LLM/WhisperLiveKit
1
0
Fork 0
mirror of https://github.com/QuentinFuxa/WhisperLiveKit.git synced 2026-03-07 14:23:18 +00:00
Code Issues Packages Projects Releases Wiki Activity

better documentation, help message and logging prints

Browse Source
This commit is contained in:
Dominik Macháček
2024-04-17 14:49:12 +02:00
parent 8883397b44
commit e0f5d42b13
3 changed files with 15 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -183,7 +183,7 @@ online.init() # refresh if you're going to re-use the object for the next audio
### Server -- real-time from mic
`whisper_online_server.py` has the same model options as `whisper_online.py`, plus `--host` and `--port` of the TCP connection. See help message (`-h` option).
`whisper_online_server.py` has the same model options as `whisper_online.py`, plus `--host` and `--port` of the TCP connection and the `--warmup-file`. See the help message (`-h` option).
Client example:

2
whisper_online.py
View File

@@ -625,7 +625,7 @@ if __name__ == "__main__":
# load the audio into the LRU cache before we start the timer
a = load_audio_chunk(audio_path,0,1)
# warm up the ASR, because the very first transcribe takes much more time than the other
# warm up the ASR because the very first transcribe takes much more time than the other
asr.transcribe(a)
beg = args.start_at

27
whisper_online_server.py
View File

@@ -10,8 +10,8 @@ parser = argparse.ArgumentParser()
# server options
parser.add_argument("--host", type=str, default='localhost')
parser.add_argument("--port", type=int, default=43007)
parser.add_argument("--warmup-file", type=str, dest="warmup_file")
parser.add_argument("--warmup-file", type=str, dest="warmup_file",
help="The path to a speech audio wav file to warm up Whisper so that the very first chunk processing is fast. It can be e.g. https://github.com/ggerganov/whisper.cpp/raw/master/samples/jfk.wav .")
# options from whisper_online
@@ -41,19 +41,18 @@ else:
tokenizer = None
online = OnlineASRProcessor(asr,tokenizer,buffer_trimming=(args.buffer_trimming, args.buffer_trimming_sec))
if args.warmup_file and os.path.exists(args.warmup_file):
# load the audio into the LRU cache before we start the timer
a = load_audio_chunk(args.warmup_file,0,1)
# TODO: it should be tested whether it's meaningful
# warm up the ASR, because the very first transcribe takes much more time than the other
asr.transcribe(a)
# warm up the ASR because the very first transcribe takes more time than the others.
# Test results in https://github.com/ufal/whisper_streaming/pull/81
msg = "Whisper is not warmed up. The first chunk processing may take longer."
if args.warmup_file:
if os.path.isfile(args.warmup_file):
a = load_audio_chunk(args.warmup_file,0,1)
asr.transcribe(a)
print("INFO: Whisper is warmed up.",file=sys.stderr)
else:
print("WARNING: The warm up file is not available. "+msg,file=sys.stderr)
else:
print("Whisper is not warmed up",file=sys.stderr)
print("WARNING: " + msg, file=sys.stderr)
######### Server objects