Build a Retrieval Augmented System (RAG) system in just 4 lines of code!
Welcome to the?latest edition of the AI in 5 newsletter with Clarifai!
Every week, we bring you the models, tools and tips to build production-ready AI!
This week, we bring you: ??
RAG in 4 lines of code ???
By now, we all know that Retrieval-Augmented Generation (RAG) is an architecture that provides the most relevant and contextually important data to the LLMs when answering questions.
But we're sure you did not know this - You can now build a RAG system in just 4 lines of code using Clarifai's Python SDK!
The following video guides you through a step-by-step process of building a RAG system in 4 lines of code. ??
Checkout the video here
New models in the Clarifai platform ??
Conformer-2: Conformer-2 is the latest speech-to-text model from Assembly AI trained on 1.1 million hours of English audio data.? Conformer-2 builds upon its predecessor, Conformer-1, and it offers more robustness to noisy audio.
You can use the model for various transcription services, including converting audio recordings, interviews, meetings, and video content into written text, as well as for voice assistants, chatbots, and content creation.
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Meet the Winners of the NextGen GPT AI Hackathon ??
We had a fantastic time at the NextGen GPT AI Hackathon!
There were numerous intriguing projects created using GPT-4 Vision, GPT-4 Turbo, DALL-E 3, Text-to-Speech, and other models from the Clarifai community.
For a quick rundown of the hackathon, read the blog here.
Collaborators feature now available for all plans ??
In Clarifai, Collaboration is a functionality that allows you to share your apps to work with your team members to label data, create models, and more!
You can give a trusted collaborator full access privileges, invite a worker, and grant them limited permissions.
Read more about the feature in the blog here.
AI tip of the week: ??
Clarifai Data Utils
With the new Clarifai Data Utils library, you can now load different annotation formats, convert them to a dataset loader, and upload them into the platform.
The following code shows how to load data in COCO format and upload it to the Clarifai platform using the Python SDK. Check out the code here.
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