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Resources on Cognee, Semantic Memory, and GraphRAG

This document provides a structured overview of key resources covering cognee, semantic memory, and GraphRAG, categorized by beginner, intermediate, and advanced levels. These resources include documentation, research papers, blog posts, community discussions, and industry reports.

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📌 Beginner Resources

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1. Cognee Documentation

📄 Entry point to understand how cognee works with quick tutorials, core concepts, how-to guides, and integration guidelines. 🔗 Read here

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2. Sample Use Cases

📄 Introduction to real-world examples of how cognee is used. 🔗 Read here

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3. Case Study with Dynamo.fyi

📝 A real-life example showcasing how cognee significantly improved answer relevancy. 🔗 Read here

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4. Intro to LLM Memory

📝 Explaining what AI memory is and how it is used with LLMs. 🔗 Read here

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5. AI Memory in Claude Desktop

🎥 Showing how cognee is used as a memory system in the Claude Desktop App. 🔗 Watch here

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6. Cognee GraphRAG in 4 Minutes + Visualization

🎥 Quick guide to building a GraphRAG solution with cognee. 🔗 Watch here

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7. Interactive Notebooks for Hands-on Learning

📓 Hands-on resources for working with cognee’s tasks, building code graphs, and querying with advanced techniques.

• Cognee Notebooks Collection
• Code Graph Pipeline Colab Notebook
• Demo with Cognee Tasks Colab Notebook
• Cognee GraphRAG Simple Example

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📌 Intermediate Resources

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8. Cognitive Architectures for Language Agents

📝 Defining cognitive architecture based on an impactful paper (CoALA) and how cognee builds on it. 🔗 Read here

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9. Cognee GraphRAG

📝 Explaining cognee’s GraphRAG approach where it merges graph and vector stores for advanced retrieval and querying. 🔗 Read here

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10. Building Knowledge Graphs & Deploying

🎥 Explanation of how graphs are connected to LLMs and deployed. 🔗 Watch here

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11. Memory as a Key Component of LLM-Powered Autonomous Agents

📝 Developer-friendly yet conceptually rigorous insights into semantic memory and long-term AI memory structures. 🔗 Read here

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12. Microsoft GraphRAG Project

📚 Overview of GraphRAG by Microsoft, detailing its benefits and implementation. 🔗 Read here

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13. Descriptive Graph Metrics

🎥 Exploration of cognee’s graph metrics for evaluating generated knowledge graphs. 🔗 Watch here

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14. Cognee Evaluation Framework

📄 Overview of how evaluation is structured at cognee, including sample results. 🔗 Read here

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15. Community & Industry Discussions on GraphRAG

💬 Conversations from Hacker News and Reddit showcasing industry and developer interest in GraphRAG.

• Hacker News Discussion on GraphRAG
• GraphRAG Discussion on Reddit

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📌 Advanced Resources

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16. Knowledge Graphs with Ontology

📝 Showing how ontology integration enhances knowledge graphs and their retrieval capabilities. 🔗 Read here

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17. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

📄 The foundational NeurIPS 2020 paper introducing the RAG paradigm. 🔗 Read here

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18. From Local to Global: A GraphRAG Approach to Query-Focused Summarization

📄 Microsoft’s primary research paper underpinning GraphRAG and its applications. 🔗 Read here

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19. Long-Term Memory: The Foundation of AI Self-Evolution

📄 Exploring how AI models could develop cognitive abilities and build internal representations. 🔗 Read here

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20. Personalized Graph-Based Retrieval for Large Language Models

📄 Demonstrates the real-world advantages of graph-based retrieval over purely vector-based solutions. 🔗 Read here

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21. Memory, Consciousness, and Large Language Models

📄 Proposing a “duality” between Tulving’s theory of human memory and the memory mechanisms of LLMs. 🔗 Read here

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22. Hugging Face GraphRAG Paper Collection

📚 A collection of research papers on GraphRAG curated by Hugging Face. 🔗 Read here