mirror of
https://github.com/linyqh/NarratoAI.git
synced 2026-06-17 12:52:15 +00:00
342fc15f3b
新增OmniVoice语音合成引擎全流程支持，包含配置项、WebUI界面与服务实现 集成Tavily联网搜索能力，支持短剧剧情分析前自动检索剧情背景信息 新增多视频源剪辑支持，完善脚本校验规则并重构剪辑逻辑适配多视频路径 重构LLM剧情分析Prompt，优化输出格式适配多场景与联网检索结果 调整streamlit版本至1.56.0修复兼容性问题 新增相关单元测试与多语言翻译，更新配置示例文件
213 lines
8.2 KiB
Python
213 lines
8.2 KiB
Python
"""
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输出格式验证器
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提供严格的输出格式验证机制，确保大模型输出符合预期格式
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"""
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import json
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import re
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from typing import Any, Dict, List, Optional, Union
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from loguru import logger
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from .exceptions import ValidationError
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class OutputValidator:
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"""输出格式验证器"""
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@staticmethod
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def validate_json_output(output: str, schema: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
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"""
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验证JSON输出格式
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Args:
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output: 待验证的输出字符串
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schema: JSON Schema (可选)
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Returns:
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解析后的JSON对象
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Raises:
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ValidationError: 验证失败时抛出
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"""
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try:
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# 清理输出字符串，移除可能的markdown代码块标记
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cleaned_output = OutputValidator._clean_json_output(output)
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# 解析JSON
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parsed_json = json.loads(cleaned_output)
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# 如果提供了schema，进行schema验证
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if schema:
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OutputValidator._validate_json_schema(parsed_json, schema)
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return parsed_json
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except json.JSONDecodeError as e:
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logger.error(f"JSON解析失败: {str(e)}")
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logger.error(f"原始输出: {output}")
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raise ValidationError(f"JSON格式无效: {str(e)}", "json_parse", output)
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except Exception as e:
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logger.error(f"JSON验证失败: {str(e)}")
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raise ValidationError(f"JSON验证失败: {str(e)}", "json_validation", output)
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@staticmethod
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def _clean_json_output(output: str) -> str:
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"""清理JSON输出，移除markdown标记等"""
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# 移除可能的markdown代码块标记
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output = re.sub(r'^```json\s*', '', output, flags=re.MULTILINE)
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output = re.sub(r'^```\s*$', '', output, flags=re.MULTILINE)
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output = re.sub(r'^```.*$', '', output, flags=re.MULTILINE)
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# 移除开头和结尾的```标记
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output = re.sub(r'^```', '', output)
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output = re.sub(r'```$', '', output)
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# 移除前后空白字符
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output = output.strip()
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return output
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@staticmethod
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def _validate_json_schema(data: Dict[str, Any], schema: Dict[str, Any]):
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"""验证JSON Schema (简化版本)"""
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# 这里可以集成jsonschema库进行更严格的验证
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# 目前实现基础的类型检查
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if "type" in schema:
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expected_type = schema["type"]
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if expected_type == "object" and not isinstance(data, dict):
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raise ValidationError(f"期望对象类型，实际为 {type(data)}", "schema_type")
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elif expected_type == "array" and not isinstance(data, list):
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raise ValidationError(f"期望数组类型，实际为 {type(data)}", "schema_type")
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if "required" in schema and isinstance(data, dict):
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for required_field in schema["required"]:
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if required_field not in data:
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raise ValidationError(f"缺少必需字段: {required_field}", "schema_required")
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@staticmethod
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def validate_narration_script(output: str) -> List[Dict[str, Any]]:
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"""
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验证解说文案输出格式
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Args:
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output: 待验证的解说文案输出
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Returns:
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解析后的解说文案列表
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Raises:
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ValidationError: 验证失败时抛出
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"""
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try:
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# 定义解说文案的JSON Schema
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narration_schema = {
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"type": "object",
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"required": ["items"],
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"properties": {
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"items": {
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"type": "array",
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"items": {
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"type": "object",
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"required": ["_id", "timestamp", "picture", "narration"],
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"properties": {
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"_id": {"type": "number"},
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"video_id": {"type": "number"},
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"video_name": {"type": "string"},
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"timestamp": {"type": "string"},
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"picture": {"type": "string"},
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"narration": {"type": "string"},
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"OST": {"type": "number"}
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}
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}
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}
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}
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}
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# 验证JSON格式
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parsed_data = OutputValidator.validate_json_output(output, narration_schema)
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# 提取items数组
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items = parsed_data.get("items", [])
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# 验证每个item的具体内容
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for i, item in enumerate(items):
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OutputValidator._validate_narration_item(item, i)
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logger.info(f"解说文案验证成功，共 {len(items)} 个片段")
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return items
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except ValidationError:
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raise
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except Exception as e:
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logger.error(f"解说文案验证失败: {str(e)}")
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raise ValidationError(f"解说文案验证失败: {str(e)}", "narration_validation", output)
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@staticmethod
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def _validate_narration_item(item: Dict[str, Any], index: int):
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"""验证单个解说文案项目"""
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# 验证时间戳格式
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timestamp = item.get("timestamp", "")
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if not re.match(r'\d{2}:\d{2}:\d{2},\d{3}-\d{2}:\d{2}:\d{2},\d{3}', timestamp):
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raise ValidationError(f"第{index+1}项时间戳格式无效: {timestamp}", "timestamp_format")
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# 验证内容不为空
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if not item.get("picture", "").strip():
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raise ValidationError(f"第{index+1}项画面描述不能为空", "empty_picture")
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if not item.get("narration", "").strip():
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raise ValidationError(f"第{index+1}项解说文案不能为空", "empty_narration")
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# 验证ID为正整数
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item_id = item.get("_id")
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if not isinstance(item_id, (int, float)) or item_id <= 0:
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raise ValidationError(f"第{index+1}项ID必须为正整数: {item_id}", "invalid_id")
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video_id = item.get("video_id")
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if video_id not in (None, "") and (
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not isinstance(video_id, (int, float)) or video_id <= 0
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):
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raise ValidationError(f"第{index+1}项video_id必须为正整数: {video_id}", "invalid_video_id")
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video_name = item.get("video_name")
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if video_name not in (None, "") and not isinstance(video_name, str):
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raise ValidationError(f"第{index+1}项video_name必须为字符串: {video_name}", "invalid_video_name")
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@staticmethod
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def validate_subtitle_analysis(output: str) -> str:
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"""
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验证字幕分析输出格式
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Args:
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output: 待验证的字幕分析输出
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Returns:
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验证后的分析内容
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Raises:
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ValidationError: 验证失败时抛出
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"""
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try:
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# 基础验证：内容不能为空
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if not output or not output.strip():
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raise ValidationError("字幕分析结果不能为空", "empty_analysis")
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# 验证内容长度合理
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if len(output.strip()) < 50:
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raise ValidationError("字幕分析结果过短，可能不完整", "analysis_too_short")
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# 验证是否包含基本的分析要素（可根据需要调整）
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analysis_keywords = ["剧情", "情节", "角色", "故事", "内容"]
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if not any(keyword in output for keyword in analysis_keywords):
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logger.warning("字幕分析结果可能缺少关键分析要素")
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logger.info("字幕分析验证成功")
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return output.strip()
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except ValidationError:
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raise
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except Exception as e:
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logger.error(f"字幕分析验证失败: {str(e)}")
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raise ValidationError(f"字幕分析验证失败: {str(e)}", "analysis_validation", output)
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