awesome-azure-openai-llm

by kimtthβœ“ Verified

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

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Python
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8/23/2026
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Installation

Add to your Claude Code skills directory:

# Add to your Claude Code skills
git clone https://github.com/kimtth/awesome-azure-openai-llm

Getting Started

Guides for using skills like awesome-azure-openai-llm.

Security Report

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Last scanned: β€”

{
  "status": "PASSED",
  "issues": []
}

README.md

Azure OpenAI + LLM

GitHub last commit Azure OpenAI GitHub Created At

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

πŸ”ΉConcise Summaries: Each resource is briefly described for quick understanding
πŸ”ΉChronological Organization: Resources appended with date (first commit, publication, or paper release)
πŸ”ΉMonthly Updates: The list is updated monthly; candidate entries before the update are tracked in the issue.

🧭 Quick Navigation (Propedia-style)

Layer / EraWhat it controlsJump to sections
Weights
2022-2023
Parametric knowledge baked into the model.
Themes: Pretraining, Scaling Laws, Fine-tuning, RLHF, Alignment, Instruction-following, Few-shot
Foundations: Large Language Model Landscape, Large Language Model Collection, Foundation Model Providers
Training: Large Language Model Training and Optimization, Model Training & Inference, Training & Fine-tuning
Behavior and safety: Trust, Safety, and Security, Safety, Security & LLMOps
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, Azure AI Search, RAG Best Practices
Memory and context windows: Context and Long-Context Limits, Memory, Data Processing & Memory
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: AI Application, Agent Frameworks, Agent Development, Agent Best Practices
Protocols and tools: Agent Protocol, Coding & Research, Skills, Harness, Loop Engineering, Dev Tools, MCP & Extensions
Apps and operations: Evaluating Large Language Models, LLMOps, Learning Resources & Workshops, Code Samples & Workshops

Refereces: DailyDoseOfDS - Evolution of the Agent Landscape

1. App & Agent

πŸš€ 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

⬆ back to top

4. Datasets, Evaluation, and Extras

πŸ› οΈ Training Data, Datasets & Evaluation Methods

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5. Best Practices

πŸ“‹ Curated Blogs, Patterns, and Implementation Guidelines

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🧭 Start Here

CategoryGoalSuggested path
RAGExplore RAG patternsRAG β†’ GraphRAG β†’ RAG Application β†’ RAG Best Practices β†’ RAG Research
AI EngineeringBuild an AI Engineering WorkflowRAG β†’ AI Application β†’ Agent Protocol β†’ Coding β†’ Deep Research β†’ Domain-Specific Agents β†’ Skills β†’ Harness β†’ Loop Engineering
Skills & HarnessesExtend a Coding AgentSkills β†’ Harness β†’ Loop Engineering β†’ Coding β†’ Tool Use β†’ Evaluation Metrics
AgentsDesign an agent workflowTop Agent Frameworks β†’ Agent Design Patterns β†’ Tool Use β†’ Memory β†’ Agent Research
Data & AnalyticsBuild a data or analytics agentData & Analytics Agents β†’ Data Processing & OCR β†’ Memory β†’ Tool Use β†’ Evaluating Large Language Models
Local LLMsBuild a local or self-hosted LLM applicationLarge Language Model Collection β†’ Model Serving & Local Runtimes β†’ Model Gateway β†’ UI & No-Code Tool β†’ Observability & LLMOps
MCP & IntegrationBuild MCP-enabled toolsModel Context Protocol β†’ Dev Tools, MCP & Extensions β†’ Safety, Security & LLMOps β†’ Agent Best Practices
Developer AgentsBuild coding or research agentsCoding β†’ Deep Research β†’ Skills β†’ Harness β†’ Loop Engineering β†’ Tool Calling & Agentic
Azure / RAGBuild an Azure RAG applicationAzure OpenAI & Foundry Overview β†’ Azure AI Search β†’ RAG Solution Design β†’ Sample Applications β†’ Evaluating Large Language Models
Azure / AgentsBuild an Azure agentAgent Frameworks β†’ Agent Design Patterns β†’ Model Context Protocol β†’ Agent Development β†’ Evaluating Large Language Models
Microsoft 365Build a Microsoft 365 agentMicrosoft 365 Agent Development β†’ Copilot Product Catalog β†’ Dev Tools, MCP & Extensions β†’ Agent Development
ProductionOperate an AI application in productionArchitecture Patterns & Use Cases β†’ Safety, Security & LLMOps β†’ LLMOps β†’ Evaluating Large Language Models
ResearchLearn the LLM landscapeLarge Language Model Landscape β†’ Survey and Reference β†’ LLM Research
Model DevelopmentTrain or fine-tune a modelLarge Language Model Collection β†’ Model Training & Inference β†’ Training & Fine-tuning β†’ Datasets for LLM Training β†’ Evaluating Large Language Models
MultimodalBuild a multimodal applicationMultimodal Models β†’ Data Processing & OCR β†’ RAG Application β†’ Vision & Multimodal
EvaluationChoose and benchmark a modelLarge Language Model Collection β†’ Architecture Comparisons β†’ Evaluating Large Language Models β†’ LLM Evaluation Benchmarks β†’ Evaluation Metrics

πŸ“– Legend & Notation

SymbolMeaningSymbolMeaning
githubGitHub repositoryπŸ—„οΈArchived files
πŸ’‘πŸ†RecommendπŸ“ΊVideo content
πŸ“‘Academic paperπŸ€—Huggingface

Info: Applications that have been archived or have had no commits for more than 12 months are listed in applications.old.md.

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Frequently Asked Questions

What is awesome-azure-openai-llm?βŒ„

awesome-azure-openai-llm is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by kimtth. A curated collection of resources for 🌌 Azure OpenAI, πŸ¦™ LLMs (+RAG, Agents). Monthly Updates. It has 397 GitHub stars.

Is awesome-azure-openai-llm safe to use?βŒ„

Yes. awesome-azure-openai-llm passed SkillsLLM's automated security scan β€” a dependency vulnerability audit plus prompt-injection heuristics β€” with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install awesome-azure-openai-llm?βŒ„

Clone the repository with "git clone https://github.com/kimtth/awesome-azure-openai-llm" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is awesome-azure-openai-llm written in?βŒ„

awesome-azure-openai-llm is primarily written in Python. It is open-source under kimtth on GitHub, so you can review or fork the full source.

Are there alternatives to awesome-azure-openai-llm?βŒ„

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh awesome-azure-openai-llm against similar tools.

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