如何与YouTubers聊天 | LangChain、ChatGPT和Pinecone

Table of Contents:

1. Introduction
2. Building a Chat Window
3. Transcribing a YouTube Video
4. Setting Up AI Tools
5. Using Pinecone for Vector Database
6. Getting API Keys from Open AI
7. Running the Code and Chatting
8. Deep Dive into the Code
9. Using Langchain for Conversational AI
10. Conclusion

Introduction

In today's video, I'm going to Show You how you can start chatting with your favorite YouTube content Creators for free. I'll be giving away the source code and walking you through the three simple steps to get everything working. Let's get started!

Building a Chat Window

To start chatting with your favorite YouTubers, you just need to follow these three simple steps. First, we'll transcribe the YouTube video you want to chat about. Then, we'll set up some AI tools to make the magic happen. Lastly, all you have to do is run the code provided. Let's dive into the details!

Transcribing a YouTube Video

The first step in the process is transcribing the YouTube video you want to chat about. Thanks to the Whisper API released by OpenAI, transcribing videos has become super simple. We'll be using tools like Assembly AI playground, which make it easy to convert a YouTube video into text. Simply paste the video link and follow the instructions. The tool will transcribe the video and provide you with the text. Keep the transcript open as we'll need it later.

Setting Up AI Tools

Now that we have the transcript, it's time to set up some AI tools to make the magic happen. We'll be using two tools: Pinecone and OpenAI. Pinecone is a vector database that allows us to convert text into numbers and store them for later use. OpenAI, on the other HAND, provides powerful natural language processing models that we'll use for conversational AI.

To get started, sign up for a free account on Pinecone and Create a new vector database. Make note of the API keys and index name. Then, sign up for an account on OpenAI and generate a new API key. Keep these keys safe as we'll need them later.

Using Pinecone for Vector Database

With Pinecone, we can easily convert our transcript into vectors and store them in a database. The code provided will handle chunking the text, creating documents, and saving them to the vector database. The Pinecone API will allow us to query the database and retrieve Relevant information Based on the user's questions. The code is simple and straightforward to understand.

Getting API Keys from Open AI

OpenAI provides powerful AI models that we'll use for conversational AI. We'll create a new endpoint to Interact with the OpenAI API. By passing in the user's question and chat history, we can get back an answer from the model. This allows us to simulate a chat conversation with the AI. The code provided handles all the interactions with OpenAI and makes it easy to integrate into our chat application.

Running the Code and Chatting

Now it's time to run the code and start chatting with your favorite YouTuber! Clone the code from the GitHub repo provided and install the necessary dependencies. Update the environment variables with your API keys and Pinecone index name. Then, start the application by running the command. You can now access the chat window on localhost and input your questions to chat with the AI. It's as simple as that!

Deep Dive into the Code

Let's take a closer look at the code that makes all of this work. The project is built using the T3 stack, which consists of Next.js, Tailwind, TypeScript, and trpc. We have two backend routes: one for Pinecone and one for Langchain. Pinecone is used to interact with the vector database, while Langchain is used for conversational AI with OpenAI models. The code is well-documented and easy to follow, so feel free to explore and customize it to suit your needs.

Using Langchain for Conversational AI

Langchain is a powerful tool that enhances the capabilities of OpenAI models. It provides a wrapper around the OpenAI API and makes it easier to interact with the models. With Langchain, we can pass in the user's question and chat history to retrieve relevant answers from the model. The code provided handles all the interactions with Langchain and enables seamless conversational AI in our chat application.

Conclusion

Congratulations! You've learned how to start chatting with your favorite YouTube content creators using AI. By transcribing videos, setting up AI tools, and running the code provided, you can have engaging conversations with AI models. This opens up a whole new world of possibilities for interaction and learning. Give it a try and start chatting today!

Highlights:

• Learn how to chat with your favorite YouTube content creators for free
• Transcribe YouTube videos using AI tools like Assembly AI
• Set up Pinecone for vector database and OpenAI for conversational AI
• Run the code and start chatting with AI models
• Deep dive into the code and understand the technical details
• Enhance conversational AI with Langchain
• Start engaging conversations and learn from AI models

FAQ:

Q: How can I transcribe YouTube videos? A: You can use AI tools like Assembly AI playground to easily transcribe YouTube videos. Simply paste the video link and follow the instructions.

Q: Can I use Pinecone for other applications? A: Yes, Pinecone is a versatile vector database that can be used for various applications beyond chatbots. It allows you to convert text into vectors and store them for efficient retrieval.

Q: How can I enhance conversational AI with Langchain? A: Langchain provides powerful capabilities to enhance conversational AI using OpenAI models. By passing in user questions and chat history, you can get more relevant answers from the models.

Q: Can I customize the code to suit my specific needs? A: Certainly! The code provided is well-documented and easy to understand. Feel free to modify it to fit your requirements and experiment with different AI models and techniques.