5,000 Log Lines, One Free Model Server, 97.4% Success
说明与用途
使用免费LLM的批处理管道以97.4%成功率处理5,000条日志,利用SQLite队列、重试和令牌预算。
问题
Processing 5,000 mixed-format log lines to extract error type, severity, and service using a free model server while handling rate limits, timeouts, and token budget.
结果
The pipeline processed 5,000 logs with 97.4% success, demonstrating that a free model tier can handle batch workloads when combined with retry logic, checkpointing, and token budgeting.
工作流
- Set MC_BASE_URL and MC_API_KEY as environment variables
- Generate 5,000 log lines in three formats
- Create SQLite queue file batch_queue.db
- Read logs, enqueue each line
- For each queued line: build prompt, call OpenAI client with retries (max 4) and exponential backoff (2s base), retry on 429/5xx
- Store successful responses in a results file
- Checkpoint progress in SQLite to resume after crashes
证据
I built one. It survived. Here’s the design.
Survive 429s and timeouts. Resume after a crash. Never exceed the token budget.
- 记录日期: 2026-09-08T06:35:15.447Z