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Unlocking Creativity with Azure OpenAI

Unlocking Creativity with Azure OpenAI

By : AMIT MUKHERJEE, Adithya Saladi
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Unlocking Creativity with Azure OpenAI

Unlocking Creativity with Azure OpenAI

By: AMIT MUKHERJEE, Adithya Saladi

Overview of this book

Azure OpenAI, a cutting-edge service by Microsoft, harnesses the power of OpenAI's Large Language Model (LLM) to drive cloud-based innovations within enterprises. This service integrates advanced LLM models into business functions, transforming Microsoft products like GitHub Copilot, Microsoft 365 Copilot, and Bing Chat, making them more advanced and interactive. Azure OpenAI is accessible via REST APIs, Python SDK, or Azure OpenAI Studio, opening doors to build innovative AI applications. This book is a comprehensive guide to build GenAI applications using Azure OpenAI. It begins with the fundamentals, including how to access Azure OpenAI and how to effectively utilize its REST API and Python SDK. It takes a deep dive into various AI models and emphasizes the crucial aspects of prompt engineering and fine-tuning for optimal output. It further underlines the significance of content filters and prevention of misuse, maintaining a strong focus on safety and security protocols and finally the significance of Azure OpenAI Studio in deployment and administration is emphasized. Practical applications are showcased like content generations, summarization, semantic search, code documentation and code generation. Combining Azure Cognitive services amplifies Generative AI potential and finally aligns with Microsoft's ethical AI principles.
Table of Contents (19 chapters)
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1
Part 1: Foundations of Generative AI and Azure OpenAI
5
Part 2: Practical Applications of Azure OpenAI: Real-World Use Cases
13
Part 3: Mastering Governance, Operations, and AI Optimization with Azure OpenAI

Creating a Multimodal Multi-Agent Framework with the Azure OpenAI Assistants API

In this chapter, we will explore how to build a system using the Azure OpenAI Assistants API that allows multiple intelligent agents to work together. These agents use advanced language models to understand and generate natural language, making them capable of performing tasks independently and making decisions on their own.

For example, imagine a team of AI agents collaborating to create and enhance images based on user input. One agent could generate an initial image, another agent could refine the details, and a third agent could adjust the colors and textures. This collaborative process results in high-quality and intricate outputs that a single agent might struggle to achieve alone. This example serves as a comprehensive guide for developers looking to harness the capabilities of multiple AI agents working in concert. It shows how agents can communicate and collaborate to process complex tasks...

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