Strands Agents is an open-source Python library that provides a unified toolkit for developing autonomous AI agents. It bridges the gap between large language models and practical applications by offering ready-to-use tools for file operations, system execution, API interactions, mathematical operations, and more.

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Steps to Get Started

1

Prerequisites

  • Bright Data API Key
  • Python 3.10+
2

Installation

Set up the strands-agents-tools package by either using the quick pip install or the full development installation with virtual environment and pre-commit hooks.
Quick Install
pip install strands-agents-tools
3

Set the environment variable

Set your Bright Data API key and unlocker zone as an environment variables:
export BRIGHT_DATA_API_KEY="your_api_key_here"
export BRIGHT_DATA_ZONE="your_unlocker_zone_here"
4

Bright Data Usage Examples

from strands import Agent
from strands.models.litellm import LiteLLMModel
import strands_tools.bright_data as bright_data
import os
from dotenv import load_dotenv


load_dotenv()


def main():
load_dotenv()
print("🔍 Testing Bright Data Tool with OpenAI GPT-4o via LiteLLM")
print("=" * 50)

# Configure OpenAI model via LiteLLM
openai_model = LiteLLMModel(
    client_args={
        "api_key": os.getenv("OPENAI_API_KEY"), 
    },
    model_id="openai/gpt-4o",
)

# Create agent with LiteLLM model and bright_data tool
agent = Agent(
    model=openai_model,
    tools=[bright_data],
    system_prompt="you are a helpful Web Search assistant, whenever user asks you to search the web you will use avilable tools, always set zone name to 'unlocker'"
)

# Test the bright_data tool with a relevant query
print("Testing web scraping...")
result = agent("Please scrape the content from https://example.com and return it as markdown")
print(f'\n\nScraping Result:\n{result}')

print("\n" + "=" * 50)
print("Testing web search...")
result2 = agent("Please search Google for 'Python programming tutorials")
print(f'\n\nSearch Result:\n{result2}')


if __name__ == "__main__":
main()