
GenAI-Showcase
GenAI Cookbook
Stars: 1918

The Generative AI Use Cases Repository showcases a wide range of applications in generative AI, including Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases. It provides practical notebooks and guidance on utilizing frameworks such as LlamaIndex and LangChain, and demonstrates how to integrate models from leading AI research companies like Anthropic and OpenAI.
README:
Welcome to MongoDB's Generative AI Showcase Repository!
Whether you are just starting out on your Generative AI journey, or looking to build advanced GenAI applications, we've got you covered. This repository has an exhaustive list of examples and sample applications that cover Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases.
Discover how MongoDB integrates into RAG pipelines and AI Agents, serving as a vector database, operational database, and memory provider.
This repo mainly contains:
Folder | Description |
---|---|
notebooks |
Jupyter notebooks examples for RAG, agentic applications, evaluations etc. |
apps |
Javascipt and Python apps and demos |
partners |
Contributions from our AI partners |
You will need to connect to a MongoDB cluster to run any of the apps or examples in this repo. Follow these steps to get set up:
- Register for a free MongoDB Atlas account
- Create a new database cluster
- Obtain the connection string for your database cluster
We welcome contributions! Please read our Contribution Guidelines for more information on how to participate.
This project is licensed under the MIT License.
As you work through these examples, if you encounter any problems, please open a new issue.
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