Moved model to fixture and changed imports

Author: wrisa

instrumentation-genai/opentelemetry-instrumentation-langchain/src/opentelemetry/instrumentation/langchain/callback_handler.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from typing import Any, Dict, List, Optional
+from __future__ import annotations
+
+from typing import Any
 from uuid import UUID
 
 from langchain_core.callbacks import BaseCallbackHandler  # type: ignore
@@ -43,13 +45,13 @@ def __init__(
 
     def on_chat_model_start(
         self,
-        serialized: Dict[str, Any],
+        serialized: dict[str, Any],
         messages: List[List[BaseMessage]],  # type: ignore
         *,
         run_id: UUID,
-        tags: Optional[List[str]] = None,
-        parent_run_id: Optional[UUID] = None,
-        metadata: Optional[Dict[str, Any]] = None,
+        tags: list[str] | None,
+        parent_run_id: UUID | None,
+        metadata: dict[str, Any] | None,
         **kwargs: Any,
     ) -> None:
         invocation_params = kwargs.get("invocation_params")
@@ -91,7 +93,6 @@ def on_chat_model_start(
                 span.set_attribute(GenAI.GEN_AI_REQUEST_MAX_TOKENS, max_tokens)
             provider = metadata.get("ls_provider")
             if provider is not None:
-                # TODO: add to semantic conventions
                 span.set_attribute("gen_ai.provider.name", provider)
             temperature = metadata.get("ls_temperature")
             if temperature is not None:
@@ -104,7 +105,7 @@ def on_llm_end(
         response: LLMResult,  # type: ignore
         *,
         run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
+        parent_run_id: UUID | None,
         **kwargs: Any,
     ) -> None:
         span = self.span_manager.get_span(run_id)
@@ -113,7 +114,7 @@ def on_llm_end(
             # If the span does not exist, we cannot set attributes or end it
             return
 
-        finish_reasons: List[str] = []
+        finish_reasons: list[str] = []
         for generation in getattr(response, "generations", []):  # type: ignore
             for chat_generation in generation:
                 generation_info = getattr(
@@ -166,7 +167,7 @@ def on_llm_error(
         error: BaseException,
         *,
         run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
+        parent_run_id: UUID | None,
         **kwargs: Any,
     ) -> None:
         self.span_manager.handle_error(error, run_id)

instrumentation-genai/opentelemetry-instrumentation-langchain/src/opentelemetry/instrumentation/langchain/span_manager.py

@@ -86,7 +86,8 @@ def create_llm_span(
             GenAI.GEN_AI_OPERATION_NAME,
             GenAI.GenAiOperationNameValues.CHAT.value,
         )
-        span.set_attribute(GenAI.GEN_AI_REQUEST_MODEL, request_model)
+        if request_model:
+            span.set_attribute(GenAI.GEN_AI_REQUEST_MODEL, request_model)
 
         return span
 

instrumentation-genai/opentelemetry-instrumentation-langchain/tests/conftest.py

@@ -14,6 +14,19 @@
     InMemorySpanExporter,
 )
 
+@pytest.fixture(scope="function", name="llm_model")
+def fixture_llm_model():
+    llm = ChatOpenAI(
+        model="gpt-3.5-turbo",
+        temperature=0.1,
+        max_tokens=100,
+        top_p=0.9,
+        frequency_penalty=0.5,
+        presence_penalty=0.5,
+        stop_sequences=["\n", "Human:", "AI:"],
+        seed=100,
+    )
+    yield llm
 
 @pytest.fixture(scope="function", name="span_exporter")
 def fixture_span_exporter():
@@ -47,11 +60,6 @@ def environment():
         os.environ["OPENAI_API_KEY"] = "test_openai_api_key"
 
 
-@pytest.fixture
-def chatOpenAI_client():
-    return ChatOpenAI()
-
-
 @pytest.fixture(scope="module")
 def vcr_config():
     return {

instrumentation-genai/opentelemetry-instrumentation-langchain/tests/test_llm_call.py

@@ -8,28 +8,18 @@
 from opentelemetry.semconv._incubating.attributes import gen_ai_attributes
 
 
-# span_exporter, chatOpenAI_client, start_instrumentation are coming from fixtures defined in conftest.py
+# span_exporter, start_instrumentation, llm_model are coming from fixtures defined in conftest.py
 @pytest.mark.vcr()
 def test_langchain_call(
-    span_exporter, chatOpenAI_client, start_instrumentation
+    span_exporter, start_instrumentation, llm_model
 ):
-    llm = ChatOpenAI(
-        model="gpt-3.5-turbo",
-        temperature=0.1,
-        max_tokens=100,
-        top_p=0.9,
-        frequency_penalty=0.5,
-        presence_penalty=0.5,
-        stop_sequences=["\n", "Human:", "AI:"],
-        seed=100,
-    )
 
     messages = [
         SystemMessage(content="You are a helpful assistant!"),
         HumanMessage(content="What is the capital of France?"),
     ]
 
-    response = llm.invoke(messages)
+    response = llm_model.invoke(messages)
     assert response.content == "The capital of France is Paris."
 
     # verify spans