feat: add simple python example

This commit is contained in:
lxobr 2024-11-05 10:05:14 +01:00
parent cc77d844b6
commit 17d4aca538

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import cognee
import asyncio
from cognee.api.v1.search import SearchType
# Prerequisites:
# 1. Copy `.env.template` and rename it to `.env`.
# 2. Add your OpenAI API key to the `.env` file in the `LLM_API_KEY` field:
# LLM_API_KEY = "your_key_here"
# 3. (Optional) To minimize setup effort, set `VECTOR_DB_PROVIDER="lancedb"` in `.env".
async def main():
# Create a clean slate for cognee -- reset data and system state
await cognee.prune.prune_data()
await cognee.prune.prune_system(metadata=True)
# cognee knowledge graph will be created based on this text
text = """
Natural language processing (NLP) is an interdisciplinary
subfield of computer science and information retrieval.
"""
# Add the text, and make it available for cognify
await cognee.add(text)
# Use LLMs and cognee to create knowledge graph
await cognee.cognify()
# Query cognee for insights on the added text
search_results = await cognee.search(
SearchType.INSIGHTS,
{'query': 'Tell me about NLP'}
)
# Display search results
for result_text in search_results:
print(result_text)
if __name__ == '__main__':
asyncio.run(main())