"Want to integrate multiple AI models? Turns out you don't need to change your code to do it"



Hey everyone, good evening! After discussing education earlier, today let's talk about the chat apps we use daily. Now there are more and more AI models, some excel at chatting about daily life, some are quick at searching information, and others have strong logical analysis.

If an app wants to integrate all these models and let users choose based on their needs, wouldn't that require a lot of effort?

But there's a Klok chat app with 2.5 million users. They faced this exact problem before—different AI service providers have different interfaces, so connecting each model required code modifications, and they also had to handle performance differences among models. Any small issue could impact user experience.

As a result, after using @miranetwork, they surprisingly solved this problem easily.

Mira's interface is compatible with OpenAI, so Klok didn't need to overhaul their existing code. They could connect several top models through a single interface, like DeepSeek R1, GPT-4o mini, and others.

Basically, Mira acts as a "transit station" for these different AI models. Developers no longer have to deal with a bunch of complex interfaces and can focus on making the user experience comfortable—like designing the interface and optimizing response speed.

I think this is really a must-have for developers.
Nowadays, everyone uses apps for convenience. No one wants to switch between several apps just to access different AI features. But if developers try to integrate models themselves, just connecting and maintaining them would require a lot of effort.

Mira essentially handles all the "technical chores," allowing developers to focus on core user experience. That's probably why many teams choose it.

And if problems arise, they can work with the Mira team to solve them—not just providing a tool and leaving it at that. This is quite reliable, and worth paying attention to!
#Mira
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