ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/gaia-experience/AWorld/tests/runners/callback/run-test.py

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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.
+import json
+import os
+
+from dotenv import load_dotenv
+
+from aworld.agents.llm_agent import Agent
+from aworld.config.conf import AgentConfig, TaskConfig
+from aworld.core.task import Task
+
+from aworld.runner import Runners
+from aworld.runners.callback.decorator import reg_callback
+from aworld.tools.mcp_tool import async_mcp_tool
+
+@reg_callback("print_content")
+def simple_callback(content):
+    """Simple callback function, prints content and returns it
+
+        Args:
+            content: Content to print
+
+        Returns:
+            The input content
+        """
+    print(f"callback content: {content}")
+    return content
+
+async def run():
+    load_dotenv()
+    llm_provider = os.getenv("LLM_PROVIDER_WEATHER", "openai")
+    llm_model_name = os.getenv("LLM_MODEL_NAME_WEATHER")
+    llm_api_key = os.getenv("LLM_API_KEY_WEATHER")
+    llm_base_url = os.getenv("LLM_BASE_URL_WEATHER")
+    llm_temperature = os.getenv("LLM_TEMPERATURE_WEATHER", 0.0)
+
+    agent_config = AgentConfig(
+        llm_provider=llm_provider,
+        llm_model_name=llm_model_name,
+        llm_api_key=llm_api_key,
+        llm_base_url=llm_base_url,
+        llm_temperature=llm_temperature,
+    )
+    #mcp_servers = ["filewrite_server", "fileread_server"]
+    #mcp_servers = ["amap-amap-sse","filewrite_server", "fileread_server"]
+    #mcp_servers = ["file_server"]
+    #mcp_servers = ["amap-amap-sse"]
+    mcp_servers = ["aworldsearch_server"]
+    #mcp_servers = ["gen_video_server"]
+   # mcp_servers = ["picsearch_server"]
+    #mcp_servers = ["gen_audio_server"]
+    #mcp_servers = ["playwright"]
+    #mcp_servers = ["tavily-mcp"]
+
+    path_cwd = os.path.dirname(os.path.abspath(__file__))
+    mcp_path = os.path.join(path_cwd, "mcp.json")
+    with open(mcp_path, "r") as f:
+        mcp_config = json.load(f)
+
+    print("-------------------mcp_config--------------",mcp_config)
+
+    #sand_box = Sandbox(mcp_servers=mcp_servers,mcp_config=mcp_config)
+    # You can specify sandbox
+    #sand_box = Sandbox(mcp_servers=mcp_servers, mcp_config=mcp_config,env_type=SandboxEnvType.K8S)
+    #sand_box = Sandbox(mcp_servers=mcp_servers, mcp_config=mcp_config,env_type=SandboxEnvType.SUPERCOMPUTER)
+
+    search_sys_prompt = "You are a versatile assistant"
+    search = Agent(
+        conf=agent_config,
+        name="search_agent",
+        system_prompt=search_sys_prompt,
+        mcp_config=mcp_config,
+        mcp_servers=mcp_servers,
+        #sandbox=sand_box,
+    )
+
+    # Run agent
+    # Runners.sync_run(input="Use tavily-mcp to check what tourist attractions are in Hangzhou", agent=search)
+    task = Task(
+        # input="Use tavily-mcp to check what tourist attractions are in Hangzhou",
+        # input="Use the file_server tool to analyze this audio link: https://amap-aibox-data.oss-cn-zhangjiakou.aliyuncs.com/.mp3",
+        # input="Use the amap-amap-sse tool to find hotels within one kilometer of West Lake in Hangzhou",
+        input="Use the aworldsearch_server tool to search for the origin of the Dragon Boat Festival",
+        # input="Use the picsearch_server tool to search for Captain America",
+        # input="Make sure to use the human_confirm tool to let the user confirm this message: 'Do you want to make a payment to this customer'",
+        # input="Use the gen_audio_server tool to convert this sentence to audio: 'Nice to meet you'",
+        #input="Use the gen_video_server tool to generate a video of this description: 'A cat walking alone on a snowy day'",
+        # input="First call the filewrite_server tool, then call the fileread_server tool",
+        # input="Use the playwright tool, with Google browser, search for the latest news about the Trump administration on www.baidu.com",
+        # input="Use tavily-mcp",
+        agent=search,
+        conf=TaskConfig(),
+        event_driven=True
+    )
+
+    async for output in Runners.streamed_run_task(task).stream_events():
+        print(f"Agent Ouput: {output}")