Awesome Azure Openai Llm Overview

A curated reference for 🌌 Azure OpenAI, 🦙 LLMs (RAG, Agents), and resources.

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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

1. App & Agent

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

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

2. Azure OpenAI

🌌 Microsoft's Cloud-Based AI Platform and Services

• Overview: Azure OpenAI Overview
• Frameworks: LLM Frameworks, Agent Frameworks
• Tooling: Prompt Tooling, Developer Tooling
• Products: Microsoft Copilot Products, Agent Development, Copilot Development
• Services: Azure AI Search, Azure AI Services
• Research: Microsoft Research
• Applications: Azure OpenAI Application, Azure OpenAI Accelerator & Samples, Use Case & Architecture References

3. Research & Survey

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

• Landscape: Large Language Model: Landscape, Comparison, Evolutionary Tree, Model Collection
• Prompting: Prompt Engineering and Visual Prompts
• Finetuning: Finetuning, Quantization Techniques, Other Techniques and LLM Patterns
• Challenges: Large Language Model: Challenges and Solutions, 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 and Reference, Survey on Large Language Models, Build an LLMs from Scratch, Business Use Cases

4. Tools & Resource

🛠️ 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, LLMOps: Large Language Model Operations

5. Best Practices

📋 Curated Blogs, Patterns, and Implementation Guidelines

• RAG: RAG Best Practices, The Problem with RAG, RAG Solution Design, RAG Research
• Agent: Agent Best Practices, Agent Design Patterns, Tool Use: LLM to Master APIs
• Reference: Proposals & Glossary

Legend & Notation

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