fix: Fix Duplicate Trace Calls for Async Functions and Optimize Tracer Implementation

[viniciusdsmello]

Fix: Eliminate Duplicate Trace Calls in Async Functions and Optimize Tracer Implementation

Problem Statement

The Openlayer Python SDK was experiencing duplicate trace calls when using the @trace() decorator on async functions. Instead of generating a single unified trace, async functions created multiple duplicate traces with different data, causing test failures and incorrect tracing behavior.

Root Cause Analysis

The issue was traced to the @trace_async() decorator's incompatibility with async generator functions:

• The decorator used context managers (with create_step()) that interfered with yield statements
• This caused wrapper functions to return coroutine objects instead of async_generator objects
• The context manager became "stuck" waiting for generators to complete before finalizing steps
• Regular async functions worked correctly, but async generators failed

Solution Implementation

1. Async Generator Detection and Handling

• Detection: Added inspect.isasyncgenfunction(func) at decoration time to identify async generators
• Manual Step Management: For async generators, replaced context managers with manual step creation and finalization
• Preserved Context Managers: Regular async functions continue using context managers for optimal performance
• Top-Level Yields: Ensured yield statements remain at the top level of wrapper functions

2. Code Optimization

Identified and eliminated massive code duplication across three wrapper functions:

3. Client Authentication Fix

• Issue: _client was initialized at import time before environment variables were set
• Solution: Implemented lazy initialization using _get_client() function
• Result: Client now created when first needed, ensuring API credentials are available

4. Test Refactoring

Created comprehensive nested test scenario with single orchestrator method:

• New Structure: Single intelligent_assistant_main() method with 7 nested operations
• Realistic Workflow: Simulates complex AI assistant with preprocessing, intent extraction, context retrieval, synthesis, streaming, validation, post-processing, and logging
• Single Trace: Generates one comprehensive trace instead of multiple separate tests