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azure-openai

Generate Azure OpenAI Service configurations with Bicep and Terraform templates.

1|Updated Mar 2, 2026
Search Tags:#deployment#code generation#ai#rag#azure#openai
One-click install
npx skills add https://github.com/sitharaj88/claude-skills --skill azure-openai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: azure-openai
Source: https://github.com/sitharaj88/claude-skills/tree/main/skills/azure-openai
Command: npx skills add https://github.com/sitharaj88/claude-skills --skill azure-openai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill simplifies the process of configuring and integrating Azure OpenAI Service for AI-powered applications, from model deployments to advanced RAG patterns.

Core Features & Use Cases

  • Resource Deployment: Generates Bicep and Terraform templates for Azure OpenAI resources.
  • AI Integration Code: Provides TypeScript and Python examples for chat completions, embeddings, and RAG.
  • Advanced Patterns: Includes guidance on Assistants API, content filtering, rate limiting, and integrations with LangChain and Semantic Kernel.
  • Use Case: You need to set up a new Azure OpenAI resource, deploy GPT-4o and an embedding model, and then write code to build a RAG application that answers questions from your company's documentation.

Quick Start

Use the azure-openai skill to generate a Bicep template for deploying GPT-4o and text-embedding-3-small models.

Frequently Asked Questions about azure-openai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy Azure OpenAI resources using Bicep or Terraform?▼

Yes, the skill provides TypeScript and Python code examples for Retrieval-Augmented Generation (RAG). It includes integration patterns for chat completions and embeddings, enabling you to build applications that answer questions from company documentation using frameworks like LangChain and Semantic Kernel.

Can I use this to generate RAG application code with LangChain and Azure OpenAI?▼

Yes, the skill provides TypeScript and Python code examples for Retrieval-Augmented Generation (RAG). It includes integration patterns for chat completions and embeddings, enabling you to build applications that answer questions from company documentation using frameworks like LangChain and Semantic Kernel.

What is the best way to configure production-ready Azure OpenAI integrations for chatbots?▼

Yes, you can generate semantic search and embedding code examples in both Python and TypeScript. The skill provides patterns for integrating text-embedding-3-small models to build search applications and AI assistants powered by Azure OpenAI.

Does this support generating Python and TypeScript examples for Azure OpenAI embeddings?▼

Yes, you can generate semantic search and embedding code examples in both Python and TypeScript. The skill provides patterns for integrating text-embedding-3-small models to build search applications and AI assistants powered by Azure OpenAI.

Do I need Terraform or Bicep to automate Azure OpenAI model deployments?▼

You do not strictly need both, but having either Terraform or Bicep allows you to fully automate Azure OpenAI model deployments. The skill generates templates for both, enabling infrastructure-as-code provisioning for models like GPT-4o.

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