diff --git a/.release-please-manifest.json b/.release-please-manifest.json
index d426d689..ce266685 100644
--- a/.release-please-manifest.json
+++ b/.release-please-manifest.json
@@ -1,3 +1,3 @@
 {
-  ".": "0.2.0-alpha.43"
+  ".": "0.2.0-alpha.44"
 }
\ No newline at end of file
diff --git a/CHANGELOG.md b/CHANGELOG.md
index a6ef4d09..1b791912 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -5,6 +5,14 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
+## 0.2.0-alpha.44 (2025-02-26)
+
+Full Changelog: [v0.2.0-alpha.43...v0.2.0-alpha.44](https://github.com/openlayer-ai/openlayer-python/compare/v0.2.0-alpha.43...v0.2.0-alpha.44)
+
+### Features
+
+* feat(tracing): completes OPEN-6538 Surface root step metadata at the request level ([1bcedcf](https://github.com/openlayer-ai/openlayer-python/commit/1bcedcf57d509064f89e2a5fae3fb39f22da5920))
+
 ## 0.2.0-alpha.43 (2025-02-24)
 
 Full Changelog: [v0.2.0-alpha.42...v0.2.0-alpha.43](https://github.com/openlayer-ai/openlayer-python/compare/v0.2.0-alpha.42...v0.2.0-alpha.43)
diff --git a/pyproject.toml b/pyproject.toml
index cb19b4dd..d4becc59 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "openlayer"
-version = "0.2.0-alpha.43"
+version = "0.2.0-alpha.44"
 description = "The official Python library for the openlayer API"
 dynamic = ["readme"]
 license = "Apache-2.0"
diff --git a/src/openlayer/_version.py b/src/openlayer/_version.py
index 628b0bc9..e2408930 100644
--- a/src/openlayer/_version.py
+++ b/src/openlayer/_version.py
@@ -1,4 +1,4 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 __title__ = "openlayer"
-__version__ = "0.2.0-alpha.43"  # x-release-please-version
+__version__ = "0.2.0-alpha.44"  # x-release-please-version
diff --git a/src/openlayer/lib/tracing/tracer.py b/src/openlayer/lib/tracing/tracer.py
index b9ecc886..4057ad0d 100644
--- a/src/openlayer/lib/tracing/tracer.py
+++ b/src/openlayer/lib/tracing/tracer.py
@@ -131,7 +131,12 @@ def add_chat_completion_step_to_trace(**kwargs) -> None:
 
 
 # ----------------------------- Tracing decorator ---------------------------- #
-def trace(*step_args, inference_pipeline_id: Optional[str] = None, context_kwarg: Optional[str] = None, **step_kwargs):
+def trace(
+    *step_args,
+    inference_pipeline_id: Optional[str] = None,
+    context_kwarg: Optional[str] = None,
+    **step_kwargs,
+):
     """Decorator to trace a function.
 
     Examples
@@ -175,7 +180,9 @@ def decorator(func):
         def wrapper(*func_args, **func_kwargs):
             if step_kwargs.get("name") is None:
                 step_kwargs["name"] = func.__name__
-            with create_step(*step_args, inference_pipeline_id=inference_pipeline_id, **step_kwargs) as step:
+            with create_step(
+                *step_args, inference_pipeline_id=inference_pipeline_id, **step_kwargs
+            ) as step:
                 output = exception = None
                 try:
                     output = func(*func_args, **func_kwargs)
@@ -196,7 +203,10 @@ def wrapper(*func_args, **func_kwargs):
                     if context_kwarg in inputs:
                         log_context(inputs.get(context_kwarg))
                     else:
-                        logger.warning("Context kwarg `%s` not found in inputs of the current function.", context_kwarg)
+                        logger.warning(
+                            "Context kwarg `%s` not found in inputs of the current function.",
+                            context_kwarg,
+                        )
 
                 step.log(
                     inputs=inputs,
@@ -215,7 +225,10 @@ def wrapper(*func_args, **func_kwargs):
 
 
 def trace_async(
-    *step_args, inference_pipeline_id: Optional[str] = None, context_kwarg: Optional[str] = None, **step_kwargs
+    *step_args,
+    inference_pipeline_id: Optional[str] = None,
+    context_kwarg: Optional[str] = None,
+    **step_kwargs,
 ):
     """Decorator to trace a function.
 
@@ -260,7 +273,9 @@ def decorator(func):
         async def wrapper(*func_args, **func_kwargs):
             if step_kwargs.get("name") is None:
                 step_kwargs["name"] = func.__name__
-            with create_step(*step_args, inference_pipeline_id=inference_pipeline_id, **step_kwargs) as step:
+            with create_step(
+                *step_args, inference_pipeline_id=inference_pipeline_id, **step_kwargs
+            ) as step:
                 output = exception = None
                 try:
                     output = await func(*func_args, **func_kwargs)
@@ -281,7 +296,10 @@ async def wrapper(*func_args, **func_kwargs):
                     if context_kwarg in inputs:
                         log_context(inputs.get(context_kwarg))
                     else:
-                        logger.warning("Context kwarg `%s` not found in inputs of the current function.", context_kwarg)
+                        logger.warning(
+                            "Context kwarg `%s` not found in inputs of the current function.",
+                            context_kwarg,
+                        )
 
                 step.log(
                     inputs=inputs,
@@ -299,7 +317,9 @@ async def wrapper(*func_args, **func_kwargs):
     return decorator
 
 
-async def _invoke_with_context(coroutine: Awaitable[Any]) -> Tuple[contextvars.Context, Any]:
+async def _invoke_with_context(
+    coroutine: Awaitable[Any],
+) -> Tuple[contextvars.Context, Any]:
     """Runs a coroutine and preserves the context variables set within it."""
     result = await coroutine
     context = contextvars.copy_context()
@@ -356,6 +376,7 @@ def post_process_trace(
         "cost": processed_steps[0].get("cost", 0),
         "tokens": processed_steps[0].get("tokens", 0),
         "steps": processed_steps,
+        **root_step.metadata,
     }
     if input_variables:
         trace_data.update(input_variables)