Private Chat with your Documents with Ollama and PrivateGPT | Use Case | Easy Set up

In this video, the host demonstrates how to use Ollama and private GPT to interact with documents, specifically a PDF book titled 'Think and Grow Rich'. The process involves installing AMA, setting up a local large language model, and integrating private GPT. The host guides viewers through installing AMA on Mac OS, testing it, and using terminal commands to run models like Mistral. The integration of private GPT is showcased through a GitHub repository where viewers can clone the necessary files. After setting up a virtual environment and installing dependencies, the host instructs on how to ingest documents into the system and ask questions, providing an example query about failure in executing strategies from the book. The video concludes with a summary of the steps and an invitation for viewers to engage with the content and the host's other projects.

Takeaways

• 📚 The video demonstrates how to use Ollama and private GPT to interact with documents, such as a PDF book about success and mindset.
• 💡 Private GPT is powered by large language models from Ollama, allowing users to ask questions to their documents.
• 🔍 The process involves installing AMA, a chat interface for large language models, which is currently available for Mac OS and Linux but not Windows.
• 📝 Users can ask questions to various file formats like CSV, PDF, and more through the AMA interface.
• 🚀 The video provides a step-by-step guide on setting up a local large language model, integrating private GPT, and asking questions to documents.
• 📁 The AMA private GPT folder contains different files and a README with instructions for users to follow.
• 🛠️ A virtual environment named 'private' is set up for the project, using Python version 3.11.
• 📈 The process includes installing necessary requirements from a requirements.txt file.
• 📂 Users are guided to create a 'source documents' directory and place their documents there for ingestion.
• ⏳ The ingestion process involves reading and processing the document into chunks to create embeddings.
• 🔎 After ingestion, the private GPT can be run to ask questions and receive answers based on the document's content.
• 🔗 The video is a response to viewer comments and questions about interacting with documents through a chat interface.

Q & A

What is the main purpose of using Ollama and PrivateGPT together?

The main purpose of using Ollama and PrivateGPT together is to enable users to interact with their documents, such as a PDF book, by asking questions and receiving answers based on the content of the documents.

How does the technology of PrivateGPT work with documents?

PrivateGPT uses a large language model to understand and analyze the content of the documents. It can then provide responses to questions about the document's content, simulating a conversation with the document.

What is the first step in setting up a system to chat with documents using AMA and PrivateGPT?

The first step is to install AMA, which can be done by downloading it from the provided website and following the installation instructions for your operating system.

What is the role of the AMA run command in the process?

The 'AMA run' command is used to start up the large language model locally. It is an essential part of powering the PrivateGPT with the language models from Ollama.

How does one integrate PrivateGPT with their existing setup?

Integration is done by cloning the relevant GitHub repository that contains the necessary code for setting up the AMA private GPD chat with documents. Users are guided through the process via a README file in the repository.

What kind of files can be used with this system to ask questions?

The system can handle various file types, including CSV, DOC, PDF, ePub, HTML, and more. The example in the script uses a PDF file of the book 'Think and Grow Rich'.

What is the process of ingesting files in the system?

After uploading the source document into the designated folder, the ingest script is run to process the file. This involves reading the document, splitting it into chunks, and creating embeddings for the content.

How can users ask questions to the documents using the system?

Once the document is ingested and the PrivateGPT is running, users can simply enter a query or question in the command line interface, and the system will provide an answer based on the document's content.

What are some of the limitations or considerations when using this system?

The system's performance and accuracy depend on the model used and the quality of the document's content. Additionally, the system currently does not support Windows and the process requires some technical knowledge to set up.

How long does it typically take for the system to ingest a document?

The time it takes to ingest a document can vary based on the document's size and complexity, but in the provided example, the process was completed relatively quickly, without the need for significant waiting.

What is the significance of creating a virtual environment in this setup?

Creating a virtual environment helps to isolate the project's dependencies from other projects and the system's default Python installation. This ensures that the required packages and versions for the AMA private GPD chat are properly managed.

Can the AMA private GPD system be used for other types of interactions besides asking questions?

While the primary demonstration in the script is asking questions and receiving answers, the system's underlying technology could potentially be adapted for other types of interactions with documents, depending on the capabilities of the language model being used.

Outlines

00:00

📚 Introduction to Using Olama and Private GPT for Document Interaction

The video begins with the host introducing the use of Olama and private GPT to interact with documents, specifically a PDF book titled 'Think and Grow Rich.' The host explains that they will be asking questions to the book using private GPT technology and Olama for powering the GPT. The video is a response to viewer comments about asking questions to uploaded files and the limitations of the system. The host demonstrates how to install AMA on Mac OS and run it, and then how to use Olama to run a language model for chatting. They also guide viewers on how to integrate private GPT with Olama by using a GitHub repository and provide instructions on how to get started with the process.

05:00

💻 Setting Up the Environment and Cloning the GitHub Repository

The host details the steps to set up a virtual environment using 'conda' and specifies the creation of an environment named 'private' with Python version 3.11. They guide viewers on how to activate this environment and proceed with the installation of necessary requirements from a 'requirements.txt' file. The host then instructs on cloning a specific GitHub repository containing the necessary code for the project. They also demonstrate how to pull the models into AMA, using 'AMA pull mistal' as an example, and how to create a 'source documents' directory for storing documents that will be interacted with using the system.

10:02

📂 Uploading and Ingesting the Source Document

The host shows how to upload a document (in this case, the 'Think and Grow Rich' book) into the 'source documents' folder. They then explain the process of ingesting the files using an 'ingest' script, which reads the document, splits it into chunks, and creates embeddings. This process allows the system to understand and interact with the content of the document. The host emphasizes the speed and efficiency of the ingestion process and confirms that the document has been successfully uploaded and processed.

15:02

🔍 Running Private GPT and Asking Questions to the Document

After ingestion, the host demonstrates how to run the 'private GPT' script and asks a question about the reasons for failure in executing strategies mentioned in the 'Think and Grow Rich' book. The system quickly provides an answer, highlighting lack of decision-making and procrastination as key reasons for failure. The host also asks for five key learnings from the document and receives a summary with sources. They explain the dependency of the system's performance on the model used and mention the availability of different models in AMA. The host summarizes the entire process, emphasizing the successful integration and interaction with the document using private GPT powered by Olama.

📢 Conclusion and Call to Action

The host concludes the video by inviting viewers to request more videos on topics they are interested in and assures that despite many projects, they will endeavor to create content as needed. They highlight their current focus on integrating 'mgpd autogen' with AMA APIs or server calling. The host encourages viewers to subscribe to their channel for more interesting content, share the video if they found it useful, and leave a comment. They also invite viewers to join them and sign off with a friendly farewell, reminding viewers to watch other videos on the channel.

Keywords

Ollama

Ollama is an open-source software mentioned in the video that is used to power the private GPT (Generative Pre-trained Transformer). It is a key component in the system the host is demonstrating, allowing users to interact with documents through a chat interface. In the script, Ollama is used to run large language models locally, which is a significant part of setting up the system for chatting with documents.

Private GPT

Private GPT refers to a private instance of the Generative Pre-trained Transformer model, which is a type of AI used for natural language processing tasks. In the context of the video, it is integrated with Ollama to allow users to ask questions and receive answers from documents they upload. The host demonstrates how to use Private GPT to query a book about success and mindset.

Think and Grow Rich

Think and Grow Rich is a book that focuses on personal development and success principles. The video script mentions this book as an example document that viewers can interact with using the setup explained. It is used to illustrate the potential of the technology to engage with content on a deeper level.

AMA (Ask Me Anything)

AMA, which stands for Ask Me Anything, is a term often used in online communities where people can ask questions to a particular individual or about a specific topic. In the video, AMA is used as a part of the software stack to facilitate the interaction with the documents. It is mentioned in the context of running and testing the system.

CSV file

A CSV (Comma-Separated Values) file is a type of file used in computing for storing tabular data. In the video, the host refers to a comment asking how to ask questions to a CSV file, indicating that the system being demonstrated can interact with various file formats, not just PDFs.

Language Model

A language model is a type of artificial intelligence used for understanding and predicting sequences of words or phrases in a natural language. In the video, the host starts up a large language model locally using AMA, which is then used to power the Private GPT for chatting with documents.

GitHub

GitHub is a platform for version control and collaboration that allows developers to work on projects together. In the video, the host guides viewers to a GitHub repository where they can find the code necessary for setting up the system to chat with documents. GitHub is essential for sharing and accessing the required scripts and files.

Virtual Environment

A virtual environment in computing is an isolated working environment for software projects. The host instructs viewers to set up a virtual environment named 'private' using the conda tool. This environment is used to manage dependencies and ensure that the project runs correctly without interfering with the system's other Python projects.

Ingestion

In the context of the video, ingestion refers to the process of uploading and preparing the document for analysis by the AI system. The host demonstrates how to ingest a document, such as the 'Think and Grow Rich' book, into the system so that it can be queried and interacted with.

Embeddings

Embeddings in machine learning and AI are vector representations of words or phrases that capture their semantic meaning. The video mentions creating embeddings as part of the ingestion process, which allows the AI to understand and process the content of the uploaded documents effectively.

Decision Making

Decision making is a cognitive process that results in the selection of a course of action. In the video, the host uses the system to ask why most people fail in executing strategies from the book 'Think and Grow Rich', and one of the reasons provided is a lack of decision making.

Highlights

Introducing the use of Ollama and Private GPT to interact with documents, specifically a PDF book on success and mindset.

Demonstrating the ability to ask questions to a 200-page book using Private GPT technology.

Installing AMA for local setup and its compatibility with Mac OS and Linux.

Running AMA and testing it through the terminal with a simple command.

Using the 'Ollama run' command to initiate conversation with the system.

Integration of a large language model locally with AMA for Private GPT.

Answering user questions about interacting with various file types like CSV through the AMA interface.

Guiding viewers on how to clone GitHub repositories for Private GPT integration.

Setting up a virtual environment for the Private GPT project using 'conda'.

Installing necessary requirements for the Private GPT project from a requirements.txt file.

Pulling models into AMA using the 'AMA pull' command.

Creating a 'Source documents' directory for file uploads.

Uploading a book into the 'Source documents' folder for interaction.

Ingesting files into the system to prepare them for interaction.

Running the Private GPT model to ask questions and receive answers from the uploaded document.

Asking a specific question about failure in executing strategies from the book 'Think and Grow Rich'.

Receiving insights and key learnings from the document, showcasing the model's analytical capabilities.

Highlighting the flexibility of the system to work with various document formats like CSV, DOC, and ePub.

Summarizing the steps required to set up and use Private GPT with AMA for document interaction.

Invitation to subscribe for more content on the channel and an offer to make videos based on user questions.