Speeding Up the Agent › Parallel Tool Calls

import time
import asyncio
import os
from anthropic import Anthropic

## Simulated tool functions
def get_weather(city):
    """Simulate weather API call."""
    time.sleep(1)  # Simulate network delay
    return f"Weather in {city}: Sunny, 72°F"

def get_news(topic):
    """Simulate news API call."""
    time.sleep(1)  # Simulate network delay
    return f"Latest news on {topic}: [News headlines...]"

def get_stock_price(symbol):
    """Simulate stock API call."""
    time.sleep(1)  # Simulate network delay
    return f"Stock price for {symbol}: $150.25"

## Sequential execution (slow)
def sequential_tools():
    """Call tools one after another."""
    start = time.time()
    
    weather = get_weather("San Francisco")
    news = get_news("technology")
    stock = get_stock_price("AAPL")
    
    elapsed = time.time() - start
    print(f"Sequential execution: {elapsed:.2f}s")
    return weather, news, stock

## Parallel execution (fast)
async def parallel_tools():
    """Call tools simultaneously."""
    start = time.time()
    
    # Run all tools in parallel
    weather_task = asyncio.to_thread(get_weather, "San Francisco")
    news_task = asyncio.to_thread(get_news, "technology")
    stock_task = asyncio.to_thread(get_stock_price, "AAPL")
    
    # Wait for all to complete
    weather, news, stock = await asyncio.gather(
        weather_task, news_task, stock_task
    )
    
    elapsed = time.time() - start
    print(f"Parallel execution: {elapsed:.2f}s")
    return weather, news, stock

## Compare the approaches
print("Testing sequential execution:")
sequential_tools()

print("\nTesting parallel execution:")
await parallel_tools()