BrightDataWebScraperAPI

Bright Data provides a powerful Web Scraper API that allows you to extract structured data from 100+ ppular domains, including Amazon product details, LinkedIn profiles, and more, making it particularly useful for AI agents requiring reliable structured web data feeds.

Overview

Integration details

Class	Package	Serializable	JS support	Package latest
BrightDataWebScraperAPI	langchain-brightdata	✅	❌

Tool features

Native async	Returns artifact	Return data	Pricing
❌	❌	Structured data from websites (Amazon products, LinkedIn profiles, etc.)	Requires Bright Data account

Setup

The integration lives in the langchain-brightdata package.

pip install langchain-brightdata

You'll need a Bright Data API key to use this tool. You can set it as an environment variable:

import os

os.environ["BRIGHT_DATA_API_KEY"] = "your-api-key"

Or pass it directly when initializing the tool:

from langchain_brightdata import BrightDataWebScraperAPI

scraper_tool = BrightDataWebScraperAPI(bright_data_api_key="your-api-key")

Instantiation

Here we show how to instantiate an instance of the BrightDataWebScraperAPI tool. This tool allows you to extract structured data from various websites including Amazon product details, LinkedIn profiles, and more using Bright Data's Dataset API.

The tool accepts various parameters during instantiation:

• bright_data_api_key (required, str): Your Bright Data API key for authentication.
• dataset_mapping (optional, Dict[str, str]): A dictionary mapping dataset types to their corresponding Bright Data dataset IDs. The default mapping includes:
  • "amazon_product": "gd_l7q7dkf244hwjntr0"
  • "amazon_product_reviews": "gd_le8e811kzy4ggddlq"
  • "linkedin_person_profile": "gd_l1viktl72bvl7bjuj0"
  • "linkedin_company_profile": "gd_l1vikfnt1wgvvqz95w"

Invocation

Basic Usage

from langchain_brightdata import BrightDataWebScraperAPI

# Initialize the tool
scraper_tool = BrightDataWebScraperAPI(
    bright_data_api_key="your-api-key"  # Optional if set in environment variables
)

# Extract Amazon product data
results = scraper_tool.invoke(
    {"url": "https://www.amazon.com/dp/B08L5TNJHG", "dataset_type": "amazon_product"}
)

print(results)

Advanced Usage with Parameters

from langchain_brightdata import BrightDataWebScraperAPI

# Initialize with default parameters
scraper_tool = BrightDataWebScraperAPI(bright_data_api_key="your-api-key")

# Extract Amazon product data with location-specific pricing
results = scraper_tool.invoke(
    {
        "url": "https://www.amazon.com/dp/B08L5TNJHG",
        "dataset_type": "amazon_product",
        "zipcode": "10001",  # Get pricing for New York City
    }
)

print(results)

# Extract LinkedIn profile data
linkedin_results = scraper_tool.invoke(
    {
        "url": "https://www.linkedin.com/in/satyanadella/",
        "dataset_type": "linkedin_person_profile",
    }
)

print(linkedin_results)

Customization Options

The BrightDataWebScraperAPI tool accepts several parameters for customization:

Parameter	Type	Description
url	str	The URL to extract data from
dataset_type	str	Type of dataset to use (e.g., "amazon_product")
zipcode	str	Optional zipcode for location-specific data

Available Dataset Types

The tool supports the following dataset types for structured data extraction:

Dataset Type	Description
amazon_product	Extract detailed Amazon product data
amazon_product_reviews	Extract Amazon product reviews
linkedin_person_profile	Extract LinkedIn person profile data
linkedin_company_profile	Extract LinkedIn company profile data

Use within an agent

from langchain_brightdata import BrightDataWebScraperAPI
from langchain_google_genai import ChatGoogleGenerativeAI
from langgraph.prebuilt import create_react_agent

# Initialize the LLM
llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", google_api_key="your-api-key")

# Initialize the Bright Data Web Scraper API tool
scraper_tool = BrightDataWebScraperAPI(bright_data_api_key="your-api-key")

# Create the agent with the tool
agent = create_react_agent(llm, [scraper_tool])

# Provide a user query
user_input = "Scrape Amazon product data for https://www.amazon.com/dp/B0D2Q9397Y?th=1 in New York (zipcode 10001)."

# Stream the agent's step-by-step output
for step in agent.stream(
    {"messages": user_input},
    stream_mode="values",
):
    step["messages"][-1].pretty_print()

API Reference:ChatGoogleGenerativeAI | create_react_agent

API reference

• Bright Data API Documentation

Related

• Tool conceptual guide
• Tool how-to guides