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      <title>Agent &#43; Local Model &#43; Evals — One‑Pager</title>
      <link>https://www.fabswill.com/blog/2025-08-10-agent-plus-local-model-plus-evals-onepager/</link>
      <pubDate>Sun, 10 Aug 2025 00:00:00 +0000</pubDate>
      
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      <description>🚀 Purpose If you’ve ever wondered how to compare a locally‑hosted LLM with a hosted OpenAI model side‑by‑side, while keeping the whole experiment observable from end‑to‑end, you’re in the right place. This one‑pager walks you through the starter repo that stitches together three distinct paths:
   Path Stack Observability     A .NET 8 + Semantic Kernel + Ollama (local model) Azure Monitor (OTEL)   B OpenAI Agents SDK (TypeScript/Node) OpenAI Logs → optional OTLP → Azure Monitor   C Python Evals (OpenAI‑provided) Same prompts, same metrics    The goal?</description>
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      <title>Microsoft Graph and Python</title>
      <link>https://www.fabswill.com/blog/graphwithpython/</link>
      <pubDate>Mon, 10 May 2021 00:00:00 +0000</pubDate>
      
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      <description>Why you should read this post If you are interested in Microsoft Graph and how it can work with Python this post gives two examples of an art of the possible. In this post i will be addressing the following topics:
 Using MSAL libraries in Python Using 2 different Authentication Flows to gain access to Microsoft Graph resources Bonus - Access to my GitHub repo where you can get the code as well as a Jupyter Notebook to runs this on your own  Wiring this all up This is not very onerous, in fact if you have ever played with Python, its the simplicity that is really astounding.</description>
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