diff --git a/app/services/SDP/generate_script_short.py b/app/services/SDP/generate_script_short.py
index c8c062a..07108e5 100644
--- a/app/services/SDP/generate_script_short.py
+++ b/app/services/SDP/generate_script_short.py
@@ -1,6 +1,8 @@
"""
视频脚本生成pipeline，串联各个处理步骤
"""
+import json
+import os
from typing import Any, Dict, Optional
from loguru import logger
@@ -16,6 +18,10 @@ def generate_script_result(
base_url: str = None,
custom_clips: int = 5,
provider: str = None,
+ video_paths=None,
+ plot_analysis: Optional[str] = None,
+ short_name: str = "",
+ drama_genre: str = "",
*,
srt_path: Optional[str] = None,
subtitle_content: Optional[str] = None,
@@ -30,6 +36,10 @@ def generate_script_result(
base_url: API基础URL，可选
custom_clips: 自定义片段数量，默认5
provider: LLM服务提供商，可选
+ video_paths: 原始视频路径列表，用于生成 video_id/video_name
+ plot_analysis: 已完成的剧情理解文本，提供时会跳过混剪内部剧情理解
+ short_name: 短剧名称
+ drama_genre: 短剧类型
srt_path: 字幕文件路径（向后兼容）
subtitle_content: 字幕文本内容
subtitle_file_path: 字幕文件路径（推荐）
@@ -56,10 +66,23 @@ def generate_script_result(
provider=provider,
srt_path=resolved_path,
subtitle_content=resolved_content,
+ plot_analysis=plot_analysis,
+ video_paths=video_paths,
+ short_name=short_name,
+ drama_genre=drama_genre,
)
- adjusted_results = openai_analysis['plot_points']
- final_script = merge_script(adjusted_results, output_path)
+ if openai_analysis.get("script_items"):
+ final_script = openai_analysis["script_items"]
+ if not output_path or not str(output_path).strip():
+ raise ValueError("output_path不能为空")
+ os.makedirs(os.path.dirname(str(output_path)) or ".", exist_ok=True)
+ with open(output_path, "w", encoding="utf-8") as f:
+ json.dump(final_script, f, ensure_ascii=False, indent=4)
+ logger.info(f"短剧混剪脚本生成完成：{output_path}")
+ else:
+ adjusted_results = openai_analysis['plot_points']
+ final_script = merge_script(adjusted_results, output_path, video_paths=video_paths)
return {"status": "success", "script": final_script}
@@ -79,6 +102,10 @@ def generate_script(
base_url: str = None,
custom_clips: int = 5,
provider: str = None,
+ video_paths=None,
+ plot_analysis: Optional[str] = None,
+ short_name: str = "",
+ drama_genre: str = "",
*,
subtitle_content: Optional[str] = None,
subtitle_file_path: Optional[str] = None,
@@ -93,6 +120,10 @@ def generate_script(
base_url: API基础URL，可选
custom_clips: 自定义片段数量，默认5
provider: LLM服务提供商，可选
+ video_paths: 原始视频路径列表，用于生成 video_id/video_name
+ plot_analysis: 已完成的剧情理解文本
+ short_name: 短剧名称
+ drama_genre: 短剧类型
subtitle_content: 字幕文本内容（可选）
subtitle_file_path: 字幕文件路径（推荐使用，可选）
@@ -110,6 +141,10 @@ def generate_script(
base_url=base_url,
custom_clips=custom_clips,
provider=provider,
+ video_paths=video_paths,
+ plot_analysis=plot_analysis,
+ short_name=short_name,
+ drama_genre=drama_genre,
srt_path=srt_path,
subtitle_content=subtitle_content,
subtitle_file_path=subtitle_file_path,
diff --git a/app/services/SDP/utils/step1_subtitle_analyzer_openai.py b/app/services/SDP/utils/step1_subtitle_analyzer_openai.py
index 2d7a7e7..71f5f7d 100644
--- a/app/services/SDP/utils/step1_subtitle_analyzer_openai.py
+++ b/app/services/SDP/utils/step1_subtitle_analyzer_openai.py
@@ -1,11 +1,16 @@
"""
使用统一LLM服务，分析字幕文件，返回剧情梗概和爆点
"""
+import os
import traceback
import json
from loguru import logger
from app.services.subtitle_text import has_timecodes, normalize_subtitle_text, read_subtitle_text
+from app.services.short_drama_narration_validation import (
+ build_subtitle_index,
+ parse_script_timestamp_range,
+)
# 导入新的提示词管理系统
from app.services.prompts import PromptManager
# 导入统一LLM服务
@@ -14,6 +19,176 @@ from app.services.llm.unified_service import UnifiedLLMService
from app.services.llm.migration_adapter import _run_async_safely
+def _normalize_paths(paths):
+ if isinstance(paths, str):
+ paths = [paths]
+ if not paths:
+ return []
+
+ normalized_paths = []
+ seen = set()
+ for path in paths:
+ if not isinstance(path, str):
+ continue
+ path = path.strip()
+ if not path or path in seen:
+ continue
+ normalized_paths.append(path)
+ seen.add(path)
+ return normalized_paths
+
+
+def _coerce_positive_int(value):
+ try:
+ number = int(value)
+ except (TypeError, ValueError):
+ return None
+ return number if number > 0 else None
+
+
+def _match_video_id_by_name(video_name, video_paths):
+ video_name = os.path.basename(str(video_name or "").strip())
+ if not video_name:
+ return None
+
+ for index, video_path in enumerate(video_paths, start=1):
+ if os.path.basename(video_path) == video_name:
+ return index
+ return None
+
+
+def _default_video_name(video_id, video_paths):
+ if 1 <= video_id <= len(video_paths):
+ return os.path.basename(video_paths[video_id - 1])
+ return ""
+
+
+def _normalize_short_mix_items(items, video_paths, subtitle_content):
+ if not isinstance(items, list) or not items:
+ raise ValueError("短剧混剪脚本 items 必须是非空数组")
+
+ normalized_video_paths = _normalize_paths(video_paths)
+ subtitle_index = build_subtitle_index(subtitle_content, normalized_video_paths)
+ available_video_ids = {cue.video_id for cue in subtitle_index}
+ if normalized_video_paths:
+ available_video_ids.update(range(1, len(normalized_video_paths) + 1))
+
+ normalized_items = []
+ ranges_by_video = {}
+ for index, raw_item in enumerate(items, start=1):
+ if not isinstance(raw_item, dict):
+ raise ValueError(f"第 {index} 个混剪片段必须是对象")
+
+ item_id = index
+ video_id = (
+ _match_video_id_by_name(raw_item.get("video_name") or raw_item.get("source_video"), normalized_video_paths)
+ or _coerce_positive_int(raw_item.get("video_id") or raw_item.get("video_index"))
+ or 1
+ )
+ if available_video_ids and video_id not in available_video_ids:
+ raise ValueError(f"片段 {item_id} 的 video_id={video_id} 不在已选视频范围内")
+
+ try:
+ start_ms, end_ms, timestamp = parse_script_timestamp_range(raw_item.get("timestamp", ""))
+ except ValueError as exc:
+ raise ValueError(f"片段 {item_id}: {exc}") from exc
+ if start_ms >= end_ms:
+ raise ValueError(f"片段 {item_id} 的开始时间必须早于结束时间")
+
+ video_cues = [cue for cue in subtitle_index if cue.video_id == video_id]
+ if video_cues:
+ min_start = min(cue.start_ms for cue in video_cues)
+ max_end = max(cue.end_ms for cue in video_cues)
+ if start_ms < min_start or end_ms > max_end:
+ raise ValueError(f"片段 {item_id} 的时间戳不在视频 {video_id} 的字幕范围内")
+ if not any(start_ms < cue.end_ms and end_ms > cue.start_ms for cue in video_cues):
+ raise ValueError(f"片段 {item_id} 的时间戳没有命中视频 {video_id} 的字幕内容")
+
+ picture = str(
+ raw_item.get("picture")
+ or raw_item.get("title")
+ or raw_item.get("narrative_function")
+ or raw_item.get("intent")
+ or raw_item.get("story_role")
+ or ""
+ ).strip()
+ if not picture:
+ raise ValueError(f"片段 {item_id} 的 picture 不能为空")
+
+ video_name = str(raw_item.get("video_name") or "").strip()
+ if normalized_video_paths:
+ video_name = _default_video_name(video_id, normalized_video_paths)
+
+ normalized_items.append(
+ {
+ "_id": item_id,
+ "video_id": video_id,
+ "video_name": video_name,
+ "timestamp": timestamp,
+ "picture": picture,
+ "narration": f"播放原片{item_id}",
+ "OST": 1,
+ }
+ )
+ ranges_by_video.setdefault(video_id, []).append((start_ms, end_ms, item_id))
+
+ for video_id, ranges in ranges_by_video.items():
+ ranges = sorted(ranges, key=lambda item: (item[0], item[1], item[2]))
+ previous_start, previous_end, previous_id = ranges[0]
+ for start_ms, end_ms, item_id in ranges[1:]:
+ if start_ms < previous_end:
+ raise ValueError(f"视频 {video_id} 的片段 {item_id} 与片段 {previous_id} 时间戳重叠")
+ if end_ms > previous_end:
+ previous_start, previous_end, previous_id = start_ms, end_ms, item_id
+
+ return normalized_items
+
+
+def _generate_short_mix_script(
+ *,
+ subtitle_content,
+ plot_analysis,
+ custom_clips,
+ provider,
+ model_name,
+ api_key,
+ base_url,
+ video_paths=None,
+ short_name="",
+ drama_genre="",
+):
+ script_generation_prompt = PromptManager.get_prompt(
+ category="short_drama_editing",
+ name="script_generation",
+ parameters={
+ "drama_name": short_name or "短剧",
+ "drama_genre": drama_genre or "短剧",
+ "plot_analysis": plot_analysis,
+ "subtitle_content": subtitle_content,
+ "custom_clips": int(custom_clips or 5),
+ },
+ )
+
+ response = _run_async_safely(
+ UnifiedLLMService.generate_text,
+ prompt=script_generation_prompt,
+ provider=provider,
+ model=model_name,
+ api_key=api_key,
+ base_url=base_url,
+ temperature=0.1,
+ max_tokens=4000,
+ )
+
+ from webui.tools.generate_short_summary import parse_and_fix_json
+ script_data = parse_and_fix_json(response)
+ if not script_data:
+ raise ValueError("无法解析短剧混剪脚本JSON")
+
+ script_items = script_data.get("items") or script_data.get("segments") or script_data.get("plot_points")
+ return _normalize_short_mix_items(script_items, video_paths, subtitle_content)
+
+
def analyze_subtitle(
model_name: str,
api_key: str = None,
@@ -21,7 +196,11 @@ def analyze_subtitle(
custom_clips: int = 5,
provider: str = None,
srt_path: str = None,
- subtitle_content: str = None
+ subtitle_content: str = None,
+ plot_analysis: str = None,
+ video_paths=None,
+ short_name: str = "",
+ drama_genre: str = "",
) -> dict:
"""分析字幕内容，返回完整的分析结果
@@ -33,6 +212,10 @@ def analyze_subtitle(
provider (str, optional): LLM服务提供商. Defaults to None.
srt_path (str, optional): SRT字幕文件路径（与subtitle_content二选一）
subtitle_content (str, optional): SRT字幕文本内容（与srt_path二选一）
+ plot_analysis (str, optional): 已审核/缓存的剧情理解文本，提供时直接进入混剪脚本生成
+ video_paths (list, optional): 原始视频路径列表，用于补齐 video_id/video_name
+ short_name (str, optional): 短剧名称
+ drama_genre (str, optional): 短剧类型
Returns:
dict: 包含剧情梗概和结构化的时间段分析的字典
@@ -87,6 +270,27 @@ def analyze_subtitle(
logger.info(f"使用LLM服务分析字幕，提供商: {provider}, 模型: {model_name}")
+ if plot_analysis and str(plot_analysis).strip():
+ logger.info("使用已有剧情理解直接生成短剧混剪脚本")
+ script_items = _generate_short_mix_script(
+ subtitle_content=subtitle_content,
+ plot_analysis=str(plot_analysis).strip(),
+ custom_clips=custom_clips,
+ provider=provider,
+ model_name=model_name,
+ api_key=api_key,
+ base_url=base_url,
+ video_paths=video_paths,
+ short_name=short_name,
+ drama_genre=drama_genre,
+ )
+ return {
+ "summary": str(plot_analysis).strip(),
+ "plot_titles": [],
+ "plot_points": [],
+ "script_items": script_items,
+ }
+
# 使用新的提示词管理系统
subtitle_analysis_prompt = PromptManager.get_prompt(
category="short_drama_editing",
@@ -120,6 +324,28 @@ def analyze_subtitle(
logger.info(f"字幕分析完成，找到 {len(summary_data.get('plot_titles', []))} 个关键情节")
logger.debug(json.dumps(summary_data, indent=4, ensure_ascii=False))
+ try:
+ script_items = _generate_short_mix_script(
+ subtitle_content=subtitle_content,
+ plot_analysis=json.dumps(summary_data, ensure_ascii=False, indent=2),
+ custom_clips=custom_clips,
+ provider=provider,
+ model_name=model_name,
+ api_key=api_key,
+ base_url=base_url,
+ video_paths=video_paths,
+ short_name=short_name,
+ drama_genre=drama_genre,
+ )
+ return {
+ "summary": summary_data.get("summary", ""),
+ "plot_titles": summary_data.get("plot_titles", []),
+ "plot_points": [],
+ "script_items": script_items,
+ }
+ except Exception as direct_script_error:
+ logger.warning(f"直接生成短剧混剪脚本失败，回退到时间段定位: {direct_script_error}")
+
# 构建爆点标题列表
plot_titles_text = ""
logger.info(f"找到 {len(summary_data.get('plot_titles', []))} 个片段")
diff --git a/app/services/SDP/utils/step5_merge_script.py b/app/services/SDP/utils/step5_merge_script.py
index a4d2802..a385bd4 100644
--- a/app/services/SDP/utils/step5_merge_script.py
+++ b/app/services/SDP/utils/step5_merge_script.py
@@ -8,7 +8,8 @@ from typing import Dict, List
def merge_script(
plot_points: List[Dict],
- output_path: str
+ output_path: str,
+ video_paths=None,
):
"""合并生成最终脚本
@@ -19,6 +20,10 @@ def merge_script(
Returns:
str: 最终合并的脚本
"""
+ if isinstance(video_paths, str):
+ video_paths = [video_paths]
+ video_paths = [path for path in (video_paths or []) if isinstance(path, str) and path.strip()]
+
# 创建包含所有信息的临时列表
final_script = []
@@ -29,9 +34,12 @@ def merge_script(
"_id": number,
"timestamp": plot_point["timestamp"],
"picture": plot_point["picture"],
- "narration": f"播放原生_{os.urandom(4).hex()}",
+ "narration": f"播放原片{number}",
"OST": 1, # OST=0 仅保留解说 OST=2 保留解说和原声
}
+ if video_paths:
+ script_item["video_id"] = 1
+ script_item["video_name"] = os.path.basename(video_paths[0])
final_script.append(script_item)
number += 1
diff --git a/app/services/prompts/short_drama_editing/__init__.py b/app/services/prompts/short_drama_editing/__init__.py
index 0f3bd04..2d53ed5 100644
--- a/app/services/prompts/short_drama_editing/__init__.py
+++ b/app/services/prompts/short_drama_editing/__init__.py
@@ -11,6 +11,7 @@
from .subtitle_analysis import SubtitleAnalysisPrompt
from .plot_extraction import PlotExtractionPrompt
+from .script_generation import ScriptGenerationPrompt
from ..manager import PromptManager
@@ -25,9 +26,14 @@ def register_prompts():
plot_extraction_prompt = PlotExtractionPrompt()
PromptManager.register_prompt(plot_extraction_prompt, is_default=True)
+ # 注册混剪脚本生成提示词
+ script_generation_prompt = ScriptGenerationPrompt()
+ PromptManager.register_prompt(script_generation_prompt, is_default=True)
+
__all__ = [
"SubtitleAnalysisPrompt",
- "PlotExtractionPrompt",
+ "PlotExtractionPrompt",
+ "ScriptGenerationPrompt",
"register_prompts"
]
diff --git a/app/services/prompts/short_drama_editing/script_generation.py b/app/services/prompts/short_drama_editing/script_generation.py
new file mode 100644
index 0000000..ca9bbd6
--- /dev/null
+++ b/app/services/prompts/short_drama_editing/script_generation.py
@@ -0,0 +1,113 @@
+#!/usr/bin/env python
+# -*- coding: UTF-8 -*-
+
+"""
+@Project: 短剧混剪-剪辑脚本生成
+@File : script_generation.py
+@Description: 基于剧情理解和字幕直接生成短剧混剪脚本
+"""
+
+from ..base import ParameterizedPrompt, PromptMetadata, ModelType, OutputFormat
+
+
+class ScriptGenerationPrompt(ParameterizedPrompt):
+ """短剧混剪脚本生成提示词"""
+
+ def __init__(self):
+ metadata = PromptMetadata(
+ name="script_generation",
+ category="short_drama_editing",
+ version="v1.0",
+ description="基于剧情理解和原始字幕直接生成短剧混剪脚本，不生成解说文案",
+ model_type=ModelType.TEXT,
+ output_format=OutputFormat.JSON,
+ tags=["短剧", "混剪", "剪辑脚本", "时间戳", "多视频", "原声"],
+ parameters=[
+ "drama_name",
+ "drama_genre",
+ "plot_analysis",
+ "subtitle_content",
+ "custom_clips",
+ ],
+ )
+ super().__init__(
+ metadata,
+ required_parameters=["plot_analysis", "subtitle_content", "custom_clips"],
+ )
+
+ self._system_prompt = (
+ "你是一名专业短剧混剪剪辑师。你必须严格输出JSON，"
+ "只从字幕中选择真实存在的可剪辑原声片段，不生成解说文案。"
+ )
+
+ def get_template(self) -> str:
+ return """# 短剧混剪脚本生成任务
+
+## 目标
+根据剧情理解和原始字幕，为短剧《${drama_name}》生成一份可直接裁剪的混剪 JSON 脚本。
+
+短剧混剪与短剧解说的区别：
+- 不生成解说文案。
+- 不需要用户审核旁白。
+- 直接从剧情理解中选择能串成故事线的原片片段。
+- 每个片段默认保留原声，OST 必须为 1。
+
+## 用户选择的短剧类型
+
+${drama_genre}
+
+
+## 需要生成的片段数量
+
+${custom_clips}
+
+
+## 剧情理解材料
+
+${plot_analysis}
+
+
+## 原始字幕（含视频编号和局部时间戳）
+
+${subtitle_content}
+
+
+## 选择原则
+1. 选择 ${custom_clips} 个片段，尽量形成“开端 -> 冲突升级 -> 高潮/反转 -> 悬念或阶段结果”的完整观看路径。
+2. 只能使用原始字幕中真实存在的视频编号、视频文件名和时间范围。
+3. timestamp 必须是对应 video_id 内部的局部时间戳，格式为 "HH:MM:SS,mmm-HH:MM:SS,mmm"。
+4. 同一个 video_id 内的片段不得交叉或重叠；整体顺序要服务剧情理解，单个视频内尽量按时间顺序。
+5. 优先选择关键对白、身份揭露、情绪爆发、反转、冲突升级和能看懂前因后果的片段。
+6. 单个片段建议 5-45 秒；不要只截 1-2 秒的孤立金句，也不要截过长的流水账。
+7. 如果两个关键剧情之间跳跃太大，优先选择包含上下文的连续时间段，而不是硬切爆点。
+8. picture 要描述画面中人物、动作、情绪、场景和该片段的剧情作用。
+9. narration 字段必须写成“播放原片+_id”，例如 _id 为 3 时写“播放原片3”。
+10. OST 必须为 1，表示保留原片原声。
+
+## 字段规则
+- _id：从 1 开始连续递增。
+- video_id：来自字幕分段标题，例如“视频 2”就填 2；单视频填 1。
+- video_name：对应视频文件名，必须从字幕分段标题提取；单视频也要填写。
+- timestamp：必须来自对应视频字幕时间轴。
+- picture：非空字符串。
+- narration：固定为“播放原片+_id”。
+- OST：固定为 1。
+
+## 输出格式
+只输出严格 JSON：
+
+{
+ "items": [
+ {
+ "_id": 1,
+ "video_id": 1,
+ "video_name": "1.mp4",
+ "timestamp": "00:00:01,000-00:00:12,500",
+ "picture": "女主被当众羞辱仍然强撑，冲突正式爆发，为后续逆袭埋下情绪钩子",
+ "narration": "播放原片1",
+ "OST": 1
+ }
+ ]
+}
+
+现在请生成短剧混剪脚本。"""
diff --git a/webui/components/script_settings.py b/webui/components/script_settings.py
index ea345a6..6eb6193 100644
--- a/webui/components/script_settings.py
+++ b/webui/components/script_settings.py
@@ -26,6 +26,7 @@ from webui.tools.generate_short_summary import (
SCRIPT_TABLE_BASE_COLUMNS = ["_id", "video_id", "video_name", "timestamp", "picture", "narration", "OST"]
+SCRIPT_TABLE_TEXT_COLUMNS = {"video_name", "timestamp", "picture", "narration", "value"}
MODE_FILE = "file_selection"
MODE_AUTO = "auto"
MODE_SHORT = "short"
@@ -666,16 +667,42 @@ def render_short_generate_options(tr):
渲染Short Generate模式下的特殊选项
在Short Generate模式下，替换原有的输入框为自定义片段选项
"""
- summary_narration_panel(tr, SUMMARY_MODE_CONFIGS[MODE_SHORT_SUMMARY])
- # 显示自定义片段数量选择器
- custom_clips = st.number_input(
- tr("自定义片段"),
- min_value=1,
- max_value=20,
- value=st.session_state.get('custom_clips', 5),
- help=tr("设置需要生成的短视频片段数量"),
- key="custom_clips_input"
- )
+ summary_config = SUMMARY_MODE_CONFIGS[MODE_SHORT_SUMMARY]
+ summary_narration_panel(tr, summary_config)
+
+ type_option_key = _summary_state_key(summary_config, "type_option")
+ custom_type_key = _summary_state_key(summary_config, "custom_type")
+ type_options = [code for code, _ in summary_config["type_options"]]
+ if st.session_state.get(type_option_key) not in type_options:
+ st.session_state[type_option_key] = summary_config["default_type"]
+
+ show_custom_type = st.session_state.get(type_option_key, summary_config["default_type"]) == "custom"
+ option_cols = st.columns([1.1, 1.1, 1], vertical_alignment="bottom") if show_custom_type else st.columns([1.1, 1], vertical_alignment="bottom")
+ with option_cols[0]:
+ st.selectbox(
+ tr(summary_config["type_label_key"]),
+ options=type_options,
+ format_func=lambda code: tr(dict(summary_config["type_options"]).get(code, code)),
+ key=type_option_key,
+ )
+ option_index = 1
+ if show_custom_type:
+ with option_cols[option_index]:
+ st.text_input(
+ tr(summary_config["custom_type_label_key"]),
+ key=custom_type_key,
+ placeholder=tr(summary_config["custom_type_placeholder_key"]),
+ )
+ option_index += 1
+ with option_cols[option_index]:
+ custom_clips = st.number_input(
+ tr("自定义片段"),
+ min_value=1,
+ max_value=20,
+ value=st.session_state.get('custom_clips', 5),
+ help=tr("设置需要生成的短视频片段数量"),
+ key="custom_clips_input"
+ )
st.session_state['custom_clips'] = custom_clips
@@ -729,6 +756,7 @@ def summary_narration_panel(tr, summary_config):
plot_analysis_key = _summary_state_key(summary_config, "plot_analysis")
plot_source_key = _summary_state_key(summary_config, "plot_analysis_subtitle_path")
plot_signature_key = _summary_state_key(summary_config, "plot_analysis_signature")
+ pending_plot_key = _summary_state_key(summary_config, "pending_plot_analysis")
st.markdown(
f"""
@@ -815,6 +843,15 @@ def summary_narration_panel(tr, summary_config):
st.session_state[plot_analysis_key] = ""
st.session_state[plot_source_key] = ""
st.session_state[plot_signature_key] = ""
+ st.session_state.pop(pending_plot_key, None)
+ else:
+ pending_plot = st.session_state.pop(pending_plot_key, None)
+ if isinstance(pending_plot, dict) and pending_plot.get("signature") == current_signature:
+ pending_analysis = str(pending_plot.get("plot_analysis") or "")
+ if pending_analysis:
+ st.session_state[plot_analysis_key] = pending_analysis
+ st.session_state[plot_source_key] = pending_plot.get("subtitle_path") or current_subtitle_path
+ st.session_state[plot_signature_key] = current_signature
if analyze_plot_clicked:
with st.spinner(tr("Analyzing plot...")):
@@ -1003,10 +1040,17 @@ def _script_json_to_table(script_data):
{"value": json.dumps(item, ensure_ascii=False)}
for item in script_data
]
- return pd.DataFrame(rows, columns=["value"])
+ return _normalize_script_table_types(pd.DataFrame(rows, columns=["value"]))
columns = _ordered_script_columns(script_data)
- return pd.DataFrame(script_data, columns=columns)
+ return _normalize_script_table_types(pd.DataFrame(script_data, columns=columns))
+
+
+def _normalize_script_table_types(table_data):
+ for column in SCRIPT_TABLE_TEXT_COLUMNS:
+ if column in table_data.columns:
+ table_data[column] = table_data[column].where(table_data[column].notna(), "").astype(str).astype("object")
+ return table_data
def _normalize_script_table_value(column, value):
@@ -1723,8 +1767,66 @@ def render_script_buttons(tr, params):
generate_script_docu(params, tr)
elif script_path == "short":
# 执行 短剧混剪 脚本生成
+ summary_config = SUMMARY_MODE_CONFIGS[MODE_SHORT_SUMMARY]
+ type_option_key = _summary_state_key(summary_config, "type_option")
+ custom_type_key = _summary_state_key(summary_config, "custom_type")
+ web_search_key = _summary_state_key(summary_config, "web_search_enabled")
+ plot_analysis_key = _summary_state_key(summary_config, "plot_analysis")
+ plot_source_key = _summary_state_key(summary_config, "plot_analysis_subtitle_path")
+ plot_signature_key = _summary_state_key(summary_config, "plot_analysis_signature")
+ pending_plot_key = _summary_state_key(summary_config, "pending_plot_analysis")
+ if (
+ st.session_state.get(type_option_key) == "custom"
+ and not str(st.session_state.get(custom_type_key, '') or '').strip()
+ ):
+ st.error(tr(summary_config["custom_type_empty_key"]))
+ st.stop()
+
+ subtitle_paths = _selected_subtitle_paths()
+ subtitle_path = subtitle_paths[0] if subtitle_paths else None
+ video_theme = st.session_state.get('video_theme')
+ web_search_enabled = bool(st.session_state.get(web_search_key, False))
+ current_signature = _short_drama_plot_analysis_signature(
+ subtitle_paths,
+ video_theme,
+ web_search_enabled,
+ _selected_video_paths(),
+ )
+ plot_analysis = ""
+ if st.session_state.get(plot_signature_key) == current_signature:
+ plot_analysis = st.session_state.get(plot_analysis_key, '')
+ elif (
+ not web_search_enabled
+ and st.session_state.get(plot_source_key) == subtitle_path
+ ):
+ plot_analysis = st.session_state.get(plot_analysis_key, '')
+
custom_clips = st.session_state.get('custom_clips')
- generate_script_short(tr, params, custom_clips)
+ short_result = generate_script_short(
+ tr,
+ params,
+ custom_clips,
+ subtitle_paths=subtitle_paths,
+ video_theme=video_theme,
+ temperature=st.session_state.get('temperature', 0.7),
+ plot_analysis=plot_analysis,
+ subtitle_content=st.session_state.get('subtitle_content', ''),
+ enable_web_search=web_search_enabled,
+ video_paths=_selected_video_paths(),
+ drama_genre=_resolve_short_drama_type(),
+ prompt_category=summary_config["prompt_category"],
+ search_keywords=summary_config["search_keywords"],
+ empty_title_message_key=summary_config["empty_title_message_key"],
+ web_search_context_description=summary_config["web_search_context_description"],
+ )
+ if short_result and short_result.get("plot_analysis"):
+ st.session_state[pending_plot_key] = {
+ "plot_analysis": short_result["plot_analysis"],
+ "subtitle_path": subtitle_path,
+ "signature": current_signature,
+ }
+ st.session_state[plot_source_key] = subtitle_path
+ st.session_state[plot_signature_key] = current_signature
else:
load_script(tr, script_path)
diff --git a/webui/tools/generate_script_short.py b/webui/tools/generate_script_short.py
index 5c7b43d..e01b921 100644
--- a/webui/tools/generate_script_short.py
+++ b/webui/tools/generate_script_short.py
@@ -8,9 +8,32 @@ from loguru import logger
from app.config import config
from app.services.upload_validation import ensure_existing_file, InputValidationError
from app.utils import utils
+from webui.tools.generate_short_summary import (
+ SHORT_DRAMA_PROMPT_CATEGORY,
+ SHORT_DRAMA_SEARCH_KEYWORDS,
+ _build_combined_subtitle_content,
+ _normalize_paths,
+ analyze_short_drama_plot,
+)
-def generate_script_short(tr, params, custom_clips=5):
+def generate_script_short(
+ tr,
+ params,
+ custom_clips=5,
+ subtitle_paths=None,
+ video_theme=None,
+ temperature=0.7,
+ plot_analysis=None,
+ subtitle_content=None,
+ enable_web_search=False,
+ video_paths=None,
+ drama_genre="逆袭/复仇",
+ prompt_category=SHORT_DRAMA_PROMPT_CATEGORY,
+ search_keywords=SHORT_DRAMA_SEARCH_KEYWORDS,
+ empty_title_message_key="Please enter short drama name before web search",
+ web_search_context_description="短剧名称、人物关系、剧情背景和公开剧情梗概",
+):
"""
生成短视频脚本
@@ -18,6 +41,14 @@ def generate_script_short(tr, params, custom_clips=5):
tr: 翻译函数
params: 视频参数对象
custom_clips: 自定义片段数量，默认为5
+ subtitle_paths: 已转写/上传/翻译/校准后的字幕路径列表
+ video_theme: 短剧名称
+ temperature: LLM温度
+ plot_analysis: 已完成的剧情理解文本
+ subtitle_content: 已合并的字幕文本
+ enable_web_search: 是否在剧情理解前联网搜索
+ video_paths: 原始视频路径列表
+ drama_genre: 用户选择的短剧类型
"""
progress_bar = st.progress(0)
status_text = st.empty()
@@ -33,38 +64,47 @@ def generate_script_short(tr, params, custom_clips=5):
with st.spinner(tr("Generating script...")):
# ========== 严格验证：必须上传视频和字幕（与短剧解说保持一致）==========
# 1. 验证视频文件
- video_path = getattr(params, "video_origin_path", None)
- if not video_path or not str(video_path).strip():
+ selected_video_paths = _normalize_paths(
+ video_paths
+ or getattr(params, "video_origin_paths", [])
+ or getattr(params, "video_origin_path", "")
+ )
+ if not selected_video_paths:
st.error(tr("Please select video file first"))
st.stop()
- try:
- ensure_existing_file(
- str(video_path),
- label=tr("Video"),
- allowed_exts=(".mp4", ".mov", ".avi", ".flv", ".mkv"),
- )
- except InputValidationError as e:
- st.error(str(e))
- st.stop()
+ for video_path in selected_video_paths:
+ try:
+ ensure_existing_file(
+ str(video_path),
+ label=tr("Video"),
+ allowed_exts=(".mp4", ".mov", ".avi", ".flv", ".mkv"),
+ )
+ except InputValidationError as e:
+ st.error(str(e))
+ st.stop()
# 2. 验证字幕文件（移除推断逻辑，必须上传）
- subtitle_path = st.session_state.get("subtitle_path")
- if not subtitle_path or not str(subtitle_path).strip():
+ subtitle_paths = _normalize_paths(subtitle_paths or st.session_state.get("subtitle_paths") or st.session_state.get("subtitle_path"))
+ if not subtitle_paths:
st.error(tr("Please upload subtitle file first"))
st.stop()
+ validated_subtitle_paths = []
try:
- subtitle_path = ensure_existing_file(
- str(subtitle_path),
- label=tr("Subtitle"),
- allowed_exts=(".srt",),
- )
+ for subtitle_path in subtitle_paths:
+ validated_subtitle_paths.append(
+ ensure_existing_file(
+ str(subtitle_path),
+ label=tr("Subtitle"),
+ allowed_exts=(".srt",),
+ )
+ )
except InputValidationError as e:
st.error(str(e))
st.stop()
- logger.info(f"使用用户上传的字幕文件: {subtitle_path}")
+ logger.info(f"使用用户处理后的字幕文件: {validated_subtitle_paths}")
# ========== 获取 LLM 配置 ==========
text_provider = config.app.get('text_llm_provider', 'gemini').lower()
@@ -80,18 +120,40 @@ def generate_script_short(tr, params, custom_clips=5):
update_progress(20, tr("Preparing script generation"))
+ subtitle_content = str(subtitle_content or "").strip() or _build_combined_subtitle_content(
+ validated_subtitle_paths,
+ selected_video_paths,
+ )
+ if not subtitle_content:
+ st.error(tr("Subtitle file is empty or unreadable"))
+ st.stop()
+
+ plot_analysis = str(plot_analysis or "").strip()
+ if not plot_analysis:
+ update_progress(35, tr("Analyzing subtitles with model..."))
+ plot_analysis = analyze_short_drama_plot(
+ validated_subtitle_paths,
+ temperature,
+ tr,
+ subtitle_content=subtitle_content,
+ short_name=video_theme,
+ enable_web_search=enable_web_search,
+ video_paths=selected_video_paths,
+ prompt_category=prompt_category,
+ search_keywords=search_keywords,
+ empty_title_message_key=empty_title_message_key,
+ web_search_context_description=web_search_context_description,
+ )
+ if not plot_analysis:
+ st.error(tr("Script generation failed check logs"))
+ st.stop()
+
# ========== 调用后端生成脚本 ==========
from app.services.SDP.generate_script_short import generate_script_result
output_path = os.path.join(utils.script_dir(), "merged_subtitle.json")
- subtitle_content = st.session_state.get("subtitle_content")
- subtitle_kwargs = (
- {"subtitle_content": str(subtitle_content)}
- if subtitle_content is not None and str(subtitle_content).strip()
- else {"subtitle_file_path": subtitle_path}
- )
-
+ update_progress(55, tr("Generating script..."))
result = generate_script_result(
api_key=text_api_key,
model_name=text_model,
@@ -99,7 +161,11 @@ def generate_script_short(tr, params, custom_clips=5):
base_url=text_base_url,
custom_clips=custom_clips,
provider=text_provider,
- **subtitle_kwargs,
+ subtitle_content=subtitle_content,
+ video_paths=selected_video_paths,
+ plot_analysis=plot_analysis,
+ short_name=video_theme or "",
+ drama_genre=drama_genre or "",
)
if result.get("status") != "success":
@@ -120,8 +186,14 @@ def generate_script_short(tr, params, custom_clips=5):
progress_bar.progress(100)
status_text.text(tr("Script generation completed!"))
st.success(tr("Video script generated successfully"))
+ return {
+ "script": st.session_state.get('video_clip_json', []),
+ "plot_analysis": plot_analysis,
+ "subtitle_content": subtitle_content,
+ }
except Exception as err:
progress_bar.progress(100)
st.error(f"{tr('Generation error')}: {str(err)}")
logger.exception(f"生成脚本时发生错误\n{traceback.format_exc()}")
+ return None