【柴亮太のAI最前線】LlamaIndexとGeminiで築く！自律型マルチエージェントの衝撃

pip install llama-index llama-index-utils-workflow llama-index-llms-google-genai llama-index-tools-google

import os
from llama_index.llms.google_genai import GoogleGenAI

# os.environ['GEMINI_API_KEY'] = 'YOUR_API_KEY_HERE' # 実際には環境変数に設定
assert 'GEMINI_API_KEY' in os.environ
llm = GoogleGenAI(model="gemini-3.6-flash")

from google.genai import types
google_search_tool = types.Tool(google_search=types.GoogleSearch())
llm_with_search = GoogleGenAI(
    model="gemini-3.6-flash",
    generation_config=types.GenerateContentConfig(tools=[google_search_tool])
)

# 検索が必要なクエリでLLMをテスト
# response = await llm_with_search.acomplete("What's the weather like today in Biarritz?")
# print(response)

from llama_index.core.workflow import Context

async def search_web(ctx: Context, query: str) -> str:
    # GeminiとGoogle Searchを使ってウェブ検索
    ...

async def record_notes(ctx: Context, notes: str, notes_title: str) -> str:
    # 検索結果をContextに記録
    current_state = await ctx.store.get("state")
    if "research_notes" not in current_state:
        current_state["research_notes"] = {}
    current_state["research_notes"][notes_title] = notes
    await ctx.store.set("state", current_state)
    return "Notes recorded."

# write_report, review_reportなども同様に定義

from llama_index.core.agent.workflow import FunctionAgent, AgentWorkflow

research_agent = FunctionAgent(
    name="ResearchAgent",
    description="Useful for searching the web for information on a given topic and recording notes on the topic.",
    system_prompt=(
        "You are the ResearchAgent that can search the web for information on a given topic and record notes on the topic. "
        "Once notes are recorded and you are satisfied, you should hand off control to the WriteAgent to write a report on the topic."
    ),
    llm=llm,
    tools=[search_web, record_notes],
    can_handoff_to=["WriteAgent"],
)

write_agent = FunctionAgent(
    name="WriteAgent",
    description="Useful for writing a report on a given topic.",
    system_prompt=(
        "You are the WriteAgent that can write a report on a given topic. "
        "Your report should be in a markdown format. The content should be grounded in the research notes. "
        "Once the report is written, you should get feedback at least once from the ReviewAgent."
    ),
    llm=llm,
    tools=[write_report],
    can_handoff_to=["ReviewAgent", "ResearchAgent"],
)

review_agent = FunctionAgent(
    name="ReviewAgent",
    description="Useful for reviewing a report and providing feedback.",
    system_prompt=(
        "You are the ReviewAgent that can review a report and provide feedback. "
        "Your feedback should either approve the current report or request changes for the WriteAgent to implement."
    ),
    llm=llm,
    tools=[review_report],
    can_handoff_to=["ResearchAgent", "WriteAgent"],
)

agent_workflow = AgentWorkflow(
    agents=[research_agent, write_agent, review_agent],
    root_agent=research_agent.name,
    initial_state={
        "research_notes": {},
        "report_content": "Not written yet.",
        "review": "Review required.",
    },
)

# ワークフローの実行
# handler = agent_workflow.run(user_msg="Write me a report on the history of the web...")
# for event in handler.stream_events():
#     # イベントの監視ロジック
#     ...