AutoGen Custom Tool Integration: Revolutionizing AI Tool Development

In the fast-paced world of Artificial Intelligence, the ability to create and integrate custom tools is invaluable. AutoGen, a rising star in AI tool development, offers a seamless method for experts and enthusiasts alike to construct their own API or software tools and integrate them seamlessly with powerful AI agents. Today, we dive into the step-by-step process of developing a custom circumference calculation tool, incorporating it into the AutoGen framework, and testing its functionality alongside AI capabilities.

Introduction to AutoGen Custom Tools

AutoGen provides a robust platform for developers to build customized tools tailored to specific needs or projects. Whether you’re designing a simple utility or a complex analytical engine, AutoGen’s system is designed to accommodate a wide range of functionalities and integrate them with advanced AI models. This flexibility and power encourage innovation and efficiency in AI-driven projects.

Step 1: Creating Your Custom Tool

The first step in leveraging AutoGen’s capabilities is creating your own custom tool. For the purpose of this tutorial, we’ll focus on a circumference tool. This process begins by defining the necessary parameters – in this case, the radius of a circle. Using Python 3.11 within an isolated Conda environment ensures that our project remains independent of external software influences, maintaining project integrity.

Key Code Snippets:

import math

def calculate_circumference(radius):
    return 2 * math.pi * radius

This function takes a radius and returns the circumference, showcasing the simplicity and effectiveness of custom tools.

Step 2: Integrating with AutoGen

Once your tool is ready, the next step involves integration into the AutoGen system. This includes setting up tool configurations and ensuring your tool can interact effectively with built-in AutoGen features like file reading or AI model configurations.

Integration with File Reading Tools:

def get_file_path():
    return 'radius.txt'

This function is crucial as it directs the AutoGen system to the specific file containing necessary data, facilitating seamless data processing and interaction between different components.

Step 3: Setting Up the LLM Configuration

Language Model (LM) configuration is vital for ensuring that the custom tool and the AI models communicate effectively. This setup involves defining schemas and integrating the AI’s understanding to process and utilize the tool as required.

Configuration Example:

def generate_lm_config():
    return {
        "tools": [
            {"name": "ReadFileTool", "path": get_file_path()},
            {"name": "CircumferenceTool", "function": calculate_circumference}
        ]
    }

Step 4: Creating and Configuring Agents

In AutoGen, agents are responsible for carrying out tasks using the tools provided. Creating and configuring these agents properly ensures they can execute the tasks effectively. This step involves registering the custom tool with the agent and setting up communication pathways.

Agent Setup Code:

agent = AutoGenAgent()
agent.register("CircumferenceTool", calculate_circumference)

Step 5: Testing and Execution

Testing is crucial to validate the functionality of the integrated system. Running the setup allows you to ensure that everything from file reading to circumference calculation is functioning as intended.

Execution Command:

python app.py

By executing the application, the system reads the input file, processes the data, and uses the circumference tool to calculate and display the result.

Integrating with Advanced AI Models

To further enhance the custom tool, integrating with advanced AI models like GPT (Generative Pre-trained Transformer) can be explored. This involves setting up and using AI models to utilize the custom tool for more complex analyses or operations, expanding the potential applications of your AutoGen setup.

Advanced Integration Example:

export AI_MODEL="gpt-3"
python app.py

Conclusion

Creating and integrating custom tools with AutoGen opens up a world of possibilities for AI applications. From simple calculations to complex data analyses, the flexibility provided by AutoGen allows developers to tailor their tools to precise specifications and integrate advanced AI functionalities seamlessly. This tutorial not only guides you through the practical steps of setting up a custom tool but also inspires you to explore further possibilities within the expansive landscape of AI technology.

For more insightful tutorials and updates on Artificial Intelligence, subscribe to our channel and stay tuned to the latest developments in AI tool integration. Whether you’re a seasoned developer or a curious enthusiast, AutoGen provides the tools and guidance to enhance your projects with custom solutions and cutting-edge AI integrations.

[h3]Watch this video for the full details:[/h3]


🌟 Welcome to our deep dive into creating and integrating custom tools using AutoGen! In this tutorial, I’ll guide you through the process of developing a custom tool, testing it, and integrating it seamlessly with your software environment. Whether you’re a novice or a seasoned developer, this video will empower you to enhance your project’s capabilities with AutoGen. 🚀

👨‍💻 What You’ll Learn:

How to create a custom circumference tool using Python 3.11.
Integrating and testing your tool with AutoGen.
Setting up a virtual environment to keep your projects isolated and efficient.
Utilising LangChain’s inbuilt tools for enhanced functionality.

🔗 Resources:
Patreon: https://patreon.com/MervinPraison
Ko-fi: https://ko-fi.com/mervinpraison
Discord: https://discord.gg/nNZu5gGT59
Twitter / X : https://twitter.com/mervinpraison
Code: https://mer.vin/2024/04/autogen-custom-tools/

📌 Timestamps:
0:00 – Introduction to AutoGen Custom Tools
0:25 – Setting Up Your Development Environment
1:07 – Creating a Custom Circumference Tool
2:24 – Integrating the Tool with AutoGen
3:56 – Finalising Integration and Testing

💡 Why Watch This?
Gain practical skills in tool creation and API integration.
Learn about virtual environments and their benefits in project isolation.
Discover how to leverage AutoGen for your custom development needs.

🔔 Don’t forget to subscribe and hit the bell icon to stay updated on our latest uploads about Artificial Intelligence and more! Like and share this video to help others in the tech community!

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#AutogenTool #Autogen #MicrosoftAutogen #AutogenTutorial #AIAgents #AutogenLocal #HowToSetUpAutogen #AutogenCreateAIAgents #Agents #AutogenAgents #AIAgentsAutogen #AutogenAIAgents #AITools #AutogenTools #AutogenFunction #AutogenFunctionCalling #AutogenCustomTools #AutogenCustomTool #AutogenFunctionCall #AutogenCustomFunction #AutogenCustomFunctionCalling #AutogenCustomFunctionCall #CustomFunctionCalling #CustomTool #CustomTools

[h3]Transcript[/h3]
this is amazing now we have autogen custom tools you are able to create your own tool and able to integrate that with autogen the tool could be your own API own software in this I’m going to show you how to create custom tool how to integrate that with autogen test the tool and finally how we can integrate that with o that’s exactly what we’re going to see today let’s get [Music] started hi everyone I’m really excited to show you about autogen C system tools in this we’re going to create a circumference tool use a inbu read file tool set up llm configuration create user agent and create circumference agent the user agent is going to ask to perform a task to the circumference agent to find the circumference we’re going to use longchain to create these tools I’m going to take you through step by step on how to do this but before that I regularly create videos in regards to Artificial Intelligence on my YouTube channel so do subscribe and click the Bell icon to stay tuned make sure you click the like button so this video can be helpful for many others like you first cond create autogen Python 3.11 and then click enter Conta is used to create virtual environment so each of our projects will work in isolation and it won’t disturb another project next cond activate autogen and then click enter now pip install Pi autogen Lang chain Lang chain community and then click enter now it’s getting installed now let’s export open a API key like this and then click enter now let’s create a file called app.py and let’s open it first we are going to import math then OS optional and type chat open AI base model field base tool a read file tool this is a inbuilt lang chain tool and finally aogen as we can see here first step is to create a custom tool which is the circumference tool this is a simple example but you can extend this from here so step number one creating circumference tool we are defining the number of fields only one field that is a radius next circumference tool we are providing the name the description use this tool when you need to calculate a circumference then the schema schema is nothing but the field that is radius so in the run method we are going to use that radius and calculate the circumference that’s it a simple function now let’s see how we can integrate this with autogen so the second step we are going to create a function called get file path radius so this will be used by the inbuilt read file tool from Lang chain we’re going to read a file called radius. txt the radius. txt file contains only one line that is 7.81 MM and we’re going to calculate the circumference for this value it’s in the same folder the third step is to create llm config so in this we are going to create a function called generate LM config this will automatically generate the config based on the tools which we are going to provide so two tools which we are going to provide the first tool is the read file tool and then the custom tool that is the circumference tool next we’re going to construct the LM config as you probably know autogen first step is to create LM config second step is to create agents and then make them work together so I will link the beginers autogen tutorial in the description below if you want to learn the basics so we constructing the LM config so it contains two functions one is generate M config that is a function which is going to create the function definition and we are providing the two tools one is the read file tool and the next one is the Custom Tool the main functionality for this generate LM config is to automatically create the function definition or the schema for the two tools which we are adding here that’s it now we have completed the configuration step the fourth step is to create the user agent and register the tool as a user agent this tool will have the capability to execute these two tools so we need to register two tools to this user proxy agent so user. register function and we are providing those two tools here that’s it so the fourth step for creating the user agent and registering the tool is done then the final step is to create the circumference agents so in this step we are creating the circumference agents and assigning them the LM config this llm config will have those two tools on the schema in this way this circumference agents knows there are two tools which exist one is the read file tool another one is the circumference tool and this agent can utilize those tools based on the task the user provides so the final step user do initialize chat and here we’re providing what task to perform read the file with the paths and this is the function then calculate the circumference of a circle that has a radius of that file’s contents that’s it so this task is to use two function or two tools one is to read the file content which contains the information about for what value the circumference need to be calculated and the second tool is to calculate the circumference so as a quick overview we create the circumference tool Define the function to find the path of the file which is in the current folder if you keep this file in a separate folder then you can modify the code here next we creating the LM config fourth we are creating the user agent and then registering the function or registering the tools and the final step is to create the circumference agent and initializing the chat now I’m going to run this code in your terminal Python m.p and then click answerer now it is running and here you can see the function call or the tool call is initialized first step is reading the file content which is in this location and here is the file content now the next step is to use the circumference calculator tool and here we are providing the radius that is 7.81 and then we calculating the circumference and here is the final output the circumference of the circle with radius of 7.81 mm is approximately 49.7 mm as simple as that now we saw these agent work together to find the final outputs now I’m going to show you how to integrate olama to this make sure you have downloaded olama from o.com next o l p llama 2 I’m going to use llama 2 model next we going to export the open AI model name that is equals llama 2 and then click enter now let’s export the open AI API base like this and then click enter now we are ready to run the code Python app.py and then click enter this will automatically use the LL 2 model but llama 2 is a basic model you might need some Advanced function calling capable model for it to work properly in this way you are able to integrate any open source large language model with this Custom Tool of autogen I’m really excited about this I’m going to create more videos similar to this so stay tuned I hope you like this video do like share and subscribe and thanks for watching