wehub-resource-sync
59 lines
1.4 KiB
Python
59 lines
1.4 KiB
Python
|
|
""" This tests WhisperCPP deployment and model loading. """
|
|
|
|
|
|
import os
|
|
from llmware.models import ModelCatalog
|
|
from llmware.gguf_configs import GGUFConfigs
|
|
from llmware.setup import Setup
|
|
|
|
# optional / to adjust various log/display parameters of the model
|
|
GGUFConfigs().set_config("whisper_cpp_verbose", "OFF")
|
|
GGUFConfigs().set_config("whisper_cpp_realtime_display", True)
|
|
|
|
# note: english is default output - change to 'es' | 'fr' | 'de' | 'it' ...
|
|
GGUFConfigs().set_config("whisper_language", "en")
|
|
|
|
# whether to add or remove segment markers in llm response output
|
|
GGUFConfigs().set_config("whisper_remove_segment_markers", True)
|
|
|
|
|
|
def test_whisper_cpp():
|
|
|
|
""" Execute a basic inference on Voice-to-Text model passing a file_path string """
|
|
|
|
voice_samples = Setup().load_voice_sample_files(small_only=True, over_write=True)
|
|
|
|
example = "famous_quotes"
|
|
|
|
fp = os.path.join(voice_samples,example)
|
|
|
|
files = os.listdir(fp)
|
|
|
|
# these are the two key lines
|
|
whisper_base_english = "whisper-cpp-base-english"
|
|
|
|
model = ModelCatalog().load_model(whisper_base_english)
|
|
|
|
for f in files:
|
|
|
|
if f.endswith(".wav"):
|
|
|
|
prompt = os.path.join(fp,f)
|
|
|
|
print(f"\n\nPROCESSING: prompt = {prompt}")
|
|
|
|
response = model.inference(prompt)
|
|
|
|
print("\nllm response: ", response["llm_response"])
|
|
print("usage: ", response["usage"])
|
|
|
|
assert response is not None
|
|
|
|
return 0
|
|
|
|
|
|
|
|
|
|
|