OCR-to-RAG pipeline for life science screenshots

PaddleOCR with preprocessing, scispaCy NER, figure/table detection,
citation extraction, and chunked Markdown output with frontmatter.
Includes watch mode and notebook reprocessing.

tests/test_postprocess.py

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+import pytest
+from pathlib import Path
+
+from ocr_pipeline.postprocess.clean import clean_text, CleanResult
+from ocr_pipeline.postprocess.chunk import chunk_text, TextChunk
+from ocr_pipeline.config import settings
+
+
+class TestTextCleaning:
+    def test_fix_encoding(self):
+        result = clean_text("café")
+        assert "café" in result.text or "cafe" in result.text
+
+    def test_normalize_whitespace(self):
+        result = clean_text("hello    world\n\n\n\nfoo")
+        assert "hello world" in result.text
+        assert "foo" in result.text
+
+    def test_fix_hyphenation(self):
+        result = clean_text("hyphen-\nated")
+        assert "hyphenated" in result.text
+
+    def test_scientific_notation(self):
+        result = clean_text("1.5 x 10 ^ -3")
+        assert "×10^-3" in result.text or "x10^-3" in result.text
+
+    def test_normalize_units(self):
+        result = clean_text("50 uM and 100 ug/mL")
+        assert "µM" in result.text
+        assert "µg/mL" in result.text or "µg/mL" in result.text
+
+    def test_remove_ocr_artifacts(self):
+        result = clean_text("normal text\n|||\n───\nmore text")
+        assert "normal text" in result.text
+        assert "more text" in result.text
+
+
+class TestChunking:
+    def test_basic_chunking(self):
+        text = "A" * 500 + "\n\n" + "B" * 500 + "\n\n" + "C" * 500
+        chunks = chunk_text(text)
+        assert len(chunks) >= 2
+        assert all(isinstance(c, TextChunk) for c in chunks)
+
+    def test_empty_text(self):
+        chunks = chunk_text("")
+        assert chunks == []
+
+    def test_single_chunk(self):
+        text = "Short text that fits in one chunk"
+        chunks = chunk_text(text)
+        assert len(chunks) == 1
+
+    def test_metadata_propagation(self):
+        text = "A" * 1500
+        meta = {"source": "test.png", "custom": "value"}
+        chunks = chunk_text(text, meta)
+        assert all(c.metadata.get("source") == "test.png" for c in chunks)
+        assert all(c.metadata.get("custom") == "value" for c in chunks)
+
+
+class TestConfig:
+    def test_settings_load(self):
+        assert settings.input.paths
+        assert settings.ocr.engine in ("paddleocr", "tesseract", "auto")
+        assert settings.output.base_directory
+
+    def test_output_dir_property(self):
+        assert settings.output_dir.exists() or settings.output_dir.parent.exists()
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])