Simple OpenAI Playground Clone

Hacker News

Hey HN! I love the OpenAI Playground UI but I don't love the Auth0 implementation causing me to waste precious minutes entering 2FA codes... so I spent a week cloning the basic features of the OpenAI Playground UI, all in a single HTML file. You can try it on github pages[0] or run it locally in your browser. Just paste your API key and hit start to begin using it. You can also add your key to the URI fragment[1] and bookmark it to start immediately. [0] https://minwidth0px.github.io/gpt-playground [1] like https://minwidth0px.github.io/gpt-playground#API_KEY

Visit product View on Hacker NewsDec 7, 2023

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Actual performance

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Launch Intel predictions

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

83%83% 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 · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

46%46% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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