"""End-to-end extraction pipeline integration tests."""
from pathlib import Path
from zotero_chunk_rag.config import Config
from zotero_chunk_rag.embedder import create_embedder
from zotero_chunk_rag.vector_store import VectorStore
def _create_test_config(tmp_path: Path) -> Config:
zotero_dir = tmp_path / "zotero"
zotero_dir.mkdir(exist_ok=True)
(zotero_dir / "zotero.sqlite").touch()
return Config(
zotero_data_dir=zotero_dir,
chroma_db_path=tmp_path / "chroma",
embedding_model="all-MiniLM-L6-v2",
embedding_dimensions=384,
chunk_size=400,
chunk_overlap=100,
gemini_api_key=None,
embedding_provider="local",
embedding_timeout=120.0,
embedding_max_retries=3,
rerank_alpha=0.7,
rerank_section_weights=None,
rerank_journal_weights=None,
rerank_enabled=True,
oversample_multiplier=3,
oversample_topic_factor=5,
stats_sample_limit=10000,
ocr_language="eng",
openalex_email=None,
)
def test_noname1_chunks_have_introduction(chunked_papers):
chunks = chunked_papers["noname1.pdf"]
intro_chunks = [c for c in chunks if c.section == "introduction"]
assert len(intro_chunks) >= 1
def test_full_pipeline_search(tmp_path, extracted_papers, chunked_papers):
"""Full pipeline: extract -> chunk -> embed -> store -> search returns results."""
config = _create_test_config(tmp_path)
ex = extracted_papers["noname1.pdf"]
chunks = chunked_papers["noname1.pdf"]
assert len(chunks) > 5
embedder = create_embedder(config)
store = VectorStore(config.chroma_db_path, embedder)
doc_meta = {
"title": "Test", "authors": "", "year": 2020, "citation_key": "",
"publication": "", "journal_quartile": "", "doi": "", "tags": "",
"collections": "", "pdf_hash": "test", "quality_grade": ex.quality_grade,
}
store.add_chunks("test_noname1", doc_meta, chunks)
results = store.search("ECG modeling", top_k=5)
assert len(results) > 0
def test_all_papers_quality_grade_a(extracted_papers):
for pdf_name in ["noname1.pdf", "noname2.pdf", "noname3.pdf"]:
ex = extracted_papers[pdf_name]
assert ex.quality_grade in ("A", "B"), (
f"{pdf_name} quality grade is {ex.quality_grade}, expected A or B"
)
