GitHub
azure-avatar
Build real-time AI avatars using Azure Voice Live API and GPT-Realtime with WebRTC/WebSocket streaming. Supports two modes for interactive avatar applications.
samelhousseini AI Skills
GitHub ↗Explorez les skills IA publiés de samelhousseini et consultez leurs instructions source.
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GitHub
hybrid-agents
Hybrid Agentic Workflows - Build production-ready multi-agent systems with Microsoft Agent Framework (client-side) and Azure AI Foundry Agent Service (cloud-managed). Supports MCP integration and multi-agent or...
GitHub
workflow-metrics
Track, evaluate, and analyze multi-agent AI workflows using Azure AI Foundry cloud evaluations. Use when logging agent trajectories, computing evaluation metrics, measuring plan adherence, or generating workflo...
GitHub
vscode-mcp-servers
Configure and use MCP (Model Context Protocol) servers in VS Code. Use when setting up MCP servers, configuring mcp.json, using MCP tools in chat, managing server trust, or troubleshooting MCP connections.
GitHub
fast-transcription
Azure AI Speech Fast Transcription - Transcribe contact center calls with speaker identification using stereo channel separation or mono diarization. Returns results synchronously and faster than real-time.
GitHub
postgres-ai
Azure PostgreSQL AI Integration - Vector search, RAG pipelines, and agent memory with pgvector and azure_ai extensions
GitHub
model-router
Build cost-optimized chat applications with Azure OpenAI Model Router that intelligently routes queries to the most appropriate model based on complexity, achieving up to 60% cost savings.
GitHub
content-understanding
Process multimodal content (documents, images, audio, video) using Azure AI Content Understanding. Use when extracting structured data from invoices, receipts, IDs, analyzing media files, or building multimodal...
GitHub
foundry-iq
Build enterprise RAG solutions using Foundry IQ with Azure AI Search agentic retrieval. Use when implementing policy assistants, knowledge bases with citations, or multi-hop question answering systems.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.