release: 0.2.0-alpha.44

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
- ".": "0.2.0-alpha.43"
+ ".": "0.2.0-alpha.44"
 }

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)

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"

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

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)