Awesome 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)
🔹Monthly Updates: The list is updated monthly; candidate entries before the update are tracked in the issue.

🧭 Quick Navigation (Propedia-style)

Layer / Era	What it controls	Jump to sections
Weights 2022-2023	Parametric knowledge baked into the model. Themes: Pretraining, Scaling Laws, Fine-tuning, RLHF, Alignment, Instruction-following, Few-shot	Foundations: Landscape, Comparison, Evolutionary Tree, LLM Collection Training: Finetuning, Other Techniques and LLM Patterns, Training & Fine-tuning Behavior and safety: Trustworthy, Safe and Secure LLM, Abilities, Reasoning, Orchestration Frameworks
Context 2023-2024	What the model sees at inference time. Themes: Prompting, Chain-of-Thought, RAG, Memory, Long Context, Knowledge Injection, Context Engineering	Prompting: Prompt Engineering and Visual Prompts, Prompt Engineering & Tooling Retrieval: RAG, Advanced RAG, GraphRAG, RAG Application, Vector Database & Embedding, Azure AI Search Memory and context windows: Memory, Context Constraints, Caching, RAG Solution Design, RAG Research
Harness 2025-2026	How the agent acts in the real world. Themes: Function Calling, Tool Ecosystems, MCP, Skills, Workflow Graphs, Multi-agent, A2A protocols, Orchestration, Agent Infrastructure, Security	Agent runtime: Top Agent Frameworks, Orchestration Framework, Frameworks / SDKs, Agent Frameworks, Agent Development Protocols and tools: Model Context Protocol (MCP), A2A, Computer use, Skill, Harness, Dev Tools, MCP & Extensions, Coding Ops and governance: Apps / Ready-to-use Agents, General AI Tools and Extensions, Evaluating Large Language Models, LLM Evalution Benchmarks, LLMOps, Agent Design Patterns, Agent Research, Reflection, Tool Use, Planning and Multi-agent collaboration, Proposals & Glossary

Refereces: DailyDoseOfDS - Evolution of the Agent Landscape

1. App & Agent

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

• RAG
  • RAG
  • Advanced RAG
  • GraphRAG
  • RAG Application
  • Vector Database & Embedding
• Application
  • Top Agent Frameworks
  • Orchestration Framework
  • Frameworks / SDKs
  • Apps / Ready-to-use Agents
  • Popular LLM Applications (Ranked by GitHub star count ≥1000)
  • No Code & User Interface
  • Personal AI assistant & desktop
  • Caching
  • Data Processing
  • Gateway
  • Memory
• Agent Protocols
  • MCP
  • A2A
  • Computer use
• Coding & Research
  • Coding
  • Skill / Harness
  • Domain-Specific Agents
  • Deep Research

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2. Azure OpenAI & Copilot

🌌 Microsoft's Cloud-Based AI Platform and Services

• Overview
  • Azure OpenAI & Foundry Overview
• Frameworks
  • Orchestration Frameworks
  • Agent Frameworks
• Tooling
  • Prompt Engineering & Tooling
  • Dev Tools, MCP & Extensions
• Products
  • Copilot Product Catalog
  • Agent Development
  • Microsoft 365 Agent Development
• Services
  • Azure AI Search
  • Microsoft Foundry & AI Services
• Research
  • Microsoft Research
• Applications
  • Sample Applications
  • Solution Accelerators
  • Architecture Patterns & Use Cases

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3. Research & Survey

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

• Landscape
  • Large Language Model: Landscape
  • Comparison
  • Evolutionary Tree
  • LLM Collection
• Prompting
  • Prompt Engineering and Visual Prompts
• Finetuning
  • Pre-training and Post-training
  • Other Techniques and LLM Patterns
• Challenges
  • Context Constraints
  • Trustworthy, Safe and Secure LLM
  • Large Language Model's Abilities
  • Reasoning
• Products & Impact
  • OpenAI Roadmap
  • OpenAI Models
  • OpenAI Products
  • Anthropic Products
  • Google AI Products
  • AGI Discussion and Social Impact
• Survey & Build
  • Survey on Large Language Models
  • Additional Topics: A Survey of LLMs
  • LLM Research (Ranked by cite count ≥150)
  • Build an LLMs from Scratch
  • Business Use Cases

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4. Tools, Datasets, and Evaluation

🛠️ AI Tools, Training Data, Datasets & Evaluation Methods

• Tools
  • General AI Tools and Extensions
  • LLM for Robotics
  • Awesome Demo
• Data
  • Datasets for LLM Training
• Evaluation
  • Evaluating Large Language Models
  • LLM Evalution Benchmarks
  • LLMOps: Large Language Model Operations

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5. Best Practices

📋 Curated Blogs, Patterns, and Implementation Guidelines

• RAG
  • The Problem with RAG
  • RAG Solution Design
  • RAG Research
  • RAG Research (Ranked by cite count >=100)
• Agent
  • Agent Design Patterns
  • Agent Research
  • Agent Research (Ranked by cite count >=100)
  • Reflection, Tool Use, Planning and Multi-agent collaboration
  • Tool Use: LLM to Master APIs
• Reference
  • Proposals & Glossary

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📖 Legend & Notation

Symbol	Meaning	Symbol	Meaning
✍️	Blog post / Documentation		GitHub repository
🗄️	Archived files	💡🏆	Recommend
🗣️	Source citation	📺	Video content
📑	Academic paper	🤗	Huggingface

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