Another day, An other more comprehensive solution of our problems. This is Zil-e-huma, MLSA-Beta from Pakistan and I am here for those who always struggle with finding the best data from YouTube according to their need.

YouTubeGPT is an imaginative AI-driven application that allows users to interact with YouTube data, capitalizing GPT technology to summarize, analyze, and provide insights from video content. It’s a cutting-edge solution for those who want to make sense of vast amounts of YouTube data, whether it’s for content creation, market research, or just getting concise video summaries.

In this article, we will explore what YouTubeGPT is, how it works, and provide a detailed step-by-step guide on how to set it up and run it effectively.

What is YouTubeGPT?

YouTubeGPT uses natural language processing (NLP) and machine learning models, specifically based on OpenAI’s GPT, to process YouTube videos. Its goal is to allow users to:

Summarize YouTube videos – Provide key takeaways from long or complex videos.
Analyze trends – Give insights into trending topics, audience engagement, and more.
Automate content generation – Automatically create content summaries or highlight reels from YouTube videos.

Whether you’re a creator looking to streamline your content creation process or a viewer trying to extract the essence of videos without watching the entire content, YouTubeGPT can be your go-to tool.

Key Features

Video Summarization: Automatically generate concise summaries of long videos.

Audience Insights: Use AI to analyze engagement metrics and provide actionable insights.

Natural Language Queries: Interact with video data by asking questions in plain language.

Seamless Integration with YouTube: Fetch and analyze videos directly from YouTube’s API.

Now, let’s move to the core part: how to set up and run YouTubeGPT on your machine.

How to Run YouTubeGPT: Step-by-Step Guide

Prerequisites

Before you get started, make sure you have the following set up on your machine:

.NET SDK: Since YouTubeGPT is built using .NET, you’ll need to have the .NET SDK installed. You can download it from [Microsoft’s official .NET website]
Docker: You’ll need Docker to set up services like PostgreSQL for storing data.
Access to Azure OpenAI Service or OpenAI API key.

For Azure OpenAI, you’ll need to set up an account and create an API key from Azure OpenAI Service.
For the OpenAI API, get an API key from OpenAI.

Setting Up YouTubeGPT

Here’s how you can set up and run YouTubeGPT on your local machine:

Clone the Repository

   First, start by cloning the YouTubeGPT project repository from GitHub or your local code repository: 

git clone https://github.com/Azure-Samples/YouTubeGPT.git

Navigate to the Project Directory

   After cloning, move into the project directory where the main application is located:

cd YouTubeGPT/src/YouTubeGPT.AppHost

Ensure Docker is Running

   YouTubeGPT uses Docker for handling the PostgreSQL database. Make sure your Docker service is running:

On Windows: Start Docker Desktop.
On Linux/Mac: Use the terminal command `sudo service docker start`.

Run the Application

   YouTubeGPT is built using .NET, so the next step is to run it using the `dotnet` command:

dotnet run

   Once you run this command, the system will build the application and start the distributed application. You will see logs similar to the following:

Building…

info: Aspire.Hosting.DistributedApplication[0]

Aspire version: 8.2.0

info: Aspire.Hosting.DistributedApplication[0]

Distributed application starting.

info: Aspire.Hosting.DistributedApplication[0]

Now listening on: https://localhost:15015

info: Aspire.Hosting.DistributedApplication[0]

Login to the dashboard at https://localhost:15015/login

Fix Common Issues

   At this point, you might run into some common issues like the PostgreSQL container not being set up correctly. For example, you might see the following error:

Error handling TCP connection {“Service”: {“name”:”postgres”}, “error”: “no endpoints configured”}

   This error typically occurs when Docker is unable to pull or configure the required PostgreSQL image. You can resolve this by manually pulling the correct image using:

docker pull postgres:latest

   After pulling the image, re-run the application.

Access the Dashboard

   Once everything is running smoothly, head over to the URL provided in the logs (e.g., https://localhost:15015/login) to access the YouTubeGPT dashboard. You’ll need to log in using the provided token.

Once you log in successfully, the following screen will appear. Click on the end point of the YouTubeGPTClient.

And Bam you are now in the world of YouTubeGPT, ask here the questions you want to get answers of.

Interacting with YouTube Data

Example: Using YouTubeGPT to Search for a Recipe

Now, let’s dive into how YouTubeGPT operates by conducting a search for a recipe video. In this example, we’ll look for a video on “how to make lasagna,” and let YouTubeGPT handle the rest.

Step 1: Enter the Query

Once you’re in the YouTubeGPT dashboard, you’ll find a search box where you can input your query. For this example, let’s search for a video on lasagna:

Query: “Find and summarize a video on how to make lasagna.”

Step 2: YouTubeGPT Searches and Analyzes the Video

 YouTubeGPT will use the YouTube Data API to search for relevant videos. The model will then process the description of the most relevant video and provide a summary based on that context.

Example Output:

 Summary:

“This video walks you through a step-by-step process of making lasagna from scratch. It covers the preparation of ingredients, such as creating the meat sauce, assembling the ricotta and mozzarella cheese layers, and placing the pasta sheets. The video concludes with tips on how to achieve a perfect golden-brown cheese crust while baking. The total cook time is approximately 1 hour.”

Step 3: Link to the Original Video

After summarizing, YouTubeGPT also provides a direct link to the original video for further reference:

YouTube Video Link: Lasagna Recipe Video (not linking anywhere, here just for demo perpose)

Post-Setup: Further Customizations

YouTubeGPT is highly customizable, allowing you to tweak various settings based on your requirements:

API Keys: Make sure to insert your YouTube Data API key for fetching video details.
Database: If you prefer using a different database (e.g., MySQL), update the database connection settings accordingly.

Common Errors and Debugging Tips

Docker Container Issues: If Docker fails to pull or start a container, ensure Docker is properly installed and authenticated. Command to manually pull an image:

docker pull dpage/pgadmin4:8.11

Database Port Conflict: If you encounter errors related to PostgreSQL ports, make sure the port (usually 5432) is not being used by other services.

Final Thoughts

Running YouTubeGPT opens up a world of possibilities in interacting with and analyzing YouTube data in a more meaningful way. Whether you want to automate video content creation or simply analyze trending topics, this powerful tool will enable you to do so efficiently.

Remember, this guide covers the basic setup and running process. If you plan to scale the application or integrate it with more complex systems, you might need to dive deeper into its architecture and customize the deployment process accordingly.

Happy experimenting with YouTubeGPT!

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