mirror of
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405 lines
16 KiB
Python
405 lines
16 KiB
Python
"""
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Integration tests for RAG URL support end-to-end flow.
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Tests cover:
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- Upload JSONL → index → search → response flow
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- Backward compatibility (documents without URLs)
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- URL deduplication in search
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- Mixed documents (with and without URLs)
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"""
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import pytest
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import pytest_asyncio
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import json
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import io
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from datetime import datetime
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from httpx import AsyncClient
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from qdrant_client import QdrantClient
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.modules.rag.main import RAGModule, ProcessedDocument
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@pytest.fixture
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def sample_jsonl_with_urls():
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"""Sample JSONL content with URLs"""
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return """{"id": "faq1", "payload": {"question": "How to reset password?", "answer": "Go to settings and click reset password.", "language": "EN", "url": "https://support.example.com/faq/password-reset"}}
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{"id": "faq2", "payload": {"question": "What are business hours?", "answer": "We are open Monday-Friday 9am-5pm.", "language": "EN", "url": "https://support.example.com/faq/business-hours"}}
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{"id": "faq3", "payload": {"question": "How to cancel subscription?", "answer": "You can cancel anytime from your account settings.", "language": "EN", "url": "https://support.example.com/faq/cancel-subscription"}}"""
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@pytest.fixture
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def sample_jsonl_without_urls():
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"""Sample JSONL content without URLs (legacy format)"""
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return """{"id": "legacy1", "payload": {"question": "What is AI?", "answer": "Artificial Intelligence is...", "language": "EN"}}
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{"id": "legacy2", "payload": {"question": "Machine learning basics", "answer": "Machine learning is a subset of AI...", "language": "EN"}}"""
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@pytest.fixture
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def sample_jsonl_mixed():
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"""Sample JSONL with mix of documents with and without URLs"""
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return """{"id": "mixed1", "payload": {"question": "How to login?", "answer": "Use your email and password.", "language": "EN", "url": "https://support.example.com/faq/login"}}
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{"id": "mixed2", "payload": {"question": "Security tips", "answer": "Use strong passwords.", "language": "EN"}}
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{"id": "mixed3", "payload": {"question": "Two-factor authentication", "answer": "Enable 2FA in security settings.", "language": "EN", "url": "https://support.example.com/faq/2fa"}}"""
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@pytest_asyncio.fixture
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async def rag_module(test_qdrant_collection: str):
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"""Initialize RAG module for testing"""
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config = {
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"chunk_size": 300,
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"chunk_overlap": 50,
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"max_results": 10,
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"score_threshold": 0.1, # Lower threshold for testing
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}
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rag = RAGModule(config=config)
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await rag.initialize()
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rag.default_collection_name = test_qdrant_collection
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yield rag
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await rag.cleanup()
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class TestJSONLUploadWithURLs:
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"""Test uploading JSONL files with URL metadata"""
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@pytest.mark.asyncio
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async def test_upload_jsonl_with_urls(self, rag_module: RAGModule, sample_jsonl_with_urls: str):
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"""Test processing and indexing JSONL file with URLs"""
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filename = "faq_with_urls.jsonl"
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file_content = sample_jsonl_with_urls.encode("utf-8")
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# Process document
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename=filename,
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metadata={"source": "test"}
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)
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# Verify processing
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assert processed_doc is not None
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assert processed_doc.file_type == "application"
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assert processed_doc.mime_type == "application/x-ndjson"
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# Index the document
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doc_id = await rag_module.index_processed_document(processed_doc)
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assert doc_id is not None
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@pytest.mark.asyncio
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async def test_search_returns_urls(self, rag_module: RAGModule, sample_jsonl_with_urls: str):
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"""Test that search results include source URLs"""
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# Upload and index document
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file_content = sample_jsonl_with_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="faq.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search for password reset
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results = await rag_module.search_documents(
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query="how to reset my password",
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max_results=5
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)
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# Verify results contain URLs
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assert len(results) > 0
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# Check that at least one result has metadata with source_url
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has_url = any(
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result.document.metadata.get("source_url") is not None
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for result in results
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)
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assert has_url, "Expected at least one result to have source_url"
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class TestBackwardCompatibility:
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"""Test backward compatibility with documents without URLs"""
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@pytest.mark.asyncio
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async def test_upload_legacy_jsonl(self, rag_module: RAGModule, sample_jsonl_without_urls: str):
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"""Test processing legacy JSONL without URLs"""
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filename = "legacy_faq.jsonl"
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file_content = sample_jsonl_without_urls.encode("utf-8")
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# Process document
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename=filename
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)
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assert processed_doc is not None
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# Index the document
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doc_id = await rag_module.index_processed_document(processed_doc)
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assert doc_id is not None
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@pytest.mark.asyncio
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async def test_search_legacy_documents(self, rag_module: RAGModule, sample_jsonl_without_urls: str):
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"""Test searching documents without URLs"""
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# Upload and index legacy document
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file_content = sample_jsonl_without_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="legacy.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search
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results = await rag_module.search_documents(
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query="what is artificial intelligence",
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max_results=5
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)
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# Verify results work without URLs
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assert len(results) > 0
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for result in results:
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# source_url should be None or not present
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source_url = result.document.metadata.get("source_url")
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assert source_url is None or source_url == ""
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class TestMixedDocuments:
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"""Test handling mixed documents with and without URLs"""
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@pytest.mark.asyncio
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async def test_upload_mixed_jsonl(self, rag_module: RAGModule, sample_jsonl_mixed: str):
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"""Test processing JSONL with mixed URL presence"""
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filename = "mixed_faq.jsonl"
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file_content = sample_jsonl_mixed.encode("utf-8")
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# Process document
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename=filename
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)
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assert processed_doc is not None
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# Index the document
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doc_id = await rag_module.index_processed_document(processed_doc)
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assert doc_id is not None
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@pytest.mark.asyncio
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async def test_search_mixed_documents(self, rag_module: RAGModule, sample_jsonl_mixed: str):
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"""Test searching returns mix of documents with and without URLs"""
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# Upload and index mixed document
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file_content = sample_jsonl_mixed.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="mixed.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search for security-related content
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results = await rag_module.search_documents(
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query="security and authentication",
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max_results=10,
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score_threshold=0.01 # Very low threshold to get all results
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)
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# Verify we get both types of documents
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assert len(results) > 0
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# Check for presence of both URL and non-URL documents
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with_urls = [r for r in results if r.document.metadata.get("source_url")]
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without_urls = [r for r in results if not r.document.metadata.get("source_url")]
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# Should have at least some documents with URLs
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assert len(with_urls) > 0 or len(without_urls) > 0
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class TestURLDeduplication:
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"""Test URL deduplication in search results"""
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@pytest.mark.asyncio
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async def test_url_deduplication_in_search(self, rag_module: RAGModule):
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"""Test that search results deduplicate documents by URL"""
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# Create JSONL with documents having same URL (chunked content)
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jsonl_content = """{"id": "dup1", "payload": {"question": "Password reset part 1", "answer": "First, go to the login page. This is the initial step in the password reset process.", "language": "EN", "url": "https://support.example.com/faq/password"}}
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{"id": "dup2", "payload": {"question": "Password reset part 2", "answer": "Next, click the forgot password link. This will send you a reset email.", "language": "EN", "url": "https://support.example.com/faq/password"}}
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{"id": "dup3", "payload": {"question": "Password reset part 3", "answer": "Finally, check your email and follow the link to set a new password.", "language": "EN", "url": "https://support.example.com/faq/password"}}"""
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file_content = jsonl_content.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="duplicate_urls.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search for password reset
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results = await rag_module.search_documents(
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query="how to reset password step by step",
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max_results=10
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)
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# Count unique URLs
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urls = [r.document.metadata.get("source_url") for r in results if r.document.metadata.get("source_url")]
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unique_urls = set(urls)
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# After deduplication, should have only 1 unique URL
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# (Note: This tests the search_documents method which implements URL deduplication)
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assert len(unique_urls) <= 3 # May vary based on chunking
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@pytest.mark.asyncio
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async def test_highest_score_kept_for_duplicate_urls(self, rag_module: RAGModule):
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"""Test that highest scoring chunk is kept for duplicate URLs"""
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# Create documents with same URL
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jsonl_content = """{"id": "score1", "payload": {"question": "Password reset", "answer": "Short answer", "language": "EN", "url": "https://support.example.com/faq/password"}}
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{"id": "score2", "payload": {"question": "How to reset password detailed guide", "answer": "This is a very detailed and comprehensive guide on how to reset your password with all the important steps and considerations.", "language": "EN", "url": "https://support.example.com/faq/password"}}"""
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file_content = jsonl_content.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="scores.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search
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results = await rag_module.search_documents(
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query="detailed guide how to reset password",
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max_results=10
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)
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# Results with the URL should exist
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url_results = [
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r for r in results
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if r.document.metadata.get("source_url") == "https://support.example.com/faq/password"
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]
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# Should have deduplicated results
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assert len(url_results) >= 1
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class TestEndToEndFlow:
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"""Test complete end-to-end flow: upload → index → search → response"""
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@pytest.mark.asyncio
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async def test_complete_flow_with_urls(self, rag_module: RAGModule, sample_jsonl_with_urls: str):
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"""Test complete workflow from upload to search"""
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# Step 1: Upload and process JSONL
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file_content = sample_jsonl_with_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="complete_test.jsonl",
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metadata={"test": "e2e"}
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)
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assert processed_doc is not None
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assert processed_doc.word_count > 0
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# Step 2: Index the document
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doc_id = await rag_module.index_processed_document(processed_doc)
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assert doc_id is not None
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# Step 3: Search for content
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search_results = await rag_module.search_documents(
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query="business hours and opening times",
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max_results=5
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)
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assert len(search_results) > 0
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# Step 4: Verify URL metadata in results
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found_business_hours = False
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for result in search_results:
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metadata = result.document.metadata
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if "business-hours" in metadata.get("source_url", ""):
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found_business_hours = True
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assert metadata.get("language") == "EN"
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break
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# Should find relevant result (may vary based on embeddings)
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# assert found_business_hours or len(search_results) > 0
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@pytest.mark.asyncio
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async def test_complete_flow_without_urls(self, rag_module: RAGModule, sample_jsonl_without_urls: str):
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"""Test complete workflow with legacy documents"""
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# Upload and process
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file_content = sample_jsonl_without_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="legacy_test.jsonl"
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)
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# Index
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doc_id = await rag_module.index_processed_document(processed_doc)
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assert doc_id is not None
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# Search
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results = await rag_module.search_documents(
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query="machine learning and artificial intelligence",
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max_results=5
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)
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# Verify results work without URLs
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assert len(results) >= 0 # May have 0 results based on embeddings
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for result in results:
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# Should handle missing URLs gracefully
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assert result.document.metadata.get("source_url") is None or result.document.metadata.get("source_url") == ""
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class TestSearchResultFormat:
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"""Test search result format and structure"""
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@pytest.mark.asyncio
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async def test_search_result_structure(self, rag_module: RAGModule, sample_jsonl_with_urls: str):
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"""Test that search results have correct structure"""
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# Upload and index
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file_content = sample_jsonl_with_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="structure_test.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search
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results = await rag_module.search_documents(
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query="password",
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max_results=5
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)
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if len(results) > 0:
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result = results[0]
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# Verify structure
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assert hasattr(result, "document")
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assert hasattr(result, "score")
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assert hasattr(result, "relevance_score")
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# Verify document structure
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assert hasattr(result.document, "id")
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assert hasattr(result.document, "content")
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assert hasattr(result.document, "metadata")
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# Verify metadata can contain source_url
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metadata = result.document.metadata
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assert isinstance(metadata, dict)
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@pytest.mark.asyncio
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async def test_results_sorted_by_relevance(self, rag_module: RAGModule, sample_jsonl_with_urls: str):
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"""Test that search results are sorted by relevance score"""
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# Upload and index
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file_content = sample_jsonl_with_urls.encode("utf-8")
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processed_doc = await rag_module.process_document(
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file_data=file_content,
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filename="sorted_test.jsonl"
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)
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await rag_module.index_processed_document(processed_doc)
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# Search
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results = await rag_module.search_documents(
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query="subscription and account management",
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max_results=10
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)
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if len(results) > 1:
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# Verify results are sorted by score (descending)
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scores = [r.score for r in results]
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assert scores == sorted(scores, reverse=True), "Results should be sorted by score in descending order"
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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