129 lines
3.4 KiB
Markdown
129 lines
3.4 KiB
Markdown
# cognee
|
|
|
|
Make data processing for LLMs easy
|
|
|
|
|
|
<p>
|
|
<a href="https://cognee.ai" target="_blank">
|
|
<img src="assets/cognee-logo.png" width="160px" alt="Cognee logo" />
|
|
</a>
|
|
</p>
|
|
|
|
<p>
|
|
<i>Open-source framework for creating knowledge graphs and data models for LLMs.</i>
|
|
</p>
|
|
|
|
<p>
|
|
<a href="https://github.com/topoteretes/cognee/fork">
|
|
<img src="https://img.shields.io/github/forks/topoteretes/cognee?style=for-the-badge" alt="cognee forks"/>
|
|
</a>
|
|
<a href="https://github.com/topoteretes/cognee/stargazers">
|
|
<img src="https://img.shields.io/github/stars/topoteretes/cognee?style=for-the-badge" alt="cognee stars"/>
|
|
</a>
|
|
<a href="https://github.com/topoteretes/cognee/pulls">
|
|
<img src="https://img.shields.io/github/issues-pr/topoteretes/cognee?style=for-the-badge" alt="cognee pull-requests"/>
|
|
</a>
|
|
<a href="https://github.com/topoteretes/cognee/releases">
|
|
<img src="https://img.shields.io/github/release/topoteretes/cognee?&label=Latest&style=for-the-badge" alt="cognee releases" />
|
|
</a>
|
|
</p>
|
|
|
|
|
|
## 🚀 It's alive
|
|
|
|
<p>
|
|
Try it yourself on Whatsapp with one of our <a href="https://keepi.ai" target="_blank">partners</a> by typing `/save {content you want to save}` followed by `/query {knowledge you saved previously}`
|
|
For more info here are the <a href="https://topoteretes.github.io/cognee">docs</a>
|
|
</p>
|
|
|
|
|
|
## 📦 Installation
|
|
|
|
With pip:
|
|
|
|
```bash
|
|
pip install "cognee[weaviate]"
|
|
```
|
|
|
|
With poetry:
|
|
|
|
```bash
|
|
poetry add "cognee[weaviate]"
|
|
```
|
|
|
|
## 💻 Usage
|
|
|
|
### Setup
|
|
|
|
```
|
|
import os
|
|
|
|
os.environ["WEAVIATE_URL"] = "YOUR_WEAVIATE_URL"
|
|
os.environ["WEAVIATE_API_KEY"] = "YOUR_WEAVIATE_API_KEY"
|
|
|
|
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
|
|
|
|
```
|
|
|
|
### Run
|
|
|
|
```
|
|
import cognee
|
|
|
|
text = """Natural language processing (NLP) is an interdisciplinary
|
|
subfield of computer science and information retrieval"""
|
|
|
|
cognee.add(text) # Add a new piece of information
|
|
|
|
cognee.cognify() # Use LLMs and cognee to create knowledge
|
|
|
|
search_results = cognee.search("SIMILARITY", "computer science") # Query cognee for the knowledge
|
|
|
|
for result_text in search_results[0]:
|
|
print(result_text)
|
|
|
|
```
|
|
Add alternative data types:
|
|
```
|
|
cognee.add("file://{absolute_path_to_file}", dataset_name)
|
|
```
|
|
Or
|
|
```
|
|
cognee.add("data://{absolute_path_to_directory}", dataset_name)
|
|
|
|
# This is useful if you have a directory with files organized in subdirectories.
|
|
# You can target which directory to add by providing dataset_name.
|
|
# Example:
|
|
# root
|
|
# / \
|
|
# reports bills
|
|
# / \
|
|
# 2024 2023
|
|
#
|
|
# cognee.add("data://{absolute_path_to_root}", "reports.2024")
|
|
# This will add just directory 2024 under reports.
|
|
```
|
|
|
|
Read more [here](docs/index.md#run).
|
|
|
|
## Demo
|
|
|
|
Check out our demo notebook [here](https://github.com/topoteretes/cognee/blob/main/notebooks/cognee%20-%20Get%20Started.ipynb)
|
|
|
|
|
|
## Architecture
|
|
|
|
[<img src="https://i3.ytimg.com/vi/-ARUfIzhzC4/maxresdefault.jpg" width="100%">](https://youtu.be/-ARUfIzhzC4 "Learn about cognee: 55")
|
|
|
|
|
|
### How Cognee Enhances Your Contextual Memory
|
|
|
|
Our framework for the OpenAI, Graph (Neo4j) and Vector (Weaviate) databases introduces three key enhancements:
|
|
|
|
- Query Classifiers: Navigate information graph using Pydantic OpenAI classifiers.
|
|
- Document Topology: Structure and store documents in public and private domains.
|
|
- Personalized Context: Provide a context object to the LLM for a better response.
|
|
|
|
|
|
|
|
|