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.
| 🚀 App & Agent | 🌌 Azure | 🧠 Research & Survey | 🛠️ Tools | 📋 Best Practices |
|---|---|---|---|---|
| 1. App & Agent | 2. Azure | 3. Research & Survey | 4. Tools | 5. Best Practices |
🚀 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)
🌌 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
🧠 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
🛠️ 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
📋 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
| Symbol | Meaning | Symbol | Meaning |
|---|---|---|---|
| ✍️ | Blog post / Documentation | ✨ | GitHub repository |
| 🗄️ | Archived files | 🔗 | Cross reference |
| 🗣️ | Source citation | 📺 | Video content |
| 🔢 | Citation count | 💡🏆 | Recommend |
| 📑 | Academic paper | 🤗 | Huggingface |