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-
+ AIserver is a practical framework for building autonomous AI systems. These systems use large language models to interact with tools, APIs, and databases, automating tasks and workflows. This repository contains all the code, examples, and setup instructions to get you running quickly. Click the image or link above to explore the project.
What is AIserver? · Repo Structure · Getting Started
+What is AIserver?
-
- Artificial Intelligence is the #1 thing for all developers to spend their time on now.
- The problem is, most developers aren't focusing on AI agents, which is the real way to unleash the full power of AI.
- This is why I'm creating this AI Agents Masterclass - so I can show YOU how to use AI agents to transform
- businesses and create incredibly powerful software like I've already done many times!
- Click the image or link above to go to the masterclass on YouTube.
-
+AIserver lets you turn language models into autonomous systems that can interact with the real world.
+You can automate tasks like sending emails, updating databases, scheduling events, querying APIs, or performing multi-step workflows.
-
- What are AI Agents? ·
- How this Repo Works ·
- Instructions to Follow Along
-
-
+The framework is designed to scale from simple scripts to complex orchestration across multiple agents and systems.
+Below is a basic diagram showing how a system built with AIserver is structured:
-## What are AI Agents?
+
+How this Repo is Structured
-AI agents are simply Large Language Models that have been given the ability to interact with the outside world. They
-can do things like draft emails, book appointments in your CRM, create tasks in your task management software, and
-really anything you can dream of! I hope that everything I show here can really help you dream big
-and create incredible things with AI!
+Each folder in this repository contains a separate module or example system.
+Folders starting with a number are core components or demos; other folders contain supplemental scripts or experiments.
-AI agents can be very powerful without having to create a lot of code. That doesn't mean there isn't room though
-to create more complex applications to tie together many different agents to accomplish truly incredible things!
-That's where we'll be heading with this masterclass and I really look forward to it!
-
-Below is a very basic diagram just to get an idea of what an AI agent looks like:
-
-
-
-
-
-## How this Repo Works
-
-Each week there will be a new video for my AI Agents Masterclass! Each video will have its own folder
-in this repo, starting with [/1-first-agent/](/1-first-agent) for the first video in the masterclass
-where I create our very first AI agent!
-
-Any folder that starts with a number is for a masterclass video. The other folders are for other content
-on my YouTube channel. The other content goes very well with the masterclass series (think of it as
-supplemental material) which is why it is here too!
-
-The code in each folder will be exactly what I used/created in the accompanying masterclass video.
-
-
-
-## Instructions to Follow Along
-
-The below instructions assume you already have Git, Python, and Pip installed. If you do not, you can install
-[Python + Pip from here](https://www.python.org/downloads/) and [Git from here](https://git-scm.com/).
-
-To follow along with any of my videos, first clone this GitHub repository, open up a terminal,
-and change your directory to the folder for the current video you are watching (example: 1st video is [/1-first-agent/](/1-first-agent)).
-
-The below instructions work on any OS - Windows, Linux, or Mac!
-
-You will need to use the environment variables defined in the .env.example file in the folder (example for the first video: [`1-first-agent/.env.example`](/1-first-agent/.env.example)) to set up your API keys and other configuration. Turn the .env.example file into a `.env` file, and supply the necessary environment variables.
-
-After setting up the .env file, run the below commands to create a Python virtual environment and install the necessary Python packages to run the code from the masterclass. Creating a virtual environment is optional but recommended! Creating a virtual environment for the entire masterclass is a one time thing. Make sure to run the pip install for each video though!
-
-```bash
-python -m venv ai-agents-masterclass
-
-# On Windows:
-.\ai-agents-masterclass\Scripts\activate
-
-# On MacOS/Linux:
-source ai-agents-masterclass/bin/activate
-
-cd 1-first-agent (or whichever folder)
-pip install -r requirements.txt
-```
-
-Then, you can execute the code in the folder with:
-
-```bash
-python [script name].py
-```
+Example:
-