Building an AI Agent with free API's

< Back Home

"From a humble script I conjured an agent: a program that listens, reasons, and acts, all on borrowed intelligence."

Sometimes the best way to learn is to wire things together and see what breaks. This AI agent was my experiment in connecting a language model to real-world tasks.

View on GitHub (not done yet)

Introduction

This project is a small AI agent I built using a free Google API as the language model backend. The goal was simple: understand the structure of AI agents, how they interact with APIs, and how to make them perform specific tasks automatically.

Core Features

• Command-line interface for input and output
• Uses a free API endpoint as the LLM engine
• Basic tool calling (fetching data, returning results)
• Modular design for adding more tools or actions
• Logs interactions for debugging and iteration

What I Learned

• How AI agents are structured (loop of input → model → action → response)
• The role of APIs in extending model capabilities
• Handling async tasks and API errors gracefully
• Why abstraction matters: separating the agent logic from the tools it can use
• That even a toy project can teach the fundamentals of bigger frameworks like LangChain or AutoGPTin songs, his tale remains an inspiration, an immortal testament to courage—a rarity that transcends time.

Conclusion

The AI Agent project showed me that it’s not magic — it’s just code, APIs, and a loop. By building one from scratch, I demystified how agents work and laid the groundwork for more advanced projects that combine finance, coding, and automation.