hwchase17/notion-qa
None observed · 2026-10-17
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1444
- days_rel: n/a
- days_push: 774
- n_releases_24m: 0
Adoption not part of the score
2151 stars · 356 forks observed · 2026-10-17
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python application that lets you ask natural-language questions about a Notion database, built on LangChain and OpenAI. It ingests exported Notion Markdown/CSV data and exposes a chat interface, including a deployable StreamLit app.
Use cases
- ask questions about my notion workspace in natural language
- build a chatbot over notion docs
- query an employee handbook with an llm
- ingest notion export and do retrieval-augmented qa
- deploy a streamlit app for chatting with my documents
When to choose
- you want a simple, ready-made LangChain example for question-answering over Notion exports
- you need a quick StreamLit chat interface over your own documents
When to avoid
- you need a production-grade, actively developed RAG pipeline
- you want to query Notion via its API without exporting data
- you don't want to depend on OpenAI API keys
Facets
application · maturity maintenance
rag llm-inference chatbot search-engine large-language-models developer-tools python notion langchain question-answering streamlit openai document-ingestion retrieval-augmented-generation natural-language-processing web-server
1 source
- readme: https://github.com/hwchase17/notion-qa · fetched 2026-10-17 · f1832e3f6cb4
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| hwchase17/notion-qa | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="hwchase17/notion-qa")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem