thenameless7741

A recent example: a law firm hired this person [0] to build a private AI system for document summarization and Q&A.

[0] https://xcancel.com/glitchphoton/status/1927682018772672950

If you install llama.cpp via Homebrew, llama-mtmd-cli is already included. So you can simply run `llama-mtmd-cli <args>`

AFAIK, Phi-4-multimodal doesn't support TTS, but I understand OP's point.

The recent Qwen's release is an excellent example of model providers collaborating with the local community (which include inference engine developers and model quantizers?). It would be nice if this collaboration extended to wrapper developers as well, so that end-users can enjoy a great UX from day one of any model release.

> it'll probably take a year for the FOSS community to implement and digest it completely

The local community seems to have converged on a few wrappers: Open WebUI (general-purpose), LM Studio (proprietary), and SillyTavern (for role-playing). Now that llama.cpp has an OpenAI-compatible server (llama-server), there's a lot more options to choose from.

I've noticed there really aren't many active FOSS wrappers these days - most of them have either been abandoned or aren't being released with the frequency we saw when OpenAI API first launched. So it would be awesome if you could share your wrapper with us at some point.

it's mentioned in the main thread: https://nitter.net/athyuttamre/status/1899511569274347908

> [Q] Does the Agents SDK support MCP connections? So can we easily give certain agents tools via MCP client server connections?

> [A] You're able to define any tools you want, so you could implement MCP tools via function calling

in short, we need to do some plumbing work.

relevant issue in the repo: https://github.com/openai/openai-agents-python/issues/23

I'm building an AI wrapper in the playground category.

This is probably my 10th time making wrappers, and I always try to do something different each time.

For this one, I'll focus on experimenting with reasoning UX since I'm not really satisfied with the current UX (most wrappers just show a collapsible for reasoning content and that's it). So naturally, I'm making reasoning models as the first-class citizen this time. I plan to open source it once it's done.

Interesting.. In the official API [1], there's no way to prefill the reasoning_content:

> Please note that if the reasoning_content field is included in the sequence of input messages, the API will return a 400 error. Therefore, you should remove the reasoning_content field from the API response before making the API request

So the best I can do is pass the reasoning as part of the context (which means starting over from the beginning).

[1] https://api-docs.deepseek.com/guides/reasoning_model