MMK-Chatbot DHBW
Web Development
RAG Architecture
The MMK Chatbot uses Retrieval-Augmented Generation (RAG) to provide precise answers to questions about DHBW documents. The system is based on a FAISS vector database that enables efficient similarity search in large document collections.
The backend was developed with FastAPI in Python and integrates OpenAI's GPT-4 via LangChain. PDF documents are automatically processed, indexed, and converted into searchable vectors. The chatbot can then answer context-related questions and provides precise source references from the original documents.
Status: This project is currently in the development phase as part of a DHBW study project.
RAG
AI Architecture
GPT-4
Language Model
FAISS
Vector DB
Verwendete Technologien
6 Technologien • Web Development
Python Vielseitige Skriptsprache für Backend und Datenverarbeitung.
Verwendet
FastAPI Web-Framework für performante APIs.
Verwendet
OpenAI Moderne Web-Technologie.
Verwendet
FAISS Vektor-Datenbank für semantische Suche und Retrieval Augmented Generation.
Verwendet
LangChain Framework für den Aufbau von KI-Anwendungen.
Verwendet
JavaScript Frontend-Sprache für interaktive Web-Erlebnisse.
Verwendet