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86 lines
2.0 KiB
Markdown
86 lines
2.0 KiB
Markdown
---
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title: cognee
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---
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# cognee
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[cognee](https://www.cognee.ai) is a memory management tool for AI Apps and Agents
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Qdrant is available as a native built-in vector database to store and retrieve embeddings.
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## 📦 Installation
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You can install Cognee using either **pip**, **poetry**, **uv** or any other python package manager.
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Cognee supports Python 3.8 to 3.12
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### With pip
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```bash
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pip install cognee
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```
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## Local Cognee installation
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You can install the local Cognee repo using **pip**, **poetry** and **uv**.
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For local pip installation please make sure your pip version is above version 21.3.
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### with UV with all optional dependencies
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```bash
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uv sync --all-extras
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```
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## 💻 Basic Usage
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### Setup
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```
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import os
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os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"
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VECTOR_DB_PROVIDER="qdrant"
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VECTOR_DB_URL=https://url-to-your-qdrant-cloud-instance.cloud.qdrant.io:6333
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VECTOR_DB_KEY=your-qdrant-api-key
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```
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You can also set the variables by creating .env file, using our <a href="https://github.com/topoteretes/cognee/blob/main/.env.template">template.</a>
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To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai">documentation</a>
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### Simple example
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This script will run the default pipeline:
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```python
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import cognee
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import asyncio
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async def main():
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# Add text to cognee
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await cognee.add("Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.")
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# Generate the knowledge graph
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await cognee.cognify()
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# Query the knowledge graph
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results = await cognee.search("Tell me about NLP")
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# Display the results
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for result in results:
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print(result)
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if __name__ == '__main__':
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asyncio.run(main())
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```
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Example output:
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```
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Natural Language Processing (NLP) is a cross-disciplinary and interdisciplinary field that involves computer science and information retrieval. It focuses on the interaction between computers and human language, enabling machines to understand and process natural language.
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```
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