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52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
"""
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Basic example of scraping pipeline using SmartScraper from text
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"""
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from scrapegraphai.graphs import SmartScraperGraph
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from scrapegraphai.utils import prettify_exec_info
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files = ["inputs/example_1.txt", "inputs/example_2.txt"]
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tasks = ["List me all the projects with their description.",
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"List me all the articles with their description."]
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# ************************************************
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# Define the configuration for the graph
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# ************************************************
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graph_config = {
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"llm": {
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"model": "ollama/mistral",
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"temperature": 0,
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"format": "json", # Ollama needs the format to be specified explicitly
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# "model_tokens": 2000, # set context length arbitrarily
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},
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"embeddings": {
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"model": "ollama/nomic-embed-text",
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"temperature": 0,
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}
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}
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# ************************************************
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# Create the SmartScraperGraph instance and run it
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# ************************************************
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for i in range(0, 2):
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with open(files[i], 'r', encoding="utf-8") as file:
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text = file.read()
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smart_scraper_graph = SmartScraperGraph(
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prompt=tasks[i],
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source=text,
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config=graph_config
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)
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result = smart_scraper_graph.run()
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print(result)
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# ************************************************
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# Get graph execution info
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# ************************************************
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graph_exec_info = smart_scraper_graph.get_execution_info()
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print(prettify_exec_info(graph_exec_info))
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