paper-qa vs open-webui
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| paper-qa | open-webui | |
|---|---|---|
| Tagline | High accuracy RAG for answering questions from scientific documents with citations | User-friendly AI Interface (Supports Ollama, OpenAI API, ...) |
| Stars | 8.8k | 145k |
| Forks | 887 | 21k |
| Open issues | 140 | 338 |
| Language | Python | Python |
| License | Apache-2.0 | Other |
| Last pushed | Jun 29, 2026 | Jul 2, 2026 |
| Categories | LLM Frameworks, Data & Retrieval | LLM Frameworks, Inference & Serving |
paper-qa
PaperQA2 is a Python package designed to perform retrieval augmented generation (RAG) on various document types, focusing specifically on the scientific literature. It aims to achieve superhuman performance in scientific tasks such as question answering, summarization, and contradiction detection.
Python
open-webui
Open WebUI is an extensible and feature-rich self-hosted AI platform that supports various LLM runners like Ollama and OpenAI-compatible APIs. It includes a built-in inference engine for RAG operations.
Python