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84 lines
2.6 KiB
Python
84 lines
2.6 KiB
Python
"""
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This example shows how to use custom function tools with a tool-enabled
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agent.
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"""
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import asyncio
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import os
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import random
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import sys
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from typing import List
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from agnext.application import SingleThreadedAgentRuntime
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from agnext.base import AgentInstantiationContext
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from agnext.components.models import (
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SystemMessage,
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)
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from agnext.components.tool_agent import ToolAgent
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from agnext.components.tools import FunctionTool, Tool
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from typing_extensions import Annotated
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__))))
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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from agnext.base import AgentId
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from coding_direct import Message, ToolUseAgent
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from common.utils import get_chat_completion_client_from_envs
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async def get_stock_price(ticker: str, date: Annotated[str, "The date in YYYY/MM/DD format."]) -> float:
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"""Get the stock price of a company."""
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# This is a placeholder function that returns a random number.
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return random.uniform(10, 100)
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async def main() -> None:
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# Create the runtime.
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runtime = SingleThreadedAgentRuntime()
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tools: List[Tool] = [
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# A tool that gets the stock price.
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FunctionTool(
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get_stock_price,
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description="Get the stock price of a company given the ticker and date.",
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name="get_stock_price",
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)
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]
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# Register agents.
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await runtime.register(
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"tool_executor_agent",
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lambda: ToolAgent(
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description="Tool Executor Agent",
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tools=tools,
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),
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)
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await runtime.register(
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"tool_enabled_agent",
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lambda: ToolUseAgent(
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description="Tool Use Agent",
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system_messages=[SystemMessage("You are a helpful AI Assistant. Use your tools to solve problems.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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tool_schema=[tool.schema for tool in tools],
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tool_agent=AgentId("tool_executor_agent", AgentInstantiationContext.current_agent_id().key),
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),
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)
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tool_use_agent = AgentId("tool_enabled_agent", "default")
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runtime.start()
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# Send a task to the tool user.
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response = await runtime.send_message(Message("What is the stock price of NVDA on 2024/06/01"), tool_use_agent)
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# Print the result.
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assert isinstance(response, Message)
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print(response.content)
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# Run the runtime until the task is completed.
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await runtime.stop()
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if __name__ == "__main__":
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import logging
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logging.basicConfig(level=logging.WARNING)
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logging.getLogger("agnext").setLevel(logging.DEBUG)
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asyncio.run(main())
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