Awesome Azure Openai Llm Overview

A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.

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Awesome Azure OpenAI + LLM

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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

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2. Azure OpenAI & Copilot

🌌 Microsoft's Cloud-Based AI Platform and Services

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3. Research & Survey

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

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4. Tools, Datasets, and Evaluation

🛠️ AI Tools, Training Data, Datasets & Evaluation Methods

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5. Best Practices

📋 Curated Blogs, Patterns, and Implementation Guidelines

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📖 Legend & Notation

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

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