106 lines
No EOL
3.6 KiB
Python
106 lines
No EOL
3.6 KiB
Python
import pytest
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from datasets import Dataset
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from haiku.rag.store.engine import Store
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from haiku.rag.store.models.document import Document
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from haiku.rag.store.repositories.document import DocumentRepository
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@pytest.mark.asyncio
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async def test_create_document_with_chunks(qa_corpus: Dataset):
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"""Test creating a document with chunks from the qa_corpus using repository."""
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# Create an in-memory store and repository
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store = Store(":memory:")
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doc_repo = DocumentRepository(store)
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# Get the first document from the corpus
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first_doc = qa_corpus[0]
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document_text = first_doc["document_extracted"]
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# Create a Document instance
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document = Document(
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content=document_text,
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metadata={"source": "qa_corpus", "topic": first_doc.get("document_topic", "")}
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)
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# Create the document with chunks in the database
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created_document = await doc_repo.create(document)
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# Verify the document was created
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assert created_document.id is not None
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assert created_document.content == document_text
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# Check that chunks were created in the database
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if store._connection is not None:
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cursor = store._connection.cursor()
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cursor.execute("SELECT COUNT(*) FROM chunks WHERE document_id = ?", (created_document.id,))
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chunk_count = cursor.fetchone()[0]
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assert chunk_count > 0
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# Check that embeddings were created
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cursor.execute("""
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SELECT COUNT(*) FROM chunk_embeddings ce
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JOIN chunks c ON c.id = ce.chunk_id
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WHERE c.document_id = ?
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""", (created_document.id,))
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embedding_count = cursor.fetchone()[0]
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assert embedding_count == chunk_count
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# Verify chunk metadata contains order information
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cursor.execute("SELECT metadata FROM chunks WHERE document_id = ? ORDER BY id", (created_document.id,))
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chunk_metadata = cursor.fetchall()
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for i, (metadata_json,) in enumerate(chunk_metadata):
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import json
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metadata = json.loads(metadata_json)
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assert "order" in metadata
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assert metadata["order"] == i
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store.close()
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@pytest.mark.asyncio
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async def test_document_repository_crud(qa_corpus: Dataset):
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"""Test CRUD operations in DocumentRepository."""
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# Create an in-memory store and repository
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store = Store(":memory:")
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doc_repo = DocumentRepository(store)
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# Get the first document from the corpus
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first_doc = qa_corpus[0]
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document_text = first_doc["document_extracted"]
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# Create a document
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document = Document(
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content=document_text,
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metadata={"source": "test"}
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)
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created_document = await doc_repo.create(document)
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# Test get_by_id
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assert created_document.id is not None
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retrieved_document = await doc_repo.get_by_id(created_document.id)
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assert retrieved_document is not None
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assert retrieved_document.content == document_text
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# Test update (should regenerate chunks)
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retrieved_document.content = "Updated content for testing"
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updated_document = await doc_repo.update(retrieved_document)
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assert updated_document.content == "Updated content for testing"
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# Test list_all
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all_documents = await doc_repo.list_all()
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assert len(all_documents) == 1
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assert all_documents[0].id == created_document.id
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# Test delete
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deleted = await doc_repo.delete(created_document.id)
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assert deleted is True
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# Verify document is gone
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retrieved_document = await doc_repo.get_by_id(created_document.id)
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assert retrieved_document is None
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store.close() |