MAGI is an advanced chatbot powered by open-source large language models, offering an AI solution accessible to everyone. MAGI is designed to run efficiently on consumer-grade hardware and features a plugin system that enables Internet browsing, remote operation through Telegram and image generation with Stable Diffusion.
The default configuration has all plugins disabled.
You can customize MAGI by editing the file config.cfg.
You can set MAGI to behave like a fictional character or follow a set of rules. You just have to describe what you want and MAGI will follow your instructions.
You can set your Prime Directives in the file prime_directives.txt.
To toggle between the different AI modes, type the letter m and press enter.
MAGI will hold a conversation with you in a similar way to other chatbots.
This is the default mode when the program starts.
MAGI will generate a more elaborate response based on an action list.
It will save a log in the file mission_log.txt.
You can also add useful information in the file mission_data.txt.
NERV is a virtual organization composed of AI agents.
Each agent has its own memory and remembers the ongoing conversation.
You can configure each agent to behave like a fictional character or follow a set of rules.
MAGI will save a log in the file mission_log.txt.
You can also add useful information in the file mission_data.txt.
This plugin allows MAGI to browse the Internet for up-to-date information.
ENABLE_WEB_PLUGIN: enable or disable the web plugin.
This plugin enables you to teleoperate MAGI via Telegram, allowing you to have AI support on the go. When the Telegram plugin is enabled, MAGI only accepts commands via Telegram and ignores keyboard input.
If you have both the Telegram plugin and the Stable Diffusion plugin enabled, you will receive the generated images via Telegram.
To use this plugin you have to create a Telegram bot with BotFather (username: @BotFather) and save the token assigned to your bot.
You must also write to userinfobot (username: @userinfobot) to get your user ID. MAGI will only communicate with your Telegram user and will ignore other users.
ENABLE_TELEGRAM_PLUGIN: enable or disable the Telegram plugin.
TELEGRAM_BOT_TOKEN: the token you received from BotFather.
TELEGRAM_USER_ID: your Telegram user ID, you can get it from userinfobot.
This plugin allows MAGI to download a Stable Diffusion model from Hugging Face.
MAGI will use the model to generate context-related images and save them in the folder workspace.
If the folder contains images from previous sessions, they will be overwritten.
ENABLE_STABLE_DIFFUSION_PLUGIN: enable or disable the Stable Diffusion plugin.
STABLE_DIFFUSION_MODEL: this is the model used to generate images.
STABLE_DIFFUSION_IMAGE_SPECS: these are the general features of the images you want to generate. This text will be added to the prompt used to generate each image.
STABLE_DIFFUSION_NEGATIVE_PROMPT: these are the unwanted features of the images you want to generate. This text will be the negative prompt used to generate each image.
You can use any model supported by llama-cpp-python, as long as it adheres to the ChatML prompt format:
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
After cloning the repository, save the .gguf file in the root folder.
Hermes 2 Pro on Mistral 7B is a very good general-purpose model that only requires 16 GB of RAM to operate.
This model is not censored, proceed with caution.
I strongly recommend running MAGI inside a Docker container. This method significantly mitigates potential risks by isolating the application from the host system.
- Install the following packages:
$ sudo apt install docker.io apparmor-utils
- Install Docker
-
Clone this repository.
-
Optional: save a model in the root folder if you want to store the model in the Docker image.
-
Create a Docker image, you can do it by running this command in the root folder:
$ sudo docker build --no-cache -t magi .
If you have stored the model in the Docker image, run this command:
$ sudo docker run -it magi
If you have stored the model in a local folder, run this command:
$ sudo docker run -it -v MODEL_PATH:/app/MODEL_NAME magi
Example:
$ sudo docker run -it -v /home/user/models/Hermes-2-Pro-Mistral-7B.Q8_0.gguf:/app/Hermes-2-Pro-Mistral-7B.Q8_0.gguf magi
Print the log of the last run:
$ sudo docker logs $(sudo docker ps -l -q)
To exit MAGI, type the command exit or press Ctrl + C.
- Install the following packages:
$ sudo apt install build-essential pkg-config libopenblas-dev python3-venv python3-pip apparmor-utils chromium chromium-driver
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Clone this repository.
-
Save a model in the root folder.
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Install Python packages:
$ CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install --no-cache-dir -r requirements.txt
Run this command in the root folder to start MAGI:
$ python magi.py
To exit MAGI, type the command exit or press Ctrl + C.