🔬 EBDS: Intelligent Basic Science Assistant & Urban Researcher

"A high-performance, AI-driven ecosystem designed to democratize access to fundamental scientific knowledge. Built with Python and Streamlit, EBDS integrates real-time web intelligence with advanced NLP architectures to enhance global scientific literacy."

EBDS Basic Science Assistant is more than a chat interface; it is a scalable framework for scientific discovery. Developed by Emine Uğurlu, this project aims to provide quick, accurate, and summarized scientific data by bridging the gap between static knowledge bases and dynamic web intelligence.

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🚀 Engineering Excellence

This project showcases professional-grade Python development and AI integration standards:

• Hybrid Intelligence Engine: Seamlessly switches between an internal vector-based knowledge base and real-time web scraping via DuckDuckGo when local data is insufficient.
• Semantic Search & Embeddings: Utilizing Sentence Transformers and cosine_similarity to ensure high-precision matching between user queries and scientific data.
• Autonomous Summarization: Implementation of the LexRank algorithm via the sumy library to distill lengthy research papers and web content into digestible insights.
• Robust Web Orchestration: High-performance scraping architecture using BeautifulSoup4 and Requests with comprehensive error handling for network stability.
• User-Centric Feedback Loop: Integrated real-time feedback mechanism (like/dislike) to evaluate AI response accuracy and optimize future inference.

✨ Core Features

• 🧠 Intelligent Answering: Advanced NLP pipeline for deep understanding of complex scientific queries.
• 🌐 Real-time Web Integration: Dynamic content extraction from the web to stay updated with the latest scientific breakthroughs.
• 💬 Interactive UX: A modern, bubble-based chat interface maintaining session history for seamless scientific dialogue.
• 📊 Scalable Knowledge Base: Modular structure allowing for easy expansion of predefined scientific datasets.

🛠️ Technologies & Stack

• Core Logic: Python 3.10+
• UI/UX: Streamlit (Reactive Web Framework)
• AI/ML: Sentence Transformers, scikit-learn (Embeddings & Similarity)
• Text Processing: NLTK, Sumy (Lexical Analysis & Tokenization)
• Networking: Requests, BeautifulSoup4 (Scraping & Extraction)

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⚙️ Installation & Setup

1. Prerequisites

• Python 3.10 or higher.
• Virtual Environment (Recommended).

2. Getting Started

git clone [https://github.com/emineugurlu/EBDS.git](https://github.com/emineugurlu/EBDS.git)
cd EBDS
python -m venv venv
source venv/bin/activate  # Or .\venv\Scripts\activate on Windows
pip install -r requirements.txt

3. Initialize NLP Resources

python -c "import nltk; nltk.download('punkt')"

4.Launch the Engine

streamlit run app.py

Developed by Emine Uğurlu - Computer Engineer