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Prerequisites
  • Python 3.10 or higher
  • PraisonAI Agents package installed
  • PraisonAI Tools package installed
  • sympy and pint packages installed

​
Calculator Tools

Use Calculator Tools to perform mathematical calculations with AI agents.
1

Install Dependencies

First, install the required packages:
pip install praisonaiagents praisonai-tools sympy pint
2

Import Components

Import the necessary components:
from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import (
    evaluate, solve_equation, convert_units,
    calculate_statistics, calculate_financial
)
3

Create Agent

Create a calculator agent:
calculator_agent = Agent(
    name="MathAssistant",
    role="Mathematical Computation Specialist",
    goal="Perform accurate mathematical calculations and solve equations.",
    backstory="Expert in mathematical computations and problem-solving.",
    tools=[
        evaluate, solve_equation, convert_units,
        calculate_statistics, calculate_financial
    ],
    reflection=False
)
4

Define Task

Define the calculation task:
calc_task = Task(
    description="Calculate the area of a circle with radius 5",
    expected_output="The area of the circle in square units",
    agent=calculator_agent,
    name="circle_area"
)
5

Run Agent

Initialize and run the agent:
agents = AgentTeam(
    agents=[calculator_agent],
    tasks=[calc_task],
    process="sequential"
)
agents.start()

​
Understanding Calculator Tools

What are Calculator Tools?

Calculator Tools provide mathematical computation capabilities for AI agents:
  • Expression evaluation
  • Equation solving
  • Unit conversions
  • Support for mathematical functions
  • Variable substitution

​
Key Components

Expression Evaluation

Evaluate mathematical expressions:
result = evaluate("2 + 2 * 3")

Equation Solving

Solve mathematical equations:
result = solve_equation("2*x + 3 = 7")

Unit Conversions

Convert between units:
result = convert_units(100, "meters", "kilometers")

Statistical Calculations

Calculate statistical metrics:
result = calculate_statistics([1, 2, 3, 4, 5])

Financial Calculations

Calculate financial metrics:
result = calculate_financial(1000, 5, 2)

​
Available Functions

from praisonai_tools import evaluate
from praisonai_tools import solve_equation
from praisonai_tools import convert_units
from praisonai_tools import calculate_statistics
from praisonai_tools import calculate_financial

​
Advanced Usage

Evaluate complex mathematical expressions with variables:
from praisonai_tools import evaluate

# Basic arithmetic
result = evaluate("2 + 2 * 3")

# With mathematical functions
result = evaluate("sin(pi/2) + sqrt(16)")

# With variables
result = evaluate(
    "x^2 + y",
    variables={"x": 3, "y": 4}
)
Solve different types of equations:
from praisonai_tools import solve_equation

# Linear equation
result = solve_equation("2*x + 3 = 7")

# With custom variable
result = solve_equation("y^2 = 4", variable="y")
Convert between different units:
from praisonai_tools import convert_units

# Length conversion
result = convert_units(100, "meters", "kilometers")

# Temperature conversion
result = convert_units(32, "fahrenheit", "celsius")

# Time conversion
result = convert_units(2.5, "hours", "minutes")
Calculate statistical metrics:
from praisonai_tools import calculate_statistics

result = calculate_statistics([1, 2, 3, 4, 5])
Calculate financial metrics:
from praisonai_tools import calculate_financial

result = calculate_financial(1000, 5, 2)

​
Error Handling

Error Management

The tools include comprehensive error handling:
# Returns success result
{"result": 8.0}

# Returns error message
{"error": "Invalid expression"}

​
Best Practices

Precision Control

Control calculation precision:
evaluate(
    "pi",
    precision=5
)

Safe Execution

Uses safe evaluation environment with:
  • Restricted builtins
  • Mathematical functions only
  • Variable validation

​
Examples

​
Basic Calculator Agent

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import evaluate, solve_equation, convert_units

# Create calculator agent
calc_agent = Agent(
    name="MathExpert",
    role="Mathematical Specialist",
    goal="Solve mathematical problems accurately.",
    backstory="Expert in mathematics and calculations.",
    tools=[evaluate, solve_equation, convert_units],
    reflection=False
)

# Define task
calc_task = Task(
    description="Solve the equation 2x + 5 = 15",
    expected_output="Value of x",
    agent=calc_agent,
    name="equation_solver"
)

# Run agent
agents = AgentTeam(
    agents=[calc_agent],
    tasks=[calc_task],
    process="sequential"
)
agents.start()