Course Presentation | Agent Memory Discord Server
This repository contains companion code and examples for the AI Memory Management in Agentic Systems course.
This is the companion code to the course: AI Memory Management in Agentic Systems
Viewers can access the course to watch the recording of the instructor going through each notebook and explaining the concepts in detail.
| Library/Approach | Notebook | Description |
|---|---|---|
| Information Retrieval | part1/information_retrieval/zero_to_hero_with_genai_with_mongodb_openai.ipynb |
Zero to hero guide using MongoDB and OpenAI for generative AI applications |
| LangMem | part1/langmem/memory_augmented_agent_with_mongodb.ipynb |
Memory-augmented agent implementation using MongoDB |
| Mem0 | part1/mem0/memory_augmented_agent_with_mem0_mongodb.ipynb |
Memory-augmented agent using Mem0 library with MongoDB |
| Memory Bank | part1/memory_bank/memory_augmented_agent_with_local_memory.ipynb |
Memory-augmented agent with local memory implementation |
| MemoRizz | part1/memorizz/memagent_single_agent.ipynb |
Single agent memory implementation with MemoRizz framework |
This repository demonstrates various approaches to implementing memory management in AI agents and agentic systems. It covers:
- Different memory storage backends (MongoDB, local storage)
- Various memory management libraries (LangMem, Mem0, custom implementations)
- Information retrieval techniques for memory-augmented systems
- Practical implementations of memory-enabled AI agents
Each notebook provides hands-on examples and code implementations that complement the theoretical concepts covered in the course, allowing learners to experiment with different memory management strategies in AI systems.
The utilities/ directory contains helper functions including:
pdf_chunker.py- Utilities for processing and chunking PDF documents for memory storage