fix: lint issues

packages/opentelemetry-instrumentation-bedrock/opentelemetry/instrumentation/bedrock/__init__.py

@@ -1,6 +1,5 @@
 """OpenTelemetry Bedrock instrumentation"""
 from functools import wraps
-from itertools import tee
 import json
 import logging
 import os
@@ -10,7 +9,6 @@
 
 from opentelemetry import context as context_api
 from opentelemetry.trace import get_tracer, SpanKind
-from opentelemetry.trace.status import Status, StatusCode
 
 from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
 from opentelemetry.instrumentation.utils import (
@@ -64,7 +62,7 @@ def _wrap(tracer, to_wrap, wrapped, instance, args, kwargs):
     """Instruments and calls every function defined in TO_WRAP."""
     if context_api.get_value(_SUPPRESS_INSTRUMENTATION_KEY):
         return wrapped(*args, **kwargs)
-    
+
     if kwargs.get("service_name") == "bedrock-runtime":
         client = wrapped(*args, **kwargs)
         client.invoke_model = _instrumented_model_invoke(client.invoke_model, tracer)
@@ -88,7 +86,7 @@ def with_instrumentation(*args, **kwargs):
 
             if span.is_recording():
                 (vendor, model) = kwargs.get("modelId").split(".")
-                
+
                 _set_span_attribute(span, SpanAttributes.LLM_VENDOR, vendor)
                 _set_span_attribute(span, SpanAttributes.LLM_REQUEST_MODEL, model)
 
@@ -100,11 +98,12 @@ def with_instrumentation(*args, **kwargs):
                     _set_ai21_span_attributes(span, request_body, response_body)
                 elif vendor == "meta":
                     _set_llama_span_attributes(span, request_body, response_body)
-              
+
             return response
-    
+
     return with_instrumentation
 
+
 def _set_cohere_span_attributes(span, request_body, response_body):
     _set_span_attribute(span, SpanAttributes.LLM_REQUEST_TYPE, LLMRequestTypeValues.COMPLETION.value)
     _set_span_attribute(span, SpanAttributes.LLM_TOP_P, request_body.get("p"))
@@ -117,6 +116,7 @@ def _set_cohere_span_attributes(span, request_body, response_body):
         for i, generation in enumerate(response_body.get("generations")):
             _set_span_attribute(span, f"{SpanAttributes.LLM_COMPLETIONS}.{i}.content", generation.get("text"))
 
+
 def _set_anthropic_span_attributes(span, request_body, response_body):
     _set_span_attribute(span, SpanAttributes.LLM_REQUEST_TYPE, LLMRequestTypeValues.COMPLETION.value)
     _set_span_attribute(span, SpanAttributes.LLM_TOP_P, request_body.get("top_p"))
@@ -127,17 +127,25 @@ def _set_anthropic_span_attributes(span, request_body, response_body):
         _set_span_attribute(span, f"{SpanAttributes.LLM_PROMPTS}.0.user", request_body.get("prompt"))
         _set_span_attribute(span, f"{SpanAttributes.LLM_COMPLETIONS}.0.content", response_body.get("completion"))
 
+
 def _set_ai21_span_attributes(span, request_body, response_body):
     _set_span_attribute(span, SpanAttributes.LLM_REQUEST_TYPE, LLMRequestTypeValues.COMPLETION.value)
     _set_span_attribute(span, SpanAttributes.LLM_TOP_P, request_body.get("topP"))
     _set_span_attribute(span, SpanAttributes.LLM_TEMPERATURE, request_body.get("temperature"))
     _set_span_attribute(span, SpanAttributes.LLM_REQUEST_MAX_TOKENS, request_body.get("maxTokens"))
 
     if should_send_prompts():
-        _set_span_attribute(span, f"{SpanAttributes.LLM_PROMPTS}.0.user", request_body.get("prompt"))
+        _set_span_attribute(
+            span,
+            f"{SpanAttributes.LLM_PROMPTS}.0.user", request_body.get("prompt")
+        )
 
         for i, completion in enumerate(response_body.get("completions")):
-            _set_span_attribute(span, f"{SpanAttributes.LLM_COMPLETIONS}.{i}.content", completion.get("data").get("text"))
+            _set_span_attribute(
+                span,
+                f"{SpanAttributes.LLM_COMPLETIONS}.{i}.content", completion.get("data").get("text")
+            )
+
 
 def _set_llama_span_attributes(span, request_body, response_body):
     _set_span_attribute(span, SpanAttributes.LLM_REQUEST_TYPE, LLMRequestTypeValues.COMPLETION.value)

packages/opentelemetry-instrumentation-bedrock/opentelemetry/instrumentation/bedrock/reusable_streaming_body.py

@@ -14,7 +14,7 @@ def __init__(self, raw_stream, content_length):
         super().__init__(raw_stream, content_length)
         self._buffer = None
         self._buffer_cursor = 0
-    
+
     def read(self, amt=None):
         """Read at most amt bytes from the stream.
 
@@ -28,7 +28,7 @@ def read(self, amt=None):
                 raise ReadTimeoutError(endpoint_url=e.url, error=e)
             except URLLib3ProtocolError as e:
                 raise ResponseStreamingError(error=e)
-            
+
             self._amount_read += len(self._buffer)
             if amt is None or (not self._buffer and amt > 0):
                 # If the server sends empty contents or

packages/sample-app/sample_app/bedrock_example_app.py

@@ -19,18 +19,20 @@ def create_joke():
     })
 
     response = brt.invoke_model(
-        body=body, 
-        modelId='cohere.command-text-v14', 
-        accept='application/json', 
+        body=body,
+        modelId='cohere.command-text-v14',
+        accept='application/json',
         contentType='application/json'
     )
 
     response_body = json.loads(response.get('body').read())
 
     return response_body.get('generations')[0].get('text')
 
+
 @workflow(name="pirate_joke_generator")
 def joke_workflow():
     print(create_joke())
 
+
 joke_workflow()

packages/traceloop-sdk/traceloop/sdk/tracing/tracing.py

@@ -30,7 +30,8 @@
 from typing import Dict
 
 TRACER_NAME = "traceloop.tracer"
-EXCLUDED_URLS = "api.openai.com,openai.azure.com,api.anthropic.com,api.cohere.ai,pinecone.io,traceloop.com,posthog.com,bedrock-runtime"
+EXCLUDED_URLS = ("api.openai.com,openai.azure.com,api.anthropic.com,api.cohere.ai,pinecone.io,traceloop.com,"
+                 "posthog.com,bedrock-runtime")
 
 
 class TracerWrapper(object):
@@ -369,6 +370,7 @@ def init_pymysql_instrumentor():
         if not instrumentor.is_instrumented_by_opentelemetry:
             instrumentor.instrument()
 
+
 def init_bedrock_instrumentor():
     if importlib.util.find_spec("boto3") is not None:
         from opentelemetry.instrumentation.bedrock import BedrockInstrumentor