Daily AI News Translation & Summary with GPT-4 and Telegram Delivery

This workflow automatically extracts the transcription text from a YouTube video by inputting the video ID and performs intelligent summarization. After obtaining the text using the SearchApi, it undergoes multiple steps of splitting and content merging, combined with the OpenAI GPT-4 model to generate a concise summary. This process effectively addresses the challenge of quickly extracting key information from long videos, making it suitable for content creators, educators, and market researchers, significantly improving the efficiency and accuracy of information retrieval.

This workflow can automatically identify and extract license plate numbers from uploaded vehicle images, directly returning clean license plate characters, eliminating the need for manual input by users. By integrating advanced large language models, it significantly improves the efficiency and accuracy of license plate recognition, streamlining the traditional license plate extraction process. It is applicable in various scenarios such as traffic management, parking lots, and logistics monitoring, helping users achieve rapid automated collection of vehicle information, enhance management intelligence, and save time and labor costs.

The Tech Radar workflow automates the management and intelligent querying of enterprise technology radar data by integrating various technologies. It transforms data from Google Sheets into structured text and stores it in vector and relational databases, supporting multidimensional queries. Equipped with an intelligent AI agent, it can accurately respond to user inquiries, enhancing information retrieval efficiency. Additionally, scheduled synchronization updates ensure data timeliness, lowering the information access barrier for non-technical personnel and facilitating technology decision-making and internal communication.

This workflow integrates RSS feeds from multiple mainstream cryptocurrency news sources and utilizes advanced AI models for intelligent analysis. It automatically extracts keywords and filters relevant reports to generate news summaries and market sentiment analysis. Ultimately, the results are pushed to users in real-time via a Telegram bot, helping investors and analysts efficiently access personalized cryptocurrency news and market trends, thereby addressing the cumbersome issue of information filtering.

This workflow creates an automated user interview system that utilizes AI smart agents to guide the interviews and dynamically generate open-ended questions. Users respond through an online form, and the system records the conversation in real-time, allowing the interview to be ended at any time. Interview data is quickly stored in Redis and can be exported to Google Sheets for easier subsequent analysis. This system reduces the labor costs associated with traditional interviews and provides an efficient interview experience available 24/7, making it suitable for various scenarios such as market research, product feedback, and educational institutions.

This workflow is designed to achieve automatic extraction and intelligent parsing of content from PDF documents. Users can directly upload PDF files without the need for OCR recognition, simplifying the process. It simultaneously utilizes two AI models, Claude 3.5 Sonnet and Gemini 2.0 Flash, allowing for a comparison of their performance in data extraction effectiveness, response speed, and cost. It supports customizable extraction instructions, and the output can be adjusted to JSON format, making it suitable for extracting key information from documents such as financial invoices and contracts, thereby enhancing data processing efficiency and automation levels.

This workflow achieves content-based intelligent querying by automatically retrieving and processing files stored in Supabase, combined with OpenAI's text embedding technology. It effectively deduplicates, extracts PDF and text content, and stores it in a vectorized format, supporting fast and accurate information retrieval. It is suitable for scenarios such as enterprise knowledge base management, customer support, and professional document querying, significantly enhancing document management efficiency and user interaction experience.

This workflow utilizes an AI language model to automate user interviews, capable of generating open-ended questions and recording user responses in real-time. Users initiate the interview through a form, and the interview data is stored in a Redis database and synchronized to Google Sheets for easy data analysis and sharing. Users can end the interview at any time, and the interview records can be accessed via a Webhook, ensuring data security and efficient management. This system is suitable for market research, user experience studies, and academic surveys, greatly enhancing the flexibility and efficiency of interviews.