Azure OpenAI + LLM

A comprehensive, curated collection of resources for Azure OpenAI, Large Language Models (LLMs), and their applications.

🔹Concise Summaries: Each resource is briefly described for quick understanding
🔹Chronological Organization: Resources appended with date (first commit, publication, or paper release)
🔹Active Tracking: Regular updates to capture the latest developments

Tip

A refined list focusing on Azure and Microsoft products.
Check Awesome Azure OpenAI & Copilot.

Quick Navigation

🚀 App & Agent	🌌 Azure	🧠 Research & Survey	🛠️ Tools	📋 Best Practices
1. App & Agent	2. Azure	3. Research & Survey	4. Tools	5. Best Practices

1. App & Agent

🚀 RAG Systems, LLM Applications, Agents, Frameworks & Orchestration

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Key topics:

• RAG: RAG, Advanced RAG, GraphRAG
• Application: AI Application (Agent & Application, No Code & UI, Infrastructure & Backend Services, Caching, Data Processing, Gateway, Memory)
• Agent Protocols: Agent Protocol (MCP, A2A, Computer Use)
• Coding & Research: Coding, Domain-Specific, Deep Research
• Frameworks: Top Agent Frameworks, Orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)

2. Azure OpenAI

🌌 Microsoft's Cloud-Based AI Platform and Services

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Key topics:

• Platform: Azure OpenAI vs OpenAI
• Framework: Microsoft Azure OpenAI LLM Framework
• Copilot: Microsoft Copilot
• Services: Azure AI Services
• Research: Microsoft Research
• Architecture: Reference Architectures
• Prompting: Prompt

3. Research & Survey

🧠 LLM Landscape, Prompt Engineering, Finetuning, Challenges & Surveys

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Key topics:

• Landscape: LLM Landscape, Comparison, Evolutionary Tree, Model Collection
• Prompting: Prompt Engineering & Visual Prompts
• Finetuning: Finetuning, Quantization Techniques, Other Patterns
• Challenges: Context Constraints, Trustworthy, Safe & Secure, Abilities
• Roadmap: OpenAI's Roadmap & Products, AGI & Social Impact
• Survey & Build: Survey, Build from Scratch, Business Use Cases

4. Tools & Resource

🛠️ AI Tools, Training Data, Datasets & Evaluation Methods

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Key topics:

• Tools: General AI Tools & Extensions, LLM for Robotics, Awesome Demo
• Data: Datasets for LLM Training
• Evaluation: Evaluating LLMs & LLMOps, Evaluating LLMs, LLMOps

5. Best Practices

📋 Curated Blogs, Patterns, and Implementation Guidelines

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Key topics:

• RAG: RAG Best Practices, The Problem with RAG, Solution Design, RAG Research
• Agent: Agent Best Practices, Agentic Design Frameworks, Agent Design Patterns
• Tool Use: Tool Use
• Reference: Proposals & Glossary

Legend & Notation

Symbol	Meaning	Symbol	Meaning
✍️	Blog post / Documentation	✨	GitHub repository
🗄️	Archived files	🔗	Cross reference
🗣️	Source citation	📺	Video content
🔢	Citation count	💡🏆	Recommend
📑	Academic paper	🤗	Huggingface

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