Multi-platform desktop app to download and run Large Language Models(LLM) locally in your computer.

Overview

Multi-platform desktop app to download and run Large Language Models(LLM) locally in your computer


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Features

  • 🚀 The power of AI in your computer
  • 💻 Local - it can work without internet
  • 🔒 Privacy first - your messages don't leave your computer
  • 🤫 Uncensored - you can talk whatever you want
  • 📖 Open source

Try the app

If you just want to get the app installers and try the app, go to secondbrain.sh.

How to use

The first time you open the app you will need to download a model, and then activate it.

Download a model

Secondbrain comes with some models ready to download, that we know work. You can check, or modify, the models.json to see their details.

You can also add your own model files to the /models folder, and then activate them from within Secondbrain app. The model needs to be in ggml format.

Activate the model

Just select the model and press "Activate model", and you are ready to start using the model.

The prompt is important

Language models are predictive machines, you throw some words(tokens actually) at them and they try to predict what is the most likely token to come after that, and after that new one, and so on. Not all the models work so smooth as ChatGPT, it depends on the pre-training, the fine-tuning, and the under-the-hood prompting.

When using models you need to take into account what format they understand better, for example Alpaca models were trained with this format:

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{instruction}

### Response:

So, if you want to download and use your own models, take into account the prompt and change it in the configuration screen.

With foundational models, like Llama, things get crazy, there is no fine-tuning, so finally you can flex your prompt engineering skills and play around.

How to run from source

The app is build with Tauri, so basically you need to follow this guide: https://tauri.app/v1/guides/getting-started/prerequisites/

Techstack

Contribution

Yes, please. Just send your PRs.

Gracias 🤓

Contact

Hi! you can find me here @julioandresdev

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Comments
  • [BUG] Unknown tensor.

    [BUG] Unknown tensor.

    Here is a bug reported by Rodneyg on the Reddit thread:

    Very nice! I downloaded it and it downloaded the model fine but it's getting an error when I try to activate it. On new MBP M2 Max 32 GB memory.

    The model in use is Wizard Vicuna 13b Uncensored GGML, and the error reads as:

    Error: unknown tensor 'layers.1.attention_norm.weight' in ""

    opened by SabinStargem 1
  • [SUGGESTION] Add an API function?

    [SUGGESTION] Add an API function?

    This is Darth Gius's suggestion on the Reddit thread.

    Sure, what I'd like to add is a completion endpoint for my node.js app, most chatbots create this making a local server and printing a link (to not start every time the chatbot) and the external app sends the prompt and receives the output through the link, like here (I think, it's the Tauri page for the api), or this (uses openai api in python to generates answers), but I'm no expert on this, for now I can/prefer to send context+prompt directly to your app and start it every time I need an answer (I already have a nodejs code to start a python chatbot and send prompts there and receive outputs in nodejs, now I would have to understand how your code works and change the python chatbot with your app).

    On the rustformers github page I see that one of the commands to generate the answer is llm llama infer -m ggml-gpt4all-j-v1.3-groovy.bin -p "Rust is a cool programming language because", my basic idea for now is to change the Tauri app to let it do -p prompt, which receives from my code through the link or through a shared variable (if I don't use the link and start different times your app)

    opened by SabinStargem 0
  • [SUGGESTION] Check AI hardware requirements against current machine.

    [SUGGESTION] Check AI hardware requirements against current machine.

    It would be good that when looking at an AI model, that Second Brain would list the hardware recommendations and compare them against the user's machine.

    opened by SabinStargem 0
  • [SUGGESTION] The ability to specify hardware preference for AI where applicable.

    [SUGGESTION] The ability to specify hardware preference for AI where applicable.

    Apparently, some AI models have the ability to be used on both CPU and GPUs. Being able to select which hardware (and to what degree?) may be useful for some users.

    opened by SabinStargem 0
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