RapidAPI YouTube AI Video Summary

The RapidAPI YouTube Video Summary flow is designed to automate the process of transcribing a YouTube video, summarizing the transcription using OpenAI's language model, and storing the summary as a record for further use. This solution is versatile and can be applied in various contexts such as content creation, research, and data archiving.

This flow is particularly useful for generating concise summaries of video content, which can then be used for quick reference, content management, or further analysis.

This template can be found in the Services Catalog under the following categories:

AI, Contextual Basics

What's Included

• 1 Flow

• 1 Object Type

• 1 Connection

What You'll Need

• An API key for the RapidAPI YouTube Transcriber API

• An API key for OpenAI Chat API

Ideas for Using YouTube Video Summary

• Content Creation and Curation: Automate the creation of summaries for video content to enhance content discovery and curation. This can be particularly useful for managing large libraries of video content, making it easier to find relevant information quickly.

• Research and Documentation: Summarize educational or research-related videos to create concise documentation that can be easily referenced or shared. This is ideal for academic purposes, where quick access to key insights from videos is necessary.

• Data Archiving: Use the flow to generate summaries for archiving video content. This can be useful for businesses and organizations that need to maintain records of video communications or media for compliance or internal documentation.

Flow Overview

• Flow Start: The flow begins with the injection of a YouTube video ID. This ID is sent to the RapidAPI YouTube Transcriber to retrieve the video’s transcription.

• Transcription Process: The YouTube video ID is processed through the RapidAPI YouTube Transcriber, which returns the transcription in text format.

• Summarization with OpenAI: The transcription is then sent to OpenAI's chat model via an HTTP POST request. The AI model generates a high-level summary of the video content, including three key highlights.

• Record Creation: The summarized content is formatted and stored as a new AI summary record within the system.

• Error Handling: Any errors that occur during the flow are captured and logged for review, ensuring the flow runs smoothly and issues can be quickly identified and addressed.

Flow Details

The flow includes several key steps, each handled by specific nodes within the system. Below is a detailed breakdown of the JavaScript and other configurations involved:

1. Inject Node

   • Node: Test Inject

   • Purpose: Provides initial data for testing the flow. This node injects a sample YouTube video ID (zRdhoYqCAQg) into the flow. The data is manually set for testing.

   {
      p: "payload.videoId",
      v: "zRdhoYqCAQg",
      vt: "str"
   }

2. Transcription API Interaction

   • Node: Send to RapidAPI YouTube Transcriber

   • Purpose: Sends the YouTube video ID to the RapidAPI YouTube Transcriber to retrieve the video transcription.

   {
      "name": "video_id",
      "value": "payload.videoId",
      "valueType": "msg"
   }

3. Prepare Summary Request

   • Node: Prepare OpenAI Chat Request

   • Purpose: Formats the transcription data for submission to the OpenAI Chat API. This function prepares the data by structuring the payload for the API request.

   msg.payload = {
      model: "gpt-4o-mini",
      messages: [
         {
            role: "system",
            content: "Give me a high-level summary of this video transcription and 3 key highlights."
         },
         {
            role: "user",
            content: msg.videoTranscription[0].transcriptionAsText
         }
      ]
   };
   return msg;

4. Summary API Interaction

   • Node: Prompt OpenAI Chat

   • Purpose: Sends the formatted transcription data to the OpenAI Chat API and retrieves the summary response.

5. Prepare Record Data

   • Node: Prepare AI Summary Data

   • Purpose: Formats the API response and prepares it for storage as a new record in the system. The record includes the video ID, title, and AI-generated summary.

   let body = {
      videoId: msg.event.videoId,
      videoTitle: msg.videoTranscription[0].title,
      videoSummary: msg.videoSummary.choices[0].message.content
   };
   msg.payload = body;
   return msg;

6. Record Creation

   • Node: Create AI Summary Record

   • Purpose: Creates a new record in the system using the formatted data from the previous node. This record stores the video ID, title, and AI-generated summary.

7. Error Handling

   • Nodes: Catch, Error Catch Log

   • Purpose: Captures and logs any errors that occur during the flow, ensuring smooth operation and easy troubleshooting.

Summary of Flow

• Flow Start: A YouTube video ID is injected into the flow.

• Transcription Process: The ID is sent to RapidAPI for transcription.

• Summarization: The transcription is summarized using OpenAI's chat model.

• Record Creation: The summary is formatted and stored as a record.

• Error Handling: Errors are captured and logged.