staneee / miyagi

🪄Sample, showcasing AI-first application architectures and generative AI capabilities with nascent design patterns to embed intelligence. A Hyper-personalized agent powered by SoTA foundation models and event-driven architecture

Project Miyagi - Financial coach

“start with the customer experience and work backwards for the technology” - Steve Jobs

"Systems with AI will replace systems without AI"

Project Miyagi is a showcase of AI-first architecture and user experiences. It serves as a sandbox to explore emerging programming paradigms in generative AI, such as prompt engineering (chain-of-thought, few-shot, in-context), indexing utilities for memory (vector stores, embeddings, conversational memory stores, document loaders), and agents. It also features usage examples of nascent frameworks like Semantic Kernel, LangChain, vector stores (Qdrant, Chroma, Pinecone), SD-InstructPix2Pix, ControlNet, and Foundation Models from Azure OpenAI and Cognitive Services. Utilize this project to gain insights as you modernize and transform your applications with AI and fine-tune your private data to build your own private copilot.

Embedded with intelligence and built on a scalable event-driven architecture, Project Miyagi emphasizes customer-centricity. It challenges you to rethink how AI can elevate and hyper-personalize your customers' experiences, whether in a line-of-business (LOB) or consumer-facing app. It features an easy-to-understand use case that offers concrete examples of how these new AI platforms and architectures, supported by Azure, can be leveraged for valuable insights.

This polyglot codebase relies on a multitude of microservices, choreographing retail and high-frequency trading. It includes generative text and images for personalized financial coaching, summarization, and agent-like orchestration. Built on a cloud-native EDA backbone, the architecture and codebase ensures enterprise-grade quality attributes such as availability, scalability, and maintainability.

Embark on a journey to transform your applications into cutting-edge, intelligent systems with the self-guided workshop and discover the art of the possible.

Work in Progress

Tech Stack

• Azure OpenAI
  • text-davinci-003
  • whisper
  • dall-e
• Semantic Kernel
• LangChain
• Foundation Models from CogServices
• Qdrant
• Chroma
• ControlNet
• Temporal
• DreamFusion

Partial Implementations

Due to the rapid pace of advancements in foundation models, we are incrementally implementing use cases for Miyagi in the experiments folder. So far, we have the following implemented:

1. Knowledge Graph memory using Langchain's entity cache
2. Qdrant vector store for embeddings via Langchain
3. MS Graph API intent invoked via Semantic Kernel's skills
4. Miyagi prompt engineered chat interaction using LangChain's PromptTemplate
5. Azure OpenAI GPT-3.5 basic flow
6. GPT-3.5-turbo and Whisper-1 usage to transcribe audio and demonstrate few-shot example

WIP - Architecture

WIP - Generative image use case architecture with Dreambooth

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [e-mail] with any additional questions or comments.