kimtth/azure-openai-llm-notes

Latest recorded source activity: November 4, 2026 at 07:32

SkillsMP catalog refreshed: November 12, 2026 at 12:52

skills collected: 4

GitHub stars: 422
GitHub forks: 64

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# Azure OpenAI + LLM ![GitHub last commit](https://img.shields.io/github/last-commit/kimtth/awesome-azure-openai-llm?label=commit&color=hotpink&style=flat-square) ![Azure OpenAI](https://img.shields.io/badge/llm-azure_openai-blue?style=flat-square) ![GitHub Created At](https://img.shields.io/github/created-at/kimtth/awesome-azure-openai-llm?style=flat-square) 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. 🔹A list for Azure and Microsoft products only, linted by the official Awesome rules: [Azure OpenAI & Copilot](https://github.com/kimtth/awesome-azure-openai-copilot). 🔹Applications archived or inactive for over 12 months are listed in [`applications.old.md`](./section/applications.old.md). Archived Azure repositories are listed in [`azure.old.md`](./section/azure.old.md). ## 🧭 Quick Navigation (Propedia-style) | Layer / Era | What it controls | Jump to sections | |-------------|----------------------------------------|-------------| | **Weights** 2022-2023 | Capabilities encoded in model parameters. `Themes: Pretraining, scaling, fine-tuning, alignment` | [Model landscape](section/models_research.md#large-language-model-landscape) · [Model collection](section/models_research.md#large-language-model-collection) · [Training & optimization](section/models_research.md#large-language-model-training-and-optimization) · [Model training](section/azure.md#models-training--inference) | | **Context** 2023-2024 | Instructions and knowledge supplied at inference. `Themes: Prompting, RAG, memory, long context` | [Prompting](section/models_research.md#prompt-engineering-and-visual-prompts) · [RAG](section/applications.md#rag-retrieval-augmented-generation) · [IQ, Data & Memory (Azure)](section/azure.md#iq-data--memory) · [Memory](section/applications.md#memory) · [Long-context limits](section/models_research.md#context-and-long-context-limits) | | **Agentic Engineering** 2025-2026 | How applications use models and tools to act. `Themes: Agents, MCP, skills, orchestration, evaluation` | [Agent frameworks](section/azure.md#agents--context-engineering) · [Agent protocols](section/applications.md#agent-protocol) · [Agentic engineering](section/applications.md#agentic-engineering) · [Agent best practices](section/best_practices.md#agent-best-practices) · [Evaluation](section/tools_extra.md#evaluating-large-language-models) | Refereces: [DailyDoseOfDS - *Evolution of the Agent Landscape*](https://blog.dailydoseofds.com/p/evolution-of-agent-landscape-from) ## 1. App & Agent 🚀 [RAG Systems, LLM Applications, Agents, Frameworks & Orchestration](section/applications.md) - **RAG** - [RAG](section/applications.md#rag-retrieval-augmented-generation) - [GraphRAG](section/applications.md#graphrag) - [RAG Application](section/applications.md#rag-application) - [Vector Database & Embedding](section/applications.md#vector-database--embedding) - **Application** - [Top Agent Frameworks](section/applications.md#top-agent-frameworks) - [Additional Agent Framework](section/applications.md#additional-agent-framework) - [Cache](section/applications.md#cache) - [Data & Analytics Agents](section/applications.md#data--analytics-agents) - [Data Processing & OCR](section/applications.md#data-processing--ocr) - [Desktop AI Assistant](section/applications.md#desktop-ai-assistant) - [Memory](section/applications.md#memory) - [Model Gateway](section/applications.md#model-gateway) - [Model Serving & Local Runtimes](section/applications.md#model-serving--local-runtimes) - [Observability & LLMOps](section/applications.md#observability--llmops) - [**Popular LLM Applications** (GitHub Stars >= 1000)](section/x_llm_apps.md) - [SDKs, Integration & ML Libraries](section/applications.md#sdks-integration--ml-libraries) - [Training & Fine-tuning](section/applications.md#training--fine-tuning) - [UI & No-Code Tool](section/applications.md#ui--no-code-tool) - **Agent Protocols** - [A2A](section/applications.md#a2a) - [Computer & Browser use](section/applications.md#computer--browser-use) - [Model Context Protocol (MCP)](section/applications.md#model-context-protocol-mcp) - **Coding & Research** - [Coding](section/applications.md#coding) - [Deep Research](section/applications.md#deep-research) - [Domain-Specific Agents](section/applications.md#domain-specific-agents) - [Skills](section/applications.md#skills) - [Agentic Engineering](section/applications.md#agentic-engineering): Harness Engineering → Loop Engineering → Graph Engineering **[⬆ back to top](#azure-openai--llm-wiki)** ## 2. Azure OpenAI & Copilot 🌌 [Microsoft's Cloud-Based AI Platform and Services](section/azure.md) - **Microsoft Ecosystem** - [Microsoft 365 Copilot](section/azure.md#microsoft-365-copilot) - [Power Platform & Copilot Studio](section/azure.md#power-platform--copilot-studio) - [Copilot Products](section/azure.md#copilot-products) - **Platform** - [AI Platform & Services](section/azure.md#ai-platform--services) - [Models, Training & Inference](section/azure.md#models-training--inference) - [IQ, Data & Memory](section/azure.md#iq-data--memory) - [Agents & Context Engineering](section/azure.md#agents--context-engineering) - **Operations & Design** - [Developer Tools, MCP & .NET](section/azure.md#developer-tools-mcp--net) - [Safety, Security & LLMOps](section/azure.md#safety-security--llmops) - [Architecture & Reference Designs](section/azure.md#architecture--reference-designs) - [Solution Accelerators & Samples](section/azure.md#solution-accelerators--samples) - [Use Cases & Customer Stories](section/azure.md#use-cases--customer-stories) - **Learning & Research** - [Learning Resources & Workshops](section/azure.md#learning-resources--workshops) - [Microsoft Research](section/azure.md#microsoft-research) **[⬆ back to top](#azure-openai--llm-wiki)** ## 3. Research & Survey 🧠 [LLM Landscape, Prompt Engineering, Finetuning, Challenges & Surveys](section/models_research.md) - **Landscape** - [Large Language Model Landscape](section/models_research.md#large-language-model-landscape) - [Large Language Model Collection](section/models_research.md#large-language-model-collection) - [Foundation Model Providers](section/models_research.md#foundation-model-providers) - [Domain-Specific and Specialized LLMs](section/models_research.md#domain-specific-and-specialized-llms) - **Prompting** - [Prompt Engineering and Visual Prompts](section/models_research.md#prompt-engineering-and-visual-prompts) - **Training & Optimization** - [Large Language Model Training and Optimization](section/models_research.md#large-language-model-training-and-optimization) - [Pre-training and Data Preparation](section/models_research.md#pre-training-and-data-preparation) - [Architecture and Inference Patterns](section/models_research.md#architecture-and-inference-patterns) - [Capabilities and Reasoning](section/models_research.md#capabilities-and-evaluation) - [Post-training and Fine-Tuning](section/models_research.md#post-training-and-fine-tuning) - **Impact & Products** - [AI Adoption, Impact, and Society](section/models_research.md#ai-adoption-impact-and-society) - [OpenAI Products](section/models_research.md#openai-products) - [Anthropic AI Products](section/models_research.md#anthropic-ai-products) - [Google AI Products](section/models_research.md#google-ai-products) - **Survey & Reference** - [Survey and Reference](section/models_research.md#survey-and-reference) - [Additional Topics: A Survey of LLMs](section/models_research.md#additional-topics-a-survey-of-llms) - [**LLM Research** (Ranked by cite count ≥150)](section/x_llm_papers.md) - [Learning Resources, Implementations, and Regional Materials](section/models_research.md#learning-resources-implementations-and-regional-materials) **[⬆ back to top](#azure-openai--llm-wiki)** ## 4. Datasets, Evaluation, and Extras 🛠️ [Training Data, Datasets & Evaluation Methods](section/tools_extra.md) - **Data** - [Datasets for LLM Training](section/tools_extra.md#datasets-for-llm-training) - **Evaluation** - [Evaluating Large Language Models](section/tools_extra.md#evaluating-large-language-models) - [LLM Evaluation Benchmarks](section/tools_extra.md#llm-evaluation-benchmarks) - [LLMOps: Large Language Model Operations](section/tools_extra.md#llmops-large-language-model-operations) - **Extras** - [LLM for Robotics](section/tools_extra.md#llm-for-robotics) - [Awesome Demo](section/tools_extra.md#awesome-demo) **[⬆ back to top](#azure-openai--llm-wiki)** ## 5. Best Practices 📋 [Curated Blogs, Patterns, and Implementation Guidelines](section/best_practices.md) - **RAG** - [The Problem with RAG](section/best_practices.md#the-problem-with-rag) - [RAG Solution Design](section/best_practices.md#rag-solution-design) - [RAG Research](section/best_practices.md#rag-research) - [**RAG Research** (Ranked by cite count >=100)](section/best_practices.md#rag-research-ranked-by-cite-count-100) - **Agent** - [Agent Design Patterns](section/best_practices.md#agent-design-patterns) - [Agent Research](section/best_practices.md#agent-research) - [**Agent Research** (Ranked by cite count >=100)](section/best_practices.md#agent-research-ranked-by-cite-count-100) - [Tool Use: LLM to Master APIs](section/best_practices.md#tool-use) - **Security** - [Security and Governance](section/best_practices.md#security-and-governance) - **Reference** - [Proposals & Glossary](section/best_practices.md#proposals--glossary) **[⬆ back to top](#azure-openai--llm-wiki)** ## 🧭 Start Here: Choose a Goal Pick the outcome closest to your task and follow the links in order. Each path is a short starting point, not a required sequence. | Goal | Suggested path | |------|----------------| | **Build a RAG application** | [RAG](section/applications.md#rag-retrieval-augmented-generation) → [Azure IQ, Data & Memory (AI Search)](section/azure.md#iq-data--memory) → [RAG Solution Design](section/best_practices.md#rag-solution-design) → [RAG Application](section/applications.md#rag-application) | | **Design an AI agent** | [Top Agent Frameworks](section/applications.md#top-agent-frameworks) → [Agent Design Patterns](section/best_practices.md#agent-design-patterns) → [Agents & Context Engineering](section/azure.md#agents--context-engineering) → [Memory](section/applications.md#memory) | | **Connect tools with MCP** | [Model Context Protocol](section/applications.md#model-context-protocol-mcp) → [Developer Tools, MCP & .NET](section/azure.md#developer-tools-mcp--net) → [Tool Use](section/best_practices.md#tool-use) | | **Build a Microsoft 365 agent** | [Microsoft 365 Copilot](section/azure.md#microsoft-365-copilot) → [Agents & Context Engineering](section/azure.md#agents--context-engineering) | | **Build a coding or research agent** | [Coding](section/applications.md#coding) → [Skills](section/applications.md#skills) → [Agentic Engineering](section/applications.md#agentic-engineering) → [Deep Research](section/applications.md#deep-research) | | **Run a local model application** | [Model Collection](section/models_research.md#large-language-model-collection) → [Model Serving & Local Runtimes](section/applications.md#model-serving--local-runtimes) → [Model Gateway](section/applications.md#model-gateway) → [Observability & LLMOps](section/applications.md#observability--llmops) | | **Train or evaluate a model** | [Datasets for LLM Training](section/tools_extra.md#datasets-for-llm-training) → [Training & Fine-tuning](section/applications.md#training--fine-tuning) → [Evaluating Large Language Models](section/tools_extra.md#evaluating-large-language-models) → [Evaluation Metrics](section/tools_extra.md#evaluation-metrics) | | **Operate an application in production** | [Architecture & Reference Designs](section/azure.md#architecture--reference-designs) → [Safety, Security & LLMOps](section/azure.md#safety-security--llmops) → [LLMOps](section/tools_extra.md#llmops-large-language-model-operations) → [Evaluation](section/tools_extra.md#evaluating-large-language-models) | | **Explore LLM research** | [Model Landscape](section/models_research.md#large-language-model-landscape) → [Survey and Reference](section/models_research.md#survey-and-reference) → [LLM Research](section/models_research.md#llm-research-ranked-by-cite-count-150) | ## 📖 Legend & Notation | Symbol | Meaning | Symbol | Meaning | |--------|---------|--------|---------| | ![**github**](https://img.shields.io/github/stars/kimtth/awesome-azure-openai-llm?style=flat&label=%20&color=f0f1f2&cacheSeconds=360000) | GitHub repository | 🗄️ | Archived files | | 💡🏆 | Recommend | 📺 | Video content | | 📑 | Academic paper | 🤗 | Huggingface |   **[`^ back to top ^`](#azure-openai--llm-wiki)**

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Skills in this repository

classification pending

skill

occupation

description

updated

fetch-llm-papers

unclassified

Refresh the LLM landscape paper pool (section/x_llm_papers.md) with fetch_llm_papers.py. USE FOR: refreshing citation counts or expanding topic coverage. DO NOT USE FOR: hand-curated entries (use land-section-entries) or best_practices.md citation counts (use…

2026-11-04

land-section-entries

unclassified

Classify and format resources from temp.md into temp_entries.md; insert staged entries into section/*.md only on explicit request. Use for staging or landing new knowledge-base entries, not restructuring sections or refreshing generated lists.

2026-11-04

fetch-llm-apps

unclassified

Regenerate the ranked GitHub LLM applications pool (section/x_llm_apps.md) with fetch_llm_apps.py. USE FOR: refreshing the pool linked from applications.md. DO NOT USE FOR: hand-curating entries in applications.md or adding star badges to the generated file.

2026-09-29

update-cite-count

unclassified

Update citation counts for papers in the ranked sections of section/best_practices.md with update_citation_counts.py. USE FOR: refreshing counts. DO NOT USE FOR: adding papers or classifying entries.

2026-09-29

Showing 4 of 4 collected skills.