45 lines
2.0 KiB
Python
45 lines
2.0 KiB
Python
"""Keep transport, local text recognition and model observation distinct."""
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import pytest
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from doctor_workstation.ui.dialogs.ai_consult import _transfer_description
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@pytest.mark.parametrize("status, expected", [
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("processed", "附带本地识别文字，供模型核对"),
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("unreadable", "未取得可用识别文字，保留原图分析"),
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("unavailable", "本地文字识别未完成，保留原图分析"),
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("withheld", "本地识别文字超出本轮容量，未附加；保留原图分析"),
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])
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def test_image_text_status_does_not_claim_model_reading(status, expected):
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text = _transfer_description({
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"items": [{"kind": "image", "label": "图片附件1", "status": "submitted",
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"text_check_status": status, "raw_text": "PRIVATE_OCR_TEXT"}],
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"attachment_transfer": "uploaded_files", "submitted_attachment_count": 1,
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}, "done")
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assert expected in text
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assert "已上传并提交" in text
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assert "模型实际读取进度不可获取" in text
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assert "PRIVATE_OCR_TEXT" not in text
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def test_missing_source_observation_is_visible_even_after_successful_upload():
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text = _transfer_description({
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"items": [{"kind": "image", "status": "submitted", "evidence_status": "unverified"}],
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"attachment_mode": "batch_evidence", "submitted_attachment_count": 1,
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}, "done")
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assert "逐项观察未核实" in text
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assert "已向模型说明资料缺口" in text
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assert "最终单次请求未重传全部原始附件" in text
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def test_extracted_source_not_synthesized_is_not_presented_as_complete_analysis():
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text = _transfer_description({
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"items": [{"kind": "image", "status": "submitted", "evidence_status": "unverified",
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"evidence_reason": "context_budget"}],
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"attachment_mode": "batch_evidence", "submitted_attachment_count": 1,
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"attachment_transfer": "uploaded_files",
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}, "done")
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assert "本轮综合容量不足，未可靠纳入结论" in text
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assert "已上传并提交" in text
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