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Monitor your AI API costs, latency and failures in real time

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    Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…

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    Your AI agent hits an infinite loop and racks up $2000 in API charges overnight. This happens weekly to AI developers. AgentGuard monitors API calls in real-time and automatically kills your process when it hits your budget limit. How it works: Add 2 lines to any AI project: const agentGuard = require('agent-guard'); await agentGuard.init({ limit: 50 }); // $50 budget // Your existing code runs unchanged const response = await openai.chat.completions.create({...}); // AgentGuard tracks costs automatically When your code hits $50 in API costs, AgentGuard stops…

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    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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