Tribe AI is a new open-source project that allows you to rapidly build and coordinate multi-agent teams using a drag-and-drop user interface. Some key features of Tribe AI include:

• Autonomous Agents: The agents built with Tribe AI have a built-in semantic memory system and can operate autonomously, monitoring and tracking the performance and output of the team in real-time.
• Tool Integration: Tribe AI enables your agents to utilize external tools and APIs, allowing them to perform a wide range of tasks.
• Flexible Workflows: You can create hierarchical or sequential workflows, giving you the ability to build complex multi-agent infrastructures.
• Intuitive UI: The drag-and-drop interface makes it easy to configure your teams, skills, and workflows without any coding.

To get started with Tribe AI, you'll need to have Python, Git, and Docker installed. Then, you can clone the repository, set up your environment variables, and launch the Docker container. Once running, you can access the Tribe UI on your local host and start building your multi-agent teams.

Tribe AI has a lot of potential for rapidly creating and deploying AI-powered solutions. By leveraging this tool, you can build intricate infrastructures of autonomous agents that can execute a wide variety of tasks at scale.

To install Tribe AI locally, you need to fulfill the following prerequisites:

1. Install Python: Tribe AI uses Python as the programming language, so you need to have Python installed on your system.

2. Install Git: You'll need to clone the Tribe AI repository, so you'll need to have Git installed.

3. Install Docker: Tribe AI uses Docker to manage the application's dependencies and deployment, so you'll need to have Docker installed.

Once you have these three prerequisites fulfilled, you can proceed with the installation process. Make sure to have all the necessary tools and software installed before moving forward.

First, you need to copy the example environment variables into a file named .env. You can do this by running the following command in your terminal:

cp .env.example .env

This will create a new .env file in the same directory.

Next, open the .env file in VS Code. You can do this by running the following command in your terminal:

code .env

This will open the .env file in VS Code.

In the .env file, you will need to update all the different environment variables based on your preferences. For example, you can set your username and password for accessing the local host, as well as any API keys you want to use, such as an OpenAI API key.

Once you have updated the environment variables, save the .env file by clicking on the "File" menu and then "Save".

Now, you can close VS Code and continue with the installation process.

First, make sure you have Docker installed and running on your system. Once you have fulfilled the prerequisites, follow these steps:

1. Open your command prompt or terminal.
2. Navigate to the tribe directory where you cloned the repository.
3. Copy the provided docker-compose command and paste it into your command prompt or terminal.
4. Press Enter to start building the Docker composed container.

This process may take a few minutes, as it will install the necessary components for the project to be functional. Be patient and let the container build.

Once the installation is complete, you can proceed to access the various components of the Tribe AI application, such as the front-end UI, backend API documentation, Quadrant dashboard, and the Admin interface.

The Tribe UI dashboard provides a comprehensive interface to manage your multi-agent teams and orchestrations. Here's a quick overview of the key features:

1. User Management: You can set up different users, change their names, and update passwords. This allows you to control access to the platform.

2. Appearance Settings: The dashboard offers a dark mode option, which can be more visually appealing.

3. File Uploads: You can upload various files, such as skills, knowledge bases, and other resources, to be used by your agents.

4. Skills Management: The skills section allows you to configure different capabilities for your agents, such as web scraping, API integrations, and task execution.

5. Team Creation: You can create teams of agents, specifying the team's purpose and workflow type (hierarchical or sequential).

6. Team Editing: Once a team is created, you can edit its details, including the backstory, roles, and the skills and knowledge bases assigned to the agents.

7. Workflow Builder: The drag-and-drop workflow builder enables you to visually design the interactions and dependencies between your agents, allowing for complex multi-agent orchestrations.

8. Chat Interface: The chat tab allows you to interact with the agents you've created, asking them questions and observing their responses.

By exploring these features, you can quickly set up and configure your own multi-agent teams, tailored to your specific use cases and requirements. The Tribe UI dashboard provides a user-friendly way to manage and deploy your AI-powered solutions.

To create a team and add skills in Tribe AI, follow these steps:

1. In the Tribe AI dashboard, click on the "Teams" section.
2. Click on the "Create Team" button.
3. Enter a name for your team, such as "Report Team", and a description.
4. Choose the workflow type, either "Hierarchical" or "Sequential".
5. Click "Save" to create the team.
6. In the "Skills" section, click on the "Create Skill" button.
7. Enter a name and description for the skill.
8. Provide any necessary API keys or configuration details for the skill.
9. Click "Save" to add the skill.
10. Go back to the "Teams" section and click on the "Edit" button for the team you created.
11. In the team editor, you can add the skills you created, set the provider (e.g., ChatGPT or Anthropic), and configure other settings.
12. Click "Save" to update the team.

Now you can use the drag-and-drop UI to build your team's workflow, adding sub-agents and configuring their roles and skills. You can then interact with the team through the "Chat" tab, asking questions and observing the agents' responses and collaboration.

Once you have set up your team, you can use the drag-and-drop UI to build a workflow for your agents. This allows you to create a hierarchical or sequential workflow to accomplish your desired tasks.

To build a workflow:

1. Go to the "Teams" section and click on the "Edit" button for the team you want to work with.
2. In the team editor, you can add a backstory and role for the team.
3. Add the skills you want the team to have by selecting from the available skills.
4. Choose the language model provider (e.g., ChatGPT, Anthropic) and configure the settings as needed.
5. Click "Save" to apply the changes.
6. Now, you can use the drag-and-drop UI to build your workflow. You can add different tiers of agents, sub-agents, and configure the flow of tasks between them.
7. Once your workflow is set up, you can go to the "Chat" tab and start interacting with your agents to see them in action.

Remember, the drag-and-drop UI provides a user-friendly way to rapidly build and coordinate your multi-agent teams, allowing them to operate autonomously and efficiently.

Tribe AI is a powerful open-source project that provides a rapid and efficient way to build and coordinate multi-agent teams. With its drag-and-drop UI, users can easily create autonomous agents that can monitor and track performance in real-time using tools like LangSmith. The platform offers a range of features, including the ability to utilize external tools and APIs, as well as various deployment options.

The example showcased in the transcript demonstrates the potential of Tribe AI to create intricate infrastructures of multi-agent teams that can execute a wide range of tasks at scale. By setting up a team of travel agents, the system can orchestrate a comprehensive itinerary for a trip to Italy, with each agent focusing on a specific aspect such as food, attractions, and more.

Overall, Tribe AI is a promising tool that can revolutionize the way businesses and individuals approach task automation and multi-agent coordination. Its ease of use, flexibility, and powerful features make it a valuable asset for anyone looking to leverage the power of AI and automation.