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Quick Start

1

Install Package

First, install the PraisonAI Agents package:

pip install praisonaiagents sympy pint
2

Set API Key

Set your OpenAI API key as an environment variable in your terminal:

export OPENAI_API_KEY=your_api_key_here
3

Create a file

Create a new file app.py with the basic setup:

from praisonaiagents import Agent, Task, PraisonAIAgents
from praisonaiagents.tools import (
    evaluate, solve_equation, convert_units,
    calculate_statistics, calculate_financial
)

# Create math agent
math_agent = Agent(
    role="Math Expert",
    goal="Perform complex mathematical calculations",
    backstory="Expert in mathematical computations and analysis",
    tools=[
        evaluate, solve_equation, convert_units,
        calculate_statistics, calculate_financial
    ],
    verbose=True
)

# Create a task
task = Task(
    description="Calculate compound interest and statistical analysis",
    expected_output="Detailed mathematical analysis",
    agent=math_agent
)

# Create and start the agents
agents = PraisonAIAgents(
    agents=[math_agent],
    tasks=[task],
    process="sequential",
    verbose=2
)

# Start execution
agents.start()
4

Start Agents

Type this in your terminal to run your agents:

python app.py

Requirements

  • Python 3.10 or higher
  • OpenAI API key. Generate OpenAI API key here. Use Other models using this guide.
  • sympy and pint packages (automatically installed when needed)

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Understanding Math Agents

What are Math Agents?

Math agents are specialized AI agents that can:

  • Evaluate mathematical expressions
  • Solve equations and systems of equations
  • Perform unit conversions
  • Calculate statistical metrics
  • Handle financial calculations

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Features

Expression Evaluator

Evaluates mathematical expressions and formulas.

Equation Solver

Solves mathematical equations and systems.

Unit Converter

Converts between different units of measurement.

Statistical Calculator

Calculates statistical metrics and analysis.

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Multi-Agent AI Math Analysis

1

Install Package

First, install the PraisonAI Agents package:

pip install praisonaiagents
2

Set API Key

Set your OpenAI API key as an environment variable in your terminal:

export OPENAI_API_KEY=your_api_key_here
3

Create a file

Create a new file app.py with the basic setup:

from praisonaiagents import Agent, Task, PraisonAIAgents
from praisonaiagents.tools import (
    evaluate, solve_equation, convert_units,
    calculate_statistics, calculate_financial
)

# Create first agent for calculations
calculator = Agent(
    role="Mathematical Calculator",
    goal="Perform complex calculations and analysis",
    backstory="Expert in mathematical computations",
    tools=[evaluate, solve_equation, convert_units],
    verbose=True
)

# Create second agent for statistics
statistician = Agent(
    role="Statistical Analyst",
    goal="Perform statistical analysis and interpretation",
    backstory="Expert in statistical analysis",
    tools=[calculate_statistics, calculate_financial],
    verbose=True
)

# Create first task
calc_task = Task(
    description="Calculate compound interest for $10000 at 5% for 3 years",
    expected_output="Detailed interest calculation",
    agent=calculator
)

# Create second task
stats_task = Task(
    description="Analyze the monthly interest distribution",
    expected_output="Statistical analysis of interest data",
    agent=statistician
)

# Create and start the agents
agents = PraisonAIAgents(
    agents=[calculator, statistician],
    tasks=[calc_task, stats_task],
    process="sequential"
)

# Start execution
agents.start()
4

Start Agents

Type this in your terminal to run your agents:

python app.py

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Configuration Options

# Create an agent with advanced math configuration
agent = Agent(
    role="Math Expert",
    goal="Perform complex mathematical analysis",
    backstory="Expert in mathematical computations",
    tools=[
        evaluate,
        solve_equation,
        convert_units,
        calculate_statistics,
        calculate_financial
    ],
    verbose=True,  # Enable detailed logging
    llm="gpt-4o"  # Language model to use
)

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Troubleshooting

Expression Errors

If expressions are not evaluating:

  • Check syntax and formatting
  • Verify variable definitions
  • Enable verbose mode for debugging

Calculation Issues

If calculations are incorrect:

  • Review input formats
  • Check unit compatibility
  • Verify formula structure

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Next Steps

AutoAgents

Learn about automatically created and managed AI agents

Mini Agents

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For optimal results, ensure mathematical expressions and units are properly formatted for your specific use case.