more fixing from linting instructions

- removing unused imports
changing != to is not
removing f strings with no assignment
removing double defined functions

Author: haneric00

ai_agent_instrumentation/opentelemetry-instrumentation-langchain-v2/src/opentelemetry/instrumentation/langchain_v2/callback_handler.py

@@ -186,7 +186,7 @@ def on_chat_model_start(
             model_id = kwargs["invocation_params"]["model_id"]
 
         name = self._get_name_from_callback(serialized, kwargs=kwargs)
-        if model_id != None:
+        if model_id is not None:
             name = model_id
 
         span = self._create_span(
@@ -223,7 +223,7 @@ def on_llm_start(
             model_id = kwargs["invocation_params"]["model_id"]
 
         name = self._get_name_from_callback(serialized, kwargs=kwargs)
-        if model_id != None:
+        if model_id is not None:
             name = model_id
 
         span = self._create_span(

ai_agent_instrumentation/opentelemetry-instrumentation-langchain-v2/tests/conftest.py

@@ -58,24 +58,6 @@ def scrub_aws_credentials(response):
     return response
 
 
-@pytest.fixture(scope="module")
-def vcr_config():
-    return {
-        "filter_headers": [
-            ("authorization", "AWS4-HMAC-SHA256 REDACTED"),
-            ("x-amz-date", "REDACTED_DATE"),
-            ("x-amz-security-token", "REDACTED_TOKEN"),
-            ("x-amz-content-sha256", "REDACTED_CONTENT_HASH"),
-        ],
-        "filter_query_parameters": [
-            ("X-Amz-Security-Token", "REDACTED"),
-            ("X-Amz-Signature", "REDACTED"),
-        ],
-        "decode_compressed_response": True,
-        "before_record_response": scrub_aws_credentials,
-    }
-
-
 @pytest.fixture(scope="session")
 def instrument_langchain(tracer_provider):
     langchain_instrumentor = LangChainInstrumentor()

ai_agent_instrumentation/opentelemetry-instrumentation-langchain-v2/tests/test_agents.py

@@ -81,7 +81,7 @@ def test_agents_with_events_with_content(instrument_with_content, span_exporter,
     agent_executor = AgentExecutor(agent=agent, tools=tools)
 
     prompt = "What is AWS?"
-    response = agent_executor.invoke({"input": prompt})
+    agent_executor.invoke({"input": prompt})
 
     spans = span_exporter.get_finished_spans()
 

ai_agent_instrumentation/opentelemetry-instrumentation-langchain-v2/tests/test_chains.py

@@ -1,5 +1,4 @@
 import ast
-import os
 
 import boto3
 import pytest

ai_agent_instrumentation/opentelemetry-instrumentation-langchain-v2/tests/test_langgraph_agent.py

@@ -72,12 +72,12 @@ def calculate(state: State):
 
     assert "gen_ai.prompt" in calculate_task_span.attributes
     assert "gen_ai.completion" in calculate_task_span.attributes
-    assert f"What's 5 + 5?" in calculate_task_span.attributes["gen_ai.prompt"]
+    assert "What's 5 + 5?" in calculate_task_span.attributes["gen_ai.prompt"]
 
     langgraph_span = next(span for span in spans if span.name == "chain LangGraph")
     assert "gen_ai.prompt" in langgraph_span.attributes
     assert "gen_ai.completion" in langgraph_span.attributes
-    assert f"What's 5 + 5?" in langgraph_span.attributes["gen_ai.prompt"]
+    assert "What's 5 + 5?" in langgraph_span.attributes["gen_ai.prompt"]
     assert response in langgraph_span.attributes["gen_ai.completion"]