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02_Overview_Azure_OpenAI/README.md

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# Overview of Azure OpenAI
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Azure OpenAI is a collaboration between Microsoft Azure and OpenAI, a leading research organization in artificial intelligence. It is a cloud-based platform that enables developers and data scientists to build and deploy AI models quickly and easily. With Azure OpenAI, users can access a wide range of AI tools and technologies to create intelligent applications, including natural language processing, computer vision, and deep learning.
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Azure OpenAI is designed to accelerate the development of AI applications, allowing users to focus on creating innovative solutions that deliver value to their organizations and customers.
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https://microsoft.github.io/PartnerResources/azure/data-analytics-ai/openai
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03_Overview_AI_Concepts/README.md

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# Overview of the following concepts (summaries with reference links):
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- Large Language Models (LLM)
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- Standard patterns (RAG, CoT, ReAct, etc.)
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- Vectorization and vector search
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- What are you trying to solve with finding relevant data through vector search?
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- Prompt engineering
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## Large Language Models (LLM)
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## Standard Patterns
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### RAG
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https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview
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### CoT
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https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/advanced-prompt-engineering?pivots=programming-language-chat-completions#chain-of-thought-prompting
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### ReAct
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### Others?
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https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/advanced-prompt-engineering?pivots=programming-language-chat-completions#provide-grounding-context
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## Vectorization and Vector Search
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What are you trying to solve with finding relevant data through vector?
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## Prompt Engineering
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https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/prompt-engineering
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https://learn.microsoft.com/en-us/semantic-kernel/prompt-engineering/

06_Explore_OpenAI_models/README.md

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# Explore the Azure OpenAI models and endpoints (console app)
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- Selecting an LLM
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- Explore and use models from code
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- Completions
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- Chat completions
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- Do I use an out-of-the-box model or a fine-tuned model?
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- Use the embeddings model to vectorize data
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## Selecting an LLM
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https://learn.microsoft.com/en-us/semantic-kernel/prompt-engineering/llm-models
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## Explore and use models from code
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- Completions
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- Chat completions
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## Do I use an out-of-the-box model or a fine-tuned model?
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## Use the embeddings model to vectorize data

09_Chatbot_API/README.md

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# Complete the chatbot API
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- Select an orchestration framework
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- Update the starter project to implement the Azure Cosmos DB for MongoDB database for chat history
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- Implement Azure OpenAI for embeddings and completions
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## Select an orchestration framework
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## Update the starter project to implement the Azure Cosmos DB for MongoDB database for chat history
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## Implement Azure OpenAI for embeddings and completions

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