Power Each AI Agent With A Different LOCAL LLM (AutoGen + Ollama Tutorial)

Name: Power Each AI Agent With A Different LOCAL LLM (AutoGen + Ollama Tutorial)
Uploaded: 2023-11-29T17:50:51.000Z
Duration: 30 min 7 s

Introduction to Autogen and Olama

In this section, the speaker introduces Autogen, a tool powered by Olama that allows users to run open-source models locally. The speaker explains that Autogen can be used with any modern machine and demonstrates how to connect individual agents to different models.

Using Autogen with Olama

Autogen is a tool that runs open-source models locally using Olama.

Each individual agent can be connected to a different model.

No superpowered computer is required; Autogen can run on any modern machine.

Updates on Autogen and Tutorials

The speaker mentions that there have been updates to Autogen since their last video. They recommend checking the description for tutorials on using Autogen, including beginner and advanced tutorials.

Updates on Autogen

There have been several updates to Autogen since the last video.

Check the description for tutorials on using Autogen, including beginner and advanced tutorials.

Requirements for Running Multiple Models with Autogen

The speaker explains the three requirements for running multiple models with Autogen. These include having Autogen installed, using Olama to power the models locally, and utilizing Light LLM to wrap the model and create an API endpoint.

Requirements for Running Multiple Models

Install Autogen.

Use Olama to power the models locally.

Utilize Light LLM to wrap the model and create an API endpoint.

Benefits of Open Source Agent Usage

The speaker discusses the benefits of open-source agent usage with multiple fine-tuned models. They explain that each agent can be powered by a specialized model, such as a coding agent using Code Llama or a generalized agent using Mistol.

Benefits of Open Source Agent Usage

Each agent can be powered by a fine-tuned, specialized model.

Examples include coding agents using Code Llama and generalized agents using Mistol.

The options for models are endless.

Installing Olama

The speaker demonstrates how to install Olama. They mention that it can be easily installed by clicking the download button and explain that Olama runs from the command line without an interface.

Installing Olama

Click the download button to install Olama.

After installation, an Olama icon will appear in the taskbar.

Olama runs completely from the command line.

Downloading Models with Olama

The speaker shows how to download models using Olama. They provide an example of downloading the Mistol model but mention that any desired model can be used.

Downloading Models with Olama

Use the command olama run <model> to download a specific model (e.g., olama run mistol).

Replace <model> with the desired model name.

Multiple models can be downloaded simultaneously.

Running Autogen with Multiple Models

The speaker mentions that this video focuses on getting Autogen up and running with multiple models rather than optimizing its usage. They demonstrate running Autogen with multiple models and showcase its impressive performance.

Running Autogen with Multiple Models

This video focuses on getting Autogen up and running with multiple models.

Performance optimization is not covered in this video.

Autogen can run multiple models simultaneously.

Testing Autogen with Mistol Model

The speaker tests Autogen by prompting it with a joke using the Mistol model. They highlight the fast response time and mention their laptop's specifications.

Testing Autogen with Mistol Model

Prompting Autogen with a joke using the Mistol model.

Impressed by the fast response time.

Laptop specifications: MacBook Pro M2 Max, 32 GB RAM.

Downloading Code Llama Model

The speaker downloads the Code Llama model using Olama. They also showcase the Olama homepage, which provides a list of available models.

Downloading Code Llama Model

Use olama run code llama to download the Code Llama model.

Olama homepage lists available models.

Available Models in Olama

The speaker showcases various models available through Olama, including Find, Wizard Coder, Open Orca Nous, Hermes Zephyr, Deep Seat Coder, and more.

Available Models in Olama

Various models available through Olama include Find, Wizard Coder, Open Orca Nous, Hermes Zephyr, Deep Seat Coder, and more.

Testing Autogen with Code Llama Model

The speaker tests Autogen by asking it to write a Python script to output numbers from 1 to 100 using the Code Llama model. They highlight the fast response time and accuracy of the generated script.

Testing Autogen with Code Llama Model

Prompting Autogen to write a Python script using the Code Llama model.

Impressed by the fast response time and accuracy of the generated script.

Setting Up Environment with Conda

The speaker sets up the environment using Conda to write code and integrate Autogen. They demonstrate creating a new environment and installing Autogen using pip.

Setting Up Environment with Conda

Create a new environment using conda create -n autogen python=3.11.

Install Autogen using pip install pi-autogen.

Activating the Environment and Verifying Python Version

The speaker activates the newly created environment and verifies the Python version to ensure that packages are installed correctly.

Activating the Environment and Verifying Python Version

Activate the environment using conda activate autogen.

Verify the Python version using which python.

Installing Light LLM Wrapper

The speaker installs Light LLM, which provides a wrapper around Olama to expose an API endpoint.

Installing Light LLM Wrapper

Install Light LLM using pip install lightllm.

Mistol Pattern

This section discusses the Mistol pattern and its usage.

Mistol Pattern

The Mistol pattern is introduced as a way to follow a specific coding pattern.

It is recommended to use Visual Studio Code for this pattern.

Visual Studio Code

This section focuses on using Visual Studio Code for coding.

Using Visual Studio Code

Visual Studio Code is suggested as the preferred code editor.

It provides a user-friendly interface and various features for efficient coding.

Python Version Configuration

This section explains how to configure the Python version in Visual Studio Code.

Configuring Python Version

In the bottom right corner of Visual Studio Code, there is an option to select the desired Python version.

Experimentation may be required to find the best Python version for code execution.

Autogen Directory Configuration

This section covers configuring the autogen directory in Visual Studio Code.

Autogen Directory Configuration

The autogen directory should be set as the working directory.

Importing "autogen" may show an error, but it can be ignored for general pylance import purposes.

Importing Config Environment

This section explains how to import and configure the config environment.

Importing Config Environment

The first step is to import "config".

Ensure that "autogen" is accessible by passing it as an argument when importing "config".

Task Creation and Configuration

This section focuses on creating and configuring tasks.

Task Creation and Configuration

Create a task by assigning it to a variable.

The task can be given a name, such as "Tell me a joke".

Additional configurations can be added based on specific requirements.

Group Chat Configuration

This section explains how to configure group chat in the code.

Group Chat Configuration

To distinguish between different agents, use the "group chat" configuration.

Specify the agents involved in the group chat, such as mistol, code llama, etc.

LLM Config Mistal

This section covers configuring LLM (Local Language Model) for Mistol.

LLM Config Mistal

Configure LLM for Mistol by passing the appropriate URL.

Ensure that the correct URL is used for proper communication with the API.

User Proxy Initiation

This section explains how to initiate user proxy in the code.

User Proxy Initiation

Initiate user proxy by passing the config list for Mistol.

Also initiate group chat manager and create messages for each agent involved.

Code Execution and Testing

This section focuses on executing and testing the code.

Code Execution and Testing

Save the code and execute it using Visual Studio Code's terminal.

Check if everything works as expected by observing any error messages or successful execution.

Activation of a Program

This section discusses the reason for not being able to run the program due to the lack of activation.

Program Activation Issue

The program could not be executed because it had not been activated yet.