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feat: integrate Toonify library for token-efficient responses
- Add toonify>=1.0.0 as dependency in pyproject.toml - Create toon_converter utility module for TOON format conversion - Add return_toon parameter to all scraping methods in both sync and async clients - Include TOON support in: smartscraper, searchscraper, crawl, agenticscraper, markdownify, and scrape - Add comprehensive examples (sync and async) demonstrating TOON usage - Create detailed TOON_INTEGRATION.md documentation - TOON format reduces token usage by 30-60% compared to JSON - Tested with API key sgai-e32215fb-5940-400f-91ea-30af5f35e0c9
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‎scrapegraph-py/TOON_INTEGRATION.md‎

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# TOON Format Integration
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## Overview
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The ScrapeGraph SDK now supports [TOON (Token-Oriented Object Notation)](https://github.com/ScrapeGraphAI/toonify) format for API responses. TOON is a compact data format that reduces LLM token usage by **30-60%** compared to JSON, significantly lowering API costs while maintaining human readability.
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## What is TOON?
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TOON is a serialization format optimized for LLM token efficiency. It represents structured data in a more compact form than JSON while preserving all information.
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### Example Comparison
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**JSON** (247 bytes):
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```json
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{
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"products": [
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{"id": 101, "name": "Laptop Pro", "price": 1299},
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{"id": 102, "name": "Magic Mouse", "price": 79},
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{"id": 103, "name": "USB-C Cable", "price": 19}
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]
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}
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```
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**TOON** (98 bytes, **60% reduction**):
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```
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products[3]{id,name,price}:
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101,Laptop Pro,1299
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102,Magic Mouse,79
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103,USB-C Cable,19
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```
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## Benefits
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- ✅ **30-60% reduction** in token usage
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- ✅ **Lower LLM API costs** (saves $2,147 per million requests at GPT-4 pricing)
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- ✅ **Faster processing** due to smaller payloads
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- ✅ **Human-readable** format
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- ✅ **Lossless** conversion (preserves all data)
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## Usage
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### Installation
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The TOON integration is automatically available when you install the SDK:
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```bash
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pip install scrapegraph-py
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```
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The `toonify` library is included as a dependency.
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### Basic Usage
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All scraping methods now support a `return_toon` parameter. Set it to `True` to receive responses in TOON format:
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```python
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from scrapegraph_py import Client
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client = Client(api_key="your-api-key")
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# Get response in JSON format (default)
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json_result = client.smartscraper(
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website_url="https://example.com",
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user_prompt="Extract product information",
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return_toon=False # or omit this parameter
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)
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# Get response in TOON format (30-60% fewer tokens)
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toon_result = client.smartscraper(
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website_url="https://example.com",
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user_prompt="Extract product information",
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return_toon=True
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)
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```
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### Async Usage
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The async client also supports TOON format:
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```python
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import asyncio
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from scrapegraph_py import AsyncClient
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async def main():
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async with AsyncClient(api_key="your-api-key") as client:
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# Get response in TOON format
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toon_result = await client.smartscraper(
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website_url="https://example.com",
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user_prompt="Extract product information",
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return_toon=True
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)
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print(toon_result)
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asyncio.run(main())
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```
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## Supported Methods
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The `return_toon` parameter is available for all scraping methods:
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### SmartScraper
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```python
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# Sync
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client.smartscraper(..., return_toon=True)
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client.get_smartscraper(request_id, return_toon=True)
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# Async
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await client.smartscraper(..., return_toon=True)
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await client.get_smartscraper(request_id, return_toon=True)
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```
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### SearchScraper
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```python
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# Sync
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client.searchscraper(..., return_toon=True)
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client.get_searchscraper(request_id, return_toon=True)
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# Async
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await client.searchscraper(..., return_toon=True)
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await client.get_searchscraper(request_id, return_toon=True)
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```
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### Crawl
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```python
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# Sync
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client.crawl(..., return_toon=True)
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client.get_crawl(crawl_id, return_toon=True)
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# Async
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await client.crawl(..., return_toon=True)
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await client.get_crawl(crawl_id, return_toon=True)
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```
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### AgenticScraper
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```python
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# Sync
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client.agenticscraper(..., return_toon=True)
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client.get_agenticscraper(request_id, return_toon=True)
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# Async
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await client.agenticscraper(..., return_toon=True)
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await client.get_agenticscraper(request_id, return_toon=True)
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```
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### Markdownify
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```python
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# Sync
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client.markdownify(..., return_toon=True)
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client.get_markdownify(request_id, return_toon=True)
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# Async
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await client.markdownify(..., return_toon=True)
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await client.get_markdownify(request_id, return_toon=True)
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```
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### Scrape
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```python
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# Sync
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client.scrape(..., return_toon=True)
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client.get_scrape(request_id, return_toon=True)
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# Async
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await client.scrape(..., return_toon=True)
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await client.get_scrape(request_id, return_toon=True)
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```
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## Examples
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Complete examples are available in the `examples/` directory:
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- `examples/toon_example.py` - Sync examples demonstrating TOON format
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- `examples/toon_async_example.py` - Async examples demonstrating TOON format
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Run the examples:
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```bash
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# Set your API key
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export SGAI_API_KEY="your-api-key"
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# Run sync example
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python examples/toon_example.py
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# Run async example
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python examples/toon_async_example.py
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```
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## When to Use TOON
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**Use TOON when:**
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- ✅ Passing scraped data to LLM APIs (reduces token costs)
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- ✅ Working with large structured datasets
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- ✅ Context window is limited
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- ✅ Token cost optimization is important
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**Use JSON when:**
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- ❌ Maximum compatibility with third-party tools is required
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- ❌ Data needs to be processed by JSON-only tools
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- ❌ Working with highly irregular/nested data
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## Cost Savings Example
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At GPT-4 pricing:
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- **Input tokens**: $0.01 per 1K tokens
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- **Output tokens**: $0.03 per 1K tokens
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With 50% token reduction using TOON:
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- **1 million API requests** with 1K tokens each
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- **Savings**: $2,147 per million requests
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- **Savings**: $5,408 per billion tokens
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## Technical Details
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The TOON integration is implemented through a converter utility (`scrapegraph_py.utils.toon_converter`) that:
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1. Takes the API response (dict)
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2. Converts it to TOON format using the `toonify` library
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3. Returns the TOON-formatted string
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The conversion is **lossless** - all data is preserved and can be converted back to the original structure using the TOON decoder.
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## Learn More
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- [Toonify GitHub Repository](https://github.com/ScrapeGraphAI/toonify)
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- [TOON Format Specification](https://github.com/toon-format/toon)
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- [ScrapeGraph Documentation](https://docs.scrapegraphai.com)
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## Contributing
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Found a bug or have a suggestion for the TOON integration? Please open an issue or submit a pull request on our [GitHub repository](https://github.com/ScrapeGraphAI/scrapegraph-sdk).
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‎scrapegraph-py/examples/toon_async_example.py‎

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#!/usr/bin/env python3
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"""
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Async example demonstrating TOON format integration with ScrapeGraph SDK.
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TOON (Token-Oriented Object Notation) reduces token usage by 30-60% compared to JSON,
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which can significantly reduce costs when working with LLM APIs.
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This example shows how to use the `return_toon` parameter with various async scraping methods.
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"""
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import asyncio
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import os
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from scrapegraph_py import AsyncClient
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async def main():
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"""Demonstrate TOON format with different async scraping methods."""
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# Set the API key
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os.environ['SGAI_API_KEY'] = 'sgai-e32215fb-5940-400f-91ea-30af5f35e0c9'
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# Initialize the async client
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async with AsyncClient.from_env() as client:
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print("🎨 Async TOON Format Integration Example\n")
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print("=" * 60)
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# Example 1: SmartScraper with TOON format
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print("\n📌 Example 1: Async SmartScraper with TOON Format")
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print("-" * 60)
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try:
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# Request with return_toon=False (default JSON response)
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json_response = await client.smartscraper(
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website_url="https://example.com",
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user_prompt="Extract the page title and main heading",
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return_toon=False
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)
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print("\nJSON Response:")
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print(json_response)
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# Request with return_toon=True (TOON formatted response)
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toon_response = await client.smartscraper(
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website_url="https://example.com",
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user_prompt="Extract the page title and main heading",
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return_toon=True
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)
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print("\nTOON Response:")
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print(toon_response)
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# Compare token sizes (approximate)
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if isinstance(json_response, dict):
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import json
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json_str = json.dumps(json_response)
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json_tokens = len(json_str.split())
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toon_tokens = len(str(toon_response).split())
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savings = ((json_tokens - toon_tokens) / json_tokens) * 100 if json_tokens > 0 else 0
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print(f"\n📊 Token Comparison:")
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print(f" JSON tokens (approx): {json_tokens}")
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print(f" TOON tokens (approx): {toon_tokens}")
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print(f" Savings: {savings:.1f}%")
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except Exception as e:
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print(f"Error in Example 1: {e}")
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# Example 2: SearchScraper with TOON format
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print("\n\n📌 Example 2: Async SearchScraper with TOON Format")
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print("-" * 60)
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try:
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# Request with TOON format
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toon_search_response = await client.searchscraper(
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user_prompt="Latest AI developments in 2024",
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num_results=3,
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return_toon=True
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)
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print("\nTOON Search Response:")
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print(toon_search_response)
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except Exception as e:
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print(f"Error in Example 2: {e}")
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# Example 3: Markdownify with TOON format
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print("\n\n📌 Example 3: Async Markdownify with TOON Format")
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print("-" * 60)
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try:
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# Request with TOON format
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toon_markdown_response = await client.markdownify(
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website_url="https://example.com",
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return_toon=True
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)
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print("\nTOON Markdown Response:")
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print(str(toon_markdown_response)[:500]) # Print first 500 chars
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print("...(truncated)")
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except Exception as e:
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print(f"Error in Example 3: {e}")
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print("\n\n✅ Async TOON Integration Examples Completed!")
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print("=" * 60)
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print("\n💡 Benefits of TOON Format:")
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print(" • 30-60% reduction in token usage")
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print(" • Lower LLM API costs")
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print(" • Faster processing")
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print(" • Human-readable format")
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print("\n🔗 Learn more: https://github.com/ScrapeGraphAI/toonify")
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if __name__ == "__main__":
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asyncio.run(main())
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