Blog
Mert Özen's blog posts on software development, backend, frontend, and DevOps.
The Evolution of LLM APIs: From Completions to Tool Calling, Structured Outputs and MCP
The evolution of LLM APIs with verified dates, from the first text-continuing API to the chat format, from function calling to JSON mode and structured outputs, from reasoning parameters to the Model Context Protocol and agents. We see which example in the series each step maps to, and at the end of the series we build a bridge to the next AI series.
LLM Tool Calling (2): Microsoft.Extensions.AI and Safe Tools
We hand the tool loop to UseFunctionInvocation and AIFunctionFactory, then get to the real question: should every call the model asks for run? Taking authorization from the session, approval for tools that change data, argument validation with Zod and arguments the model makes up, with real qwen3:4b output.
LLM Tool Calling (1): The Model Doesn't Call Functions, It Asks for Calls
With tool calling the model runs no functions; it produces a call request and running it is up to your code. We send a raw tools request to Ollama's /api/chat endpoint with qwen3:4b, send the result back with the tool role and build the loop in TypeScript and in package-free C#.