Intelligent YouTube Video Summarization and Q&A Generation

This workflow automatically retrieves legislative procedure data from the European Parliament's official website for the past 18 days, using advanced AI technology to intelligently filter topics related to environmental sustainability. The filtered results will be stored in Google Sheets, and Google task reminders will be generated for each relevant topic to help users efficiently track and manage legislative developments. This process significantly enhances information processing efficiency, ensuring that users can stay updated on key sustainable development policies in a timely manner.

This workflow automatically generates prompts that meet AI model requirements by receiving user queries, and it calls relevant APIs for in-depth content retrieval, extracting and outputting concise, structured answers. It can provide authoritative materials with citations, ensuring the professionalism and credibility of the results. This helps users quickly access the latest research materials in a specific field, enhancing information retrieval efficiency and content quality. It is applicable in various scenarios such as academic research, content creation, and industry analysis.

This workflow combines advanced AI language models with the Notion knowledge base to provide intelligent Q&A services. Users can input questions, and the system will automatically retrieve relevant content and generate accurate answers, along with links to Notion pages, ensuring the reliability and traceability of the information. This assistant enhances the efficiency of knowledge queries and is suitable for various scenarios such as internal knowledge management in enterprises, customer support, and personal information retrieval, helping users quickly access the information they need.

This workflow provides an intelligent personal shopping assistant feature for e-commerce platforms by integrating language models and retrieval-augmented generation technology. It can automatically identify users' shopping needs, accurately extract product search information, and match relevant products in the WooCommerce database. Additionally, for non-shopping inquiries, the system offers intelligent responses based on a knowledge base, enhancing the user experience. Through context management, it ensures the continuity of conversations, significantly improving customer satisfaction and service efficiency.

This workflow automatically scrapes the latest articles from the Paul Graham website, extracts and processes the text content, and converts it into vectors stored in the Milvus database. By integrating OpenAI's embedding model, it enables intelligent Q&A and information retrieval based on the knowledge base. It supports manual triggers and chat message triggers for AI responses, making it suitable for researchers, businesses, and content creators, enhancing information management and retrieval efficiency, and streamlining the knowledge base construction process.

This workflow builds an intelligent question-and-answer system based on company documents stored in Google Drive, utilizing a vector database and large language models to achieve rapid information retrieval and natural language interaction. By automatically synchronizing document updates, employees can obtain concise and accurate answers related to policies and processes in real time, thereby enhancing knowledge management efficiency, optimizing the self-service experience, and addressing the issues of traditional document fragmentation and retrieval difficulties. It is applicable to various scenarios, including internal knowledge bases, HR policy inquiries, and intelligent retrieval of legal compliance documents.

This workflow intelligently captures posts tagged with #damus on the Nostr social platform, utilizes AI models to analyze discussion topics, and automatically generates detailed topic reports. It distributes these reports through multiple channels, including Gmail and Telegram. This effectively addresses the cumbersome process of manually filtering information, helping community operation teams, product managers, and content creators quickly obtain valuable insights, enhance information retrieval efficiency, and achieve intelligent management and dissemination of data.

This workflow utilizes the Google Gemini 1.5 AI model to automatically analyze YouTube videos, generating diverse content such as summaries, verbatim transcriptions, timestamps, and scene descriptions. Users can dynamically adjust the prompts based on their needs to achieve precise information extraction. The processing results can be saved to Google Drive and sent via email for easy access and sharing. This tool significantly enhances the efficiency of obtaining video content, making it suitable for content creators, marketers, educational institutions, and general viewers, saving time and improving information utilization.