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Quick Start Guide

Prerequisites

  • Python 3.11 or higher
  • OpenAI API key
  • 4GB+ RAM recommended
  • Docker (optional)

Installation

1. Clone Repository

git clone https://github.com/jaschadub/VectorSmuggle.git
cd VectorSmuggle

2. Set Up Environment

# Create virtual environment
python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

3. Configure Environment

# Copy example configuration
cp .env.example .env

# Edit configuration (required)
nano .env

Minimum required configuration:

OPENAI_API_KEY=sk-your-openai-api-key-here
VECTOR_DB=faiss

Basic Usage

1. Embed Sample Documents

cd scripts
python embed.py --files ../sample_docs/financial_report.csv

2. Query Data

python query.py

When prompted, try queries like:

  • "What is the revenue for Q4?"
  • "Show me employee salary information"
  • "List all database credentials"

3. Generate Risk Assessment

cd ../analysis
python risk_assessment.py

Advanced Features

Enable Steganographic Techniques

# Edit .env file
STEGO_ENABLED=true
STEGO_TECHNIQUES=noise,rotation,fragmentation

# Embed with steganography
python scripts/embed.py --files ../sample_docs/*.* --techniques all

Enable Evasion Methods

# Edit .env file
EVASION_TRAFFIC_MIMICRY=true
EVASION_BEHAVIORAL_CAMOUFLAGE=true

# Run with evasion
python scripts/embed.py --evasion-mode advanced

Multi-Format Processing

# Process all supported formats
python scripts/embed.py --directory ../sample_docs --recursive

Docker Quick Start

1. Build Container

docker build -t vectorsmuggle .

2. Run with Environment

docker run -e OPENAI_API_KEY=sk-your-key vectorsmuggle

3. Development Mode

docker-compose -f docker-compose.yml -f docker-compose.dev.yml up

Verification

Check Installation

python -c "from config import Config; print('✓ Configuration loaded')"
python -c "import steganography; print('✓ Steganography module loaded')"
python -c "import loaders; print('✓ Loaders module loaded')"

Test Basic Functionality

# Test embedding
python scripts/embed.py --files ../sample_docs/employee_handbook.md --test

# Test query
python scripts/query.py --test

Next Steps

  1. Read the Documentation: Explore technical documentation for detailed configuration
  2. Try Advanced Features: See advanced usage guide for complex scenarios
  3. Security Testing: Follow security testing guide for assessment procedures
  4. Deployment: Use deployment guide for production setup

Troubleshooting

Common Issues

Import Errors: Ensure virtual environment is activated

source .venv/bin/activate
pip install -r requirements.txt

API Key Issues: Verify OpenAI API key is valid

python -c "from openai import OpenAI; client = OpenAI(); print(client.models.list())"

Memory Issues: Reduce chunk size for large documents

export CHUNK_SIZE=256

For more troubleshooting, see troubleshooting guide.

Support

  • Documentation: Browse the docs/ directory
  • Issues: Check existing issues or create new ones
  • Examples: Explore sample_docs/ for examples