuda_ep = "CUDAExecutionProvider"
cuda_provider_options = {
"device_id": device_id,
"arena_extend_strategy": "kNextPowerOfTwo",
"cudnn_conv_algo_search": "EXHAUSTIVE",
"do_copy_in_default_stream": "true",
}
cpu_ep = "CPUExecutionProvider"
cpu_provider_options = {
"arena_extend_strategy": "kSameAsRequested",
}
EP_list = []
if (
device_id != "-1"
and get_device() == "GPU"
and cuda_ep in get_available_providers()
):
EP_list = [(cuda_ep, cuda_provider_options)]
EP_list.append((cpu_ep, cpu_provider_options))
self._verify_model(model_file)
self.session = InferenceSession(
model_file, sess_options=sess_opt, providers=EP_list
)
if device_id != "-1" and cuda_ep not in self.session.get_providers():
logging.warnings.warn(
f"{cuda_ep} is not avaiable for current env, "
f"the inference part is automatically shifted to be executed under {cpu_ep}.\n"
"Please ensure the installed onnxruntime-gpu version matches your cuda and cudnn version, "
"you can check their relations from the offical web site: "
"https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html",
RuntimeWarning,
)
def __call__(
self, input_content: List[Union[np.ndarray, np.ndarray]]
) -> np.ndarray:
input_dict = dict(zip(self.get_input_names(), input_content))
try:
return self.session.run(self.get_output_names(), input_dict)
except Exception as e:
raise ONNXRuntimeError("ONNXRuntime inferece failed.") from e
def get_input_names(
self,
):
return [v.name for v in self.session.get_inputs()]
def get_output_names(
self,
):
return [v.name for v in self.session.get_outputs()]
def get_character_list(self, key: str = "character"):
return self.meta_dict[key].splitlines()
def have_key(self, key: str = "character") -> bool:
self.meta_dict = self.session.get_modelmeta().custom_metadata_map
if key in self.meta_dict.keys():
return True
return False
@staticmethod
def _verify_model(model_path):
model_path = Path(model_path)
if not model_path.exists():
raise FileNotFoundError(f"{model_path} does not exists.")
if not model_path.is_file():
raise FileExistsError(f"{model_path} is not a file.")
================================================
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/utils/text_post_process.py
================================================
# -*- coding:utf-8 -*-
# @FileName :text_post_process.py
# @Time :2023/4/13 15:09
# @Author :lovemefan
# @Email :lovemefan@outlook.com
from pathlib import Path
from typing import Dict, Iterable, List, Union
import numpy as np
import yaml
from typeguard import check_argument_types
class TokenIDConverterError(Exception):
pass
class TokenIDConverter:
def __init__(
self,
token_list: Union[List, str],
):
check_argument_types()
self.token_list = token_list
self.unk_symbol = token_list[-1]
self.token2id = {v: i for i, v in enumerate(self.token_list)}
self.unk_id = self.token2id[self.unk_symbol]
def get_num_vocabulary_size(self) -> int:
return len(self.token_list)
def ids2tokens(self, integers: Union[np.ndarray, Iterable[int]]) -> List[str]:
if isinstance(integers, np.ndarray) and integers.ndim != 1:
raise TokenIDConverterError(
f"Must be 1 dim ndarray, but got {integers.ndim}"
)
return [self.token_list[i] for i in integers]
def tokens2ids(self, tokens: Iterable[str]) -> List[int]:
return [self.token2id.get(i, self.unk_id) for i in tokens]
def split_to_mini_sentence(words: list, word_limit: int = 20):
assert word_limit > 1
if len(words) <= word_limit:
return [words]
sentences = []
length = len(words)
sentence_len = length // word_limit
for i in range(sentence_len):
sentences.append(words[i * word_limit : (i + 1) * word_limit])
if length % word_limit > 0:
sentences.append(words[sentence_len * word_limit :])
return sentences
def code_mix_split_words(text: str):
words = []
segs = text.split()
for seg in segs:
# There is no space in seg.
current_word = ""
for c in seg:
if len(c.encode()) == 1:
# This is an ASCII char.
current_word += c
else:
# This is a Chinese char.
if len(current_word) > 0:
words.append(current_word)
current_word = ""
words.append(c)
if len(current_word) > 0:
words.append(current_word)
return words
def read_yaml(yaml_path: Union[str, Path]) -> Dict:
if not Path(yaml_path).exists():
raise FileExistsError(f"The {yaml_path} does not exist.")
with open(str(yaml_path), "rb") as f:
data = yaml.load(f, Loader=yaml.Loader)
return data
================================================
FILE: backend/CT-Transformer-punctuation/setup.py
================================================
# -*- coding:utf-8 -*-
# @FileName :setup.py
# @Time :2023/4/4 11:22
# @Author :lovemefan
# @Email :lovemefan@outlook.com
import os
from pathlib import Path
from setuptools import find_namespace_packages, setup
dirname = Path(os.path.dirname(__file__))
version_file = dirname / "version.txt"
with open(version_file, "r") as f:
version = f.read().strip()
requirements = {
"install": [
"setuptools<=65.0",
"PyYAML",
"typeguard==2.13.3",
"onnxruntime>=1.14.1",
],
"setup": [
"numpy==1.24.2",
],
"all": [],
}
requirements["all"].extend(requirements["install"])
install_requires = requirements["install"]
setup_requires = requirements["setup"]
setup(
name="cttpunctuator",
version=version,
url="https://github.com/lovemefan/CT-Transformer-punctuation",
author="Lovemefan, Yunnan Key Laboratory of Artificial Intelligence, "
"Kunming University of Science and Technology, Kunming, Yunnan ",
author_email="lovemefan@outlook.com",
description="ctt-punctuator: A enterprise-grade punctuator after chinese asr based "
"on ct-transformer from funasr opensource",
long_description=open(os.path.join(dirname, "README.md"), encoding="utf-8").read(),
long_description_content_type="text/markdown",
license="The MIT License",
packages=find_namespace_packages(),
include_package_data=True,
install_requires=install_requires,
python_requires=">=3.7.0",
classifiers=[
"Programming Language :: Python",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Science/Research",
"Operating System :: POSIX :: Linux",
"License :: OSI Approved :: Apache Software License",
"Topic :: Multimedia :: Sound/Audio :: Speech",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development :: Libraries :: Python Modules",
],
)
================================================
FILE: backend/CT-Transformer-punctuation/test/test.py
================================================
# -*- coding:utf-8 -*-
# @FileName :test.py.py
# @Time :2023/4/19 13:39
# @Author :lovemefan
# @Email :lovemefan@outlook.com
import logging
from cttPunctuator import CttPunctuator
logging.basicConfig(
level=logging.INFO,
format="[%(asctime)s %(levelname)s] [%(filename)s:%(lineno)d %(module)s.%(funcName)s] %(message)s",
)
# offline mode
punc = CttPunctuator()
text = "据报道纽约时报使用ChatGPT创建了一个情人节消息生成器用户只需输入几个提示就可以得到一封自动生成的情书"
logging.info(punc.punctuate(text)[0])
# online mode
punc = CttPunctuator(online=True)
text_in = (
"跨境河流是养育沿岸|人民的生命之源长期以来为帮助下游地区防灾减灾中方技术人员|"
"在上游地区极为恶劣的自然条件下克服巨大困难甚至冒着生命危险|"
"向印方提供汛期水文资料处理紧急事件中方重视印方在跨境河流>问题上的关切|"
"愿意进一步完善双方联合工作机制|凡是|中方能做的我们|"
"都会去做而且会做得更好我请印度朋友们放心中国在上游的|"
"任何开发利用都会经过科学|规划和论证兼顾上下游的利益"
)
vads = text_in.split("|")
rec_result_all = ""
for vad in vads:
result = punc.punctuate(vad)
rec_result_all += result[0]
logging.info(f"Part: {rec_result_all}")
logging.info(f"Final: {rec_result_all}")
================================================
FILE: backend/CT-Transformer-punctuation/test/test2.py
================================================
from cttPunctuator import CttPunctuator
import logging
logging.basicConfig(
level=logging.INFO,
format="[%(asctime)s %(levelname)s] [%(filename)s:%(lineno)d %(module)s.%(funcName)s] %(message)s",
)
# offline mode
punc = CttPunctuator()
text = "据报道纽约时报使用ChatGPT创建了一个情人节消息生成器用户只需输入几个提示就可以得到一封自动生成的情书"
logging.info(punc.punctuate(text)[0])
# online mode
punc = CttPunctuator(online=True)
text_in = "跨境河流是养育沿岸|人民的生命之源长期以来为帮助下游地区防灾减灾中方技术人员|在上游地区极为恶劣的自然条件下克服巨大困难甚至冒着生命危险|向印方提供汛期水文资料处理紧急事件中方重视印方在跨境河流>问题上的关切|愿意进一步完善双方联合工作机制|凡是|中方能做的我们|都会去做而且会做得更好我请印度朋友们放心中国在上游的|任何开发利用都会经过科学|规划和论证兼顾上下游的利益"
vads = text_in.split("|")
rec_result_all = ""
param_dict = {"cache": []}
for vad in vads:
result = punc.punctuate(vad, param_dict=param_dict)
rec_result_all += result[0]
logging.info(f"Part: {rec_result_all}")
logging.info(f"Final: {rec_result_all}")
================================================
FILE: backend/CT-Transformer-punctuation/version.txt
================================================
0.0.3
================================================
FILE: backend/build_onefile.bat
================================================
@echo off
REM Optimized Build Script for SayKey using PyInstaller on Windows 11
REM Set the path to your virtual environment
set VENV_PATH=.\venv
REM Activate the virtual environment
call %VENV_PATH%\Scripts\activate.bat
REM Check if activation was successful
if %errorlevel% neq 0 (
echo Failed to activate the virtual environment. Please check the path and try again.
exit /b 1
)
REM Ensure Python and pip are available
where python >nul 2>nul
if %errorlevel% neq 0 (
echo Python is not available in the activated environment. Please check your virtual environment setup.
exit /b 1
)
REM Install special dependencies
echo Installing special dependencies...
cd CT-Transformer-punctuation
pip install -e .
cd ..
pip install -r requirements.txt
REM Install PyInstaller
pip install pyinstaller
REM Ensure UPX is available
where upx >nul 2>nul
if %errorlevel% neq 0 (
echo UPX is not available. Please install UPX and ensure it is in your PATH.
exit /b 1
)
REM Create the .spec file for PyInstaller
echo Creating .spec file...
pyi-makespec --onefile --name SayKey-server ^
--hidden-import=sherpa_onnx ^
--hidden-import=cttpunctuator ^
main.py
REM Build the executable using UPX
echo Building executable...
pyinstaller --clean SayKey-server.spec
REM Check if build was successful
if exist "dist\SayKey-server.exe" (
echo Build successful! Executable is located at dist\SayKey-server.exe
REM Copy specific folders to the executable directory
echo Copying necessary folders to the executable directory...
mkdir "dist\sherpa-onnx"
copy "sherpa-onnx\model.int8.onnx" "dist\sherpa-onnx\"
copy "sherpa-onnx\tokens.txt" "dist\sherpa-onnx\"
mkdir "dist\punc-onnx"
copy "punc-onnx\configuration.json" "dist\punc-onnx\"
copy "punc-onnx\punc.bin" "dist\punc-onnx\"
copy "punc-onnx\punc.onnx" "dist\punc-onnx\"
echo Build process completed. Necessary files have been copied to the executable directory.
) else (
echo Build failed. Please check the error messages above.
)
REM Deactivate the virtual environment
deactivate
pause
================================================
FILE: backend/main.py
================================================
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Author: WenJing Wu
import argparse
import asyncio
import os
import wave
from datetime import datetime
from typing import Optional, List, Dict, Any
import pyautogui
import pyperclip
import keyboard
import numpy as np
import sounddevice as sd
from loguru import logger
import sherpa_onnx
from cttPunctuator import CttPunctuator
from fastapi import FastAPI
from pydantic import BaseModel
import uvicorn
# Constants
SAMPLE_RATE = 16000 # Fixed sample rate
def type_text(text: str) -> None:
"""Type the given text"""
logger.info(f"recognized text: {text}")
# if is_text_input_focused():
pyperclip.copy(text)
pyautogui.hotkey('ctrl', 'v', interval=0.05)
# else:
# logger.warning("No active text input field detected.")
# logger.warning("Please ensure the cursor is in the desired input location.")
async def save_audio_async(samples: np.ndarray, sample_rate: int, file_path: str) -> None:
"""Asynchronously save audio samples to a WAV file."""
await asyncio.to_thread(save_audio, samples, sample_rate, file_path)
def save_audio(samples: np.ndarray, sample_rate: int, file_path: str) -> None:
"""Save audio samples to a WAV file."""
try:
with wave.open(file_path, 'wb') as wf:
wf.setnchannels(1)
wf.setsampwidth(2) # 16-bit audio
wf.setframerate(sample_rate)
wf.writeframes((samples * 32767).astype(np.int16).tobytes())
except Exception as e:
logger.error(f"Error saving audio file: {e}")
async def process_audio_async(
recognizer: sherpa_onnx.OfflineRecognizer,
audio: np.ndarray,
sample_rate: int,
punctuator: CttPunctuator,
) -> None:
"""Asynchronously process audio and perform speech recognition."""
text = await asyncio.to_thread(process_audio, recognizer, audio, sample_rate)
if text:
text = await asyncio.to_thread(add_punctuation, punctuator, text)
await asyncio.to_thread(type_text, text)
else:
logger.warning("No speech recognized.")
def process_audio(
recognizer: sherpa_onnx.OfflineRecognizer, audio: np.ndarray, sample_rate: int
) -> Optional[str]:
"""Process audio and perform speech recognition."""
asr_stream = recognizer.create_stream()
asr_stream.accept_waveform(sample_rate, audio)
recognizer.decode_stream(asr_stream)
return asr_stream.result.text.strip()
def add_punctuation(punctuator: CttPunctuator, text: str) -> str:
"""Add punctuation to the given text."""
return punctuator.punctuate(text)[0]
def ensure_data_directory() -> None:
"""Ensure the data directory exists."""
data_dir = "./data"
os.makedirs(data_dir, exist_ok=True)
print(f"Data directory ensured at: {data_dir}")
def is_device_usable(device_index):
try:
sd.check_input_settings(device=device_index)
return True
except Exception:
return False
def create_recognizer(args: argparse.Namespace) -> sherpa_onnx.OfflineRecognizer:
"""Create the speech recognizer."""
return sherpa_onnx.OfflineRecognizer.from_sense_voice(
model=args.sense_voice,
tokens=args.tokens,
num_threads=args.num_threads,
use_itn=False,
debug=False,
)
def get_args() -> argparse.Namespace:
"""Parse command-line arguments."""
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--tokens", type=str, required=True, help="Path to tokens.txt")
parser.add_argument(
"--sense-voice", type=str, required=True, help="Path to the model.onnx from SenseVoice"
)
parser.add_argument(
"--num-threads",
type=int,
default=4,
help="Number of threads for neural network computation",
)
parser.add_argument(
"--microphone-index", type=int, help="Index of the microphone to use (optional)"
)
parser.add_argument(
"--hotkey",
type=str,
default="ctrl+q",
help="""\
Hotkey combination to start recording. Examples:
- For Ctrl+Q: use 'ctrl+q'
- For Alt+S: use 'alt+s'
- For Ctrl+CapsLock: use 'ctrl+caps lock'
""",
)
parser.add_argument(
"--api-port",
type=int,
default=58652,
help="Port number for the API server",
)
parser.add_argument(
"--punc-model-dir",
type=str,
default="./punc-onnx",
help="dir of the punctuation model files (default: current directory ./punc-onnx)",
)
parser.add_argument(
"--host",
type=str,
default="localhost",
help="Host to bind the API server (default: localhost)",
)
return parser.parse_args()
class Configurations:
"""Class to hold configuration settings."""
def __init__(self, hotkey: str, microphone_index: Optional[int]):
self.hotkey = hotkey
self.microphone_index = microphone_index
class DeviceIndex(BaseModel):
index: int
class Hotkey(BaseModel):
hotkey: str
app = FastAPI()
configurations = Configurations(hotkey="ctrl+q", microphone_index=None)
@app.get("/ping")
async def ping():
"""Keep-alive endpoint."""
return {"status": "alive"}
@app.get("/list_audio_devices")
async def list_audio_devices_api() -> Dict[str, List[Dict[str, Any]]]:
"""List available audio devices."""
devices = sd.query_devices()
hostapis = sd.query_hostapis()
current_device = sd.default.device[0]
device_list = []
for i, d in enumerate(devices):
# Get the host API name for the device
hostapi_name = hostapis[d['hostapi']]['name']
# Check if this is the current device
is_current_device = i == current_device
# Only consider devices using Windows WASAPI or the current device
if (hostapi_name == 'Windows WASAPI' and d['max_input_channels'] > 0 and is_device_usable(
i)) or is_current_device:
device_list.append({
"index": i,
"name": d["name"],
"is_current": is_current_device
})
return {"devices": device_list}
@app.post("/set_audio_device")
async def set_audio_device(device: DeviceIndex):
"""Set microphone device."""
try:
# Optionally, ensure the device uses Windows WASAPI
devices = sd.query_devices()
hostapis = sd.query_hostapis()
d = devices[device.index]
hostapi_name = hostapis[d['hostapi']]['name']
if hostapi_name != 'Windows WASAPI':
raise ValueError("Selected device is not using Windows WASAPI.")
# Set the default input device
sd.default.device[0] = device.index
device_name = d['name']
configurations.microphone_index = device.index
logger.info(f"Microphone set to: {device_name}")
return {
"status": "success",
"message": "success",
"device": {
"index": device.index,
"name": device_name
}
}
except Exception as e:
logger.error(f"Error setting microphone: {e}")
return {
"status": "error",
"message": str(e),
"device": {
"index": configurations.microphone_index,
"name": sd.query_devices()[configurations.microphone_index]['name']
if configurations.microphone_index is not None else "Not set"
}
}
@app.post("/set_hotkey")
async def set_hotkey_api(hotkey: Hotkey):
"""Set hotkey."""
try:
# Validate hotkey
if not hotkey.hotkey or not keyboard.parse_hotkey(hotkey.hotkey):
raise ValueError("Invalid hotkey combination")
old_hotkey = configurations.hotkey
configurations.hotkey = hotkey.hotkey
logger.info(f"Hotkey set to: {configurations.hotkey}")
return {
"status": "success",
"message": "success",
"hotkey": configurations.hotkey
}
except Exception as e:
logger.error(f"Error setting hotkey: {e}")
return {
"status": "error",
"message": str(e),
"hotkey": configurations.hotkey # Return current hotkey
}
@app.get("/get_hotkey")
async def get_hotkey_api():
"""Get the current hotkey."""
return {"hotkey": configurations.hotkey}
async def main() -> None:
"""Main function to run the SayKey program."""
args = get_args()
# 初始化配置
configurations.hotkey = args.hotkey
configurations.microphone_index = args.microphone_index
ensure_data_directory()
# list_audio_devices()
# set_microphone(configurations.microphone_index)
punctuator = CttPunctuator(model_dir=args.punc_model_dir)
print(
f"\033[32mSayKey is running. Hold {configurations.hotkey} to start recording, release to recognize.\033[0m"
)
print("Important: Ensure the cursor is in the desired input location before using voice typing.")
recognizer = create_recognizer(args)
# This queue will hold the audio data to be processed
audio_queue = asyncio.Queue()
async def audio_processing_worker():
while True:
item = await audio_queue.get()
if item is None:
break # Exit signal
audio_data, timestamp = item
logger.info(f"Processing audio recorded at {timestamp}")
# Save audio asynchronously
original_audio_file = f"./data/{timestamp}.wav"
await save_audio_async(audio_data, SAMPLE_RATE, original_audio_file)
# Process audio
await process_audio_async(recognizer, audio_data, SAMPLE_RATE, punctuator)
audio_queue.task_done()
# Start the audio processing worker task
processing_task = asyncio.create_task(audio_processing_worker())
recording_event = asyncio.Event()
audio_buffer = []
def callback(indata, frames, time_info, status):
"""Callback function for audio input stream."""
if recording_event.is_set():
audio_buffer.extend(indata.copy())
async def monitor_hotkey():
"""Monitor the hotkey and manage recording."""
nonlocal audio_buffer
while True:
await asyncio.sleep(0.01)
if keyboard.is_pressed(configurations.hotkey):
if not recording_event.is_set():
logger.info("Recording started.")
recording_event.set()
audio_buffer = []
else:
if recording_event.is_set():
logger.info("Recording ended, adding to processing queue.")
recording_event.clear()
buffer = np.concatenate(audio_buffer)
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
await audio_queue.put((buffer, timestamp))
async def run_input_stream():
"""Run the audio input stream."""
try:
with sd.InputStream(
channels=1,
dtype="float32",
samplerate=SAMPLE_RATE,
callback=callback,
device=configurations.microphone_index,
):
while True:
await asyncio.sleep(1)
except Exception as e:
logger.error(f"Error in input stream: {e}")
raise e
async def start_server():
"""Start the FastAPI server."""
config = uvicorn.Config(app, host=args.host, port=args.api_port, log_level="info", loop="asyncio")
server = uvicorn.Server(config)
await server.serve()
tasks = [
asyncio.create_task(monitor_hotkey()),
asyncio.create_task(run_input_stream()),
asyncio.create_task(start_server()),
]
try:
await asyncio.gather(*tasks)
except KeyboardInterrupt:
logger.info("Program interrupted by user.")
except Exception as e:
logger.error(f"Error running the program: {e}")
finally:
await audio_queue.put(None)
await processing_task
await audio_queue.join()
if __name__ == "__main__":
asyncio.run(main())
================================================
FILE: backend/punc-onnx/configuration.json
================================================
{
"framework": "onnx",
"task" : "punctuation",
"model" : {
"type" : "generic-punc",
"punc_model_name" : "punc.pb",
"punc_model_config" : {
"type": "pytorch",
"code_base": "funasr",
"mode": "punc",
"lang": "zh-cn",
"batch_size": 1,
"punc_config": "punc.yaml",
"model": "damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
}
},
"pipeline": {
"type":"punc-inference"
}
}
================================================
FILE: backend/punc-onnx/punc.onnx
================================================
version https://git-lfs.github.com/spec/v1
oid sha256:ed5318d91ff9520a03a5b5a8dba264b76858931db7d914b0de6ec9e4ad35970e
size 292001778
================================================
FILE: backend/readme.md
================================================
### Init
```bash
cd ./backend
cd CT-Transformer-punctuation
pip install -e .
pip install -r requirements.txt
# Start it
python main.py --sense-voice=./sherpa-onnx/model.int8.onnx --tokens=./sherpa-onnx/tokens.txt
```
### Command Line Options
Start the server part with these options:
```bash
python main.py --sense-voice=./sherpa-onnx/model.int8.onnx --tokens=./sherpa-onnx/tokens.txt
```
You must include:
- `--tokens`: Where the tokens.txt file is
- `--sense-voice`: Where the model.onnx file for SenseVoice is
You can also add:
- `--num-threads`: How many threads to use (usually 4)
- `--microphone-index`: Which microphone to use
- `--hotkey`: Which key to press to start (usually ctrl+q)
- `--api-port`: Which port number to use (usually 58652)
- `--punc-model-dir`: Where the punctuation files are (usually ./punc-onnx)
- `--host`: Which address to use (usually localhost)
### Starting the Server
When you start the server, you'll see:
```
SayKey is running. Hold ctrl+q to start recording, release to recognize.
Important: Make sure your cursor is where you want to type before using voice typing.
INFO: Uvicorn running on http://localhost:58652 (Press CTRL+C to quit)
```
To use it, hold `ctrl+q`, speak, then let go of `ctrl+q`.
================================================
FILE: backend/requirements.txt
================================================
altgraph==0.17.4
annotated-types==0.7.0
anyio==4.6.0
certifi==2024.8.30
cffi==1.17.1
charset-normalizer==3.4.0
click==8.1.7
colorama==0.4.6
coloredlogs==15.0.1
-e ./CT-Transformer-punctuation
exceptiongroup==1.2.2
fastapi==0.115.0
flatbuffers==24.3.25
gevent==24.10.2
greenlet==3.1.1
h11==0.14.0
httptools==0.6.1
humanfriendly==10.0
idna==3.10
keyboard==0.13.5
loguru==0.7.2
MouseInfo==0.1.3
mpmath==1.3.0
numpy==2.1.2
onnxruntime==1.19.2
packaging==24.1
pefile==2024.8.26
pillow==11.0.0
protobuf==5.28.2
PyAutoGUI==0.9.54
pycparser==2.22
pydantic==2.9.2
pydantic_core==2.23.4
PyGetWindow==0.0.9
pyinstaller==6.10.0
pyinstaller-hooks-contrib==2024.8
PyMsgBox==1.0.9
pyperclip==1.9.0
pyreadline3==3.5.4
PyRect==0.2.0
PyScreeze==1.0.1
python-dotenv==1.0.1
pytweening==1.2.0
pywin32-ctypes==0.2.3
PyYAML==6.0.2
requests==2.32.3
sherpa-onnx==1.10.27
sniffio==1.3.1
sounddevice==0.5.0
soundfile==0.12.1
starlette==0.38.6
sympy==1.13.3
typeguard==2.13.3
typing_extensions==4.12.2
urllib3==2.2.3
uvicorn==0.31.1
watchfiles==0.24.0
websocket-client==1.8.0
websockets==13.1
win32-setctime==1.1.0
zope.event==5.0
zope.interface==7.1.0
================================================
FILE: backend/requirements_test.txt
================================================
altgraph==0.17.4
annotated-types==0.7.0
anyio==4.6.0
================================================
FILE: backend/sherpa-onnx/model.int8.onnx
================================================
version https://git-lfs.github.com/spec/v1
oid sha256:c71f0ce00bec95b07744e116345e33d8cbbe08cef896382cf907bf4b51a2cd51
size 239233841
================================================
FILE: backend/sherpa-onnx/tokens.txt
================================================
<unk> 0
<s> 1
</s> 2
▁the 3
s 4
▁to 5
▁and 6
▁of 7
▁a 8
' 9
▁in 10
▁I 11
▁that 12
▁is 13
▁you 14
▁it 15
t 16
▁for 17
▁we 18
▁was 19
▁with 20
▁on 21
ing 22
▁be 23
▁are 24
▁have 25
ed 26
d 27
▁as 28
▁this 29
▁not 30
▁our 31
▁at 32
▁your 33
▁can 34
▁from 35
▁The 36
▁or 37
▁will 38
▁but 39
▁he 40
▁one 41
▁an 42
re 43
▁my 44
▁by 45
▁his 46
▁all 47
▁they 48
ly 49
▁had 50
▁her 51
▁me 52
▁more 53
I 54
▁were 55
▁about 56
▁out 57
▁do 58
▁so 59
▁up 60
m 61
▁has 62
▁what 63
y 64
▁there 65
▁time 66
▁would 67
The 68
▁like 69
▁their 70
er 71
▁It 72
▁been 73
▁just 74
▁if 75
▁them 76
▁some 77
▁which 78
▁We 79
▁she 80
▁He 81
ve 82
▁also 83
▁when 84
▁two 85
▁into 86
▁no 87
▁other 88
▁get 89
▁over 90
ll 91
▁him 92
▁us 93
n 94
▁And 95
▁know 96
▁think 97
▁who 98
al 99
▁could 100
▁see 101
▁than 102
▁A 103
▁very 104
▁don 105
▁back 106
▁how 107
e 108
▁people 109
▁new 110
▁these 111
▁But 112
r 113
▁make 114
▁any 115
▁first 116
We 117
▁then 118
▁only 119
▁now 120
▁way 121
in 122
▁You 123
▁ 124
▁In 125
▁year 126
▁want 127
▁good 128
▁This 129
▁well 130
▁need 131
▁going 132
▁may 133
▁work 134
es 135
▁because 136
▁much 137
▁even 138
▁through 139
▁She 140
▁where 141
▁go 142
▁down 143
▁So 144
It 145
A 146
▁right 147
▁really 148
▁those 149
▁most 150
▁should 151
a 152
In 153
▁three 154
▁did 155
▁take 156
▁many 157
▁re 158
▁twenty 159
▁here 160
▁business 161
▁use 162
▁still 163
▁after 164
▁too 165
▁If 166
▁before 167
▁made 168
or 169
▁They 170
▁look 171
▁years 172
▁around 173
▁point 174
ers 175
And 176
▁being 177
▁day 178
▁hundred 179
▁last 180
▁little 181
▁didn 182
▁five 183
▁said 184
▁something 185
▁off 186
▁things 187
▁such 188
This 189
▁same 190
▁help 191
▁life 192
S 193
▁both 194
▁different 195
ic 196
o 197
▁find 198
▁never 199
▁each 200
▁got 201
He 202
▁quarter 203
▁come 204
l 205
▁lot 206
▁say 207
▁own 208
▁its 209
▁four 210
▁That 211
▁long 212
▁un 213
▁again 214
▁great 215
▁used 216
▁end 217
▁S 218
▁There 219
▁few 220
▁better 221
▁always 222
▁part 223
▁while 224
▁might 225
But 226
▁home 227
▁best 228
▁between 229
▁am 230
le 231
ation 232
▁every 233
▁world 234
If 235
T 236
it 237
▁feel 238
▁love 239
▁place 240
an 241
C 242
▁next 243
▁market 244
able 245
▁B 246
ion 247
▁does 248
▁s 249
g 250
P 251
▁number 252
▁found 253
▁another 254
▁growth 255
▁second 256
▁believe 257
▁thing 258
You 259
▁away 260
▁put 261
▁continue 262
c 263
▁must 264
ity 265
▁results 266
▁give 267
ar 268
▁under 269
on 270
il 271
▁sure 272
▁thought 273
▁head 274
▁hand 275
▁important 276
▁thousand 277
▁man 278
▁For 279
▁without 280
So 281
▁data 282
▁T 283
▁keep 284
▁call 285
▁able 286
▁As 287
▁company 288
▁information 289
▁bit 290
▁de 291
▁What 292
M 293
▁let 294
▁why 295
▁E 296
▁during 297
D 298
▁case 299
i 300
▁high 301
▁six 302
▁kind 303
▁When 304
▁change 305
▁course 306
▁nineteen 307
▁team 308
▁start 309
p 310
and 311
F 312
▁set 313
▁though 314
As 315
el 316
B 317
▁done 318
▁hard 319
▁using 320
▁against 321
▁small 322
E 323
▁system 324
▁left 325
▁doing 326
th 327
▁face 328
▁side 329
▁water 330
▁enough 331
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▁F 334
ch 335
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▁fact 337
▁looking 338
▁car 339
▁since 340
en 341
▁went 342
ra 343
ent 344
▁took 345
L 346
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▁room 348
▁ten 349
▁today 350
▁doesn 351
ment 352
▁process 353
▁non 354
▁line 355
▁No 356
▁past 357
▁D 358
▁far 359
ness 360
▁family 361
▁big 362
▁looked 363
▁show 364
ur 365
▁already 366
▁support 367
▁anything 368
▁experience 369
▁until 370
▁My 371
▁eight 372
▁tell 373
▁making 374
▁strong 375
▁open 376
▁actually 377
▁provide 378
▁play 379
▁working 380
▁seven 381
▁seen 382
▁game 383
G 384
▁care 385
▁across 386
▁real 387
She 388
▁expect 389
h 390
▁eyes 391
▁customers 392
▁wanted 393
▁future 394
▁mean 395
▁less 396
▁value 397
They 398
ri 399
us 400
▁together 401
▁night 402
at 403
▁free 404
▁money 405
▁ever 406
▁C 407
est 408
▁G 409
k 410
▁full 411
te 412
▁con 413
▁e 414
▁getting 415
▁level 416
ive 417
▁days 418
▁question 419
is 420
▁within 421
as 422
▁To 423
▁wasn 424
▁percent 425
▁mind 426
man 427
▁house 428
ry 429
O 430
▁power 431
▁large 432
▁try 433
▁top 434
▁understand 435
▁having 436
▁study 437
▁several 438
lo 439
▁everything 440
ro 441
▁P 442
▁cost 443
to 444
▁nothing 445
ies 446
▁light 447
▁run 448
▁forward 449
▁won 450
ter 451
▁saw 452
▁pre 453
▁started 454
▁service 455
▁possible 456
▁often 457
▁once 458
▁control 459
▁body 460
▁knew 461
▁product 462
▁felt 463
▁problem 464
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Well 1910
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By 1952
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▁Friday 2896
▁input 2897
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▁sports 2900
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▁deposit 2902
▁self 2903
house 2904
▁deserve 2905
▁February 2906
▁judgment 2907
▁rights 2908
ered 2909
▁silence 2910
mate 2911
▁log 2912
▁item 2913
▁leads 2914
▁friendly 2915
ax 2916
▁feed 2917
▁selected 2918
▁tail 2919
▁sufficient 2920
bar 2921
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▁cream 2923
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room 2925
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▁teeth 2927
▁extent 2928
▁achieved 2929
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▁boys 2931
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▁proposed 2934
▁encourage 2935
▁Canada 2936
▁circle 2937
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▁rent 2939
▁plastic 2940
▁asset 2941
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▁facility 2944
▁outcome 2945
▁paint 2946
▁debate 2947
▁desk 2948
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▁participants 2952
▁manager 2953
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▁panel 2956
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▁joy 2962
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▁row 2966
▁meat 2967
▁concerns 2968
▁names 2969
▁suggested 2970
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▁thanks 2972
ties 2973
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▁matters 2975
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▁communities 3014
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▁facilities 3033
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▁investors 3092
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▁forms 3120
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▁database 3166
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uring 3206
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▁conclude 3218
▁pages 3219
▁plane 3220
ets 3221
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vent 3239
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Con 3246
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▁aspects 3249
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▁Israel 3252
▁consumers 3253
▁proof 3254
▁accepted 3255
▁improvements 3256
▁revealed 3257
▁decades 3258
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▁owner 3260
lk 3261
▁react 3262
▁ratio 3263
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▁association 3267
▁craft 3268
▁description 3269
▁format 3270
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Thank 3272
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▁blame 3274
▁compare 3275
▁tall 3276
▁bread 3277
▁Texas 3278
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rie 3282
▁parameters 3283
▁School 3284
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▁bodies 3287
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▁Russia 3292
▁evolution 3293
▁ph 3294
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▁colors 3298
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Ma 3307
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ister 3312
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ung 3314
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▁script 3332
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▁senior 3334
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▁guarantee 3368
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Don 3378
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▁Japan 3394
▁shoes 3395
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▁blind 3397
ette 3398
load 3399
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day 3402
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▁Africa 3404
▁trick 3405
lam 3406
▁Comp 3407
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▁deals 3409
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▁advertising 3411
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read 3413
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nes 3418
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▁Congress 3422
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Ex 3469
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ied 3474
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ising 3514
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ump 3517
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ka 3520
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▁savings 3530
▁technologies 3531
▁Green 3532
▁skill 3533
▁religion 3534
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cept 3538
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▁album 3541
▁compete 3542
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▁Everyone 3544
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▁Peter 3546
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rac 3577
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▁somebody 3582
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dding 3584
▁comm 3585
▁fields 3586
▁Cr 3587
▁mechanism 3588
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▁domestic 3591
vol 3592
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ale 3594
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▁drawing 3610
▁cultural 3611
▁origin 3612
▁Art 3613
phy 3614
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▁famous 3619
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▁Does 3624
▁owners 3625
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According 3627
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▁objects 3629
▁facts 3630
▁agency 3631
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▁officers 3635
▁reform 3636
▁charges 3637
▁outcomes 3638
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▁practices 3643
gra 3644
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pers 3692
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Build 6362
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Take 6410
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Car 6540
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Ho 6745
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Everyone 7499
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Turning 7555
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Meanwhile 7595
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Add 7684
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Beyond 7743
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Right 7763
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Everything 7834
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Specifically 7873
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Nothing 7991
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Remember 8037
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Several 8203
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Ultimately 8224
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gitextract_j4dfeo4j/ ├── .gitattributes ├── .gitignore ├── LICENSE.txt ├── backend/ │ ├── .gitignore │ ├── CT-Transformer-punctuation/ │ │ ├── .flake8 │ │ ├── .gitignore │ │ ├── LICENSE │ │ ├── MANIFEST.in │ │ ├── README.md │ │ ├── cttPunctuator.py │ │ ├── cttpunctuator/ │ │ │ ├── __init__.py │ │ │ └── src/ │ │ │ ├── onnx/ │ │ │ │ └── configuration.json │ │ │ ├── punctuator.py │ │ │ └── utils/ │ │ │ ├── OrtInferSession.py │ │ │ └── text_post_process.py │ │ ├── setup.py │ │ ├── test/ │ │ │ ├── test.py │ │ │ └── test2.py │ │ └── version.txt │ ├── build_onefile.bat │ ├── main.py │ ├── punc-onnx/ │ │ ├── configuration.json │ │ └── punc.onnx │ ├── readme.md │ ├── requirements.txt │ ├── requirements_test.txt │ ├── sherpa-onnx/ │ │ ├── model.int8.onnx │ │ └── tokens.txt │ └── test_api.py ├── frontend/ │ ├── .gitignore │ ├── components.json │ ├── index.html │ ├── package.json │ ├── postcss.config.js │ ├── readme.md │ ├── src/ │ │ ├── VoiceRecognitionIcon.tsx │ │ ├── components/ │ │ │ └── ui/ │ │ │ ├── badge.tsx │ │ │ ├── button.tsx │ │ │ ├── card.tsx │ │ │ ├── hover-card.tsx │ │ │ ├── scroll-area.tsx │ │ │ ├── tabs.tsx │ │ │ └── tooltip.tsx │ │ ├── favicon/ │ │ │ └── site.webmanifest │ │ ├── globals.css │ │ ├── i18n.ts │ │ ├── index.html │ │ ├── lib/ │ │ │ └── utils.ts │ │ ├── log.html │ │ ├── main.ts │ │ ├── preload.ts │ │ ├── renderer.tsx │ │ └── styles.css │ ├── tailwind.config.js │ ├── tsconfig.json │ └── webpack.config.js ├── readme.md └── readme_zh.md
SYMBOL INDEX (94 symbols across 14 files)
FILE: backend/CT-Transformer-punctuation/cttPunctuator.py
class CttPunctuator (line 27) | class CttPunctuator:
method __init__ (line 31) | def __init__(self, online: bool = False, model_dir: str = None):
method punctuate (line 61) | def punctuate(self, text: str, param_dict=None):
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/punctuator.py
class CT_Transformer (line 17) | class CT_Transformer:
method __init__ (line 25) | def __init__(
method __call__ (line 59) | def __call__(self, text: Union[list, str], split_size=20):
method infer (line 146) | def infer(
class CT_Transformer_VadRealtime (line 153) | class CT_Transformer_VadRealtime(CT_Transformer):
method __init__ (line 161) | def __init__(
method __call__ (line 173) | def __call__(self, text: str, param_dict: map, split_size=20):
method vad_mask (line 289) | def vad_mask(self, size, vad_pos, dtype=np.bool_):
method infer (line 304) | def infer(
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/utils/OrtInferSession.py
class ONNXRuntimeError (line 20) | class ONNXRuntimeError(Exception):
class OrtInferSession (line 24) | class OrtInferSession:
method __init__ (line 25) | def __init__(self, model_file, device_id=-1, intra_op_num_threads=4):
method __call__ (line 69) | def __call__(
method get_input_names (line 78) | def get_input_names(
method get_output_names (line 83) | def get_output_names(
method get_character_list (line 88) | def get_character_list(self, key: str = "character"):
method have_key (line 91) | def have_key(self, key: str = "character") -> bool:
method _verify_model (line 98) | def _verify_model(model_path):
FILE: backend/CT-Transformer-punctuation/cttpunctuator/src/utils/text_post_process.py
class TokenIDConverterError (line 14) | class TokenIDConverterError(Exception):
class TokenIDConverter (line 18) | class TokenIDConverter:
method __init__ (line 19) | def __init__(
method get_num_vocabulary_size (line 30) | def get_num_vocabulary_size(self) -> int:
method ids2tokens (line 33) | def ids2tokens(self, integers: Union[np.ndarray, Iterable[int]]) -> Li...
method tokens2ids (line 40) | def tokens2ids(self, tokens: Iterable[str]) -> List[int]:
function split_to_mini_sentence (line 44) | def split_to_mini_sentence(words: list, word_limit: int = 20):
function code_mix_split_words (line 58) | def code_mix_split_words(text: str):
function read_yaml (line 79) | def read_yaml(yaml_path: Union[str, Path]) -> Dict:
FILE: backend/main.py
function type_text (line 29) | def type_text(text: str) -> None:
function save_audio_async (line 40) | async def save_audio_async(samples: np.ndarray, sample_rate: int, file_p...
function save_audio (line 45) | def save_audio(samples: np.ndarray, sample_rate: int, file_path: str) ->...
function process_audio_async (line 57) | async def process_audio_async(
function process_audio (line 72) | def process_audio(
function add_punctuation (line 82) | def add_punctuation(punctuator: CttPunctuator, text: str) -> str:
function ensure_data_directory (line 87) | def ensure_data_directory() -> None:
function is_device_usable (line 94) | def is_device_usable(device_index):
function create_recognizer (line 102) | def create_recognizer(args: argparse.Namespace) -> sherpa_onnx.OfflineRe...
function get_args (line 113) | def get_args() -> argparse.Namespace:
class Configurations (line 161) | class Configurations:
method __init__ (line 164) | def __init__(self, hotkey: str, microphone_index: Optional[int]):
class DeviceIndex (line 169) | class DeviceIndex(BaseModel):
class Hotkey (line 173) | class Hotkey(BaseModel):
function ping (line 182) | async def ping():
function list_audio_devices_api (line 188) | async def list_audio_devices_api() -> Dict[str, List[Dict[str, Any]]]:
function set_audio_device (line 214) | async def set_audio_device(device: DeviceIndex):
function set_hotkey_api (line 251) | async def set_hotkey_api(hotkey: Hotkey):
function get_hotkey_api (line 276) | async def get_hotkey_api():
function main (line 281) | async def main() -> None:
FILE: backend/test_api.py
function test_ping (line 5) | def test_ping():
function test_list_audio_devices (line 10) | def test_list_audio_devices():
function test_set_audio_device (line 17) | def test_set_audio_device(index):
function test_set_hotkey (line 29) | def test_set_hotkey(hotkey):
function test_get_hotkey (line 41) | def test_get_hotkey():
function test_error_cases (line 46) | def test_error_cases():
FILE: frontend/src/VoiceRecognitionIcon.tsx
type VoiceRecognitionIconProps (line 6) | interface VoiceRecognitionIconProps {
FILE: frontend/src/components/ui/badge.tsx
type BadgeProps (line 26) | interface BadgeProps
function Badge (line 30) | function Badge({ className, variant, ...props }: BadgeProps) {
FILE: frontend/src/components/ui/button.tsx
type ButtonProps (line 36) | interface ButtonProps
FILE: frontend/src/i18n.ts
type Language (line 1) | type Language = 'English' | '日本語' | '简体中文';
FILE: frontend/src/lib/utils.ts
function cn (line 4) | function cn(...inputs: ClassValue[]) {
FILE: frontend/src/main.ts
constant DEBOUNCE_TIME (line 33) | const DEBOUNCE_TIME = 300;
type ServerStatus (line 47) | type ServerStatus = 'error' | 'starting' | 'running';
function isPortAvailable (line 55) | async function isPortAvailable(port: number): Promise<boolean> {
function convertHotkeyForServer (line 64) | function convertHotkeyForServer(hotkey: string): string {
function killAllSayKeyProcesses (line 72) | function killAllSayKeyProcesses(): Promise<void> {
function isDevelopment (line 92) | function isDevelopment() {
function startBackendService (line 96) | async function startBackendService() {
function loadSettings (line 192) | function loadSettings() {
function saveSettings (line 206) | function saveSettings() {
function fetchAudioDevices (line 212) | async function fetchAudioDevices() {
function changeLanguage (line 228) | function changeLanguage(lang: Language) {
type HotkeyResponse (line 238) | type HotkeyResponse = {
function changeShortcut (line 244) | async function changeShortcut(newShortcut: string) {
function convertServerHotkeyToElectron (line 270) | function convertServerHotkeyToElectron(serverHotkey: string): string {
function getMenuTemplate (line 279) | function getMenuTemplate(): Electron.MenuItemConstructorOptions[] {
function changeMicrophone (line 430) | async function changeMicrophone(index: number) {
function setupContextMenu (line 446) | function setupContextMenu() {
function createWindow (line 465) | async function createWindow() {
function updateAlwaysOnTop (line 521) | function updateAlwaysOnTop() {
function createTray (line 527) | function createTray() {
function updateTrayMenu (line 547) | function updateTrayMenu() {
function registerGlobalShortcut (line 555) | function registerGlobalShortcut() {
function checkServerStatus (line 602) | async function checkServerStatus() {
function updateContextMenu (line 637) | function updateContextMenu() {
function startMicrophoneCheck (line 644) | function startMicrophoneCheck() {
function stopMicrophoneCheck (line 654) | function stopMicrophoneCheck() {
function createLogWindow (line 664) | function createLogWindow() {
function getCurrentHotkey (line 785) | async function getCurrentHotkey() {
function restartBackendService (line 800) | function restartBackendService() {
FILE: frontend/src/preload.ts
type MediaDeviceInfo (line 5) | interface MediaDeviceInfo {
FILE: frontend/src/renderer.tsx
type Window (line 10) | interface Window {
function App (line 36) | function App() {
Condensed preview — 58 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (518K chars).
[
{
"path": ".gitattributes",
"chars": 136,
"preview": "backend/punc-onnx/punc.onnx filter=lfs diff=lfs merge=lfs -text\nbackend/sherpa-onnx/model.int8.onnx filter=lfs diff=lfs "
},
{
"path": ".gitignore",
"chars": 69,
"preview": "\n.idea/\nSayKey-v1.0.0\nSayKey\nSayKey-v1.0.0.zip\nSayKey.zip\ndata\n*.wav\n"
},
{
"path": "LICENSE.txt",
"chars": 1118,
"preview": "The MIT License (MIT)\n\nCopyright (c) 2014-2017 Alexey Popravka\nCopyright (c) 2021 Sean Stewart\n\nPermission is hereby gra"
},
{
"path": "backend/.gitignore",
"chars": 50,
"preview": "\nvenv/\n\n\nbuild/\ndist/\n*.spec\n\n.idea/\n\ndata/\n*.wav\n"
},
{
"path": "backend/CT-Transformer-punctuation/.flake8",
"chars": 414,
"preview": "[flake8]\nshow-source=true\nstatistics=true\nmax-line-length = 108\nper-file-ignores =\n # line too long\n runtime/src/u"
},
{
"path": "backend/CT-Transformer-punctuation/.gitignore",
"chars": 3091,
"preview": "*.bin\n*.onnx\n\n# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribu"
},
{
"path": "backend/CT-Transformer-punctuation/LICENSE",
"chars": 1118,
"preview": "The MIT License (MIT)\n\nCopyright (c) 2014-2017 Alexey Popravka\nCopyright (c) 2021 Sean Stewart\n\nPermission is hereby gra"
},
{
"path": "backend/CT-Transformer-punctuation/MANIFEST.in",
"chars": 131,
"preview": "include cttpunctuator/src/onnx/configuration.json\ninclude cttpunctuator/src/onnx/punc.onnx\ninclude cttpunctuator/src/onn"
},
{
"path": "backend/CT-Transformer-punctuation/README.md",
"chars": 6195,
"preview": "\n\n<br/>\n<h2 align=\"center\">Ctt punctuator</h2>\n<br/>\n\n\n\n!"
},
{
"path": "backend/CT-Transformer-punctuation/cttPunctuator.py",
"chars": 2301,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :ctt-punctuator.py\n# @Time :2023/4/13 15:03\n# @Author :lovemefan\n# @Email "
},
{
"path": "backend/CT-Transformer-punctuation/cttpunctuator/__init__.py",
"chars": 142,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :__init__.py.py\n# @Time :2023/4/13 14:58\n# @Author :lovemefan\n# @Email :"
},
{
"path": "backend/CT-Transformer-punctuation/cttpunctuator/src/onnx/configuration.json",
"chars": 449,
"preview": "{\n \"framework\": \"onnx\",\n \"task\" : \"punctuation\",\n \"model\" : {\n \"type\" : \"generic-punc\",\n \"punc_model_name\" : \"p"
},
{
"path": "backend/CT-Transformer-punctuation/cttpunctuator/src/punctuator.py",
"chars": 12966,
"preview": "import logging\nimport os.path\nimport pickle\nfrom pathlib import Path\nfrom typing import Tuple, Union\n\nimport numpy as np"
},
{
"path": "backend/CT-Transformer-punctuation/cttpunctuator/src/utils/OrtInferSession.py",
"chars": 3483,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :OrtInferSession.py\n# @Time :2023/4/13 15:13\n# @Author :lovemefan\n# @Email "
},
{
"path": "backend/CT-Transformer-punctuation/cttpunctuator/src/utils/text_post_process.py",
"chars": 2539,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :text_post_process.py\n# @Time :2023/4/13 15:09\n# @Author :lovemefan\n# @Email"
},
{
"path": "backend/CT-Transformer-punctuation/setup.py",
"chars": 2154,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :setup.py\n# @Time :2023/4/4 11:22\n# @Author :lovemefan\n# @Email :lovemef"
},
{
"path": "backend/CT-Transformer-punctuation/test/test.py",
"chars": 991,
"preview": "# -*- coding:utf-8 -*-\n# @FileName :test.py.py\n# @Time :2023/4/19 13:39\n# @Author :lovemefan\n# @Email :love"
},
{
"path": "backend/CT-Transformer-punctuation/test/test2.py",
"chars": 856,
"preview": "from cttPunctuator import CttPunctuator\nimport logging\nlogging.basicConfig(\n level=logging.INFO,\n format=\"[%(ascti"
},
{
"path": "backend/CT-Transformer-punctuation/version.txt",
"chars": 6,
"preview": "0.0.3\n"
},
{
"path": "backend/build_onefile.bat",
"chars": 2115,
"preview": "@echo off\nREM Optimized Build Script for SayKey using PyInstaller on Windows 11\n\nREM Set the path to your virtual enviro"
},
{
"path": "backend/main.py",
"chars": 12301,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# Author: WenJing Wu\n\nimport argparse\nimport asyncio\nimport os\nimport wav"
},
{
"path": "backend/punc-onnx/configuration.json",
"chars": 449,
"preview": "{\n \"framework\": \"onnx\",\n \"task\" : \"punctuation\",\n \"model\" : {\n \"type\" : \"generic-punc\",\n \"punc_model_name\" : \"p"
},
{
"path": "backend/punc-onnx/punc.onnx",
"chars": 134,
"preview": "version https://git-lfs.github.com/spec/v1\noid sha256:ed5318d91ff9520a03a5b5a8dba264b76858931db7d914b0de6ec9e4ad35970e\ns"
},
{
"path": "backend/readme.md",
"chars": 1276,
"preview": "### Init\n\n```bash\n cd ./backend\n cd CT-Transformer-punctuation\n pip install -e .\n pip install -r requirements.tx"
},
{
"path": "backend/requirements.txt",
"chars": 1125,
"preview": "altgraph==0.17.4\nannotated-types==0.7.0\nanyio==4.6.0\ncertifi==2024.8.30\ncffi==1.17.1\ncharset-normalizer==3.4.0\nclick==8."
},
{
"path": "backend/requirements_test.txt",
"chars": 53,
"preview": "altgraph==0.17.4\nannotated-types==0.7.0\nanyio==4.6.0\n"
},
{
"path": "backend/sherpa-onnx/model.int8.onnx",
"chars": 134,
"preview": "version https://git-lfs.github.com/spec/v1\noid sha256:c71f0ce00bec95b07744e116345e33d8cbbe08cef896382cf907bf4b51a2cd51\ns"
},
{
"path": "backend/sherpa-onnx/tokens.txt",
"chars": 254654,
"preview": "<unk> 0\n<s> 1\n</s> 2\n▁the 3\ns 4\n▁to 5\n▁and 6\n▁of 7\n▁a 8\n' 9\n▁in 10\n▁I 11\n▁that 12\n▁is 13\n▁you 14\n▁it 15\nt 16\n▁for 17\n▁we"
},
{
"path": "backend/test_api.py",
"chars": 3232,
"preview": "# test_api.py\n\nimport requests\n\ndef test_ping():\n print('Testing /ping endpoint...')\n response = requests.get('htt"
},
{
"path": "frontend/.gitignore",
"chars": 69,
"preview": "/node_modules\n\n/dist\n/build\n\n.next\nout\nrelease\n\n.idea/\n\n*.tmp\n*.temp\n"
},
{
"path": "frontend/components.json",
"chars": 354,
"preview": "{\n \"$schema\": \"https://ui.shadcn.com/schema.json\",\n \"style\": \"default\",\n \"rsc\": false,\n \"tsx\": true,\n \"ta"
},
{
"path": "frontend/index.html",
"chars": 717,
"preview": "<!DOCTYPE html>\n<html>\n <head>\n <meta charset=\"UTF-8\" />\n <title>SayKey</title>\n <link rel=\"icon\" href=\"favico"
},
{
"path": "frontend/package.json",
"chars": 1990,
"preview": "{\n \"name\": \"SayKey\",\n \"productName\": \"SayKey\",\n \"version\": \"1.0.1\",\n \"description\": \"SayKey\",\n \"main\": \"dist/main.j"
},
{
"path": "frontend/postcss.config.js",
"chars": 80,
"preview": "module.exports = {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n }\n}"
},
{
"path": "frontend/readme.md",
"chars": 163,
"preview": "\n ```bash\n # Install\n cd ./frontend\n npm install\n # Start\n npm run build\n npm start\n # Build exe\n npm "
},
{
"path": "frontend/src/VoiceRecognitionIcon.tsx",
"chars": 10525,
"preview": "import React, {useState, useEffect, useCallback, useRef} from \"react\";\nimport {motion, AnimatePresence} from \"framer-mot"
},
{
"path": "frontend/src/components/ui/badge.tsx",
"chars": 1128,
"preview": "import * as React from \"react\"\nimport { cva, type VariantProps } from \"class-variance-authority\"\n\nimport { cn } from \"@/"
},
{
"path": "frontend/src/components/ui/button.tsx",
"chars": 1820,
"preview": "import * as React from \"react\"\nimport { Slot } from \"@radix-ui/react-slot\"\nimport { cva, type VariantProps } from \"class"
},
{
"path": "frontend/src/components/ui/card.tsx",
"chars": 1877,
"preview": "import * as React from \"react\"\n\nimport { cn } from \"@/lib/utils\"\n\nconst Card = React.forwardRef<\n HTMLDivElement,\n Rea"
},
{
"path": "frontend/src/components/ui/hover-card.tsx",
"chars": 1184,
"preview": "import * as React from \"react\"\nimport * as HoverCardPrimitive from \"@radix-ui/react-hover-card\"\n\nimport { cn } from \"@/l"
},
{
"path": "frontend/src/components/ui/scroll-area.tsx",
"chars": 1642,
"preview": "import * as React from \"react\"\nimport * as ScrollAreaPrimitive from \"@radix-ui/react-scroll-area\"\n\nimport { cn } from \"@"
},
{
"path": "frontend/src/components/ui/tabs.tsx",
"chars": 1883,
"preview": "import * as React from \"react\"\nimport * as TabsPrimitive from \"@radix-ui/react-tabs\"\n\nimport { cn } from \"@/lib/utils\"\n\n"
},
{
"path": "frontend/src/components/ui/tooltip.tsx",
"chars": 1145,
"preview": "import * as React from \"react\"\nimport * as TooltipPrimitive from \"@radix-ui/react-tooltip\"\n\nimport { cn } from \"@/lib/ut"
},
{
"path": "frontend/src/favicon/site.webmanifest",
"chars": 276,
"preview": "{\"background_color\":\"#ffffff\",\"display\":\"standalone\",\"icons\":[{\"sizes\":\"192x192\",\"src\":\"/android-chrome-192x192.png\",\"ty"
},
{
"path": "frontend/src/globals.css",
"chars": 1685,
"preview": "@tailwind base;\n@tailwind components;\n@tailwind utilities;\n \n@layer base {\n :root {\n --background: 0 0% 100%;\n --"
},
{
"path": "frontend/src/i18n.ts",
"chars": 2843,
"preview": "type Language = 'English' | '日本語' | '简体中文';\n\nconst translations: Record<Language, Record<string, string>> = {\n 'Engli"
},
{
"path": "frontend/src/index.html",
"chars": 717,
"preview": "<!DOCTYPE html>\n<html>\n <head>\n <meta charset=\"UTF-8\" />\n <title>SayKey</title>\n <link rel=\"icon\" href=\"favico"
},
{
"path": "frontend/src/lib/utils.ts",
"chars": 165,
"preview": "import { type ClassValue, clsx } from \"clsx\"\nimport { twMerge } from \"tailwind-merge\"\n\nexport function cn(...inputs: Cla"
},
{
"path": "frontend/src/log.html",
"chars": 18150,
"preview": "<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n\t<meta charset=\"UTF-8\">\n\t<meta name=\"viewport\" content=\"width=device-width, init"
},
{
"path": "frontend/src/main.ts",
"chars": 24457,
"preview": "// main.ts\nimport {\n app,\n BrowserWindow,\n screen,\n Tray,\n Menu,\n globalShortcut,\n ipcMain,\n Men"
},
{
"path": "frontend/src/preload.ts",
"chars": 3289,
"preview": "// preload.ts\nimport {contextBridge, ipcRenderer} from 'electron';\nimport {Language} from './i18n';\n\ninterface MediaDevi"
},
{
"path": "frontend/src/renderer.tsx",
"chars": 7864,
"preview": "// renderer.tsx\nimport React, {useEffect, useState, useRef, useCallback} from 'react';\nimport ReactDOM from 'react-dom';"
},
{
"path": "frontend/src/styles.css",
"chars": 58,
"preview": "@tailwind base;\n@tailwind components;\n@tailwind utilities;"
},
{
"path": "frontend/tailwind.config.js",
"chars": 2686,
"preview": "/** @type {import('tailwindcss').Config} */\nmodule.exports = {\n darkMode: [\"class\"],\n content: [\n './src/**/*"
},
{
"path": "frontend/tsconfig.json",
"chars": 509,
"preview": "{\n \"compilerOptions\": {\n \"target\": \"ES6\",\n \"module\": \"CommonJS\",\n \"moduleResolution\": \"node\",\n \"s"
},
{
"path": "frontend/webpack.config.js",
"chars": 963,
"preview": "const path = require('path');\nconst CopyWebpackPlugin = require('copy-webpack-plugin');\n\nmodule.exports = {\n mode: 'pro"
},
{
"path": "readme.md",
"chars": 6619,
"preview": "# SayKey \n\n[简体中文](./readme_zh.md)|English\n\nSayKey is a tool that turns your speech into text. It works fast, accurately,"
},
{
"path": "readme_zh.md",
"chars": 4802,
"preview": "# SayKey \n\n简体中文|[English](./readme.md)\n\nSayKey 是一个语音输入法，为你提供快速、准确、完全离线的语音转文字体验。由 [SenseVoice](https://github.com/FunAudi"
}
]
About this extraction
This page contains the full source code of the WenJing95/SayKey GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 58 files (403.7 KB), approximately 206.8k tokens, and a symbol index with 94 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.