73db1a5a53
<!-- .github/pull_request_template.md --> ## Description Introducing scructlog. ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin
55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
import os
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import asyncio
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import pathlib
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from cognee.shared.logging_utils import get_logger, ERROR
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import cognee
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from cognee.api.v1.search import SearchType
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# Prerequisites:
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# 1. Copy `.env.template` and rename it to `.env`.
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# 2. Add your OpenAI API key to the `.env` file in the `LLM_API_KEY` field:
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# LLM_API_KEY = "your_key_here"
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async def main():
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# Create a clean slate for cognee -- reset data and system state
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await cognee.prune.prune_data()
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await cognee.prune.prune_system(metadata=True)
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# cognee knowledge graph will be created based on the text
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# and description of these files
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mp3_file_path = os.path.join(
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pathlib.Path(__file__).parent.parent.parent,
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".data/multimedia/text_to_speech.mp3",
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)
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png_file_path = os.path.join(
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pathlib.Path(__file__).parent.parent.parent,
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".data/multimedia/example.png",
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)
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# Add the files, and make it available for cognify
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await cognee.add([mp3_file_path, png_file_path])
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# Use LLMs and cognee to create knowledge graph
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await cognee.cognify()
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# Query cognee for summaries of the data in the multimedia files
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search_results = await cognee.search(
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query_type=SearchType.SUMMARIES,
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query_text="What is in the multimedia files?",
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)
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# Display search results
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for result_text in search_results:
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print(result_text)
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if __name__ == "__main__":
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logger = get_logger(level=ERROR)
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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try:
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loop.run_until_complete(main())
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finally:
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loop.run_until_complete(loop.shutdown_asyncgens())
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