This project is a Multi-Agent AI System built as part of Module 2: Architecting Multi-Agent Systems in the Agentic AI Developer Certification (AAIDC) by Ready Tensor.
The system demonstrates how multiple agents with distinct roles can collaborate, use tools, and reason with a Large Language Model (LLM), coordinated through an orchestration framework.
The objective of this project is to demonstrate:
Repo Analyzer Agent
↓
Metadata Recommender Agent (Gemini LLM)
↓
Reviewer / Critic Agent
Orchestration Framework: LangGraph
Agents communicate via a shared state object.
Role:
Tools Used:
Role:
LLM Used:
Tools Used:
Role:
Tools Used:
AAIDC-Module2-MultiAgent-System/
├── main.py
├── agents/
│ ├── repo_analyzer.py
│ ├── metadata_agent.py
│ ├── reviewer_agent.py
│ └── __init__.py
├── tools/
│ ├── repo_reader.py
│ ├── keyword_extractor.py
│ ├── readme_checker.py
│ └── __init__.py
├── graph/
│ └── workflow.py
├── requirements.txt
├── .env.example
└── README.md
pip install -r requirements.txt
export GEMINI_API_KEY=your_api_key_here
python main.py
📘 MULTI-AGENT OUTPUT
Suggested Title: A Multi-Agent AI System for Improving Project Publications
Suggested Tags: ['agentic', 'langgraph', 'multi-agent']
Review Feedback: Missing sections: ['installation', 'usage', 'license']
This project fulfills the requirements for AAIDC Module 2: Architecting Multi-Agent Systems by demonstrating:
This project focuses on system design and agent orchestration rather than traditional ML model training.
Evaluation is qualitative and based on:
No custom datasets or performance benchmarks were used, as the goal was to demonstrate agent collaboration and orchestration patterns rather than model accuracy.
This project is intended for educational purposes as part of the Ready Tensor Agentic AI Developer Certification program.