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1. Introduction

agentools is a lightweight and flexible library designed for building smart agent assistants across various industries. Whether you're creating an AI-powered customer service bot, a data analysis assistant, or a domain-specific automation agent, agentools provides a simple yet powerful foundation.

With its modular tool system, you can easily extend your agent's capabilities by integrating a wide range of tools. Each tool is self-contained, well-documented, and can be registered dynamically—making it effortless to scale and adapt your agent to new tasks or environments.

To install and use this library please following:

git clone https://github.com/agentools
poetry install

2. Set up Agent

agentools is a flexible library for creating intelligent agents. You can configure your agent with tools, each encapsulated in a Python module under agentools.tools. This provides a workspace of tools that agents can use to interact with and operate in the realistic world. Each tool is a Python file with full documentation and it can be independently ran. For example, the agentools.tools.websearch_tools module contains code for interacting with a search API.

import os
import sys
from langchain_together import ChatTogether 
sys.path.append(os.path.join(os.getcwd(), "agentools"))
from agentools.agent.agent import Agent
from dotenv import load_dotenv
load_dotenv()

llm = ChatTogether(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo-Free"
)

# Step 1: Create Agent with tools
agent = Agent(
    llm = llm,
    tools = ['agentools.tools.yfinance_tools', 'agentools.tools.websearch_tools']
)

# Step 2: invoke the agent
df = agent.invoke("What is the price of Tesla stock in 2024?")
df.head()

png

plot = agent.invoke("Let's visualize Tesla stock in 2024?")

png

plot = agent.invoke("Let's visualize the return of Tesla stock in 2024?")

3. Register function tool

Function tools are registered directly in your runtime code by decorating them with the @function_tool without saving them into python module files.

import json
import os
from functools import wraps
from typing import Dict, Any
import inspect
from pathlib import Path
from agentools.register.tool import function_tool
from typing import List

@function_tool
def sum_of_series(x: List[float]):
    return f"Sum of list is {sum(x)}"
agent.invoke("Sum of this list: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]?")
'Sum of list is 55'