Run Your Own Local ChatGPT: Ollama WebUI

NeuralNine
14 Feb 202408:27

TLDRIn this video, the presenter introduces Ollama WebUI, a tool that enables users to run a local ChatGPT interface with both local and OpenAI models. By installing Docker and following the instructions from the Olama AI website, users can operate models like Llama or Mixol on their systems. The video demonstrates the installation process, switching between models, and accessing the OpenAI API with an API key. It highlights the flexibility and potential cost-effectiveness of using local models for simple tasks and the API for more complex queries.

Takeaways

  • 🌐 Introduce Ollama WebUI, a tool for running a local ChatGPT interface.
  • 🔧 Compatible with local models like Llama and Mixol, as well as the OpenAI API.
  • 🛠️ Installation involves setting up Docker and having Ollama installed on your system.
  • 🚀 Available for macOS, Linux, and Windows with Windows Subsystem for Linux.
  • 💡 Docker container is utilized to run the Ollama WebUI.
  • 📚 Models need to be installed for the system to function, with Llama 2 being an example.
  • 🔄 The web interface resembles ChatGPT and allows model selection.
  • 🔗 Access the web interface locally via localhost and port number.
  • 🔄 Switch between models easily and interact with them through the interface.
  • 🔑 External API keys, such as OpenAI, can be added for access to more powerful models.
  • 💰 Using the OpenAI API incurs costs based on the number of tokens used for input and output.
  • 📈 Can be a cost-effective alternative to subscription services for occasional use.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about a tool called Ollama WebUI, which allows users to run their own local ChatGPT interface at home using local models or connecting to the OpenAI API.

  • What is Ollama?

    -Ollama is a command-line tool that can be used to locally run large language models such as Llama or Mixol.

  • What are the key components required to install Ollama WebUI?

    -To install Ollama WebUI, one needs to have Docker installed and also have Ollama installed on their system.

  • How does one run the Ollama WebUI?

    -After installing Docker and Ollama, users can run the Ollama WebUI by executing a specific Docker command in the terminal which starts a Docker container with the WebUI.

  • Which models can be used with Ollama WebUI?

    -Ollama WebUI can be used with local models like Llama 2 with 13 billion parameters, Llama 2 with 7 billion parameters, uncensored Mistol, and Mixol.

  • What is the process to switch between local models and OpenAI models in Ollama WebUI?

    -In Ollama WebUI, users can switch between local models and OpenAI models by going into the settings, selecting 'external', and adding their OpenAI API key.

  • How does the payment work when using OpenAI models through Ollama WebUI?

    -When using OpenAI models, users pay per token for both input and output, based on the API usage.

  • What is the advantage of using Ollama WebUI with local models?

    -Using Ollama WebUI with local models allows for more control over the models being used and can be more cost-effective, especially for simple tasks, as it does not require payment to OpenAI.

  • What is the potential issue when trying to run larger models like Mixol locally?

    -The potential issue with running larger models like Mixol locally is that it requires significant computational resources, such as a large amount of VRAM, RAM, and CPU power.

  • How can users obtain an OpenAI API key?

    -To obtain an OpenAI API key, users need to log into the OpenAI website, navigate to the API section, and generate an API key.

  • What is an example of a task that can be performed using Ollama WebUI with local models?

    -An example task that can be performed using Ollama WebUI with local models is generating code for a simple application, such as a tick tac toe game in Python.

Outlines

00:00

🌐 Introducing the Olama Web UI

This paragraph introduces the Olama Web UI, a tool that enables users to run their own chat interface with GPT locally, compatible with both local models and the Open AI API. The video creator discusses a previous video about the Olama command line tool and presents the web interface for the first time. The user guide includes installation instructions, emphasizing the simplicity of the process which involves installing Docker, running the Docker container, and having Olama installed. The video also showcases the web interface's resemblance to Chat GPT and demonstrates its functionality with local models like Llama 2 and Mixol. The importance of having the necessary models installed is highlighted, along with the ability to switch between them seamlessly within the interface.

05:02

🔧 Utilizing Local Models and Open AI API

The second paragraph delves into the practical application of the Olama Web UI by connecting to the Open AI API using an API key. It explains how to switch from using local models to leveraging the power of GPT models through the Open AI API. The video creator demonstrates how to change settings to use the external API and provides an example of querying the mural nine YouTube channel. The paragraph also discusses the cost implications of using the Open AI API compared to a subscription model, suggesting that the pay-per-token model might be more cost-effective for some users. The video creator explores the possibility of using the local models for coding tasks, such as generating a tick tac toe game in Python, and highlights the potential of running larger models like Mixol on systems with sufficient resources.

Mindmap

Keywords

💡Ollama WebUI

Ollama WebUI is a web interface tool that enables users to run their own local chat GPT-like interface at home. It is built on top of the command-line tool called Ollama, which is used to locally run large language models such as Llama or Mixol. The WebUI mimics the look and feel of ChatGPT but allows for the use of local models, providing a versatile solution for those who wish to interact with AI models without relying solely on cloud-based services.

💡Local Models

Local models refer to AI models that are run directly on the user's own computer or device, as opposed to cloud-based models that require an internet connection to a remote server. These models can be used for various tasks, such as language processing or generating text, and offer the advantage of faster response times and privacy since data is processed locally.

💡Open AI API

The Open AI API is a service provided by OpenAI that allows developers to integrate powerful AI models, such as GPT-3 and GPT-4, into their applications. By using an API key, users can send requests to the AI models and receive responses, which can be used for a variety of purposes, including text generation, language translation, and more. The API is typically used for more complex tasks or when greater computational power is required than what local models can provide.

💡Docker

Docker is a platform that enables developers to develop, deploy, and run applications inside software containers. Containers are lightweight, portable, and self-sufficient, including everything needed to run an application, which makes them ideal for creating consistent and isolated environments. Docker simplifies the process of deploying applications by eliminating the need to install and configure complex systems directly on the host machine.

💡Llama 2

Llama 2 is a large language model that can be used for various AI tasks, such as text generation and language understanding. It is one of the models that can be run locally using the Ollama command-line tool and the WebUI. Llama 2 models come in different sizes, such as 7 billion and 13 billion parameters, with the larger models generally offering more advanced capabilities.

💡Mixol

Mixol is another large language model similar to Llama, designed for text generation and understanding tasks. However, it is significantly larger, with a size of 26 GB, making it more challenging to run locally due to the high computational resources it requires. Mixol is known for its ability to generate high-quality text and can be used for complex tasks when enough computational power is available.

💡Installation Instructions

Installation instructions are step-by-step guidelines provided to users to help them set up and configure a software application or tool. In the context of the video, these instructions guide viewers on how to install Docker, Ollama, and run the Ollama WebUI container to start using the local chat GPT interface.

💡API Key

An API key is a unique code that is used to authenticate requests to an API (Application Programming Interface). It is a crucial component for accessing services provided by platforms like OpenAI, as it allows developers to securely connect their applications to the platform's resources. API keys are often required to track usage, manage access, and ensure that the services are used within the agreed-upon terms and limits.

💡Chat GPT

Chat GPT is a conversational AI model developed by OpenAI, known for its ability to generate human-like text based on the input it receives. It is often used in chatbot applications and can simulate dialogue with users on a wide range of topics. The video discusses an alternative to using the cloud-based Chat GPT by running local models or connecting to the OpenAI API through the Ollama WebUI.

💡Python

Python is a high-level, interpreted programming language known for its readability, ease of use, and versatility. It is widely used for web development, data analysis, artificial intelligence, and various other applications. In the video, Python is mentioned as an example of a topic that the AI model can provide information about when asked.

💡Neural 9

Neural 9 is mentioned in the video as a hypothetical YouTube channel. Although it is not a real entity, its mention in the video serves as an example of how the AI model can recognize and provide information about specific subjects, even if they are not widely known or are fictional.

Highlights

Introduction to Ollama WebUI, a tool for running a local ChatGPT interface.

Ollama is a command-line tool that can run large language models like Llama and Mixol locally.

The WebUI provides a chat-like interface similar to ChatGPT for local models and OpenAI API integration.

Installation involves Docker and Ollama, with detailed instructions available in the repository.

Ollama is available for Mac, Linux, and Windows using the Windows Subsystem for Linux.

Running the Docker container is straightforward with a single command.

Models like Llama 2 with 13 billion and 7 billion parameters can be used locally.

Mixol, a 26 GB model, may be impractical for local use due to its size.

The WebUI allows users to select different models and interact with them through a chat interface.

The first interaction with a model may take longer due to model loading.

Once a model is loaded, subsequent interactions are faster and more efficient.

The OpenAI key can be added to use more powerful models from the OpenAI API.

Using the OpenAI API incurs costs, paid per token of input and output.

The video discusses the potential benefits of using the API over a subscription model.

Ollama WebUI can provide code snippets, such as a tick tac toe game in Python.

Running large models like Mixol locally requires significant system resources like VRAM, RAM, and CPU power.

Ollama WebUI offers a cost-effective solution for using local models and the OpenAI API for complex tasks.

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