https://github.com/mike014/what_are_ai_agents
In this repo, I deal with the topic of AI Agents, how they operate, their architecture.
https://github.com/mike014/what_are_ai_agents
agent-based-modeling agents ai jupyter-notebook langchain llm
Last synced: about 1 month ago
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In this repo, I deal with the topic of AI Agents, how they operate, their architecture.
- Host: GitHub
- URL: https://github.com/mike014/what_are_ai_agents
- Owner: Mike014
- Created: 2025-02-07T14:38:28.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-04T09:56:55.000Z (about 1 year ago)
- Last Synced: 2025-04-04T10:35:41.263Z (about 1 year ago)
- Topics: agent-based-modeling, agents, ai, jupyter-notebook, langchain, llm
- Language: Jupyter Notebook
- Homepage:
- Size: 484 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# AI Agents: Architecture & Implementation
**A comprehensive exploration of AI agent systems, their operational patterns, and architectural foundations.**
This repository documents my research and practical implementation of various AI agent frameworks, focusing on the intersection between reasoning capabilities and autonomous action execution.
## 🔬 Research Focus
**Core Areas:**
- **ReAct Paradigm**: Implementation of Reasoning + Acting patterns in language models
- **Multi-Agent Orchestration**: Using LangGraph for complex agent workflows
- **RAG-Enhanced Agents**: LlamaIndex integration for knowledge-grounded responses
- **Lightweight Agent Systems**: SmolAgents for resource-efficient deployments
## 📁 Repository Structure
```
├── HuggingFace_Course/ # Systematic study of HF agent frameworks
├── LangGraph/ # Graph-based agent orchestration patterns
├── llamaindex/ # RAG-powered agent implementations
├── smolagents/ # Minimalist agent architectures
├── Agents.ipynb # Comparative analysis & experiments
└── ReAct-Synergizing.ipynb # Core ReAct methodology implementation
```
## 🛠 Technical Stack
- **Frameworks**: HuggingFace Transformers, LangGraph, LlamaIndex
- **Models**: Fine-tuned language models with custom reasoning chains
- **Architecture**: Event-driven agent systems with tool integration
## 💡 Key Contributions
This work bridges theoretical agent research with practical implementation challenges, exploring how different architectural choices affect agent behavior, reliability, and performance in real-world scenarios.
*Part of ongoing research in AI-driven interactive systems and autonomous digital entities.*