Structured Outputs with Ollama and .NET

Part 6 in the “Local AI with Ollama and .NET” series: Part 1 – Ollama and .NET | Part 2 – Local RAG | Part 3 – AI Agents | Part 3.5 – MCP Server | Part 4 – Microsoft Agent Framework | Part 5 – Aspire | Version française

Asking a local model to reply in JSON directly in the prompt works most of the time. The problem is the rest of the time: the parsing blows up, and rarely at a good moment. Here’s a simple trick to get reliable JSON with Ollama and .NET.

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Orchestrating Ollama and Blazor with .NET Aspire

Part 5 in the “Local AI with Ollama and .NET” series: Part 1 – Ollama and .NET | Part 2 – Local RAG | Part 3 – AI Agents | Part 3.5 – MCP Server | Part 4 – Microsoft Agent Framework | Version française

Through the rest of the series, Ollama ran by hand: installed locally on the machine, the ollama pull done manually, and the .NET app pointing at Ollama’s local address hardcoded. It works, but it’s several manual steps to repeat on every machine. Aspire takes care of this configuration. I wanted to see what it changes.

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Categories: .NET  AI  Tags: .NET Aspire  Ollama  Blazor  .NET  AI  Orchestration 

Microsoft Agent Framework: First Agent, MCP, and Multi-Agent Workflows

Microsoft Agent Framework replaces Semantic Kernel and AutoGen. Here’s how to create a local agent with Ollama, connect an MCP server, and orchestrate two agents in sequence. [Read More]