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How to Find Key Moments in YouTube Videos Using AI

Education

Introduction

In today's digital world, the vast sea of content on platforms like YouTube can make it challenging to locate specific information quickly. However, with the assistance of AI, you can efficiently search for key moments in YouTube videos based on your queries. This article explores a script that utilizes embeddings to identify timestamps in videos where particular topics are discussed, effectively enabling users to jump to relevant sections of a video.

Overview of the Script

The script we will discuss employs a retrieval approach similar to "rag-like" methods, leveraging embeddings to facilitate searches within YouTube video transcripts.

  1. Initialization:

    • The script begins by prompting the user to select an embedding model from OpenAI. The "T-Ting three large" model is chosen for its accuracy, though alternatives are available.
    • You will need to enter the URL of the YouTube video you want to analyze.

  2. Transcription and Embedding:

    • After entering the URL, the script quickly retrieves and embeds the video's transcript using the YouTube transcript API.
    • For example, searching for "embeddings" in the video will yield timestamps where the topic is discussed.

  3. Displaying Results:

    • The script formats the results in an easy-to-read table that includes the rank, similarity score, timestamp, relevant text excerpt, and a link to jump to that section in the video. Users can control-click on the link to navigate directly to the specified timestamp.

  4. Processing Workflow:

    • The script processes video transcripts by generating embeddings for each segment, calculates similarities, and prints a success message.
    • Various methods, such as for formatting time and calculating cosine similarities, facilitate the overall functionality.

  5. User Interaction:

    • The script is designed to be user-friendly, asking for video IDs and search queries directly in the console. It utilizes regex to extract video IDs from URLs.

  6. Further Development:

    • The author mentions plans for creating a FastAPI web application version of this search functionality, allowing for broader usage and integration.

  7. Resources and Accessibility:

    • Code files for this script will be available on the author's Patreon, along with other resources for developers and learners interested in AI applications in coding.

Keywords

  • YouTube
  • AI
  • Embeddings
  • Video Transcript
  • Search
  • Timestamps
  • Cosine Similarity
  • FastAPI

FAQ

Q1: What is the purpose of the script?
A1: The script enables users to find key moments in YouTube videos by searching through transcripts and returning relevant timestamps based on user queries.

Q2: How does the script perform the search?
A2: The script uses embeddings to analyze video transcripts, calculating similarities between user queries and transcript segments to provide accurate timestamps.

Q3: What are the requirements to run the script?
A3: Users need an OpenAI API key, access to the YouTube transcript API, and certain Python libraries such as NumPy and Rich for formatting outputs.

Q4: Where can I access the code files for this script?
A4: The code files are made available on the author's Patreon page, where patrons can also access other educational resources and projects.

Q5: Is there any future development planned for this tool?
A5: Yes, the author intends to create a FastAPI web application version of the script, which will broaden its accessibility and functionality.