ABI*: The AI system for your everyday business

*Augmented Business Intelligence

Mixture of Assistants[]()

ABI is a mixture of AI-driven business intelligence assistants to power your business. This suite of assistants is designed by Naas core team and its design partners to cover business essentials with assistants focused on open data & market intelligence, content creation, growth marketing, sales conversion, operational efficiency and finance management.

Together, they form a unified system that utilizes external data for richer business insights, enhances content performance and brand awareness, improves lead generation and qualification, streamlines operations and financial transactions.

ABI's capabilities are further expanded through its integration with a variety of tools, APIs, both official and unofficial, enabling comprehensive data collection and enrichment.

How it works?

Architecture

ABI is a combination of open source tools and proprietary technology. ABI relies on Naas Workspace and Naas API to function, requiring a token to run.

We’re building the features of ChatGPT and its GPT Store with Naas Workspace and a power orchestration layer with Naas API using enterprise-grade, open source technologies.

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flowchart LR
  user[End User]

  subgraph workspace[Workspace]
    chat[Chat]
    search[Search]
    lab[Lab]
    dashboard[Dashboard]
    subgraph assistants[Assistants]
      personalassistant["AIA (Personal Assistant)"] 
      mixassistants["ABI (Mixture of Assistants)"]
      customassistants[Custom Assistants]
    end
  end

  personalassistant<-.->mixassistants<-.->customassistants<-.->personalassistant

  subgraph api[API]
    direction TB
    aimodels[AI Models]
    plugins[Plugins]
    assets[Assets]
    secrets[Secrets]
    prompts[Prompts]
  end

  subgraph storage[Storage]
    direction TB
    kg[Knowledge Graph]
    vector[Vector Search]
    object[File/Object Storage]
  end

  subgraph sources[Data Sources]
    direction TB
    subgraph Tools
      databases[Databases]
      APIs[Third Party APIs]
    end
    documents[Documents]
  end

  subgraph abirepo[ABI Repository]
    subgraph core[Core Models]
      opendata((Open Data)) --> content((Content))
      content --> growth((Growth))
      growth --> sales((Sales))
      sales --> ops((Operations))
      ops --> finance((Finance)) --> opendata
    end
    custom[Custom Models]
  end

  direction TB
  subgraph templates[Templates Repository]
    automation[Automation]
    analytics[Analytics]
        ai[AI]
  end

  subgraph workflowAPI[Orchestration]
    direction TB
    pipeline[Pipeline]
    workflows[Workflows]
  end

    user -->|Has| sources
    user -->|Creates| prompts
    user -->|Works with| workspace
  sources -->|Input| core & custom
  pipeline -->|"Schedules (Pre-process)"| workflows
  core -->|Configures| pipeline
  user -->|Configures| secrets
  aimodels -->|Used by| assistants
  workflows -->|Publish| assets & plugins
  workflows -->|Output| kg
  workflows -->|Output| vector
  workflows -->|Output| object
  workflows -->|Updates| workspace
  plugins -->|Updates| assistants
  prompts -->|Used by| assistants
  secrets -->|Used by| assistants
  storage <-.->|Used by| api
  workflows <-->|Access| api
  assets -->|Used by| assistants
  assistants <-->|Interacts with| chat
  chat -.->|"Triggers (Post process)"| workflows
  templates -->|Integrate| custom & core

If you don’t want to use Naas capabilities to run ABI, you can do it but it will require some code refactoring. Our aim is to give developers a openAI-like developer experience using open source tools.

Installation

Local Setup

To set up the project locally, follow the steps below:

git clone https://github.com/jupyter-naas/abi.git
cd abi
make all

Requirements

Miniconda: Ensure you have Miniconda installed. You can download it from here.
Docker: Make sure Docker is installed on your system.

Warning for Windows Users

If you are using Windows, you need to use WSL (Windows Subsystem for Linux) with an Ubuntu distribution. Additionally, ensure Docker is installed and properly configured to run within the WSL environment.

Accessing the `abi` Kernel

After completing the setup, the abi kernel will be installed. You can use this kernel in your VSCode or any other IDE that supports Jupyter kernels.

Setup a New Scheduler

To set up a new scheduler, follow these steps:

Edit the config.yaml file:

In the config.yaml file, add a new scheduler configuration as shown below:

schedulers:
 - name: SchedulerName   # Name of the scheduler
   abi_version: latest   # Version of abi to use. Default is "latest"
   enabled: true         # Enable or disable the scheduler
   cron: '0 9 * * *'     # Cron expression
   steps:                # Steps to run
     - type: notebook    # Type of step. Default is "notebook"
       name: CI tests    # Name of the step
       enabled: true     # Enable or disable the step
       entrypoint: tests/ci.ipynb    # Entrypoint of the step
       environment_variables:        # Environment variables. Optional
         CUSTOM_ENV_VAR: Hello World!
       inputs:                         # Inputs to the step. Will be injected by papermill after the cell tagged "parameters". Optional
         message: "Hello scheduler!"

Generate the GitHub Action configuration:

Once the config.yaml file is edited, execute the following command to generate the new GitHub Action configuration:
```
make ci-generate-schedulers
```
This will create the new GitHub Action configuration file in .github/workflows/scheduler__<scheduler name>.yaml.
Commit and push the changes:

Add the new GitHub Action configuration file to the repository, commit the changes, and push to the remote repository:
```
git add .github/workflows/scheduler__<scheduler name>.yaml
git commit -m 'ci: Adding new scheduler ...'
git push
```

By following these steps, you can successfully set up a new scheduler in your project.

Build Your Own ABI

Pre-requisites

The first step in building your ABI is to ensure that you have a GitHub account. If you do not yet have one, you can create one for free on GitHub's website.

Once you have your account, you must create a new organization. This organization will serve as the home for your forked ABI repository.

Fork ABI Repository

To get started, you must fork this repository into your own GitHub organization. This will create a copy of the repository that you can modify and manage independently of the original source.

Here's how to fork the ABI repository:

Click on the "Fork" button. A new screen will appear, asking where you want to fork the repository.
Select your GitHub organization from the list. The repository will then be forked to your organization, and you'll be redirected to your new, forked repository.

Now that you have forked the ABI repository, you can build your own version of ABI in each engine's custom folder.

Setup Git remote

Once you have forked and created your own version of the ABI repository, you need to establish a Git remote.

This will enable you to push and pull to and from the original ABI repository. Doing so will allow you to update your project with the latest changes, or contribute back to the open-source project.

Execute the following commands in your terminal:

# Access your repo
cd "your_directory_name"

# Add  remote
git remote add abi https://github.com/jupyter-naas/abi.git

# Push to main branch
git push abi main

# Pull from main branch
git pull abi main

About Git default remote

When you clone a git repository from Github or any other provider, it will always create a default remote for you, named, origin. You might already have asked yourself what this origin was. It's your default git remote.

This means that, assuming you are on the main branch, executing git push is the same as git push origin main.

So by default will just use:

The branch you are actually on
The origin remote. Even if other exists, it will always use origin by default.

jupyter-naas / abi

readme

ABI*: The AI system for your everyday business

Mixture of Assistants[]()

How it works?

Architecture

Installation

Local Setup

Requirements

Warning for Windows Users

Accessing the `abi` Kernel

Setup a New Scheduler

Build Your Own ABI

Pre-requisites

Fork ABI Repository

Setup Git remote

Product Owners

Acknowledgments

Legal

jupyter-naas / abi

readme

ABI*: The AI system for your everyday business

Mixture of Assistants[]()

How it works?

Architecture

Installation

Local Setup

Requirements

Warning for Windows Users

Accessing the abi Kernel

Setup a New Scheduler

Build Your Own ABI

Pre-requisites

Fork ABI Repository

Setup Git remote

Product Owners

Acknowledgments

Legal

Accessing the `abi` Kernel