Azure-Samples/miyagi

• highreadme#1

  Reposition the README's opening paragraph to correct miscategorization

  原因：

  当前

  Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

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  复制

  Project Miyagi is an envisioning workshop and comprehensive sample demonstrating how to design, develop, and deploy enterprise-grade intelligent applications using Microsoft's Copilot Stack. It provides practical guidance and examples for building AI-infused product experiences, exploring both generative and traditional ML use cases. This workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

  待办完成忽略
• mediumreadme#2

  Add a sentence to differentiate Miyagi from standalone AI frameworks

  原因：

  复制粘贴的修复

  复制

  Unlike standalone AI frameworks, Miyagi provides an end-to-end solution sample and architectural guidance for integrating technologies like Semantic Kernel, Promptflow, LlamaIndex, and LangChain into enterprise applications.

  待办完成忽略
• lowlicense#3

  Clarify the project's license in the README

  原因：

  复制粘贴的修复

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  ## License
  This project is licensed under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details on the applicable licenses.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to build enterprise-grade intelligent applications using generative AI and agents?

  你：未被推荐
  AI 推荐顺序：

  1. LangChain
  2. LlamaIndex
  3. OpenAI API
  4. Azure OpenAI Service
  5. Hugging Face Transformers
  6. Pinecone
  7. Weaviate
  8. Kubernetes
  9. MLflow

  AI 推荐了 9 个替代方案，却始终没点名 Azure-Samples/miyagi。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking frameworks for advanced prompt engineering, RAG, and LLM agent orchestration.

  你：未被推荐
  AI 推荐顺序：

  1. LangChain (langchain-ai/langchain)
  2. LlamaIndex (run-llama/llama_index)
  3. Haystack (deepset-ai/haystack)
  4. AutoGen (microsoft/autogen)
  5. DSPy (stanfordnlp/dspy)
  6. Magentic (jacksmith15/magentic)
  7. OpenAI Assistants API

  AI 推荐了 7 个替代方案，却始终没点名 Azure-Samples/miyagi。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of Azure-Samples/miyagi?

  pass
  ✓AI 明确点名了 Azure-Samples/miyagi

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts Azure-Samples/miyagi in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 Azure-Samples/miyagi

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo Azure-Samples/miyagi solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 Azure-Samples/miyagi

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？