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License: MIT License
The library for character-driven AI experiences.
License: MIT License
During a query, there are 2 lifecycle methods that invoke third-party models:
invokeChatAgent
: The vendor-specific part being the chatAgent.chat({ message });
line that calls GPT-3.5 TurboinvokeImageAgent
: The vendor-specific part is where we call DALL-E 2imageAgent.images.generate({
model: IMAGE_MODEL,
prompt: imageModelPrompt,
size: `${IMAGE_SIZE}x${IMAGE_SIZE}`,
quality: IMAGE_QUALITY,
n: 1
});
I've already experimented with swapping this DALL-E 2 call out with one made to Leonardo.AI using the exact same prompt to get much better images from fine-tuned models - so it works as a proof of concept.
Would be cool if - instead of just calling OpenAI during a query - we call a middleware function defined by the developer (which defaults to GPT-3.5/DALL-E 2 if none are provided) so they can use their own text or image models.
Let's say you wanted to use GPT-4 for text, or maybe you want to get outside OpenAI entirely by going with Claude 3. And for images, maybe you want to use a custom fine-tuned model that you trained using Leonardo.AI. The developer should be able to define their own middleware to send and augment prompts to whatever models they want.
I predict (hope?) that GPT-3.5 and DALL-E 2 will soon be free for general use, especially as more people see how varied the model outputs can be (how much better GPT-4 is than GPT-3.5, for example), and how advanced fine-tuned models seem compared to generic ones. I can at least imagine a pay-per-model future where some of them are free. There are already great model communities like Hugging Face and Nomic's GPT4All where developers are sharing models.
Until then, in terms of adoption Arthas might benefit from defaulting to free models that don't require an API key to get started. It would make it easier to install and adopt for developers working on LLM apps rather than having to create API keys, add credit cards, manage spending etc. before they're even able to try it.
The backbone of Arthas is the underlying data framework, giving it the ability to search and index knowledge in a conversational way. This framework - llamaindex (and there are some others out there, for example langchain) - requires model access too, and supports the following ones:
Arthas is tied to this vendor via the createIndex
and createQuery
functions, so in order to truly become model-agnostic the developer would need a middleware option surfaced to them to bypass these as well.
Ideally, a developer could just npm i arthasgpt
and use the library without needing any accounts or API keys by default, and could just start creating personas and making stuff.
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