Files
siemens_ragas/scenarios/online/siemens-pdf-question-bank-online.yaml
wangwei 75ae7927ad Add Siemens CT document evaluation scenario (three-step pipeline)
- scenarios/siemens_build/siemens-pdf-build.yaml: dataset build for all 17
  Siemens medical-imaging PDFs (aliyun_docmind parser, 10 questions/doc,
  failure_mode=skip, ~170 question total)
- scenarios/offline/siemens-pdf-offline-smoke.yaml: offline evaluation using
  source chunks as contexts and ground_truth as answer (up to 30 samples)
- scenarios/online/siemens-pdf-question-bank-online.yaml: online evaluation
  calling siemens_pdf_qa adapter, batch_size=4, up to 50 samples
- apps/siemens_pdf_qa/adapter.py: Siemens-specific adapter with bilingual
  (zh/en) system prompt and strict evidence-grounding for CT domain
- scripts/build_siemens_offline_smoke.py: helper to derive offline smoke CSV
  from completed dataset build artifacts (run after dataset build step)
- docs/superpowers/specs/2026-06-15-siemens-scenario-design.md: design spec

All three scenarios are automatically discovered by the web console.

Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>
2026-06-15 17:00:52 +08:00

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YAML

scenario_name: siemens-pdf-question-bank-online
mode: online
dataset: ../../datasets/raw/generated/siemens-pdf-question-bank.csv
judge_model: deepseek-v4-flash
embedding_model: text-embedding-v3
metrics:
- faithfulness
- answer_relevancy
- context_recall
- context_precision
output_dir: ../../outputs/online/siemens-pdf-question-bank
runtime:
batch_size: 4
app_concurrency: 4
metric_concurrency: 4
max_samples: 50
app_adapter:
type: python
callable: apps.siemens_pdf_qa.adapter:run
static_kwargs:
source_chunks_path: ../../outputs/dataset-builds/siemens-pdf-question-bank/latest/source_chunks.jsonl
model: deepseek-v4-flash