Foundry IQ：给智能代理装上统一知识层，告别数据拼图

# 安装依赖
# pip install azure-ai-projects azure-identity

import os
from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential

# 1. 用环境变量或硬编码填入你的 Foundry 项目连接字符串
project_connection_string = os.environ.get(
    "AZURE_AI_PROJECT_CONNECTION_STRING",
    "eastus.api.azureml.ms;my-subscription-id;my-resource-group;my-project-name"
)

credential = DefaultAzureCredential()
client = AIProjectClient.from_connection_string(
    credential=credential,
    connection_string=project_connection_string,
)

# 2. 创建 Agent，挂载 Foundry IQ 知识检索工具
agent = client.agents.create(
    model="gpt-4o",
    name="knowledge-agent",
    instructions="你是一个企业知识助手。回答问题时，优先从检索到的知识片段中提取事实，不要编造。",
    tools=[
        {
            "type": "foundry_iq_retrieval",  # Foundry IQ 检索工具类型
            "foundry_iq_retrieval": {
                "data_sources": [
                    # 内部数据源：Azure SQL 中的产品手册
                    {
                        "type": "azure_sql",
                        "connection_name": "my-sql-connection",  # 在 Foundry 中预先注册的连接
                        "table": "product_manuals",
                    },
                    # 内部数据源：SharePoint 文档库
                    {
                        "type": "sharepoint",
                        "connection_name": "my-sharepoint-connection",
                        "site": "https://contoso.sharepoint.com/sites/engineering",
                    },
                    # 外部数据源：公开网页知识
                    {
                        "type": "web",
                        "urls": [
                            "https://learn.microsoft.com/en-us/azure/",
                        ],
                    },
                ],
            },
        }
    ],
)

print(f"Agent created, id: {agent.id}")

# 3. 发起对话，Agent 会自动调用 Foundry IQ 检索
thread = client.agents.create_thread()
client.agents.create_message(
    thread_id=thread.id,
    role="user",
    content="Contoso X200 设备的保修政策是什么？",
)

run = client.agents.create_and_process_run(
    thread_id=thread.id,
    agent_id=agent.id,
)

# 4. 读取 Agent 回答
messages = client.agents.list_messages(thread_id=thread.id)
for msg in messages.data:
    if msg.role == "assistant":
        print("Agent 回答:", msg.content[-1].text.value)