wehub-resource-sync
32 lines
647 B
Markdown
32 lines
647 B
Markdown
# Search Graph Example
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This example shows how to implement a search graph for web content retrieval and analysis using Scrapegraph-ai.
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## Features
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- Web search integration
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- Content relevance scoring
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- Result filtering
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- Data aggregation
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## Setup
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1. Install required dependencies
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2. Copy `.env.example` to `.env`
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3. Configure your API keys in the `.env` file
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## Usage
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```python
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from scrapegraphai.graphs import SearchGraph
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graph = SearchGraph()
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results = graph.search("your search query")
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```
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## Environment Variables
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Required environment variables:
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- `OPENAI_API_KEY`: Your OpenAI API key
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- `SERP_API_KEY`: Your SERP API key (optional)
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