style: fix formating

Author: darshit-s3

src/examples/dspy_example/react.py

@@ -3,37 +3,49 @@
 import dspy
 
 # Add the local src folder to the Python path
-sys.path.insert(0, os.path.abspath('/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/src'))
+sys.path.insert(
+    0,
+    os.path.abspath(
+        "/Users/karthikkalyanaraman/work/langtrace/langtrace-python-sdk/src"
+    ),
+)
 
 # flake8: noqa
 from langtrace_python_sdk import langtrace, with_langtrace_root_span
+
 langtrace.init()
 
-turbo = dspy.OpenAI(model='gpt-3.5-turbo', max_tokens=250)
+turbo = dspy.OpenAI(model="gpt-3.5-turbo", max_tokens=250)
 dspy.settings.configure(lm=turbo)
 
-colbertv2_wiki17_abstracts = dspy.ColBERTv2(url='http://20.102.90.50:2017/wiki17_abstracts')
+colbertv2_wiki17_abstracts = dspy.ColBERTv2(
+    url="http://20.102.90.50:2017/wiki17_abstracts"
+)
 dspy.settings.configure(rm=colbertv2_wiki17_abstracts)
 retriever = dspy.Retrieve(k=3)
 
+
 # Define a simple signature for basic question answering
 class BasicQA(dspy.Signature):
     """Answer questions with short factoid answers."""
+
     question = dspy.InputField()
     answer = dspy.OutputField(desc="often between 1 and 5 words")
 
+
 @with_langtrace_root_span(name="react_example")
 def example():
 
     # Pass signature to ReAct module
     react_module = dspy.ReAct(BasicQA)
 
     # Call the ReAct module on a particular input
-    question = 'Aside from the Apple Remote, what other devices can control the program Apple Remote was originally designed to interact with?'
+    question = "Aside from the Apple Remote, what other devices can control the program Apple Remote was originally designed to interact with?"
     result = react_module(question=question)
 
     print(f"Question: {question}")
     print(f"Final Predicted Answer (after ReAct process): {result.answer}")
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     example()

src/langtrace_python_sdk/instrumentation/dspy/patch.py

@@ -34,7 +34,9 @@ def traced_method(wrapped, instance, args, kwargs):
             if args[0].prog:
                 prog = {
                     "name": args[0].prog.__class__.__name__,
-                    "signature": str(args[0].prog.signature) if args[0].prog.signature else None,
+                    "signature": (
+                        str(args[0].prog.signature) if args[0].prog.signature else None
+                    ),
                 }
                 span_attributes["dspy.optimizer.module.prog"] = json.dumps(prog)
         if "metric" in instance and instance.metric:
@@ -60,9 +62,7 @@ def traced_method(wrapped, instance, args, kwargs):
             span_attributes["dspy.optimizer.config"] = json.dumps(config)
 
         attributes = FrameworkSpanAttributes(**span_attributes)
-        with tracer.start_as_current_span(
-            operation_name, kind=SpanKind.CLIENT
-        ) as span:
+        with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span:
             _set_input_attributes(span, kwargs, attributes)
 
             try:
@@ -108,9 +108,7 @@ def traced_method(wrapped, instance, args, kwargs):
             span_attributes["dspy.signature.args"] = str(kwargs)
 
         attributes = FrameworkSpanAttributes(**span_attributes)
-        with tracer.start_as_current_span(
-            operation_name, kind=SpanKind.CLIENT
-        ) as span:
+        with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span:
             _set_input_attributes(span, kwargs, attributes)
 
             try:
@@ -156,11 +154,15 @@ def traced_method(wrapped, instance, args, kwargs):
         if "num_threads" in instance and instance.num_threads is not None:
             span_attributes["dspy.evaluate.num_threads"] = str(instance.num_threads)
         if "return_outputs" in instance and instance.return_outputs is not None:
-            span_attributes["dspy.evaluate.return_outputs"] = str(instance.return_outputs)
+            span_attributes["dspy.evaluate.return_outputs"] = str(
+                instance.return_outputs
+            )
         if "display_table" in instance and instance.display_table is not None:
             span_attributes["dspy.evaluate.display_table"] = str(instance.display_table)
         if "display_progress" in instance and instance.display_progress is not None:
-            span_attributes["dspy.evaluate.display_progress"] = str(instance.display_progress)
+            span_attributes["dspy.evaluate.display_progress"] = str(
+                instance.display_progress
+            )
         if "metric" in instance and instance.metric is not None:
             span_attributes["dspy.evaluate.metric"] = instance.metric.__name__
         if "error_count" in instance and instance.error_count is not None:
@@ -173,9 +175,7 @@ def traced_method(wrapped, instance, args, kwargs):
             span_attributes["dspy.evaluate.args"] = str(args)
 
         attributes = FrameworkSpanAttributes(**span_attributes)
-        with tracer.start_as_current_span(
-            operation_name, kind=SpanKind.CLIENT
-        ) as span:
+        with tracer.start_as_current_span(operation_name, kind=SpanKind.CLIENT) as span:
             _set_input_attributes(span, kwargs, attributes)
 
             try:

src/langtrace_python_sdk/instrumentation/openai/patch.py

@@ -471,7 +471,10 @@ def traced_method(wrapped, instance, args, kwargs):
         attributes = LLMSpanAttributes(**span_attributes)
 
         tools = []
-        if kwargs.get("temperature") is not None and kwargs.get("temperature") != NOT_GIVEN:
+        if (
+            kwargs.get("temperature") is not None
+            and kwargs.get("temperature") != NOT_GIVEN
+        ):
             attributes.llm_temperature = kwargs.get("temperature")
         if kwargs.get("top_p") is not None and kwargs.get("top_p") != NOT_GIVEN:
             attributes.llm_top_p = kwargs.get("top_p")
@@ -499,7 +502,11 @@ def traced_method(wrapped, instance, args, kwargs):
         try:
             # Attempt to call the original method
             result = wrapped(*args, **kwargs)
-            if kwargs.get("stream") is False or kwargs.get("stream") is None or kwargs.get("stream") == NOT_GIVEN:
+            if (
+                kwargs.get("stream") is False
+                or kwargs.get("stream") is None
+                or kwargs.get("stream") == NOT_GIVEN
+            ):
                 span.set_attribute("llm.model", result.model)
                 if hasattr(result, "choices") and result.choices is not None:
                     responses = [
@@ -528,7 +535,8 @@ def traced_method(wrapped, instance, args, kwargs):
                     span.set_attribute("llm.responses", json.dumps(responses))
                 if (
                     hasattr(result, "system_fingerprint")
-                    and result.system_fingerprint is not None and result.system_fingerprint != NOT_GIVEN
+                    and result.system_fingerprint is not None
+                    and result.system_fingerprint != NOT_GIVEN
                 ):
                     span.set_attribute(
                         "llm.system.fingerprint", result.system_fingerprint
@@ -555,7 +563,10 @@ def traced_method(wrapped, instance, args, kwargs):
                     )
 
                 # iterate over kwargs.get("functions") and calculate the prompt tokens
-                if kwargs.get("functions") is not None and kwargs.get("functions") != NOT_GIVEN:
+                if (
+                    kwargs.get("functions") is not None
+                    and kwargs.get("functions") != NOT_GIVEN
+                ):
                     for function in kwargs.get("functions"):
                         prompt_tokens += calculate_prompt_tokens(
                             json.dumps(function), kwargs.get("model")
@@ -641,7 +652,10 @@ async def traced_method(wrapped, instance, args, kwargs):
         attributes = LLMSpanAttributes(**span_attributes)
 
         tools = []
-        if kwargs.get("temperature") is not None and kwargs.get("temperature") != NOT_GIVEN:
+        if (
+            kwargs.get("temperature") is not None
+            and kwargs.get("temperature") != NOT_GIVEN
+        ):
             attributes.llm_temperature = kwargs.get("temperature")
         if kwargs.get("top_p") is not None and kwargs.get("top_p") != NOT_GIVEN:
             attributes.llm_top_p = kwargs.get("top_p")
@@ -667,7 +681,11 @@ async def traced_method(wrapped, instance, args, kwargs):
         try:
             # Attempt to call the original method
             result = await wrapped(*args, **kwargs)
-            if kwargs.get("stream") is False or kwargs.get("stream") is None or kwargs.get("stream") == NOT_GIVEN:
+            if (
+                kwargs.get("stream") is False
+                or kwargs.get("stream") is None
+                or kwargs.get("stream") == NOT_GIVEN
+            ):
                 span.set_attribute("llm.model", result.model)
                 if hasattr(result, "choices") and result.choices is not None:
                     responses = [
@@ -696,7 +714,8 @@ async def traced_method(wrapped, instance, args, kwargs):
                     span.set_attribute("llm.responses", json.dumps(responses))
                 if (
                     hasattr(result, "system_fingerprint")
-                    and result.system_fingerprint is not None and result.system_fingerprint != NOT_GIVEN
+                    and result.system_fingerprint is not None
+                    and result.system_fingerprint != NOT_GIVEN
                 ):
                     span.set_attribute(
                         "llm.system.fingerprint", result.system_fingerprint
@@ -723,7 +742,10 @@ async def traced_method(wrapped, instance, args, kwargs):
                     )
 
                 # iterate over kwargs.get("functions") and calculate the prompt tokens
-                if kwargs.get("functions") is not None and kwargs.get("functions") != NOT_GIVEN:
+                if (
+                    kwargs.get("functions") is not None
+                    and kwargs.get("functions") != NOT_GIVEN
+                ):
                     for function in kwargs.get("functions"):
                         prompt_tokens += calculate_prompt_tokens(
                             json.dumps(function), kwargs.get("model")