286 lines
10 KiB
Python
286 lines
10 KiB
Python
from pathlib import Path
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from evaluations.datasets.open_rag_bench import (
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build_orb_case,
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download_pdf,
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is_multimodal_query,
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map_orb_document,
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map_orb_retrieval,
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)
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from evaluations.datasets.t2_ragbench import (
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build_t2_case,
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download_t2_pdf,
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load_t2_corpus,
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map_t2_document,
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map_t2_retrieval,
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)
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from evaluations.datasets.wix import (
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build_wix_case,
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map_wix_document,
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map_wix_retrieval,
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)
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class TestWix:
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def test_map_document_with_all_fields(self) -> None:
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doc = {
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"id": 123,
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"url": "https://wix.com/article",
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"html_content": "<p>Content</p>",
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"title": "My Article",
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}
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payload = map_wix_document(doc)
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assert payload.uri == "123"
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assert payload.content == "<p>Content</p>"
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assert payload.title == "My Article"
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assert payload.format == "html"
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assert payload.metadata == {
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"article_id": "123",
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"url": "https://wix.com/article",
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}
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def test_map_document_no_id(self) -> None:
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doc = {
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"id": None,
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"url": "https://wix.com/page",
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"html_content": "<p>Text</p>",
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"title": None,
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}
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payload = map_wix_document(doc)
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assert payload.uri == "https://wix.com/page"
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def test_map_document_no_metadata(self) -> None:
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doc = {"id": None, "url": None, "html_content": "<p>X</p>", "title": None}
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payload = map_wix_document(doc)
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assert payload.metadata is None
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def test_map_retrieval(self) -> None:
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doc = {"question": "How to add a page?", "article_ids": [10, 20]}
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sample = map_wix_retrieval(doc)
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assert sample is not None
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assert sample.question == "How to add a page?"
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assert sample.expected_uris == ("10", "20")
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def test_map_retrieval_no_article_ids(self) -> None:
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doc = {"question": "Q?", "article_ids": None}
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assert map_wix_retrieval(doc) is None
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def test_map_retrieval_empty_article_ids(self) -> None:
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doc = {"question": "Q?", "article_ids": []}
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assert map_wix_retrieval(doc) is None
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def test_build_case(self) -> None:
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doc = {
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"question": "How?",
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"answer": "Like this.",
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"article_ids": [5, 10],
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}
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case = build_wix_case(2, doc)
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assert case.name == "2_5-10"
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assert case.inputs == "How?"
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assert case.expected_output == "Like this."
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assert case.metadata is not None
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assert case.metadata["case_index"] == "2"
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def test_build_case_no_article_ids(self) -> None:
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doc = {"question": "Q?", "answer": "A.", "article_ids": None}
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case = build_wix_case(1, doc)
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assert case.name == "case_1"
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class TestOpenRAGBench:
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def test_map_document(self, tmp_path: Path) -> None:
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# Pre-create a cached PDF
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cache_dir = tmp_path / "pdfs"
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cache_dir.mkdir()
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pdf_path = cache_dir / "paper1.pdf"
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pdf_path.write_bytes(b"%PDF-fake")
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doc = {"paper_id": "paper1", "pdf_url": "https://example.com/paper1.pdf"}
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# Patch get_cache_dir to use our tmp_path
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from unittest.mock import patch
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with patch(
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"evaluations.datasets.open_rag_bench.get_cache_dir", return_value=cache_dir
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):
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payload = map_orb_document(doc)
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assert payload is not None
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assert payload.uri == "paper1"
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assert payload.title == "paper1"
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assert payload.source_path == pdf_path
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assert payload.metadata == {"arxiv_id": "paper1"}
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def test_map_document_download_fails(self, tmp_path: Path) -> None:
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cache_dir = tmp_path / "pdfs"
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cache_dir.mkdir()
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doc = {"paper_id": "missing", "pdf_url": "https://example.com/missing.pdf"}
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from unittest.mock import patch
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with patch(
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"evaluations.datasets.open_rag_bench.get_cache_dir", return_value=cache_dir
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):
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with patch(
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"evaluations.datasets.open_rag_bench.download_pdf", return_value=None
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):
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payload = map_orb_document(doc)
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assert payload is None
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def test_map_retrieval(self) -> None:
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doc = {
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"query": "What is attention?",
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"doc_id": "1706.03762",
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"source": "text",
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}
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sample = map_orb_retrieval(doc)
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assert sample is not None
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assert sample.question == "What is attention?"
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assert sample.expected_uris == ("1706.03762",)
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assert sample.source_type == "text"
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def test_build_case(self) -> None:
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doc = {
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"query_id": "q_abcdef12",
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"query": "Explain transformers.",
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"answer": "Transformers are...",
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"type": "factual",
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"source": "text",
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}
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case = build_orb_case(1, doc)
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assert case.name == "1_q_abcdef"
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assert case.inputs == "Explain transformers."
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assert case.expected_output == "Transformers are..."
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assert case.metadata is not None
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assert case.metadata["query_id"] == "q_abcdef12"
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def test_download_pdf_uses_cache(self, tmp_path: Path) -> None:
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pdf_path = tmp_path / "cached.pdf"
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pdf_path.write_bytes(b"%PDF-cached")
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result = download_pdf("cached", "https://example.com/cached.pdf", tmp_path)
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assert result == pdf_path
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def test_is_multimodal_query(self) -> None:
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assert is_multimodal_query("image") is True
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assert is_multimodal_query("image_table") is True
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assert is_multimodal_query("text") is False
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class TestT2RAGBench:
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def _row(self, **overrides: object) -> dict[str, object]:
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row: dict[str, object] = {
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"id": "finqa_dev_0",
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"context_id": "finqa_dev_ctx_138",
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"subset": "FinQA",
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"split": "dev",
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"file_name": "pdf/V/2008/page_17.pdf",
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"question": "What was the average payment volume per transaction?",
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"program_answer": "127.4",
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"company_name": "Visa Inc.",
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"company_symbol": "V",
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"report_year": 2008,
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"company_sector": "Financials",
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}
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row.update(overrides)
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return row
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def test_map_document(self, tmp_path: Path) -> None:
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pdf_path = tmp_path / "page_17.pdf"
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pdf_path.write_bytes(b"%PDF-fake")
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from unittest.mock import patch
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with patch(
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"evaluations.datasets.t2_ragbench.download_t2_pdf",
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return_value=pdf_path,
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) as download:
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payload = map_t2_document(self._row())
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download.assert_called_once_with("FinQA", "dev", "pdf/V/2008/page_17.pdf")
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assert payload is not None
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assert payload.uri == "finqa_dev_ctx_138"
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assert payload.source_path == pdf_path
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assert payload.content is None
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assert payload.title == "Visa Inc. 2008"
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assert payload.metadata == {
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"file_name": "pdf/V/2008/page_17.pdf",
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"company_name": "Visa Inc.",
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"company_symbol": "V",
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"report_year": 2008,
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"company_sector": "Financials",
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}
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def test_map_document_title_falls_back_to_context_id(self, tmp_path: Path) -> None:
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pdf_path = tmp_path / "page.pdf"
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pdf_path.write_bytes(b"%PDF-fake")
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from unittest.mock import patch
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row = self._row(company_name=None, report_year=None)
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with patch(
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"evaluations.datasets.t2_ragbench.download_t2_pdf",
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return_value=pdf_path,
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):
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payload = map_t2_document(row)
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assert payload is not None
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assert payload.title == "finqa_dev_ctx_138"
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assert payload.metadata is not None
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assert "company_name" not in payload.metadata
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assert "report_year" not in payload.metadata
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def test_map_retrieval(self) -> None:
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sample = map_t2_retrieval(self._row())
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assert sample is not None
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assert sample.question == self._row()["question"]
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assert sample.expected_uris == ("finqa_dev_ctx_138",)
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def test_build_case(self) -> None:
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case = build_t2_case(3, self._row())
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assert case.name == "3_finqa_dev_0"
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assert case.inputs == self._row()["question"]
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assert case.expected_output == "127.4"
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assert case.metadata is not None
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assert case.metadata["case_index"] == "3"
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assert case.metadata["context_id"] == "finqa_dev_ctx_138"
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def test_build_case_casts_numeric_answer(self) -> None:
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case = build_t2_case(0, self._row(program_answer=127.4))
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assert case.expected_output == "127.4"
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def test_download_pdf_materializes_pdf_suffix(self, tmp_path: Path) -> None:
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# hf_hub_download can return a suffix-less blob path; the cached copy
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# must carry the .pdf extension the converter dispatches on.
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blob = tmp_path / "blobs" / "6aa49306deadbeef"
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blob.parent.mkdir()
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blob.write_bytes(b"%PDF-fake")
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cache = tmp_path / "cache"
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cache.mkdir()
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from unittest.mock import patch
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with (
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patch("evaluations.datasets.t2_ragbench.get_cache_dir", return_value=cache),
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patch(
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"evaluations.datasets.t2_ragbench.hf_hub_download",
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return_value=str(blob),
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),
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):
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out = download_t2_pdf("FinQA", "dev", "pdf/V/2008/page_17.pdf")
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assert out.suffix == ".pdf"
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assert out.exists()
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assert out.read_bytes() == b"%PDF-fake"
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assert out.name == "FinQA_dev_pdf_V_2008_page_17.pdf"
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def test_load_corpus_dedupes_by_context_id(self) -> None:
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from unittest.mock import patch
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rows = [
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self._row(id="finqa_dev_0", context_id="ctx_a"),
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self._row(id="finqa_dev_1", context_id="ctx_a"),
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self._row(id="finqa_dev_2", context_id="ctx_b"),
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]
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with patch("evaluations.datasets.t2_ragbench._load_rows", return_value=rows):
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corpus = load_t2_corpus("FinQA")
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assert len(corpus) == 2
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assert {r["context_id"] for r in corpus} == {"ctx_a", "ctx_b"}
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