by microsoft · Agent Tool · ★ 87
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AI Tour 2025 BRK451 Code-First GenAIOps from Prototype to Production with GenAI Tools Session Description In this session, we will demonstrate the development of an agentic creative assistant application leveraging state-of-the-art technologies such as Azure AI Agent Service, Prompty, GPT-4o, GPT-4o-mini, and FastAPI. The application is deployed to Azure Container Applications, utilizing azd for deployment, AppInsights for monitoring, and Azure AI Inference SDK for tracing and debugging. The session aims to highlight why Azure AI is the best platform for developing LLM-powered apps with robust end-to-end flow orchestration, tracing/debugging, and monitoring capabilities. Learning Outcomes By the end of this session, attendees will: Learn how Azure AI's code-first tooling, such as Prompty and Azure AI Agents Service, can streamline and simplify the LLM lifecycle. Understand that GenAIOps requires non-linear, iterative processes. Learn the practicalities of deploying LLM powered applications to production Gain the ability to stay in their preferred local development environment when desired and smoothly switch to Azure AI Foundry for enhanced collaboration.
| Stars | 87 |
| Forks | 19 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 52.6114744936764/100 |
| Open Issues | 2 |
| Last Updated | 2025-04-08 |
| Created | 2024-07-09 |
| Est. Tokens | ~447k |
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aitour-llmops-with-gen-ai-tools is AI Tour 2025 BRK451 Code-First LLMOps from Prototype to Production with GenAI Tools. It is categorized as a Agent Tool with 87 GitHub stars.
You can find installation instructions and usage details in the aitour-llmops-with-gen-ai-tools GitHub repository at github.com/microsoft/aitour-llmops-with-gen-ai-tools. The project has 87 stars and 19 forks, indicating an active community.
aitour-llmops-with-gen-ai-tools is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to aitour-llmops-with-gen-ai-tools on Agent Skills Hub include tutor-skills, lenny-skills, repren. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.