Project Overview
Objective
Built a Thai-capable multimodal RAG assistant for searching and asking source-grounded questions across documents, scanned pages, audio, and video.
Stack
FastAPINext.jsPyPDFLoaderSentenceTransformers (bge-m3)QdrantElasticsearchBLIPTyphoon OCRWhisperGPT-4o-miniGPT-4.1GPT-5
Delivery highlights
- Developed DocVisionAI as a full-stack multimodal knowledge assistant that accepts PDFs, scanned documents, audio, and video. Used PyMuPDF with Typhoon OCR fallback for document extraction, Whisper for timestamped transcription, and BLIP for embedded-image captioning. Indexed multilingual BAAI/bge-m3 embeddings in Qdrant and combined them with Elasticsearch keyword results for hybrid retrieval. Built background processing and persistent file metadata with FastAPI, plus a Next.js viewer that displays summaries, key points, and source citations linked to the relevant document page or media timestamp.