workflow name fix (#69)

Signed-off-by: hansrajro <[email protected]>
Co-authored-by: hansrajro <[email protected]>

src/monocle_apptrace/utils.py

@@ -6,6 +6,7 @@
 from opentelemetry.context import attach, set_value, get_value
 from monocle_apptrace.constants import azure_service_map, aws_service_map
 from json.decoder import JSONDecodeError
+logger = logging.getLogger(__name__)
 
 embedding_model_context = {}
 
@@ -161,4 +162,11 @@ def get_attribute(key: str) -> str:
     Returns:
         The value associated with the given key.
     """
-    return get_value(key)
+    return get_value(key)
+
+def get_workflow_name(span: Span) -> str:
+    try:
+        return get_value("workflow_name") or span.resource.attributes.get("service.name")
+    except Exception as e:
+        logger.exception(f"Error getting workflow name: {e}")
+        return None

src/monocle_apptrace/wrap_common.py

@@ -4,7 +4,7 @@
 import inspect
 from urllib.parse import urlparse
 from opentelemetry.trace import Span, Tracer
-from monocle_apptrace.utils import resolve_from_alias, update_span_with_infra_name, with_tracer_wrapper, get_embedding_model, get_attribute
+from monocle_apptrace.utils import resolve_from_alias, update_span_with_infra_name, with_tracer_wrapper, get_embedding_model, get_attribute, get_workflow_name
 from monocle_apptrace.utils import set_attribute
 from opentelemetry.context import get_value, attach, set_value
 logger = logging.getLogger(__name__)
@@ -105,7 +105,7 @@ def process_span(to_wrap, span, instance, args):
     # Check if the output_processor is a valid JSON (in Python, that means it's a dictionary)
     span_index = 1
     if is_root_span(span):
-        workflow_name = get_value("workflow_name")
+        workflow_name = get_workflow_name(span)
         if workflow_name:
             span.set_attribute(f"entity.{span_index}.name", workflow_name)
         # workflow type

tests/langchain_custom_output_processor_test.py

@@ -18,6 +18,7 @@
 from langchain_community.vectorstores import faiss
 from langchain_core.messages.ai import AIMessage
 from langchain_core.runnables import RunnablePassthrough
+from monocle_apptrace.wrap_common import WORKFLOW_TYPE_MAP
 from monocle_apptrace.constants import (
     AZURE_APP_SERVICE_ENV_NAME,
     AZURE_APP_SERVICE_NAME,
@@ -175,6 +176,9 @@ def test_llm_chain(self, test_name, test_input_infra, llm_type, mock_post):
             This can be used to do more asserts'''
             dataBodyStr = mock_post.call_args.kwargs['data']
             dataJson =  json.loads(dataBodyStr) # more asserts can be added on individual fields
+            root_attributes = [x for x in dataJson["batch"] if x["parent_id"] == "None"][0]["attributes"]
+            assert root_attributes["entity.1.name"] == app_name
+            assert root_attributes["entity.1.type"] == WORKFLOW_TYPE_MAP['langchain']
             if llm_type == "FakeListLLM":
                 llm_vector_store_retriever_span = [x for x in dataJson["batch"] if 'langchain.task.VectorStoreRetriever' in x["name"]][0]
                 inference_span = [x for x in dataJson["batch"] if 'langchain.task.FakeListLLM' in x["name"]][0]