하위 에이전트 트레이스

import weave
from weave.conversation import Message, Usage

weave.init("[YOUR-TEAM]/[YOUR-PROJECT]")

with weave.start_conversation(agent_name="supervisor") as conversation:
    with conversation.start_turn(user_message="Research the founders of Anthropic.") as turn:

        # 슈퍼바이저 LLM 호출: 어떤 전문가에게 위임할지 결정합니다.
        with weave.start_llm(model="gpt-4o", provider_name="openai") as llm:
            llm.input_messages = [Message(role="user", content="Research the founders of Anthropic.")]
            llm.output("Delegating to the research specialist.")
            llm.usage = Usage(input_tokens=80, output_tokens=10)

        # 리서치 전문가에게 하위 에이전트로 위임합니다.
        with weave.start_subagent(name="research-specialist", model="gpt-4o") as sub:
            with sub.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                sub_llm.input_messages = [Message(role="user", content="Find founders of Anthropic.")]
                sub_llm.output("I should search for this.")
                sub_llm.usage = Usage(input_tokens=120, output_tokens=15)

                with weave.start_tool(name="wikipedia_search", arguments='{"query":"Anthropic"}') as tool:
                    tool.result = "Anthropic was founded by Dario and Daniela Amodei in 2021."

            with sub.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                sub_llm.output("Anthropic was founded by Dario and Daniela Amodei in 2021.")
                sub_llm.usage = Usage(input_tokens=200, output_tokens=25)

        # 슈퍼바이저 turn으로 돌아와 최종 답변을 종합합니다.
        with weave.start_llm(model="gpt-4o", provider_name="openai") as llm:
            llm.output("Anthropic was founded by Dario and Daniela Amodei in 2021.")
            llm.usage = Usage(input_tokens=300, output_tokens=20)

with weave.start_conversation(agent_name="content-pipeline") as conversation:
    with conversation.start_turn(user_message="Write a short blog post about Anthropic.") as turn:

        # Researcher 하위 에이전트: 사실 수집.
        with weave.start_subagent(name="researcher", model="gpt-4o") as researcher:
            with researcher.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                sub_llm.input_messages = [Message(role="user", content="Find key facts about Anthropic.")]
                sub_llm.output("I should search Wikipedia.")
                sub_llm.usage = Usage(input_tokens=80, output_tokens=15)

                with weave.start_tool(name="wikipedia_search", arguments='{"query":"Anthropic"}') as tool:
                    tool.result = "Anthropic was founded by Dario and Daniela Amodei in 2021."

        # Writer 하위 에이전트: 게시물 초안 작성.
        with weave.start_subagent(name="writer", model="gpt-4o") as writer:
            with writer.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                sub_llm.input_messages = [Message(role="user", content="Draft a post using the research.")]
                sub_llm.output("Anthropic, founded in 2021 by Dario and Daniela Amodei, builds AI safety research...")
                sub_llm.usage = Usage(input_tokens=180, output_tokens=120)

        # Reviewer 하위 에이전트: 초안 다듬기.
        with weave.start_subagent(name="reviewer", model="gpt-4o") as reviewer:
            with reviewer.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                sub_llm.input_messages = [Message(role="user", content="Review and tighten the draft.")]
                sub_llm.output("Final post: Anthropic, founded in 2021 by Dario and Daniela Amodei, builds AI safety research...")
                sub_llm.usage = Usage(input_tokens=200, output_tokens=140)

with weave.start_conversation(agent_name="orchestrator") as conversation:
    with conversation.start_turn(user_message="Compare Anthropic and OpenAI.") as turn:

        with weave.start_subagent(name="research-coordinator") as coordinator:
            with weave.start_subagent(name="anthropic-researcher") as r1:
                with r1.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                    sub_llm.output("Anthropic facts...")
                    sub_llm.usage = Usage(input_tokens=120, output_tokens=30)

                # 중첩: 연구자가 자체 요약 하위 에이전트에 작업을 위임합니다.
                with weave.start_subagent(name="anthropic-summarizer") as summarizer:
                    with summarizer.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                        sub_llm.output("Anthropic summary: ...")
                        sub_llm.usage = Usage(input_tokens=80, output_tokens=20)

            with weave.start_subagent(name="openai-researcher") as r2:
                with r2.llm(model="gpt-4o", provider_name="openai") as sub_llm:
                    sub_llm.output("OpenAI facts...")
                    sub_llm.usage = Usage(input_tokens=120, output_tokens=30)