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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

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.