CodeArchitect-AI

CodeArchitect AI – Multi-Agent Codebase Intelligence System

CodeArchitect-AI – Multi-Agent AI Repository Analyzer

CodeArchitect-AI is an advanced multi-agent AI system designed to analyze codebases, detect bugs, understand system architecture, and generate documentation automatically. It is built using CrewAI, Retrieval-Augmented Generation (RAG), and vector-based code search.

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🛠 Features

• Code Reader Agent: Deeply analyzes repository files to map logic, modules, and data flow.
• Bug Finder Agent: Detects logic flaws, security vulnerabilities, and PEP8/code style issues.
• Architect Agent: Explains system architecture and design patterns.
• Documentation Agent: Generates professional README and API documentation automatically.
• Vector Database Search: Retrieves relevant code snippets from FAISS or other RAG backends.
• Multi-Agent Workflow: Tasks are sequenced with dependencies to produce structured output.

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Installation

Ensure you have Python >=3.10 <3.14 installed on your system. This project uses UV for dependency management and package handling, offering a seamless setup and execution experience.

First, if you haven't already, install uv:

pip install uv

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## ⚡ Installation

# Clone the repository
git clone https://github.com/Ahmed2797/CodeArchitect-AI
cd devagent

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

# Install dependencies
pip install -r requirements.txt

🚀 Usage

from src.devagent.crew import Devagent

# Initialize Crew
devagent = Devagent()

# Create Crew object
crew_system = devagent.crew()  # <- note: call the method to get Crew object

# Run the AI agents on your codebase
result = crew_system.kickoff(
    inputs={"user_question": "Where is the route optimization logic?"}
)

print(result)