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

2026-08-20 13:12:50 +00:00
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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.
+import asyncio
+import json
+import os
+
+from dotenv import load_dotenv
+
+from aworld.config.conf import AgentConfig, TaskConfig
+from aworld.agents.llm_agent import Agent
+from aworld.core.task import Task
+from aworld.runner import Runners
+
+
+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 = ["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)
+
+    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,
+    )
+
+    # Run agent
+    task = Task(
+        input="Use tavily-mcp to check what tourist attractions are in Hangzhou",
+        agent=search,
+        conf=TaskConfig(),
+    )
+
+    result = Runners.sync_run_task(task)
+    print( "----------------------------------------------------------------------------------------------")
+    print(result)