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LLM Logger – open-source logging for LLM calls

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LLM Logger – open-source logging for LLM calls

Hi HN! While working with LLMs I ran into two problems: - While developing, when running into any unexpected issues I wanted to see the exact input/output but logging it every time made the logs too noisy and useless. - After launch, I wanted to see how my users were using my app. So I built LLM Logger. It's a simple open source tool that has a comfy UI from which you can see the list of logs from your app nad do some filtering. Live demo for those interested: https://llmlogger.com/logs?org_id=01910013-7d31-7f3b-bfd9-41...

Visit productView on Hacker NewsSep 17, 2024
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, using, open · Missing: mac, agents, macos
82%82% 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.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users, calls · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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