share_text_parse_tool_wrapper
Extract video content from TikTok share links and convert speech to text using specified API parameters.
Instructions
提取视频内容，需要传递apikey，否则无法使用视频内容提取功能！
参数:
- text: 抖音分享文本，包含分享链接
- api_base_url: API基础URL，默认使用siliconflow.cn
- model: 语音识别模型，默认使用FunAudioLLM/SenseVoiceSmall
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| api_base_url | No | ||
| model | No |
Implementation Reference
- yby6_video_mcp_server/server.py:54-62 (registration)Registration of the MCP tool 'share_text_parse_tool_wrapper' using @mcp.tool decorator. The description string defines the tool schema including parameters and usage.
@mcp.tool( description=""" 提取视频内容，需要传递apikey，否则无法使用视频内容提取功能！ 参数: - text: 抖音分享文本，包含分享链接 - api_base_url: API基础URL，默认使用siliconflow.cn - model: 语音识别模型，默认使用FunAudioLLM/SenseVoiceSmall """ ) - yby6_video_mcp_server/server.py:63-82 (handler)The handler function that implements the logic for 'share_text_parse_tool_wrapper'. It delegates to the core 'share_text_parse_tool' utility function in utils/tools.py.
async def share_text_parse_tool_wrapper( text: str, api_base_url: Optional[str] = None, model: Optional[str] = None, ctx: Context = None, ) -> Dict[str, Any]: """ 解析抖音分享链接，提取无水印视频地址 下载无水印视频 提取音频 转换音频为文本 清理临时文件 参数: - text: 抖音分享文本，包含分享链接 - api_base_url: API基础URL，默认使用SiliconFlow - model: 语音识别模型，默认使用SenseVoiceSmall """ return await share_text_parse_tool(text, api_base_url, model, ctx) - Core helper function 'share_text_parse_tool' that contains the main implementation logic for parsing share text, downloading video, extracting audio, transcribing to text, and cleanup. Called by the wrapper handler.
async def share_text_parse_tool( text: str, api_base_url: Optional[str] = None, model: Optional[str] = None, ctx: Context = None, ) -> Dict[str, Any]: """ 解析抖音分享链接，提取无水印视频地址 下载无水印视频 提取音频 转换音频为文本 清理临时文件 参数: - text: 抖音分享文本，包含分享链接 - api_base_url: API基础URL，默认使用SiliconFlow - model: 语音识别模型，默认使用SenseVoiceSmall """ if not text or not isinstance(text, str): return create_error_response("文本参数不能为空") try: # 获取配置参数 api_key, api_base_url, model = get_api_configuration(ctx, api_base_url, model) if not api_key: error_msg = "没有传递apikey，请通过参数传入apikey或请求头传入apikey，或者设置环境变量API_KEY，否则无法使用视频内容提取功能！" logger.error(error_msg) return create_error_response(error_msg) processor = VideoProcessor(api_key, api_base_url, model) # 解析视频链接 video_share_url = extract_url_from_text(text) if not video_share_url: error_msg = f"无法从文本中提取视频链接: {text}" logger.error(error_msg) return create_error_response(error_msg) video_obj = await parse_video_share_url(video_share_url) video_info = create_success_response("解析成功", video_obj.__dict__) # 处理视频下载和文本提取 try: download_video_info = { "url": video_info["data"]["video_url"], "title": video_info["data"]["title"], "video_id": str(int(time.time())), } logger.info(f"开始下载视频: {download_video_info['title']}") video_path = await processor.download_video(download_video_info) ctx.info(f"视频下载地址: {video_path}") logger.info("开始提取音频") audio_path = processor.extract_audio(video_path) ctx.info(f"音频提取地址: {audio_path}") logger.info("开始转换音频为文本") text_content = processor.extract_text_from_audio(audio_path) ctx.info(f"文本提取内容: {text_content}") logger.info("清理临时文件") processor.cleanup_files(video_path, audio_path) ctx.info(f"临时文件清理: {video_path}, {audio_path}") return { "code": DEFAULT_RESPONSE_CODES['SUCCESS'], "msg": "解析成功", "data": video_info["data"], "text_content": text_content, } except Exception as processing_err: logger.error(f"视频处理失败: {processing_err}") # 确保清理可能存在的临时文件 try: if 'video_path' in locals() and 'audio_path' in locals(): processor.cleanup_files(video_path, audio_path) except Exception: pass raise processing_err except ValueError as err: logger.error(f"参数错误: {err}") if ctx: ctx.error(f"参数错误: {str(err)}") return create_error_response(str(err)) except Exception as err: logger.error(f"未知错误: {err}") if ctx: ctx.error(f"解析失败: {str(err)}") return create_error_response(f"解析失败: {str(err)}")