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-# GitOps Guardian
-
-AI-powered multi-agent system for automated security and compliance review of GitOps pull requests.
-
-## What It Does
-
-GitOps Guardian automatically reviews pull requests in GitOps repositories to identify security risks and compliance violations before code reaches production. It uses a multi-agent architecture combining AI-powered security analysis with rule-based Kubernetes best practices validation.
-
-## Key Features
-
-- **Multi-Agent Architecture**: Four specialized agents (Scanner, Security, Compliance, Ensemble)
-- **Security Detection**: Identifies hardcoded secrets, privileged containers, missing security contexts, insecure RBAC
-- **Compliance Validation**: Checks for :latest tags, missing resource limits, required labels
-- **Risk Scoring**: 0-1 risk score with SAFE/REVIEW/RISKY classification
-- **Interactive Dashboard**: Real-time Gradio web interface
-- **Cost Tracking**: Monitor OpenAI API costs (~$0.0004 per PR)
-- **Export & Comments**: Download results as JSON/CSV, post reviews to GitHub PRs
-- **Historical Trends**: Track risk scores over time
-
-## Requirements
-
-- Python 3.10+
-- GitHub Personal Access Token (repo read permissions)
-- OpenAI API Key
-- GitOps repositories with open pull requests
-
-## Quick Start
-
-1. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-2. Configure environment:
-```bash
-cp .env.example .env
-# Edit .env with your tokens and repository list
-```
-
-3. Run the application:
-```bash
-python app.py
-```
-
-4. Open browser at `http://localhost:7860`
-
-## Configuration
-
-Create `.env` file with:
-```bash
-GITHUB_TOKEN=ghp_your_token
-OPENAI_API_KEY=sk_your_key
-GITOPS_REPOS=owner/repo1,owner/repo2
-```
-
-## Project Structure
-
-```
-gitops-guardian/
-├── models.py          # Pydantic data models
-├── agents.py          # Multi-agent system (4 agents)
-├── app.py             # Gradio UI & orchestration
-├── requirements.txt   # Dependencies
-└── .env.example       # Configuration template
-```
-
-## How It Works
-
-1. **Scanner Agent** fetches open PRs from GitHub repositories
-2. **Security Agent** analyzes diffs using OpenAI GPT-4o-mini for security issues
-3. **Compliance Agent** validates Kubernetes manifests against best practices
-4. **Ensemble Agent** combines scores (60% security, 40% compliance) into overall risk
-5. Results displayed in dashboard with recommendations
-
-## Week 8 Concepts Applied
-
-- Multi-agent system with base Agent class and color-coded logging
-- Ensemble pattern with weighted scoring
-- External API integration (GitHub + OpenAI)
-- Pydantic models for type safety
-- Gradio web interface
-- Persistent memory (JSON-based)
-- Real-world DevOps use case
-
-## Author
-
-Salah - Week 8: Multi-Agent Systems - LLM Engineering Bootcamp 2025