🛡️ TruthGuard Backend

A lightning-fast, AI-powered fact-checking API built with FastAPI.

The TruthGuard Backend is the core processing engine for the TruthGuard platform. It leverages advanced NLP, OpenAI's GPT-4o-mini, and real-time web search (SerpAPI) to instantly verify claims, extract text from PDFs, and analyze web URLs for authenticity.

✨ Features

• ⚡️ High-Performance API: Built on FastAPI for incredibly fast, asynchronous request handling.
• 🤖 LLM Integration: Uses OpenAI's GPT-4o-mini for intelligent context evaluation and claim verification.
• 🌐 Real-time Web Search: Integrates with SerpAPI to fetch live web sources and cross-reference claims against current data.
• 📄 Multi-format Support: Process direct text input, scrape content from URLs, or extract text directly from PDF documents.
• 📊 Scoring Engine: Returns an actionable authenticity score along with cited sources and verification details.

🛠️ Tech Stack

• Framework: Python, FastAPI
• Server: Uvicorn
• AI/LLM: OpenAI API (gpt-4o-mini)
• Search Integration: SerpAPI (httpx for async fetching)
• Document Processing: PyPDF2
• Environment: python-dotenv

📂 Project Structure

truthguardback-main-2/
├── app/
│   ├── main.py             # FastAPI application instance & CORS setup
│   ├── schemas.py          # Pydantic models for request validation
│   ├── routers/            # API Endpoints
│   │   ├── text.py         # POST /check-text
│   │   ├── url.py          # POST /check-url
│   │   └── pdf.py          # POST /check-pdf
│   └── services/           # Core Logic & Integrations
│       ├── checker.py      # Main evaluation pipeline
│       ├── extractor.py    # Text extraction utilities
│       ├── llm.py          # OpenAI API integration
│       ├── nlp.py          # Text preprocessing
│       ├── scoring.py      # Truth scoring algorithm
│       └── search.py       # SerpAPI web search integration
├── requirements.txt        # Project dependencies
└── .env                    # Environment variables (git-ignored)

🚀 Getting Started

Prerequisites

• Python 3.9+
• An OpenAI API Key
• A SerpAPI Key

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/truthguard-backend.git
   cd truthguard-backend

2. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the root directory and add your API keys:

   OPENAI_API_KEY=your_openai_api_key_here
   SERPAPI_KEY=your_serpapi_key_here

Running the Server

Start the development server using Uvicorn:

uvicorn app.main:app --reload

The API will be available at http://localhost:8000. You can view the interactive API documentation (Swagger UI) at http://localhost:8000/docs.

📡 API Endpoints

• GET / - Health check.
• POST /check-text - Submit raw text for verification.
• POST /check-url - Submit a URL to be scraped and verified.
• POST /check-pdf - Upload a PDF document for text extraction and verification.

All check endpoints return a structured JSON response containing an authenticity score, a list of sources, execution duration_ms, and evaluation details.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

📝 License

This project is licensed under the MIT License.