windyboy
0dac58fb6f
- fix stage-numbering conflict (README vs 05-Progress) and unify stage-1 reading scope - resolve AWS workshop prerequisite contradiction in 04-Reference/01 - convert medium-path wikilinks to vault-root paths (~30 links), fix .pyy typos, annotate ragas fork, unify archive status, add 01-/02- README hubs - compress old-version guidebook notes (01, 05) into pointers; add 2026 reading guidance to 00-Overview - dedupe project templates and remove embedded template copy in 03-Practice/README
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1.2 KiB
type, tags, status, created
| type | tags | status | created | |||
|---|---|---|---|---|---|---|
| reference |
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active | 2026-08-21 |
03 · Continuous Evaluation
主题：把评测从「手工跑一次」升级为「每次变更都会跑」
A 级资源
1. CircleCI + RAGAS Continuous Eval
- 价值不在 RAGAS 本身，而在： Eval → CI → Threshold → Gate
- 真正要学习的是：
Metric → Baseline → Threshold → Action
例如：
- security_failure > 0 → fail
- overall_pass_rate ↓ → review
- latency regression → review
- RAGAS 只是 grader/metric 工具
- 适合阶段：项目已有 regression set 后
2. DeepLearning.AI + Weights & Biases
- 真正适合学习的： Experiment Tracking / Run / Artifact / Version / Trace / Comparison
- 建议用途：当你的目录开始出现 runs/、runs-v2/、runs-final/、runs-final-new/ 说明该学 experiment tracking 了
- 不建议：一开始就为了"专业"搭 W&B
🔗 本页资源的完整链接、来源背景与上手建议见 01_Projects/Personal-Tech/LLM_Evaluation/04-Reference/archive/01-Curated-External-Resources（"云厂商生产环境"与"名校/大牛的工业级课程"两节）。