""" Integration tests for DocumentRAG streaming functionality These tests verify the streaming behavior of DocumentRAG, testing token-by-token response delivery through the complete pipeline. """ import pytest from unittest.mock import AsyncMock from trustgraph.retrieval.document_rag.document_rag import DocumentRag from trustgraph.schema import ChunkMatch from trustgraph.base import PromptResult from tests.utils.streaming_assertions import ( assert_streaming_chunks_valid, assert_callback_invoked, ) # Sample chunk content for testing - maps chunk_id to content CHUNK_CONTENT = { "doc/c1": "Machine learning is a subset of AI.", "doc/c2": "Deep learning uses neural networks.", "doc/c3": "Supervised learning needs labeled data.", } @pytest.mark.integration class TestDocumentRagStreaming: """Integration tests for DocumentRAG streaming""" @pytest.fixture def mock_embeddings_client(self): """Mock embeddings client""" client = AsyncMock() # New batch format: [[[vectors_for_text1]]] client.embed.return_value = [[[0.1, 0.2, 0.3, 0.4, 0.5]]] return client @pytest.fixture def mock_doc_embeddings_client(self): """Mock document embeddings client that returns chunk matches""" client = AsyncMock() # Returns ChunkMatch objects with chunk_id and score client.query.return_value = [ ChunkMatch(chunk_id="doc/c1", score=0.95), ChunkMatch(chunk_id="doc/c2", score=0.90), ChunkMatch(chunk_id="doc/c3", score=0.85) ] return client @pytest.fixture def mock_fetch_chunk(self): """Mock fetch_chunk function that retrieves chunk content from librarian""" async def fetch(chunk_id, user): return CHUNK_CONTENT.get(chunk_id, f"Content for {chunk_id}") return fetch @pytest.fixture def mock_streaming_prompt_client(self, mock_streaming_llm_response): """Mock prompt client with streaming support""" client = AsyncMock() async def document_prompt_side_effect(query, documents, timeout=600, streaming=False, chunk_callback=None): # Both modes return the same text full_text = "Machine learning is a subset of artificial intelligence that focuses on algorithms that learn from data." if streaming and chunk_callback: # Simulate streaming chunks with end_of_stream flags chunks = [] async for chunk in mock_streaming_llm_response(): chunks.append(chunk) # Send all chunks with end_of_stream=False except the last for i, chunk in enumerate(chunks): is_final = (i == len(chunks) - 1) await chunk_callback(chunk, is_final) return PromptResult(response_type="text", text=full_text) else: # Non-streaming response - same text return PromptResult(response_type="text", text=full_text) client.document_prompt.side_effect = document_prompt_side_effect # Mock prompt() for extract-concepts call in DocumentRag client.prompt.return_value = PromptResult(response_type="text", text="") return client @pytest.fixture def document_rag_streaming(self, mock_embeddings_client, mock_doc_embeddings_client, mock_streaming_prompt_client, mock_fetch_chunk): """Create DocumentRag instance with streaming support""" return DocumentRag( embeddings_client=mock_embeddings_client, doc_embeddings_client=mock_doc_embeddings_client, prompt_client=mock_streaming_prompt_client, fetch_chunk=mock_fetch_chunk, verbose=True ) @pytest.mark.asyncio async def test_document_rag_streaming_basic(self, document_rag_streaming, streaming_chunk_collector): """Test basic DocumentRAG streaming functionality""" # Arrange query = "What is machine learning?" collector = streaming_chunk_collector() # Act result = await document_rag_streaming.query( query=query, user="test_user", collection="test_collection", doc_limit=10, streaming=True, chunk_callback=collector.collect ) # Assert assert_streaming_chunks_valid(collector.chunks, min_chunks=1) assert_callback_invoked(AsyncMock(call_count=len(collector.chunks)), min_calls=1) # Verify streaming protocol compliance collector.verify_streaming_protocol() # Verify full response matches concatenated chunks result_text, usage = result full_from_chunks = collector.get_full_text() assert result_text == full_from_chunks # Verify content is reasonable assert len(result_text) > 0 @pytest.mark.asyncio async def test_document_rag_streaming_vs_non_streaming(self, document_rag_streaming): """Test that streaming and non-streaming produce equivalent results""" # Arrange query = "What is machine learning?" user = "test_user" collection = "test_collection" doc_limit = 10 # Act - Non-streaming non_streaming_result = await document_rag_streaming.query( query=query, user=user, collection=collection, doc_limit=doc_limit, streaming=False ) # Act - Streaming streaming_chunks = [] async def collect(chunk, end_of_stream): streaming_chunks.append(chunk) streaming_result = await document_rag_streaming.query( query=query, user=user, collection=collection, doc_limit=doc_limit, streaming=True, chunk_callback=collect ) # Assert - Results should be equivalent non_streaming_text, _ = non_streaming_result streaming_text, _ = streaming_result assert streaming_text == non_streaming_text assert len(streaming_chunks) > 0 assert "".join(streaming_chunks) == streaming_text @pytest.mark.asyncio async def test_document_rag_streaming_callback_invocation(self, document_rag_streaming): """Test that chunk callback is invoked correctly""" # Arrange callback = AsyncMock() # Act result = await document_rag_streaming.query( query="test query", user="test_user", collection="test_collection", doc_limit=5, streaming=True, chunk_callback=callback ) # Assert result_text, usage = result assert callback.call_count > 0 assert result_text is not None # Verify all callback invocations had string arguments for call in callback.call_args_list: assert isinstance(call.args[0], str) @pytest.mark.asyncio async def test_document_rag_streaming_without_callback(self, document_rag_streaming): """Test streaming parameter without callback (should fall back to non-streaming)""" # Arrange & Act result = await document_rag_streaming.query( query="test query", user="test_user", collection="test_collection", doc_limit=5, streaming=True, chunk_callback=None # No callback provided ) # Assert - Should complete without error assert result is not None result_text, usage = result assert isinstance(result_text, str) @pytest.mark.asyncio async def test_document_rag_streaming_with_no_documents(self, document_rag_streaming, mock_doc_embeddings_client): """Test streaming with no documents found""" # Arrange mock_doc_embeddings_client.query.return_value = [] # No chunk_ids callback = AsyncMock() # Act result = await document_rag_streaming.query( query="unknown topic", user="test_user", collection="test_collection", doc_limit=10, streaming=True, chunk_callback=callback ) # Assert - Should still produce streamed response result_text, usage = result assert result_text is not None assert callback.call_count > 0 @pytest.mark.asyncio async def test_document_rag_streaming_error_propagation(self, document_rag_streaming, mock_embeddings_client): """Test that errors during streaming are properly propagated""" # Arrange mock_embeddings_client.embed.side_effect = Exception("Embeddings error") callback = AsyncMock() # Act & Assert with pytest.raises(Exception) as exc_info: await document_rag_streaming.query( query="test query", user="test_user", collection="test_collection", doc_limit=5, streaming=True, chunk_callback=callback ) assert "Embeddings error" in str(exc_info.value) @pytest.mark.asyncio async def test_document_rag_streaming_with_different_doc_limits(self, document_rag_streaming, mock_doc_embeddings_client): """Test streaming with various document limits""" # Arrange callback = AsyncMock() doc_limits = [1, 5, 10, 20] for limit in doc_limits: # Reset mocks mock_doc_embeddings_client.reset_mock() callback.reset_mock() # Act result = await document_rag_streaming.query( query="test query", user="test_user", collection="test_collection", doc_limit=limit, streaming=True, chunk_callback=callback ) # Assert result_text, usage = result assert result_text is not None assert callback.call_count > 0 # Verify doc_limit was passed correctly call_args = mock_doc_embeddings_client.query.call_args assert call_args.kwargs['limit'] == limit @pytest.mark.asyncio async def test_document_rag_streaming_preserves_user_collection(self, document_rag_streaming, mock_doc_embeddings_client): """Test that streaming preserves user/collection isolation""" # Arrange callback = AsyncMock() user = "test_user_123" collection = "test_collection_456" # Act await document_rag_streaming.query( query="test query", user=user, collection=collection, doc_limit=10, streaming=True, chunk_callback=callback ) # Assert - Verify user/collection were passed to document embeddings client call_args = mock_doc_embeddings_client.query.call_args assert call_args.kwargs['user'] == user assert call_args.kwargs['collection'] == collection