OpenTelemetry Traces를 Weave로 전송하기

import base64
import json
import os
from opentelemetry import trace
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, BatchSpanProcessor

# 설정
ENTITY = "YOUR_ENTITY"
PROJECT = "YOUR_PROJECT"
PROJECT_ID = f"{ENTITY}/{PROJECT}"
WANDB_API_KEY = os.environ["WANDB_API_KEY"]

# OTLP 엔드포인트 및 헤더 설정
OTEL_EXPORTER_OTLP_ENDPOINT="https://trace.wandb.ai/otel/v1/traces"
AUTH = base64.b64encode(f"api:{WANDB_API_KEY}".encode()).decode()
OTEL_EXPORTER_OTLP_HEADERS = {
    "Authorization": f"Basic {AUTH}",
    "project_id": PROJECT_ID,
}

# tracer provider 초기화
tracer_provider = trace_sdk.TracerProvider()

# OTLP 엑스포터 구성
exporter = OTLPSpanExporter(
    endpoint=OTEL_EXPORTER_OTLP_ENDPOINT,
    headers=OTEL_EXPORTER_OTLP_HEADERS,
)

# tracer provider에 엑스포터 추가
tracer_provider.add_span_processor(BatchSpanProcessor(exporter))

# 선택적으로 콘솔에 span 출력
tracer_provider.add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))

# tracer provider 설정
trace.set_tracer_provider(tracer_provider)

# 글로벌 tracer provider에서 tracer 생성
tracer = trace.get_tracer(__name__)

def example_1_basic_thread_and_turn():
    """예시 1: 단일 턴을 가진 기본 thread"""
    print("\n=== 예시 1: 기본 Thread와 턴 ===")

    # thread 컨텍스트 생성
    thread_id = "thread_example_1"

    # 이 span은 턴을 나타냄 (thread의 직계 자식)
    with tracer.start_as_current_span("process_user_message") as turn_span:
        # thread 속성 설정
        turn_span.set_attribute("wandb.thread_id", thread_id)
        turn_span.set_attribute("wandb.is_turn", True)

        # 예시 속성 추가
        turn_span.set_attribute("input.value", "Hello, help me with setup")

        # 중첩된 span으로 작업 시뮬레이션
        with tracer.start_as_current_span("generate_response") as nested_span:
            # 턴 내의 중첩된 호출이므로 is_turn은 false 또는 설정하지 않음
            nested_span.set_attribute("wandb.thread_id", thread_id)
            # wandb.is_turn은 중첩 호출에 대해 설정하지 않거나 False로 설정

            response = "I'll help you get started with the setup process."
            nested_span.set_attribute("output.value", response)

        turn_span.set_attribute("output.value", response)
        print(f"Thread에서 턴 완료: {thread_id}")

def main():
    example_1_basic_thread_and_turn()
if __name__ == "__main__":
    main()

def example_2_multiple_turns():
    """예시 2: 단일 thread 내의 여러 턴"""
    print("\n=== 예시 2: Thread 내 여러 턴 ===")

    thread_id = "thread_conversation_123"

    # 턴 1
    with tracer.start_as_current_span("process_message_turn1") as turn1_span:
        turn1_span.set_attribute("wandb.thread_id", thread_id)
        turn1_span.set_attribute("wandb.is_turn", True)
        turn1_span.set_attribute("input.value", "What programming languages do you recommend?")

        # 중첩 작업
        with tracer.start_as_current_span("analyze_query") as analyze_span:
            analyze_span.set_attribute("wandb.thread_id", thread_id)
            # 중첩 span에 대해서는 is_turn 속성 없음 또는 False로 설정

        response1 = "I recommend Python for beginners and JavaScript for web development."
        turn1_span.set_attribute("output.value", response1)
        print(f"Thread에서 턴 1 완료: {thread_id}")

    # 턴 2
    with tracer.start_as_current_span("process_message_turn2") as turn2_span:
        turn2_span.set_attribute("wandb.thread_id", thread_id)
        turn2_span.set_attribute("wandb.is_turn", True)
        turn2_span.set_attribute("input.value", "Can you explain Python vs JavaScript?")

        # 중첩 작업
        with tracer.start_as_current_span("comparison_analysis") as compare_span:
            compare_span.set_attribute("wandb.thread_id", thread_id)
            compare_span.set_attribute("wandb.is_turn", False)  # 중첩 작업에 대해 명시적 False

        response2 = "Python excels at data science while JavaScript dominates web development."
        turn2_span.set_attribute("output.value", response2)
        print(f"Thread에서 턴 2 완료: {thread_id}")

def main():
    example_2_multiple_turns()
if __name__ == "__main__":
    main()

def example_3_complex_nested_structure():
    """예시 3: 여러 레벨의 복잡한 중첩 구조"""
    print("\n=== 예시 3: 복잡한 중첩 구조 ===")

    thread_id = "thread_complex_456"

    # 여러 레벨의 중첩을 가진 턴
    with tracer.start_as_current_span("handle_complex_request") as turn_span:
        turn_span.set_attribute("wandb.thread_id", thread_id)
        turn_span.set_attribute("wandb.is_turn", True)
        turn_span.set_attribute("input.value", "Analyze this code and suggest improvements")

        # 레벨 1 중첩 작업
        with tracer.start_as_current_span("code_analysis") as analysis_span:
            analysis_span.set_attribute("wandb.thread_id", thread_id)
            # 중첩 작업에 대해 is_turn 없음

            # 레벨 2 중첩 작업
            with tracer.start_as_current_span("syntax_check") as syntax_span:
                syntax_span.set_attribute("wandb.thread_id", thread_id)
                syntax_span.set_attribute("result", "No syntax errors found")

            # 또 다른 레벨 2 중첩 작업
            with tracer.start_as_current_span("performance_check") as perf_span:
                perf_span.set_attribute("wandb.thread_id", thread_id)
                perf_span.set_attribute("result", "Found 2 optimization opportunities")

        # 또 다른 레벨 1 중첩 작업
        with tracer.start_as_current_span("generate_suggestions") as suggest_span:
            suggest_span.set_attribute("wandb.thread_id", thread_id)
            suggestions = ["Use list comprehension", "Consider caching results"]
            suggest_span.set_attribute("suggestions", json.dumps(suggestions))

        turn_span.set_attribute("output.value", "Analysis complete with 2 improvement suggestions")
        print(f"Thread에서 복잡한 턴 완료: {thread_id}")

def main():
    example_3_complex_nested_structure()
if __name__ == "__main__":
    main()

def example_4_non_turn_operations():
    """예시 4: thread의 일부이지만 턴은 아닌 작업"""
    print("\n=== 예시 4: 턴이 아닌 Thread 작업 ===")

    thread_id = "thread_background_789"

    # thread의 일부이지만 턴은 아닌 백그라운드 작업
    with tracer.start_as_current_span("background_indexing") as bg_span:
        bg_span.set_attribute("wandb.thread_id", thread_id)
        # wandb.is_turn은 설정되지 않거나 false - 이것은 턴이 아님
        bg_span.set_attribute("wandb.is_turn", False)
        bg_span.set_attribute("operation", "Indexing conversation history")
        print(f"Thread 내 백그라운드 작업: {thread_id}")

    # 동일한 thread의 실제 턴
    with tracer.start_as_current_span("user_query") as turn_span:
        turn_span.set_attribute("wandb.thread_id", thread_id)
        turn_span.set_attribute("wandb.is_turn", True)
        turn_span.set_attribute("input.value", "Search my previous conversations")
        turn_span.set_attribute("output.value", "Found 5 relevant conversations")
        print(f"Thread에서 턴 완료: {thread_id}")

def main():
    example_4_non_turn_operations()
if __name__ == "__main__":
    main()