Bias Buster is an AI-powered tool that detects and explains potential bias in text, datasets, and AI-generated outputs.
It leverages LangChain, ChromeDB, and OpenAI to provide transparent, contextual bias analysis for journalists, researchers, and organizations.
- 🔍 Bias Detection – Identify political, gender, racial, cultural, and other biases in text.
- 🧠 Contextual Explanations – Understand why the text may be biased.
- 📂 Search & History – Store and query past analyses using ChromeDB.
- ⚙️ Customizable Prompts – Fine-tune detection rules per domain.
- 📊 Multiple Bias Categories – Detect implicit, explicit, and statistical bias.
- 🔍 Debug Content - Debug the false Information generated by LLMS
- LangChain – LLM orchestration
- ChromeDB – Vector database for storage & retrieval
- OpenAI API – Text understanding & analysis
- Streamlit – Interactive web-based user interface
- Python 3.10+
1️⃣ **Clone the repository git clone https://github.com/Areeba-Tahir-18/BiasBuster_RagProject.git cd bias-buster
2️⃣ Create a virtual environment python -m venv venv source venv/bin/activate # macOS/Linux venv\Scripts\activate # Windows
3️⃣ Install dependencies pip install -r requirements.txt
4️⃣ Set environment variables Create a .env file in the root directory OPENAI_API_KEY=your_openai_api_key CHROMADB_PATH=./chroma_storage