Designing the Agent's Brain (Architecture) › Adding Decision Logic

import os
import anthropic
import re

class DecisionAgent:
    def __init__(self, model="claude-sonnet-4-5"):
        self.client = anthropic.Anthropic()
        self.model = model
        self.conversation_history = []
        
    def needs_calculation(self, text):
        # Simple heuristic: look for math expressions
        return bool(re.search(r'\d+\s*[\+\-\*\/]\s*\d+', text))
    
    def calculate(self, expression):
        # Extract and evaluate the math expression
        match = re.search(r'(\d+)\s*([\+\-\*\/])\s*(\d+)', expression)
        if match:
            a, op, b = match.groups()
            a, b = int(a), int(b)
            if op == '+': return a + b
            elif op == '-': return a - b
            elif op == '*': return a * b
            elif op == '/': return a / b if b != 0 else "Error: division by zero"
        return None
    
    def run(self, user_input):
        # Update state
        self.conversation_history.append({
            "role": "user",
            "content": user_input
        })
        
        # Decision point: do we need a tool?
        if self.needs_calculation(user_input):
            # Use the calculator tool
            result = self.calculate(user_input)
            response_text = f"The answer is {result}"
            
            # Log what we did (observability)
            print(f"[Agent Decision] Used calculator tool: {result}")
        else:
            # Use the language model
            response = self.client.messages.create(
                model=self.model,
                messages=self.conversation_history,
                max_tokens=1024
            )
            response_text = response.content[0].text
            print(f"[Agent Decision] Used language model")
        
        # Update state with response
        self.conversation_history.append({
            "role": "assistant",
            "content": response_text
        })
        
        return response_text

## Try it out
agent = DecisionAgent()
print(agent.run("What's 156 * 23?"))
print(agent.run("What's the capital of Spain?"))