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asr.py
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asr.py
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import logging
import os
import time
import tomli
from base_util import (
get_asset_info,
asr_output_dir,
save_provenance,
PROVENANCE_JSON_FILE,
)
from config import (
s3_endpoint_url,
w_word_timestamps,
w_device,
w_model,
w_beam_size,
w_best_of,
w_vad,
)
from download import download_uri
from whisper import run_asr, WHISPER_JSON_FILE
from s3_util import S3Store, parse_s3_uri
from transcode import try_transcode
from daan_transcript import generate_daan_transcript, DAAN_JSON_FILE
logger = logging.getLogger(__name__)
def _get_project_meta():
with open("pyproject.toml", mode="rb") as pyproject:
return tomli.load(pyproject)["tool"]["poetry"]
pkg_meta = _get_project_meta()
version = str(pkg_meta["version"])
def run(input_uri: str, output_uri: str, model=None) -> bool:
logger.info(f"Processing {input_uri} (save to --> {output_uri})")
start_time = time.time()
prov_steps = [] # track provenance
# 1. download input
result = download_uri(input_uri)
logger.info(result)
if not result:
logger.error("Could not obtain input, quitting...")
return False
prov_steps.append(result.provenance)
input_path = result.file_path
asset_id, extension = get_asset_info(input_path)
output_path = asr_output_dir(input_path)
# 2. check if the input file is suitable for processing any further
transcode_output = try_transcode(input_path, asset_id, extension)
if not transcode_output:
logger.error("The transcode failed to yield a valid file to continue with")
return False
else:
input_path = transcode_output.transcoded_file_path
prov_steps.append(transcode_output.provenance)
# 3. run ASR
if not asr_already_done(output_path):
logger.info("No Whisper transcript found")
whisper_prov = run_asr(input_path, output_path, model)
if whisper_prov:
prov_steps.append(whisper_prov)
else:
logger.info(f"Whisper transcript already present in {output_path}")
provenance = {
"activity_name": "Whisper transcript already exists",
"activity_description": "",
"processing_time_ms": "",
"start_time_unix": "",
"parameters": [],
"software_version": "",
"input_data": "",
"output_data": "",
"steps": [],
}
prov_steps.append(provenance)
# 4. generate JSON transcript
if not daan_transcript_already_done(output_path):
logger.info("No DAAN transcript found")
daan_prov = generate_daan_transcript(output_path)
if daan_prov:
prov_steps.append(daan_prov)
else:
logger.warning("Could not generate DAAN transcript")
else:
logger.info(f"DAAN transcript already present in {output_path}")
provenance = {
"activity_name": "DAAN transcript already exists",
"activity_description": "",
"processing_time_ms": "",
"start_time_unix": "",
"parameters": [],
"software_version": "",
"input_data": "",
"output_data": "",
"steps": [],
}
prov_steps.append(provenance)
end_time = (time.time() - start_time) * 1000
final_prov = {
"activity_name": "Whisper ASR Worker",
"activity_description": "Worker that gets a video/audio file as input and outputs JSON transcripts in various formats",
"processing_time_ms": end_time,
"start_time_unix": start_time,
"parameters": {
"word_timestamps": w_word_timestamps,
"device": w_device,
"vad": w_vad,
"model": w_model,
"beam_size": w_beam_size,
"best_of": w_best_of,
},
"software_version": version,
"input_data": input_uri,
"output_data": output_uri if output_uri else output_path,
"steps": prov_steps,
}
prov_success = save_provenance(final_prov, output_path)
if not prov_success:
logger.warning("Could not save the provenance")
# 5. transfer output
if output_uri:
transfer_asr_output(output_path, output_uri)
else:
logger.info("No output_uri specified, so all is done")
return True
# if S3 output_uri is supplied transfers data to S3 location
def transfer_asr_output(output_path: str, output_uri: str) -> bool:
logger.info(f"Transferring {output_path} to S3 (destination={output_uri})")
if not s3_endpoint_url:
logger.warning("Transfer to S3 configured without an S3_ENDPOINT_URL!")
return False
s3_bucket, s3_folder_in_bucket = parse_s3_uri(output_uri)
s3 = S3Store(s3_endpoint_url)
return s3.transfer_to_s3(
s3_bucket,
s3_folder_in_bucket,
[
os.path.join(output_path, DAAN_JSON_FILE),
os.path.join(output_path, WHISPER_JSON_FILE),
os.path.join(output_path, PROVENANCE_JSON_FILE),
],
)
# check if there is a whisper-transcript.json
def asr_already_done(output_dir: str) -> bool:
whisper_transcript = os.path.join(output_dir, WHISPER_JSON_FILE)
logger.info(f"Checking existence of {whisper_transcript}")
return os.path.exists(os.path.join(output_dir, WHISPER_JSON_FILE))
# check if there is a daan-es-transcript.json
def daan_transcript_already_done(output_dir: str) -> bool:
daan_transcript = os.path.join(output_dir, DAAN_JSON_FILE)
logger.info(f"Checking existence of {daan_transcript}")
return os.path.exists(os.path.join(output_dir, DAAN_JSON_FILE))