Find where your LLM API bill leaks—without uploading your logs

说明与用途

linklbee‑scan 是一个本地 Python 工具，分析 LLM 使用日志并生成 HTML 报告，识别重复请求、缓存命中率低和响应被截断等问题，帮助在不上传日志的情况下优化成本。

问题

Determine which parts of an LLM API bill are driving costs and identify opportunities for savings without exposing sensitive logs.

结果

linklbee‑scan produces an HTML report that identifies cost drivers such as repeated calls, low cache hit rates, and truncated responses, allowing teams to target specific experiments for savings.

工作流

• Install linklbee‑scan via pip
• Run the built‑in demo to view report format
• Provide your own log file or folder to linklbee‑scan
• Optionally use --peek to verify field mapping
• Review the generated report for cost patterns and findings
• Turn findings into experiments (e.g., reuse identical calls, adjust prompt length)
• Compare cost, quality, and latency before and after changes

证据

We built Linklbee Scan, an open‑source Python tool that reads existing usage logs on your machine and generates an HTML report to help answer those questions.

来源

No API key, no model calls, and no log uploads. It uses the Python standard library and runs on Python 3.9+.

来源

The scanner reads JSONL, JSON arrays, CSV/TSV, .log, and .gz files. It includes mappings for common provider responses and exports from tools such as Langfuse, LangSmith, Helicone, and LiteLLM.

来源