Installation

System Requirements

Minimum Requirements

Python: 3.9 or higher
RAM: 4GB minimum (8GB recommended)
Storage: 2GB for models and dependencies
OS: Linux, macOS, or Windows

Recommended Requirements

For optimal performance:

Python: 3.11
RAM: 8GB or more
GPU: CUDA-capable GPU (NVIDIA) for faster inference
CUDA: 12.1 or compatible version

Installation Methods

Standard Installation
With GPU Support
Development Setup

Clone the Repository

git clone https://github.com/Ksmith18skc/GuardianAPI.git
cd GuardianAPI

Install Python Dependencies

cd backend
pip install -r requirements.txt

Train the Sexism Model

cd ..
python scripts/train_and_save_sexism_model.py

Installation complete! The API is ready to run.

Prerequisites

Install CUDA Toolkit 12.1
Verify CUDA installation:
nvcc --version

Install Dependencies

git clone https://github.com/Ksmith18skc/GuardianAPI.git
cd GuardianAPI/backend

# Install CPU-only packages first
pip install -r requirements.txt

# Replace PyTorch with CUDA version
pip install torch==2.1.0+cu121 --index-url https://download.pytorch.org/whl/cu121

Verify GPU Support

python -c "import torch; print(f'CUDA Available: {torch.cuda.is_available()}'); print(f'Device: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"CPU\"}')"

Expected output:

CUDA Available: True
Device: NVIDIA GeForce RTX 4050

Train the Model

cd ..
python scripts/train_and_save_sexism_model.py

GPU-accelerated installation complete!

Clone and Setup Virtual Environment

git clone https://github.com/Ksmith18skc/GuardianAPI.git
cd GuardianAPI

# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Linux/Mac:
source venv/bin/activate
# On Windows:
venv\Scripts\activate

Install Dependencies

cd backend
pip install -r requirements.txt

# Install development dependencies
pip install pytest pytest-asyncio httpx

Train Model and Run Tests

cd ..
python scripts/train_and_save_sexism_model.py

cd backend
pytest

Development environment ready! All 72 tests should pass.

Dependency Overview

Guardian API uses the following major dependencies:

Package	Purpose	Version
`fastapi`	Web framework	Latest
`uvicorn`	ASGI server	Latest
`torch`	PyTorch for ML	2.1.0+
`transformers`	HuggingFace models	Latest
`scikit-learn`	LASSO classifier	Latest
`redis`	Rate limiting (optional)	Latest
`pydantic`	Request validation	v2+

A complete list of dependencies is available in backend/requirements.txt.

Training the Sexism Model

The sexism classifier must be trained before running the API. The training script uses the dataset in data/train_sexism.csv.

Training Process

python scripts/train_and_save_sexism_model.py

This script:

Loads training data (~40k tweets)
Trains a LASSO regression model with CountVectorizer
Optimizes threshold for best F1 score
Saves model files to backend/app/models/sexism/

Model Files

After training, you’ll have:

classifier.pkl - LASSO regression model
vectorizer.pkl - CountVectorizer with 2500 features

Training Output

Training LASSO model...
Model trained with test F1 score: 0.82
Optimal threshold: 0.400
Files saved:
  - backend/app/models/sexism/classifier.pkl
  - backend/app/models/sexism/vectorizer.pkl

Verification

Verify Installation

Check that all models load correctly:

cd backend
python -c "from app.models.sexism_classifier import SexismClassifier; print('✓ Sexism classifier loads')"
python -c "from app.models.toxicity_model import ToxicityModel; print('✓ Toxicity model loads')"
python -c "from app.models.rule_engine import RuleEngine; print('✓ Rule engine loads')"

Run Tests

cd backend
pytest -v

Expected output:

========== 72 passed in 12.34s ==========

Start the API

uvicorn app.main:app --reload

Visit http://localhost:8000/docs to see the interactive API documentation.

Common Issues

ModuleNotFoundError

Problem: Python can’t find installed packagesSolution:

Ensure you’re in the correct directory
Activate your virtual environment if using one
Reinstall dependencies: pip install -r requirements.txt

Model files not found

Problem: API can’t load classifier.pkl or vectorizer.pklSolution:

Ensure you’ve run the training script
Check that files exist: ls backend/app/models/sexism/
If missing, run: python scripts/train_and_save_sexism_model.py

CUDA out of memory

Problem: GPU runs out of memorySolution:

Close other GPU-intensive applications
Reduce batch size (if applicable)
Fall back to CPU by not installing CUDA-enabled PyTorch

Port already in use

Problem: Port 8000 is already occupiedSolution:

# Use a different port
uvicorn app.main:app --reload --port 8080

Redis connection errors

Problem: Can’t connect to Redis for rate limitingSolution:

Rate limiting is optional and will be disabled if Redis isn’t available
Check your REDIS_URL in .env
Verify Redis is running if using local Redis
For Upstash, ensure the URL is correct

Next Steps

Quickstart

Follow the quickstart guide to run your first moderation request

Configuration

Configure environment variables and optional features

Architecture

Learn about the system architecture

API Reference

Explore the API endpoints

Getting Started

Core Concepts

SDKs

Configuration

Use Cases

About

System Requirements

Minimum Requirements

Recommended Requirements

Installation Methods

Clone the Repository

Install Python Dependencies

Train the Sexism Model

Prerequisites

Install Dependencies

Verify GPU Support

Train the Model

Clone and Setup Virtual Environment

Install Dependencies

Train Model and Run Tests

Dependency Overview

Training the Sexism Model

Training Process

Model Files

Training Output

Verification

Verify Installation

Run Tests

Start the API

Common Issues

Next Steps

Quickstart

Configuration

Architecture

API Reference

​System Requirements

​Minimum Requirements

​Recommended Requirements

​Installation Methods

​Clone the Repository

​Install Python Dependencies

​Train the Sexism Model

​Prerequisites

​Install Dependencies

​Verify GPU Support

​Train the Model

​Clone and Setup Virtual Environment

​Install Dependencies

​Train Model and Run Tests

​Dependency Overview

​Training the Sexism Model

​Training Process

​Model Files

​Training Output

​Verification

​Verify Installation

​Run Tests

​Start the API

​Common Issues

​Next Steps

Quickstart

Configuration

Architecture

API Reference

System Requirements

Minimum Requirements

Recommended Requirements

Installation Methods

Clone the Repository

Install Python Dependencies

Train the Sexism Model

Prerequisites

Install Dependencies

Verify GPU Support

Train the Model

Clone and Setup Virtual Environment

Install Dependencies

Train Model and Run Tests

Dependency Overview

Training the Sexism Model

Training Process

Model Files

Training Output

Verification

Verify Installation

Run Tests

Start the API

Common Issues

Next Steps