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