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 | Representative themes | Jump to sections | |-------------|-------------|-------------|-------------| | Weights 2022-2023 | Parametric knowledge baked into the model | 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, LLM Frameworks | | Context 2023-2024 | What the model sees at inference time | Prompting, Chain-of-Thought, RAG, Memory, Long Context, Knowledge Injection, Context Engineering | Prompting: Prompt Engineering and Visual Prompts, Prompt Tooling, Coding 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 | 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, Developer Tooling 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
- Application
- Agent Protocols
- Coding & Research
2. Azure OpenAI & Copilot
🌌 Microsoft's Cloud-Based AI Platform and Services
- Overview
- Frameworks
- Tooling
- Products
- Services
- Research
- Applications
3. Research & Survey
🧠 LLM Landscape, Prompt Engineering, Finetuning, Challenges & Surveys
- Landscape
- Prompting
- Finetuning
- Challenges
- Products & Impact
- Survey & Build