Chat with Local Files for Free – Keep your PDFs, TXT, and Word Docs Private! (Installation)

Hey, what's up guys? Welcome back to the world of AI. In today's video, I'm excited to share with you a new project called Private GBT. This project has been gaining a lot of popularity recently, and for good reason. Private GBT is a variant of the GPT language model that allows you to ask questions about your own documents without the need for an internet connection. Best of all, it's completely free and prioritizes your privacy.

The underlying technology behind Private GBT is based on the LMS developed by OpenAI, specifically the GPT 3.5 architecture. These models have been trained on a vast amount of textual data and are capable of generating human-like responses to various prompts. However, what sets Private GBT apart is its ability to work locally without relying on an internet connection. This makes it perfect for situations where privacy or limited connectivity is a concern.

One of the main reasons why Private GBT has been gaining so much popularity is because many applications today heavily rely on internet connectivity, which can not only compromise your privacy but also limit your accessibility. With Private GBT, you get the best of both worlds. You can protect your privacy and run the application without the need for an internet connection.

In this video, I'll be showing you how you can install Private GBT on your desktop and give you a better understanding of how it works. But before we dive into that, I want to take a moment to talk more about the project and its benefits.

Private GBT allows you to ingest your own documents into the model, creating a custom knowledge base for your queries. This ingestion process involves providing the model with relevant text data, such as PDFs, text documents, and notes. You can find more information about the requirements and supported file types in the repository, which I'll link in the description below. By keeping the entire process within the local execution environment, Private GBT ensures that your data remains private and secure.

The benefits of using Private GBT are numerous. First and foremost, you can ask questions and get responses from your own documents without needing an internet connection. This is particularly useful in situations where internet access is limited or restricted. Additionally, the privacy-focused design of Private GBT ensures that sensitive information or data you don't want to be transferred outside of your local desktop stays safe.

Now, let's get into the exciting part of this video where we'll be setting up the environment and installing Private GBT. To begin, you'll need to install two files: The Groovy file, which is around 3.5 GB in size, and the GGML model, which is around 3 GB. You can find links to download these files in the description. Once you have downloaded and installed these files, you can proceed with the installation process.

To install Private GBT, you'll need Git, Python, and Visual Studio Code. Git is used to clone the repository onto your desktop, Python is your language editor, and Visual Studio Code is a code editor that allows you to edit the code and set up the application. Once you have these tools installed, open the command prompt and navigate to the Private GBT folder by typing “cd private-gbt” in the command prompt.

From here, you can start installing the required environments by copying and pasting the provided code. This code will install the necessary files onto your desktop. Once the installation is complete, open Visual Studio Code and click on “Open Folder”. Select the Private GBT folder that you cloned from the repository.

In Visual Studio Code, you'll see an example.in file. Rename this file to remove the “example” part. This is where you'll be editing the parameters for the application if needed. Now, create a new folder named “models”, where you'll place the two files you downloaded earlier. You can do this by clicking the “Upload” button and selecting the files.

With the models uploaded, you can now upload your own text documents to the SourceDocuments folder. This is where you'll provide the application with the content it needs to generate responses to your queries. Once you've finished uploading your files, click on the play button to start the application. It will load the necessary information and you can then start asking questions or working with prompts related to your documents.

That's it for today's video, guys! I hope you found this walkthrough useful and gained a better understanding of how to install and use Private GBT. If you enjoyed this video, please consider subscribing to my channel and following me on Twitter for more AI-related content. Your support means a lot to me.

Thank you for watching, and I'll catch you in the next video. Have an amazing day and keep smiling! Peace out, fellas!

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Frequently Asked Questions:

1. What is Private GPT and how does it differ from the GPT language model?

Private GPT is a variant of the GPT language model that allows users to ask questions to their own documents without the need for an internet connection. It prioritizes user privacy by ensuring that no data is left behind in the execution environment.

2. How is the underlying technology behind Private GPT based on the LMS developed by OpenAI?

The underlying technology of Private GPT is based on the LMS developed by OpenAI, specifically the GPT 3.5 architecture. These models are trained on vast amounts of text data and are capable of generating human-like responses on various prompts.

3. What are the benefits of using Private GPT?

Using Private GPT allows users to ask questions and get responses from their own documents without the need for an internet connection. This is particularly useful in situations where internet access is limited or restricted. The privacy-focused design ensures that sensitive information remains safe and secure on the local desktop.

4. How can I install and run Private GPT locally on my desktop?

To install and run Private GPT locally, you would need to have Git, Python, and Visual Studio Code installed. First, clone the repository onto your desktop using Git. Then, install the necessary files and dependencies as specified in the repository. Finally, use Visual Studio Code to edit the code and set up the environment for ingesting your own documents.

5. What type of documents can be used with Private GPT?

Private GPT supports various types of documents, including PDFs, text documents, notes, and other specified documents. These documents can be ingested into the model, allowing you to ask questions or query the content of the documents.