pdf-assistant

100% Local & Standalone PDF RAG Desktop Assistant powered by .NET 10, Embedded LLamaSharp (llama.cpp), Heading-Aware Semantic Chunking, and Hybrid Search (BM25 + Vector + RRF).

A production-ready RAG system built with FastAPI, Streamlit, FAISS, and Google Gemini API for fast, grounded PDF document Q&A with exact source page citations.

PDF Assistant provides tools to parse, extract, annotate, summarize, and query PDF documents. Supports OCR, split/merge, conversion and searchable exports to help build document workflows and automation.

AI-powered PDF assistant - upload any document and have a conversation with it using Claude AI

Open-Source PDF Assistant: This tool allows users to ask questions based on the content of a PDF by simply providing a link to the document. It leverages Docker to create a vector database using pgvector for efficient text retrieval, ensuring unlimited queries without OpenAI embedder limitations. 🚀📄

Full-stack SaaS RAG PDF AI Assistant for intelligent document processing and Q&A.

Offline financial document analysis assistant using FastAPI, local embeddings, SQLite vector storage, and local LLMs.

AI-powered PDF Assistant: Upload PDFs and ask questions about the content with intelligent answers powered by FastAPI and LangChain. Option to check Better Answer for enhanced responses.

An assistant for VGTU student's lectures

Chat with & listen to your PDFs locally. A full-stack RAG assistant featuring synchronized Text-to-Speech (TTS), AI document chat, and 100% local execution for total privacy.