bb679c2dd7
* Update cognify and the networkx client to prepare for running in Neo4j * Fix for openai model * Add the fix to the infra so that the models can be passed to the library. Enable llm_provider to be passed. * Auto graph generation now works with neo4j * Added fixes for both neo4j and networkx * Explicitly name semantic node connections * Added updated docs, readme, chunkers and updates to cognify * Make docs build trigger only when changes on it happen * Update docs, test git actions * Separate cognify logic into tasks * Introduce dspy knowledge graph extraction --------- Co-authored-by: Boris Arzentar <borisarzentar@gmail.com>
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cognee
Deterministic LLMs Outputs for AI Engineers
Open-source framework for loading and structuring LLM context to create accurate and explainable AI solutions using knowledge graphs and vector stores
Let's learn about cogneeHub!
cogneeHub is a free and open-sourced learning platform for those interested in creating deterministic LLM outputs. We help people with using graphs, LLMs and adding vector retrieval to their ML stack.
- Get started — Get started with cognee quickly and try it out for yourself.
- Conceptual Overview — Learn about the core concepts of cognee and how it fits into your projects.
- Data Engineering and LLMOps — Learn about some data engineering and llmops core concepts that will help you build better AI apps.
- RAGs — We provide easy-to-follow learning materials to help you learn about RAGs.
- Research — A list of resources to help you learn more about cognee and LLM memory research
- Blog — A blog where you can read about the latest news and updates about cognee.
- Support — Book time with our team.
Vision
Architecture
Why use cognee?
The question of using cognee is fundamentally a question of why to have deterministic outputs for your llm workflows.
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Cost-effective — cognee extends the capabilities of your LLMs without the need for expensive data processing tools.
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Self-contained — cognee runs as a library and is simple to use
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Interpretable — Navigate graphs instead of embeddings to understand your data.
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User Guided — cognee lets you control your input and provide your own Pydantic data models
License
This project is licensed under the terms of the Apache License 2.0.