GenAI-Showcase and genai-cookbook
These are competing resources that both provide recipe-based guides for building generative AI applications, with the MongoDB project being significantly more established and comprehensive.
About GenAI-Showcase
mongodb-developer/GenAI-Showcase
GenAI Cookbook
Provides hands-on examples and applications for building RAG systems and AI agents, with MongoDB serving as the vector store, operational database, and memory layer. Includes Jupyter notebooks, production-ready JavaScript/Python apps, and self-paced workshops covering evaluations and industry-specific use cases. Integrates with major GenAI frameworks and partners, with all examples runnable against MongoDB Atlas.
About genai-cookbook
dmatrix/genai-cookbook
A mixture of Gen AI cookbook recipes for Gen AI applications.
Provides hands-on Python notebooks covering prompting strategies, RAG systems, fine-tuning, function calling, and agent architectures across multiple LLM providers (OpenAI, Anthropic, Gemini, Ollama). Includes DSPy framework examples as an alternative to traditional prompt engineering, plus evaluation tooling with MLflow and vector database integrations for semantic search. Targets beginner developers building production LLM applications with practical API examples and multi-model provider support through environment-based configuration.
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