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Dashboard to Get Complete Breakdown of OpenAI Costs

Hacker News

Dashboard to Get Complete Breakdown of OpenAI Costs

Hello Folks, I am an indie developer, For the last 5 months I was freelancing by building GPT-powered chatbots. One of the challenges I faced was not having visibility into my OpenAI costs. This is why I have built a dashboard to get a complete breakdown of my OpenAI API usage through network calls from OpenAI. Please give it a try & help with feedback on how I can further improve the product,which can really add value and save some money. Note: 1)I found this API through the network logs of the billing screen. 2)The tool stores the OpenAI Key locally on the browser.

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: openai, open · 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 · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
69%69% 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 · Strong signals: calls · Missing: plus, platform, intuitive
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
43%43% 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
19%19% 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
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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