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docs: fixed speechgraphexample
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README.md
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README.md
@ -8,7 +8,8 @@
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[](https://discord.gg/gkxQDAjfeX)
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ScrapeGraphAI is a *web scraping* python library that uses LLM and direct graph logic to create scraping pipelines for websites, documents and XML files.
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ScrapeGraphAI is a *web scraping* python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, etc.).
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Just say which information you want to extract and the library will do it for you!
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<p align="center">
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@ -136,26 +137,34 @@ The output will be a list of recipes like the following:
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You just need to pass the OpenAI API key and the model name.
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```python
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from scrapegraphai.graphs import SmartScraperGraph
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from scrapegraphai.graphs import SpeechGraph
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# Define the configuration for the graph
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graph_config = {
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"llm": {
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"api_key": "OPENAI_API_KEY",
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"model": "gpt-3.5-turbo",
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},
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"tts_model": {
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"api_key": "OPENAI_API_KEY",
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"model": "tts-1",
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"voice": "alloy"
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},
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"output_path": "audio_summary.mp3",
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}
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# Create the SmartScraperGraph instance
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smart_scraper_graph = SmartScraperGraph(
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prompt="Make a detailed audio summary of the projects on this page",
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source="https://perinim.github.io/projects",
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config=graph_config
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# ************************************************
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# Create the SpeechGraph instance and run it
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# ************************************************
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speech_graph = SpeechGraph(
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prompt="Make a detailed audio summary of the projects.",
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source="https://perinim.github.io/projects/",
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config=graph_config,
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)
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# Run the graph
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result = smart_scraper_graph.run()
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result = speech_graph.run()
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print(result)
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```
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The output will be an audio file with the summary of the projects on the page.
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