docs: update README simple example

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lxobr 2024-11-05 10:05:43 +01:00
parent 17d4aca538
commit 6c395d7d7f

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@ -96,24 +96,40 @@ DB_PASSWORD=cognee
### Simple example
Run the default cognee pipeline:
First, copy `.env.template` to `.env` and add your OpenAI API key to the LLM_API_KEY field.
```
Optionally, set `VECTOR_DB_PROVIDER="lancedb"` in `.env` to simplify setup.
This script will run the default pipeline:
```python
import cognee
import asyncio
from cognee.api.v1.search import SearchType
text = """Natural language processing (NLP) is an interdisciplinary
subfield of computer science and information retrieval"""
async def main():
await cognee.prune.prune_data() # Reset cognee data
await cognee.prune.prune_system(metadata=True) # Reset cognee system state
await cognee.add(text) # Add a new piece of information
text = """
Natural language processing (NLP) is an interdisciplinary
subfield of computer science and information retrieval.
"""
await cognee.cognify() # Use LLMs and cognee to create a knowledge graph
await cognee.add(text) # Add text to cognee
await cognee.cognify() # Use LLMs and cognee to create knowledge graph
search_results = await cognee.search("INSIGHTS", {'query': 'NLP'}) # Query cognee for the insights
search_results = await cognee.search( # Search cognee for insights
SearchType.INSIGHTS,
{'query': 'Tell me about NLP'}
)
for result in search_results:
do_something_with_result(result)
for result_text in search_results: # Display results
print(result_text)
asyncio.run(main())
```
A version of this example is here: `examples/pyton/simple_example.py`
### Create your own memory store