wmeints/effective-llm-applications
Learn how to build effective LLM-based applications with Semantic Kernel in C#
This is a comprehensive guide for software developers who want to build sophisticated applications leveraging Large Language Models (LLMs). It provides practical knowledge and code samples for integrating LLMs into software using Microsoft's Semantic Kernel. Developers learn how to take raw data and LLM outputs, transforming them into intelligent application features.
Use this if you are a software developer looking for practical guidance and code examples to build real-world applications powered by Large Language Models using Semantic Kernel.
Not ideal if you are a non-technical user simply looking to understand what LLMs are or how to use existing LLM tools, rather than building custom applications.
Stars
16
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Jan 19, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/wmeints/effective-llm-applications"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
WangRongsheng/awesome-LLM-resources
🧑🚀 全世界最好的LLM资料总结（多模态生成、Agent、辅助编程、AI审稿、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型） | Summary of the...
SylphAI-Inc/AdalFlow
AdalFlow: The library to build & auto-optimize LLM applications.
LazyAGI/LazyLLM
Easiest and laziest way for building multi-agent LLMs applications.
luhengshiwo/LLMForEverybody
每个人都能看懂的大模型知识分享，LLMs春/秋招大模型面试前必看，让你和面试官侃侃而谈
katanaml/sparrow
Structured data extraction and instruction calling with ML, LLM and Vision LLM