dify/api/tests/unit_tests/extensions/otel/test_retrieval_tracing.py
2026-07-24 02:27:16 +00:00

123 lines
4.5 KiB
Python

import threading
from unittest.mock import MagicMock, patch
from uuid import uuid4
from opentelemetry.trace import StatusCode, get_current_span, get_tracer
from core.rag.rerank.rerank_type import RerankMode
from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
from core.workflow.nodes.knowledge_retrieval.retrieval import KnowledgeRetrievalRequest
from models.dataset import Dataset
def test_knowledge_retrieval_creates_a_child_otel_span(
memory_span_exporter,
tracer_provider_with_memory_exporter,
) -> None:
"""The retrieval entry point must be visible beneath its workflow node span."""
request = KnowledgeRetrievalRequest(
tenant_id=str(uuid4()),
user_id=str(uuid4()),
app_id=str(uuid4()),
user_from="account",
dataset_ids=[str(uuid4())],
retrieval_mode="multiple",
query="test query",
)
retrieval = DatasetRetrieval()
with (
patch("extensions.otel.decorators.base.dify_config.ENABLE_OTEL", True),
patch.object(retrieval, "_check_knowledge_rate_limit"),
patch.object(retrieval, "_get_available_datasets", return_value=[]),
get_tracer(__name__).start_as_current_span("knowledge-retrieval-node") as node_span,
):
assert retrieval.knowledge_retrieval(MagicMock(), request) == []
retrieval_span = next(
span
for span in memory_span_exporter.get_finished_spans()
if span.name == "core.rag.retrieval.dataset_retrieval.DatasetRetrieval.knowledge_retrieval"
)
node_span_context = node_span.get_span_context()
assert retrieval_span.context.trace_id == node_span_context.trace_id
assert retrieval_span.parent is not None
assert retrieval_span.parent.span_id == node_span_context.span_id
def test_multiple_retrieve_preserves_otel_context_in_dataset_thread(
app,
tracer_provider_with_memory_exporter,
) -> None:
"""Per-dataset retrieval spans must remain in the workflow node trace."""
retrieval = DatasetRetrieval()
dataset = MagicMock(spec=Dataset)
dataset.id = str(uuid4())
dataset.indexing_technique = "high_quality"
dataset.embedding_model = "text-embedding-3-small"
dataset.embedding_model_provider = "openai"
observed_trace_ids: list[int] = []
def record_active_trace(**_kwargs: object) -> None:
observed_trace_ids.append(get_current_span().get_span_context().trace_id)
with (
app.app_context(),
patch("extensions.otel.decorators.base.dify_config.ENABLE_OTEL", True),
patch.object(retrieval, "_multiple_retrieve_thread", side_effect=record_active_trace),
patch.object(retrieval, "_on_query"),
get_tracer(__name__).start_as_current_span("knowledge-retrieval-node") as node_span,
):
retrieval.multiple_retrieve(
app_id=str(uuid4()),
tenant_id=str(uuid4()),
user_id=str(uuid4()),
user_from="account",
available_datasets=[dataset],
query="test query",
top_k=4,
score_threshold=0.0,
reranking_mode=RerankMode.RERANKING_MODEL,
reranking_enable=False,
)
assert observed_trace_ids == [node_span.get_span_context().trace_id]
def test_retriever_thread_exception_sets_error_span_and_is_collected(
app,
memory_span_exporter,
tracer_provider_with_memory_exporter,
) -> None:
retrieval = DatasetRetrieval()
cancel_event = threading.Event()
thread_exceptions: list[Exception] = []
expected_error = RuntimeError("retrieval failed")
with (
patch("extensions.otel.decorators.base.dify_config.ENABLE_OTEL", True),
patch("core.rag.retrieval.dataset_retrieval.session_factory.create_session"),
patch.object(retrieval, "_retriever", side_effect=expected_error),
):
retrieval._run_retriever_thread_safely(
flask_app=app,
dataset_id=str(uuid4()),
query="test query",
top_k=4,
all_documents=[],
document_ids_filter=None,
metadata_condition=None,
attachment_ids=None,
cancel_event=cancel_event,
thread_exceptions=thread_exceptions,
)
retrieval_span = next(
span
for span in memory_span_exporter.get_finished_spans()
if span.name.endswith("DatasetRetrieval._run_retriever_thread")
)
assert retrieval_span.status.status_code == StatusCode.ERROR
assert cancel_event.is_set()
assert thread_exceptions == [expected_error]