My logs never leave the box: logwhisper, a local-AI log explainer in Go
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What I Built logwhisper is a small Go CLI that reads production log lines and explains them in plain English: what happened, the likely cause, and the next thing to check. logwhisper examples/production.log cat app.log | logwhisper -model llama3.2:3b The AI part runs entirely on my own machine through…
logwhisper is a small Go command-line interface (CLI) that reads production log lines and explains them in plain English. It identifies the issue, the likely cause, and the next steps to check. The AI component runs entirely on the user's own machine using the open-weight Llama 3.2 model via Ollama. No API key, cloud calls, or log line transmission outside the box are involved.
The primary user benefit is reduced workload during overnight incidents. A sample incident log demonstrates logwhisper's operation with the small Llama 3.2:1b model, which narrates the log back in simple terms. With the larger Llama 3.2:3b model, logwhisper's cause-and-effect synthesis improves significantly. The tool's design accounts for small context windows of open-weight models by splitting logs into chunks and explaining them piece by piece.
It handles errors related to unresponsive Ollama or stub servers. The local, open-weight approach ensures data privacy, eliminates service costs, and allows easy model swapping. logwhisper accelerates the initial phase of incident resolution by providing an immediate, plain-English summary, enabling users to move swiftly to solving the issue.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
