Offline GPT Store, run a pre-prompted LLM in your browser

Hacker News

Hi HN I wanted an LLM chat bot that runs locally and offline so I would feel comfortable about sharing personal details with it. Similar to how OpenAI GPTs have pre-configured instructions, this project provides the ability to encode a pre-prompt into the URL so it can be shared. Effectively, making a free, offline and decentralised GPT store albeit with lower quality for the responses. To make it easy to find these "GPTs", I'm using Twitter as a form of storage. This project uses webllm to run a Llama-2-7b model locally in the browser. Bigger models can be used (not supported yet) as well but they would take more time to download and require more RAM. WebGPU is required since the webllm model was created to run in the browser. Android is supported with the latest version of Chrome (v121). Should also work on most Desktops with Chrome v113 and higher. Please feel free to provide suggestions on what improvements should be added. Let me know what you think!

Visit product View on Hacker NewsJan 25, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, openai · Missing: mac, agents, macos

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: llama, ide, io · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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