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1, optimize the subtitle generation in edge mode

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2, optimize the llm prompt, use the same language as the video subject
This commit is contained in:
harry
2024-03-24 17:50:50 +08:00
parent 296a1370d3
commit b471a272b6
4 changed files with 20 additions and 9 deletions
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10
app/services/task.py
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@@ -58,7 +58,13 @@ def start(task_id, params: VideoParams):
if not video_terms:
video_terms = llm.generate_terms(video_subject=video_subject, video_script=video_script, amount=5)
else:
video_terms = [term.strip() for term in re.split(r'[,，]', video_terms)]
if isinstance(video_terms, str):
video_terms = [term.strip() for term in re.split(r'[,，]', video_terms)]
elif isinstance(video_terms, list):
video_terms = [term.strip() for term in video_terms]
else:
raise ValueError("video_terms must be a string or a list of strings.")
logger.debug(f"video terms: {utils.to_json(video_terms)}")
script_file = path.join(utils.task_dir(task_id), f"script.json")
@@ -95,7 +101,7 @@ def start(task_id, params: VideoParams):
else:
subtitle_lines = subtitle.file_to_subtitles(subtitle_path)
if not subtitle_lines:
logger.warning(f"subtitle file is invalid: {subtitle_path}")
logger.warning(f"subtitle file is invalid, fallback to whisper : {subtitle_path}")
subtitle_fallback = True
if subtitle_provider == "whisper" or subtitle_fallback: