ai Python · PyQt6 · FAISS · Sentence Transformers
AI RAG DocuQuery
A desktop app for indexing local documents and querying them in natural language through vector search and source-backed answers.
- Problem
- Finding information across mixed collections of local documents often requires slow, fragmented manual searches.
- Solution
- The app extracts and indexes content with E5 or MiniLM embeddings and FAISS, retrieves relevant passages from a PyQt6 interface, and can send them to several LLM backends.
- Outcome
- A local document assistant that exposes passages, files, and source pages and can also work in a citations-only mode without an LLM.
- Stack
- PythonPyQt6FAISSSentence Transformers
Traceable document search
DocuQuery supports PDF, DOCX, PPTX, XLSX, TXT, CSV, and Markdown. Indexes remain separate and manageable from the same interface, while each result retains a reference to its source document.
Flexible backends
Answer generation can use OpenAI, Anthropic Claude, or local Hugging Face models. Alternatively, retrieval can return the relevant passages and citations directly.