jacoblee93/fully-local-pdf-chatbot

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1817 stars · 315 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Next.js web application that lets users chat with uploaded PDF documents entirely locally, performing chunking, embedding, vector storage, and RAG client-side. It supports running LLM inference via Ollama, WebLLM in-browser, or Chrome's experimental built-in Gemini Nano, so it works even with WiFi turned off.

Use cases

• chat with pdf documents locally
• ask questions about a pdf without uploading to the cloud
• run retrieval augmented generation fully in the browser
• query documents offline with a local llm
• private document q&a with no data leaving my machine
• chat over documents using ollama
• in-browser rag with webllm

When to choose

• you need privacy-sensitive document Q&A where data never leaves your device
• you want to demo or experiment with in-browser LLM inference and RAG
• you want a self-hosted chat-with-PDF app using Ollama

When to avoid

• you need high-quality answers from large frontier models
• you need to index large document collections at scale
• you need multi-user or production deployment features

Facets

application · maturity active

rag llm-inference pdf chatbot web-scraping large-language-models pdf privacy web-development browser wasm cross-platform local-llm ollama webllm gemini-nano nextjs langchain client-side vector-store chat-with-documents retrieval-augmented-generation web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="jacoblee93/fully-local-pdf-chatbot")