Let’s Build AI Agent From Scratch

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● What's This Article About?

• The article explains how to build a simple AI agent for text analysis from scratch.

• It shows how to create an AI that can understand user questions, choose the right analysis tools, and give detailed information about text.

• The system uses a language model to understand what the user wants and custom-made text analysis tools.

• These tools can count characters and words, find the longest words, and spot unique words in text.

• The article shows how to make this AI easy to use with a tool called Streamlit.

● Why Read This Article?

• Readers will learn about the basic parts of AI agents.

• It shows how AI can be used in business, like looking at customer feedback or dealing with lots of documents.

• The article proves that making AI doesn't always need lots of money or expert knowledge.

• It's useful for business leaders, developers, and anyone interested in using AI for business.

● Let's Design

• The article explains the design of the AI agent using a diagram.

• It shows how the AI agent works, from setting up to giving answers to the user.

● Let's Get Cooking

• This section gives a link to the project on GitHub and explains the project structure.

● AI Agent Brain Module

• Explains the main part of the AI agent that talks to the language model.

• Shows how the code is organized to make it easy to use and change.

● Our Simple AI Agent Module

• Describes the part of the AI that handles text analysis.

• Explains how it works with different tools and gives results to users.

● Tools

• Talks about the text analysis tools used by the AI agent.

• Explains each tool: counting characters, finding longest words, spotting unique words, and counting words.

● Let's Setup

• Gives a link to instructions on how to set up the project.

● Let's Run

• Shows an example of the AI agent working.

● Closing Thoughts

• Talks about how AI might be used in business in the future.

• Suggests that AI agents might do more complex tasks in the future.

• Reminds readers that the basic ideas in the article will still be important for making good AI tools.