支持批量生成功能
This commit is contained in:
puke
@@ -21,60 +21,152 @@ from web.utils.async_helpers import get_project_version
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def render_content_input():
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def render_content_input():
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"""Render content input section (left column)"""
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"""Render content input section (left column) with batch support"""
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with st.container(border=True):
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with st.container(border=True):
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st.markdown(f"**{tr('section.content_input')}**")
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st.markdown(f"**{tr('section.content_input')}**")
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# Processing mode selection
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# ====================================================================
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mode = st.radio(
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# Step 1: Batch mode toggle (highest priority)
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"Processing Mode",
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# ====================================================================
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["generate", "fixed"],
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batch_mode = st.checkbox(
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horizontal=True,
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tr("batch.mode_label"),
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format_func=lambda x: tr(f"mode.{x}"),
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value=False,
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label_visibility="collapsed"
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help=tr("batch.mode_help")
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)
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)
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# Text input (unified for both modes)
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if not batch_mode:
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text_placeholder = tr("input.topic_placeholder") if mode == "generate" else tr("input.content_placeholder")
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# ================================================================
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text_height = 120 if mode == "generate" else 200
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# Single task mode (original logic, unchanged)
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text_help = tr("input.text_help_generate") if mode == "generate" else tr("input.text_help_fixed")
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# ================================================================
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# Processing mode selection
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mode = st.radio(
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"Processing Mode",
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["generate", "fixed"],
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horizontal=True,
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format_func=lambda x: tr(f"mode.{x}"),
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label_visibility="collapsed"
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)
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# Text input (unified for both modes)
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text_placeholder = tr("input.topic_placeholder") if mode == "generate" else tr("input.content_placeholder")
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text_height = 120 if mode == "generate" else 200
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text_help = tr("input.text_help_generate") if mode == "generate" else tr("input.text_help_fixed")
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text = st.text_area(
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tr("input.text"),
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placeholder=text_placeholder,
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height=text_height,
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help=text_help
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)
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# Title input (optional for both modes)
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title = st.text_input(
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tr("input.title"),
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placeholder=tr("input.title_placeholder"),
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help=tr("input.title_help")
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)
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# Number of scenes (only show in generate mode)
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if mode == "generate":
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n_scenes = st.slider(
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tr("video.frames"),
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min_value=3,
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max_value=30,
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value=5,
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help=tr("video.frames_help"),
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label_visibility="collapsed"
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)
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st.caption(tr("video.frames_label", n=n_scenes))
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else:
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# Fixed mode: n_scenes is ignored, set default value
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n_scenes = 5
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st.info(tr("video.frames_fixed_mode_hint"))
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return {
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"batch_mode": False,
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"mode": mode,
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"text": text,
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"title": title,
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"n_scenes": n_scenes
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}
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text = st.text_area(
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else:
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tr("input.text"),
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# ================================================================
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placeholder=text_placeholder,
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# Batch mode (simplified YAGNI version)
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height=text_height,
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# ================================================================
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help=text_help
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st.markdown(f"**{tr('batch.section_title')}**")
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)
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# Batch rules info
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# Title input (optional for both modes)
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st.info(f"""
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title = st.text_input(
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**{tr('batch.rules_title')}**
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tr("input.title"),
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- ✅ {tr('batch.rule_1')}
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placeholder=tr("input.title_placeholder"),
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- ✅ {tr('batch.rule_2')}
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help=tr("input.title_help")
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- ✅ {tr('batch.rule_3')}
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)
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""")
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# Number of scenes (only show in generate mode)
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# Batch topics input
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if mode == "generate":
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text_input = st.text_area(
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tr("batch.topics_label"),
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height=300,
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placeholder=tr("batch.topics_placeholder"),
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help=tr("batch.topics_help")
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)
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# Split topics by newline
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if text_input:
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# Simple split by newline, filter empty lines
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topics = [
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line.strip()
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for line in text_input.strip().split('\n')
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if line.strip()
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]
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if topics:
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# Check count limit
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if len(topics) > 100:
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st.error(tr("batch.count_error", count=len(topics)))
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topics = []
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else:
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st.success(tr("batch.count_success", count=len(topics)))
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# Preview topics list
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with st.expander(tr("batch.preview_title"), expanded=False):
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for i, topic in enumerate(topics, 1):
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st.markdown(f"`{i}.` {topic}")
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else:
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topics = []
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else:
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topics = []
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st.markdown("---")
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# Title prefix (optional)
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title_prefix = st.text_input(
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tr("batch.title_prefix_label"),
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placeholder=tr("batch.title_prefix_placeholder"),
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help=tr("batch.title_prefix_help")
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)
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# Number of scenes (unified for all videos)
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n_scenes = st.slider(
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n_scenes = st.slider(
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tr("video.frames"),
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tr("batch.n_scenes_label"),
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min_value=3,
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min_value=3,
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max_value=30,
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max_value=30,
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value=5,
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value=5,
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help=tr("video.frames_help"),
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help=tr("batch.n_scenes_help")
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label_visibility="collapsed"
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)
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)
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st.caption(tr("video.frames_label", n=n_scenes))
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st.caption(tr("batch.n_scenes_caption", n=n_scenes))
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else:
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# Fixed mode: n_scenes is ignored, set default value
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# Config info
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n_scenes = 5
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st.info(f"📌 {tr('batch.config_info')}")
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st.info(tr("video.frames_fixed_mode_hint"))
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return {
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return {
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"batch_mode": True,
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"mode": mode,
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"topics": topics,
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"text": text,
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"mode": "generate", # Fixed to AI generate content
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"title": title,
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"title_prefix": title_prefix,
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"n_scenes": n_scenes
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"n_scenes": n_scenes,
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}
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}
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def render_bgm_section():
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def render_bgm_section():
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@@ -29,6 +29,19 @@ from pixelle_video.config import config_manager
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def render_output_preview(pixelle_video, video_params):
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def render_output_preview(pixelle_video, video_params):
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"""Render output preview section (right column)"""
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"""Render output preview section (right column)"""
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# Check if batch mode
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is_batch = video_params.get("batch_mode", False)
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if is_batch:
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# Batch generation mode
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render_batch_output(pixelle_video, video_params)
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else:
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# Single video generation mode (original logic)
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render_single_output(pixelle_video, video_params)
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def render_single_output(pixelle_video, video_params):
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"""Render single video generation output (original logic, unchanged)"""
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# Extract parameters from video_params dict
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# Extract parameters from video_params dict
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text = video_params.get("text", "")
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text = video_params.get("text", "")
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mode = video_params.get("mode", "generate")
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mode = video_params.get("mode", "generate")
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@@ -193,4 +206,179 @@ def render_output_preview(pixelle_video, video_params):
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st.error(tr("status.error", error=str(e)))
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st.error(tr("status.error", error=str(e)))
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logger.exception(e)
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logger.exception(e)
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st.stop()
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st.stop()
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def render_batch_output(pixelle_video, video_params):
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"""Render batch generation output (minimal, redirect to History)"""
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topics = video_params.get("topics", [])
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with st.container(border=True):
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st.markdown(f"**{tr('batch.section_generation')}**")
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# Check if topics are provided
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if not topics:
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st.warning(tr("batch.no_topics"))
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return
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# Check system configuration
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if not config_manager.validate():
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st.warning(tr("settings.not_configured"))
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return
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batch_count = len(topics)
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# Display batch info
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st.info(tr("batch.prepare_info", count=batch_count))
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# Estimated time (optional)
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estimated_minutes = batch_count * 3 # Assume 3 minutes per video
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st.caption(tr("batch.estimated_time", minutes=estimated_minutes))
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# Generate button with batch semantics
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if st.button(
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tr("batch.generate_button", count=batch_count),
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type="primary",
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use_container_width=True,
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help=tr("batch.generate_help")
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):
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# Prepare shared config
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shared_config = {
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"title_prefix": video_params.get("title_prefix"),
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"n_scenes": video_params.get("n_scenes", 5),
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"image_workflow": video_params.get("image_workflow"),
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"frame_template": video_params.get("frame_template"),
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"prompt_prefix": video_params.get("prompt_prefix", ""),
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"bgm_path": video_params.get("bgm_path"),
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"bgm_volume": video_params.get("bgm_volume", 0.2),
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"tts_inference_mode": video_params.get("tts_inference_mode", "local"),
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}
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# Add TTS parameters
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if shared_config["tts_inference_mode"] == "local":
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shared_config["tts_voice"] = video_params.get("tts_voice")
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shared_config["tts_speed"] = video_params.get("tts_speed")
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else:
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shared_config["tts_workflow"] = video_params.get("tts_workflow")
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if video_params.get("ref_audio"):
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shared_config["ref_audio"] = str(video_params["ref_audio"])
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# Add template parameters
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if video_params.get("template_params"):
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shared_config["template_params"] = video_params["template_params"]
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# UI containers
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overall_progress_container = st.container()
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current_task_container = st.container()
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# Overall progress UI
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overall_progress_bar = overall_progress_container.progress(0)
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overall_status = overall_progress_container.empty()
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# Current task progress UI
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current_task_title = current_task_container.empty()
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current_task_progress = current_task_container.progress(0)
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current_task_status = current_task_container.empty()
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# Overall progress callback
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def update_overall_progress(current, total, topic):
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progress = (current - 1) / total
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overall_progress_bar.progress(progress)
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overall_status.markdown(
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f"📊 **{tr('batch.overall_progress')}**: {current}/{total} ({int(progress * 100)}%)"
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)
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# Single task progress callback factory
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def make_task_progress_callback(task_idx, topic):
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def callback(event: ProgressEvent):
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# Display current task title
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current_task_title.markdown(f"🎬 **{tr('batch.current_task')} {task_idx}**: {topic}")
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# Update task detailed progress
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if event.event_type == "frame_step":
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action_key = f"progress.step_{event.action}"
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action_text = tr(action_key)
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message = tr(
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"progress.frame_step",
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current=event.frame_current,
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total=event.frame_total,
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step=event.step,
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action=action_text
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)
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elif event.event_type == "processing_frame":
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message = tr(
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"progress.frame",
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current=event.frame_current,
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total=event.frame_total
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)
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else:
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message = tr(f"progress.{event.event_type}")
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current_task_progress.progress(event.progress)
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current_task_status.text(message)
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return callback
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# Execute batch generation
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from web.utils.batch_manager import SimpleBatchManager
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import time
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batch_manager = SimpleBatchManager()
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start_time = time.time()
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batch_result = batch_manager.execute_batch(
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pixelle_video=pixelle_video,
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topics=topics,
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shared_config=shared_config,
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overall_progress_callback=update_overall_progress,
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task_progress_callback_factory=make_task_progress_callback
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)
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total_time = time.time() - start_time
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# Clear progress displays
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overall_progress_bar.progress(1.0)
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overall_status.markdown(f"✅ **{tr('batch.completed')}**")
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current_task_title.empty()
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current_task_progress.empty()
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current_task_status.empty()
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# Display results summary
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st.markdown("---")
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st.markdown(f"**{tr('batch.results_title')}**")
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col1, col2, col3 = st.columns(3)
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col1.metric(tr("batch.total"), batch_result["total_count"])
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col2.metric(f"✅ {tr('batch.success')}", batch_result["success_count"])
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col3.metric(f"❌ {tr('batch.failed')}", batch_result["failed_count"])
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# Display total time
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minutes = int(total_time / 60)
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seconds = int(total_time % 60)
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st.caption(f"⏱️ {tr('batch.total_time')}: {minutes}{tr('batch.minutes')}{seconds}{tr('batch.seconds')}")
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# Redirect to History page
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st.markdown("---")
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st.success(tr("batch.success_message"))
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st.info(tr("batch.view_in_history"))
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# Button to go to History page
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if st.button(
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f"📚 {tr('batch.goto_history')}",
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type="secondary",
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use_container_width=True
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):
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st.switch_page("pages/2_📚_History.py")
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# Show failed tasks if any
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if batch_result["errors"]:
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st.markdown("---")
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st.markdown(f"#### {tr('batch.failed_list')}")
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for item in batch_result["errors"]:
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with st.expander(f"🔴 {tr('batch.task')} {item['index']}: {item['topic']}", expanded=False):
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st.error(f"**{tr('batch.error')}**: {item['error']}")
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# Detailed error (collapsed)
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with st.expander(tr("batch.error_detail")):
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st.code(item['traceback'], language="python")
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@@ -320,7 +320,51 @@
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"history.action.delete_confirm": "Confirm deletion? This action cannot be undone!",
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"history.action.delete_confirm": "Confirm deletion? This action cannot be undone!",
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"history.action.delete_success": "✅ Task deleted",
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"history.action.delete_success": "✅ Task deleted",
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"history.action.delete_failed": "❌ Deletion failed: {error}",
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"history.action.delete_failed": "❌ Deletion failed: {error}",
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"history.page_info": "Page {page} / {total_pages}"
|
"history.page_info": "Page {page} / {total_pages}",
|
||||||
|
|
||||||
|
"batch.mode_label": "🔢 Batch Generation Mode",
|
||||||
|
"batch.mode_help": "Generate multiple videos, one topic per line",
|
||||||
|
"batch.section_title": "Batch Topics Input",
|
||||||
|
"batch.section_generation": "📦 Batch Video Generation",
|
||||||
|
"batch.rules_title": "Batch Generation Rules",
|
||||||
|
"batch.rule_1": "Automatically use 'AI Generate Content' mode",
|
||||||
|
"batch.rule_2": "Enter one topic per line",
|
||||||
|
"batch.rule_3": "All videos use the same configuration (TTS, template, workflow, etc.)",
|
||||||
|
"batch.topics_label": "Batch Topics (one per line)",
|
||||||
|
"batch.topics_placeholder": "Why develop a reading habit\nHow to manage time efficiently\n5 secrets to healthy living\nBenefits of waking up early\nHow to overcome procrastination\nTechniques to stay focused\nEmotional management methods\nTips to improve memory\nBuilding good relationships\nWealth management basics",
|
||||||
|
"batch.topics_help": "One video topic per line, AI will generate content based on the topic",
|
||||||
|
"batch.count_success": "✅ Detected {count} topics",
|
||||||
|
"batch.count_error": "❌ Batch size exceeds limit (max 100), current: {count}",
|
||||||
|
"batch.preview_title": "📋 Preview Topic List",
|
||||||
|
"batch.title_prefix_label": "Title Prefix (optional)",
|
||||||
|
"batch.title_prefix_placeholder": "e.g., Knowledge Sharing",
|
||||||
|
"batch.title_prefix_help": "Final title format: {prefix} - {topic}, e.g., Knowledge Sharing - Why develop a reading habit",
|
||||||
|
"batch.n_scenes_label": "Scenes (unified for all videos)",
|
||||||
|
"batch.n_scenes_help": "Number of scenes per video, same setting for all videos",
|
||||||
|
"batch.n_scenes_caption": "Scenes: {n}",
|
||||||
|
"batch.config_info": "Other configurations: TTS voice, video template, image workflow, etc. will use the settings from the right panel, unified for all videos",
|
||||||
|
"batch.no_topics": "⚠️ Please enter batch topics on the left (one per line)",
|
||||||
|
"batch.prepare_info": "📊 Ready to generate {count} videos (using same configuration)",
|
||||||
|
"batch.estimated_time": "⏱️ Estimated time: about {minutes} minutes",
|
||||||
|
"batch.generate_button": "🚀 Batch Generate {count} Videos",
|
||||||
|
"batch.generate_help": "⚠️ Please keep the page open during batch generation, do not close the browser",
|
||||||
|
"batch.overall_progress": "Overall Progress",
|
||||||
|
"batch.current_task": "Current Task",
|
||||||
|
"batch.completed": "Batch generation completed!",
|
||||||
|
"batch.results_title": "📊 Batch Generation Results",
|
||||||
|
"batch.total": "Total",
|
||||||
|
"batch.success": "Success",
|
||||||
|
"batch.failed": "Failed",
|
||||||
|
"batch.total_time": "Total Time",
|
||||||
|
"batch.minutes": "m",
|
||||||
|
"batch.seconds": "s",
|
||||||
|
"batch.success_message": "✅ Batch generation completed! All videos have been saved to history.",
|
||||||
|
"batch.view_in_history": "💡 Tip: You can view all generated videos in the '📚 History' page.",
|
||||||
|
"batch.goto_history": "Go to History Page",
|
||||||
|
"batch.failed_list": "❌ Failed Tasks",
|
||||||
|
"batch.task": "Task",
|
||||||
|
"batch.error": "Error",
|
||||||
|
"batch.error_detail": "View detailed error stack"
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|||||||
@@ -320,7 +320,51 @@
|
|||||||
"history.action.delete_confirm": "确认删除该任务？此操作无法撤销！",
|
"history.action.delete_confirm": "确认删除该任务？此操作无法撤销！",
|
||||||
"history.action.delete_success": "✅ 任务已删除",
|
"history.action.delete_success": "✅ 任务已删除",
|
||||||
"history.action.delete_failed": "❌ 删除失败：{error}",
|
"history.action.delete_failed": "❌ 删除失败：{error}",
|
||||||
"history.page_info": "第 {page} 页 / 共 {total_pages} 页"
|
"history.page_info": "第 {page} 页 / 共 {total_pages} 页",
|
||||||
|
|
||||||
|
"batch.mode_label": "🔢 批量生成模式",
|
||||||
|
"batch.mode_help": "批量生成多个视频，每行一个主题",
|
||||||
|
"batch.section_title": "批量主题输入",
|
||||||
|
"batch.section_generation": "📦 批量视频生成",
|
||||||
|
"batch.rules_title": "批量生成规则",
|
||||||
|
"batch.rule_1": "自动使用「AI 生成内容」模式",
|
||||||
|
"batch.rule_2": "每行输入一个主题",
|
||||||
|
"batch.rule_3": "所有视频使用相同的配置（TTS、模板、工作流等）",
|
||||||
|
"batch.topics_label": "批量主题（每行一个）",
|
||||||
|
"batch.topics_placeholder": "为什么要养成阅读习惯\n如何高效管理时间\n健康生活的5个秘诀\n早起的好处\n如何克服拖延症\n保持专注的技巧\n情绪管理的方法\n提升记忆力的窍门\n建立良好人际关系\n财富管理基础知识",
|
||||||
|
"batch.topics_help": "每行一个视频主题，AI会根据主题自动生成文案",
|
||||||
|
"batch.count_success": "✅ 识别到 {count} 个主题",
|
||||||
|
"batch.count_error": "❌ 批量数量超过限制（最多100个），当前: {count}",
|
||||||
|
"batch.preview_title": "📋 预览主题列表",
|
||||||
|
"batch.title_prefix_label": "标题前缀（可选）",
|
||||||
|
"batch.title_prefix_placeholder": "例如：知识分享",
|
||||||
|
"batch.title_prefix_help": "最终标题格式：{标题前缀} - {主题}，如：知识分享 - 为什么要养成阅读习惯",
|
||||||
|
"batch.n_scenes_label": "分镜数（所有视频统一）",
|
||||||
|
"batch.n_scenes_help": "每个视频的分镜数量，所有视频使用相同设置",
|
||||||
|
"batch.n_scenes_caption": "分镜数：{n}",
|
||||||
|
"batch.config_info": "其他配置：TTS语音、视频模板、图像工作流等配置将使用右侧栏的设置，所有视频统一",
|
||||||
|
"batch.no_topics": "⚠️ 请先在左侧输入批量主题（每行一个）",
|
||||||
|
"batch.prepare_info": "📊 准备生成 {count} 个视频（使用相同配置）",
|
||||||
|
"batch.estimated_time": "⏱️ 预估总耗时: 约 {minutes} 分钟",
|
||||||
|
"batch.generate_button": "🚀 批量生成 {count} 个视频",
|
||||||
|
"batch.generate_help": "⚠️ 批量生成期间请保持页面打开，不要关闭浏览器",
|
||||||
|
"batch.overall_progress": "整体进度",
|
||||||
|
"batch.current_task": "当前任务",
|
||||||
|
"batch.completed": "批量生成完成！",
|
||||||
|
"batch.results_title": "📊 批量生成结果",
|
||||||
|
"batch.total": "总数",
|
||||||
|
"batch.success": "成功",
|
||||||
|
"batch.failed": "失败",
|
||||||
|
"batch.total_time": "总耗时",
|
||||||
|
"batch.minutes": "分",
|
||||||
|
"batch.seconds": "秒",
|
||||||
|
"batch.success_message": "✅ 批量生成完成！所有视频已保存到历史记录。",
|
||||||
|
"batch.view_in_history": "💡 提示：可以在「📚 历史记录」页面查看所有生成的视频。",
|
||||||
|
"batch.goto_history": "前往历史记录页面",
|
||||||
|
"batch.failed_list": "❌ 失败的任务",
|
||||||
|
"batch.task": "任务",
|
||||||
|
"batch.error": "错误信息",
|
||||||
|
"batch.error_detail": "查看详细错误堆栈"
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|||||||
164
web/utils/batch_manager.py
Normal file
164
web/utils/batch_manager.py
Normal file
@@ -0,0 +1,164 @@
|
|||||||
|
# Copyright (C) 2025 AIDC-AI
|
||||||
|
#
|
||||||
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
# you may not use this file except in compliance with the License.
|
||||||
|
# You may obtain a copy of the License at
|
||||||
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
# Unless required by applicable law or agreed to in writing, software
|
||||||
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
# See the License for the specific language governing permissions and
|
||||||
|
# limitations under the License.
|
||||||
|
|
||||||
|
"""
|
||||||
|
Lightweight batch manager for Streamlit (Simplified YAGNI version)
|
||||||
|
"""
|
||||||
|
import time
|
||||||
|
import traceback
|
||||||
|
from typing import List, Dict, Any, Optional, Callable
|
||||||
|
from loguru import logger
|
||||||
|
|
||||||
|
|
||||||
|
class SimpleBatchManager:
|
||||||
|
"""
|
||||||
|
Ultra-simple batch manager following YAGNI principle
|
||||||
|
|
||||||
|
Design principles:
|
||||||
|
1. Only supports "AI generate content" mode
|
||||||
|
2. Same config for all videos, only topics differ
|
||||||
|
3. No CSV, no complex validation, just loop and execute
|
||||||
|
"""
|
||||||
|
|
||||||
|
def __init__(self):
|
||||||
|
self.results = []
|
||||||
|
self.errors = []
|
||||||
|
self.current_index = 0
|
||||||
|
self.total_count = 0
|
||||||
|
|
||||||
|
def execute_batch(
|
||||||
|
self,
|
||||||
|
pixelle_video,
|
||||||
|
topics: List[str],
|
||||||
|
shared_config: Dict[str, Any],
|
||||||
|
overall_progress_callback: Optional[Callable] = None,
|
||||||
|
task_progress_callback_factory: Optional[Callable] = None
|
||||||
|
) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
Execute batch generation with shared config
|
||||||
|
|
||||||
|
Args:
|
||||||
|
pixelle_video: PixelleVideoCore instance
|
||||||
|
topics: List of topics (one per video)
|
||||||
|
shared_config: Shared configuration for all videos
|
||||||
|
overall_progress_callback: Callback for overall progress
|
||||||
|
task_progress_callback_factory: Factory function to create per-task callback
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
{
|
||||||
|
"results": [...],
|
||||||
|
"errors": [...],
|
||||||
|
"total_count": N,
|
||||||
|
"success_count": M,
|
||||||
|
"failed_count": K
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
self.results = []
|
||||||
|
self.errors = []
|
||||||
|
self.total_count = len(topics)
|
||||||
|
|
||||||
|
logger.info(f"Starting batch generation: {self.total_count} topics")
|
||||||
|
|
||||||
|
for idx, topic in enumerate(topics, 1):
|
||||||
|
self.current_index = idx
|
||||||
|
|
||||||
|
# Report overall progress
|
||||||
|
if overall_progress_callback:
|
||||||
|
overall_progress_callback(
|
||||||
|
current=idx,
|
||||||
|
total=self.total_count,
|
||||||
|
topic=topic
|
||||||
|
)
|
||||||
|
|
||||||
|
try:
|
||||||
|
logger.info(f"Task {idx}/{self.total_count} started: {topic}")
|
||||||
|
|
||||||
|
# Extract title_prefix from shared_config (not a valid parameter for generate_video)
|
||||||
|
title_prefix = shared_config.get("title_prefix")
|
||||||
|
|
||||||
|
# Build task params (merge topic with shared config, excluding title_prefix)
|
||||||
|
task_params = {
|
||||||
|
"text": topic, # Topic as input
|
||||||
|
"mode": "generate", # Fixed mode
|
||||||
|
}
|
||||||
|
|
||||||
|
# Merge shared config, excluding title_prefix
|
||||||
|
for key, value in shared_config.items():
|
||||||
|
if key != "title_prefix":
|
||||||
|
task_params[key] = value
|
||||||
|
|
||||||
|
# Generate title using title_prefix
|
||||||
|
if title_prefix:
|
||||||
|
task_params["title"] = f"{title_prefix} - {topic}"
|
||||||
|
else:
|
||||||
|
# Use topic as title
|
||||||
|
task_params["title"] = topic
|
||||||
|
|
||||||
|
# Add per-task progress callback
|
||||||
|
if task_progress_callback_factory:
|
||||||
|
task_params["progress_callback"] = task_progress_callback_factory(idx, topic)
|
||||||
|
|
||||||
|
# Execute generation
|
||||||
|
from web.utils.async_helpers import run_async
|
||||||
|
result = run_async(pixelle_video.generate_video(**task_params))
|
||||||
|
|
||||||
|
# Extract task_id from video_path (e.g., output/20251118_173821_f96a/final.mp4)
|
||||||
|
from pathlib import Path
|
||||||
|
task_id = Path(result.video_path).parent.name
|
||||||
|
|
||||||
|
# Record success
|
||||||
|
self.results.append({
|
||||||
|
"index": idx,
|
||||||
|
"topic": topic,
|
||||||
|
"task_id": task_id,
|
||||||
|
"video_path": result.video_path,
|
||||||
|
"status": "success"
|
||||||
|
})
|
||||||
|
|
||||||
|
logger.info(f"Task {idx}/{self.total_count} completed: {result.video_path}")
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
# Record error but continue
|
||||||
|
error_msg = str(e)
|
||||||
|
error_trace = traceback.format_exc()
|
||||||
|
|
||||||
|
logger.error(f"Task {idx}/{self.total_count} failed: {error_msg}")
|
||||||
|
logger.debug(f"Error traceback:\n{error_trace}")
|
||||||
|
|
||||||
|
self.errors.append({
|
||||||
|
"index": idx,
|
||||||
|
"topic": topic,
|
||||||
|
"error": error_msg,
|
||||||
|
"traceback": error_trace,
|
||||||
|
"status": "failed"
|
||||||
|
})
|
||||||
|
|
||||||
|
# Continue to next task
|
||||||
|
continue
|
||||||
|
|
||||||
|
success_count = len(self.results)
|
||||||
|
failed_count = len(self.errors)
|
||||||
|
|
||||||
|
logger.info(
|
||||||
|
f"Batch generation completed: "
|
||||||
|
f"{success_count}/{self.total_count} succeeded, "
|
||||||
|
f"{failed_count} failed"
|
||||||
|
)
|
||||||
|
|
||||||
|
return {
|
||||||
|
"results": self.results,
|
||||||
|
"errors": self.errors,
|
||||||
|
"total_count": self.total_count,
|
||||||
|
"success_count": success_count,
|
||||||
|
"failed_count": failed_count
|
||||||
|
}
|
||||||
|
|
||||||
Reference in New Issue
Block a user