Create scrapegraphtool.mdx integration

[VinciGit00]

No description provided.

[joaomdmoura]

Disclaimer: This review was made by a crew of AI Agents.

Code Review Comment for scrapegraphtool.mdx

Overall Assessment

The new documentation file introduces the ScrapegraphScrapeTool effectively, detailing installation, usage, and configuration. It's structured well but could benefit from several enhancements to improve clarity and completeness.

Strengths

• Clear Organization: The sections are logically arranged, making navigation straightforward.
• Practical Examples: The inclusion of example code aids understanding.
• Comprehensive Arguments Table: It covers all necessary parameters thoroughly.
• Error Handling Documentation: Good details on error management are provided.
• Transparent Pricing Information: Clear pricing outlines remove ambiguity for users.

Issues and Suggested Improvements

1. Metadata Section

The current metadata lacks certain details. For improved discoverability, consider adding fields such as category, sidebar_position, and tags:

---
title: Scrapegraph AI Scraper
description: The ScrapegraphScrapeTool uses AI to transform any website into clean, structured data.
icon: spider
category: Tools
sidebar_position: 1
tags: ['scraping', 'ai', 'data-extraction']
---

2. Installation Section

The installation instructions currently omit version pinning. This can lead to compatibility issues in the future. A suggestion is:

pip install "scrapegraph-py>=1.0.0,<2.0.0" "crewai[tools]>=1.0.0,<2.0.0"

3. Example Code Improvements

The example code can be enhanced for better clarity and error handling. Consider the following modifications:

from crewai import Agent, Crew, Task
from crewai_tools import ScrapegraphScrapeTool
from typing import Dict, Any
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

def create_scraping_crew(target_url: str) -> Dict[str, Any]:
    """
    Creates and configures a CrewAI setup for web scraping.
    
    Args:
        target_url: The URL to scrape
    Returns:
        Dict containing the scraping results
    """
    try:
        tool = ScrapegraphScrapeTool(
            website_url=target_url,
            enable_logging=True
        )
    except ValueError as e:
        raise ValueError(f"Failed to initialize ScrapegraphScrapeTool: {e}")

    agent = Agent(
        role="Web Research Specialist",
        goal="Extract and structure web data with high accuracy",
        backstory="""You are an expert web researcher with extensive experience 
        in data extraction and analysis. You specialize in converting 
        unstructured web content into meaningful data.""",
        tools=[tool],
        verbose=True
    )

    task = Task(
        name="Web Content Extraction",
        description=f"""
        1. Visit {target_url}
        2. Extract all relevant product information
        3. Ensure data is properly structured
        4. Validate extracted content
        """,
        expected_output="A JSON object containing structured product data",
        agent=agent,
    )

    return Crew(
        agents=[agent],
        tasks=[task],
        verbose=True
    ).kickoff()

if __name__ == "__main__":
    website = "https://www.ebay.it/sch/i.html?_nkw=keyboard"
    results = create_scraping_crew(website)

4. More Specific Error Handling Section

Enhance the error handling section with specific exceptions to guide users more effectively:

try:
    tool = ScrapegraphScrapeTool()
    result = tool.scrape("https://example.com")
except ValueError as e:
    print(f"Configuration error: {e}")
except RateLimitError as e:
    print(f"Rate limit exceeded: {e}. Retry after {e.retry_after} seconds")
except RuntimeError as e:
    print(f"Scraping failed: {e}")

5. Additional Recommendations

• Best Practices Section:

## Best Practices

- Always implement rate limiting in production environments.
- Cache results where feasible to minimize repeated requests.
- Handle pagination efficiently for large datasets.
- Implement thorough error handling.
- Monitor API usage to avoid reaching limits.

• Troubleshooting Section:

## Troubleshooting

Common issues and their solutions:
1. API Key Issues: Ensure SCRAPEGRAPH_API_KEY is set correctly.
2. Rate Limits: Use exponential backoff techniques.
3. Timeout Errors: Adjust request timeouts appropriately.
4. Invalid URLs: Always validate URLs prior to scraping.

• Version Compatibility Matrix:

## Version Compatibility

| ScrapegraphScrapeTool Version | CrewAI Version | Python Version |
|:------------------------------|:---------------|:---------------|
| 1.0.x                         | >=0.x.x        | >=3.8         |
| 1.1.x                         | >=1.x.x        | >=3.9         |

6. Code Style and Documentation Standards

• Maintain consistent heading levels throughout all sections for better readability.
• Include type hints for all functions to improve code clarity and facilitate type checking.
• Provide docstrings for all functions to explain their purpose and usage.
• Add inline comments to elaborate on complex operations to assist future maintainers.

Implementing these enhancements will lead to clearer, more maintainable, and user-friendly documentation, aligning with best practices for technical writing.

[bhancockio]

@VinciGit00 we are creating a crewai community tools repository where we plan on placing tools until they become widely adopted (~5k followers on LinkedIn).

I will be sharing more information once we create the new repo, but I wanted to give you a heads up because the tool and documentation for the tool will all need to move over.