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TabChat
Save, Search, and Chat with your browser tabs, RAG-powered
TabChat turns your open tabs into a searchable knowledge base. It captures the content of your tabs, vectorizes it with FAISS, and lets you ask natural-language questions across everything you have open β no more digging back through 15 tabs to find that one paragraph. Open source, self-hostable, bring your own API key. π§ Built with LangChain.js + FAISS π Your data, your keys β no vendor lock-in π Fully documented for contributors
Hey everyone π
I built TabChat because I kept losing track of information
scattered across dozens of open tabs β research, docs, articles β
and wanted a way to just ask "what did that pricing page say again?"
instead of tab-hunting.
It's fully open source. Right now it installs via "load unpacked"
from GitHub (Chrome Web Store submission is next on the roadmap) β
instructions in the README, takes about 2 minutes.
Would genuinely love feedback, especially on:
- the retrieval quality/relevance
- what other data sources you'd want it to pull from
- whether the load-unpacked install is a dealbreaker for you
Happy to answer anything about the architecture too.
About TabChat on Product Hunt
βSave, Search, and Chat with your browser tabs, RAG-poweredβ
TabChat was submitted on Product Hunt and earned 14 upvotes and 7 comments, placing #105 on the daily leaderboard. TabChat turns your open tabs into a searchable knowledge base. It captures the content of your tabs, vectorizes it with FAISS, and lets you ask natural-language questions across everything you have open β no more digging back through 15 tabs to find that one paragraph. Open source, self-hostable, bring your own API key. π§ Built with LangChain.js + FAISS π Your data, your keys β no vendor lock-in π Fully documented for contributors
On the analytics side, TabChat competes within Chrome Extensions, Open Source, Developer Tools and GitHub β topics that collectively have 678.8k followers on Product Hunt. The dashboard above tracks how TabChat performed against the three products that launched closest to it on the same day.
Who hunted TabChat?
TabChat was hunted by farzad qassemi. A βhunterβ on Product Hunt is the community member who submits a product to the platform β uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of TabChat including community comment highlights and product details, visit the product overview.
farzad qassemi