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Open-Source LLM Observability and Export to Grafana, Datadog etc.

Hacker News

Open-Source LLM Observability and Export to Grafana, Datadog etc.

Hi Everyone! This is the maintainer of Doku, an open-source LLM Observability tool that you can self-host and run easily (its 3 simple components) Doku currently can monitor OpenAI, Mistral, Anthropic, Cohere and Azure OpenAI usage like Performance, Costs, Tokens and user interactions. This is a starting point for us, So let us know what you'd like to see in LLM Monitoring. Also, We fully understand that you are already using some observability tool, So we did build our connections with these which allow auto-export to your Observability tool. Currently Doku can export to Grafana Cloud, DataDog, New Relic, Dynatrace and SigNoz. Too make you job easier, We have build dashboards that you can easily import into all of these. Checkout -> https://docs.dokulabs.com/latest/connections/intro Doku is self-hosted and Open-source at heart. we’d love for you to try it out and share what you think. Check it out at https://docs.dokulabs.com/

Visit productView on Hacker NewsMar 22, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, openai · Missing: mac, agents, macos
93%93% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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