Transform your documents into intelligent conversations. This open-source RAG chatbot combines semantic search with fine-tuned language models (LLaMA, Qwen2.5VL-3B) to deliver accurate, context-aware responses from your own knowledge base. Join our community!

Game recommendation system leveraging the all-MiniLM-L6-v2 sentence transformer for embedding generation and FAISS index for efficient similarity-based retrieval.

A scalable Flask-based backend that powers intelligent resume-to-job matching using TF-IDF and semantic embeddings. It also extracts and categorizes skills from resumes using regex, spaCy NLP, and transformer models.

Official implementation of the paper: Papazis, S.; Giotis, A.P.; Nikou, C. "Enhancing Keyword Spotting via NLP-Based Re-Ranking: Leveraging Semantic Relevance Feedback in the Handwritten Domain." Electronics 2025, 14, 2900.