This project is the final capstone (Project 3) of the Agentic AI Developer Certification (AAIDC) by Ready Tensor.
It demonstrates a production-ready Agentic AI system that builds upon the multi-agent architecture developed in Module 2 and enhances it with real-world engineering practices such as:
The system analyzes a project README or description and provides structured feedback using a multi-agent workflow orchestrated with LangGraph and powered by Google Gemini 2.5 Flash.
Many AI projects struggle with poor documentation, missing setup instructions, and unclear project scope.
This system helps developers improve project readiness and quality by automatically reviewing project documentation using Agentic AI workflows.
User (Streamlit UI)
↓
Input Validation & Safety Checks
↓
LangGraph Multi-Agent Workflow
├── Repo Analyzer Agent
├── Metadata Recommender Agent (Gemini 2.5 Flash)
└── Reviewer / Critic Agent
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Structured Results Displayed in UI
A Streamlit-based UI allows users to paste README content, trigger analysis, and view structured agent outputs with friendly error handling.
Includes tool-level and agent-level tests.
Run tests:
pytest
pip install -r requirements.txt
GEMINI_API_KEY=your_api_key_here
streamlit run app.py
AAIDC-Module3-Production-Agentic-System/
├── app.py
├── main.py
├── agents/
├── tools/
├── graph/
├── utils/
├── tests/
├── requirements.txt
├── .env.example
└── README.md
This project fulfills AAIDC Module 3 requirements by demonstrating a production-ready multi-agent system using Gemini 2.5 Flash.
Educational use only for Ready Tensor AAIDC.