3 ms·

Is there some sort of dedicated tool for this type of setup, or did you hand-craft it ?

by toyg 2mo ago

seanmcdirmid 2mo ago
Not parent, but I use Goose for my non-handcrafted Qwen use cases, I’m also working on handcrafting as well. Goose was the only harness that didnt bloat context too much with system prompts (like openclaw) and I could get reasonable web search working with Qwen.
jermaustin1 2mo ago
Somewhat hand rolled, somewhat claude coded. Back in 2023 I started my own C# LLM library for doing tool calls and structured output, and over the years it has morphed bigger and bigger, and that is the backbone of almost all of my LLM-based projects. I've never released it, but its easy to understand, and simple to add your own tools: [AIDescription("Get current weather for a location")] static string GetWeather( [AIDescription("The city name")] string city, [AIDescription("The country name")] string country, [AIDescription("Temperature unit", ["C", "F"])] string unit = "C") { // make some API call to a weather API and return a string to the LLM return $"The weather in {city}, {country} is 22°{unit} and sunny"; } var chat = client.StartConversation("You are a helpful assistant with access to weather data."); var response = await chat.SendAsync<string>("What's the weather in London?", GetWeather); I'm sure plenty of better libraries exist for this now, but in 2023, I don't think any existed in the dotnet ecosystem. I've never released it though, because I've never "finished" it.
- rhplus 2mo ago
  It looks like you’re describing something like an MCP server and a client model. If you’re in the C# ecosystem you could consider converting your APIs to MCP format tools using the MCP SDK. https://devblogs.microsoft.com/dotnet/build-a-model-context-protocol-mcp-server-in-csharp/ https://devblogs.microsoft.com/dotnet/build-a-model-context-... And then leveraging Microsoft Agent Framework for the client and orchestration side of things: https://learn.microsoft.com/en-us/agent-framework/ https://learn.microsoft.com/en-us/agent-framework/

Is there some sort of dedicated tool for this type of setup, or did you hand-craft it ?

by toyg 2mo ago

Is there some sort of dedicated tool for this type of setup, or did you hand-craft it ?

Not parent, but I use Goose for my non-handcrafted Qwen use cases, I’m also working on handcrafting as well. Goose was the only harness that didnt bloat context too much with system prompts (like openclaw) and I could get reasonable web search working with Qwen.

jermaustin1 2mo ago

Somewhat hand rolled, somewhat claude coded. Back in 2023 I started my own C# LLM library for doing tool calls and structured output, and over the years it has morphed bigger and bigger, and that is the backbone of almost all of my LLM-based projects. I've never released it, but its easy to understand, and simple to add your own tools: [AIDescription("Get current weather for a location")] static string GetWeather( [AIDescription("The city name")] string city, [AIDescription("The country name")] string country, [AIDescription("Temperature unit", ["C", "F"])] string unit = "C") { // make some API call to a weather API and return a string to the LLM return $"The weather in {city}, {country} is 22°{unit} and sunny"; } var chat = client.StartConversation("You are a helpful assistant with access to weather data."); var response = await chat.SendAsync<string>("What's the weather in London?", GetWeather); I'm sure plenty of better libraries exist for this now, but in 2023, I don't think any existed in the dotnet ecosystem. I've never released it though, because I've never "finished" it.

rhplus 2mo ago
It looks like you’re describing something like an MCP server and a client model. If you’re in the C# ecosystem you could consider converting your APIs to MCP format tools using the MCP SDK. https://devblogs.microsoft.com/dotnet/build-a-model-context-protocol-mcp-server-in-csharp/ https://devblogs.microsoft.com/dotnet/build-a-model-context-... And then leveraging Microsoft Agent Framework for the client and orchestration side of things: https://learn.microsoft.com/en-us/agent-framework/ https://learn.microsoft.com/en-us/agent-framework/