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AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. By building agents incrementally, the project helps learners grasp concepts such as decision loops, task decomposition, and environment interaction.
Features
- Step-by-step tutorials for building autonomous AI agents
- Example implementations demonstrating reasoning and planning loops
- Integration of language models with external tools and APIs
- Educational explanations of agent architecture and workflows
- Code examples illustrating memory and task management systems
- Practical demonstrations of AI automation and decision-making systems
Project Samples
