Exciting news, Product Hunters! 🚀 I'm thrilled to introduce SciPhi – the ultimate cloud platform for Retrieval Augmented Generation (RAG). SciPhi empowers developers to effortlessly build and deploy serverless RAG pipelines with just one click! Built on top of the open-source R2R framework, SciPhi streamlines the entire process, allowing developers to focus on what truly matters – creating innovative applications that push the boundaries of what's possible with AI. Our early users have reported that SciPhi+R2R's streamlined workflow saves them significant time and eliminates the headaches associated with deploying to production and iterating on their RAG pipelines. With SciPhi, you can: ✅ Deploy production-ready RAG pipelines in seconds ✅ Customize your pipeline using intuitive configuration files ✅ Extend your pipeline logic with code ✅ Secure your sensitive data with encrypted secret management ✅ Automatically scale your pipeline as your application grows ✅ Monitor and optimize your system with comprehensive insights We've been working tirelessly to bring you a platform that accelerates the development, deployment, and optimization of RAG pipelines, all without the hassle of managing infrastructure. Whether you're a seasoned developer or just starting your AI journey, SciPhi provides a seamless experience tailored to your needs. But don't just take our word for it – dive into our comprehensive documentation and see for yourself how easy it is to get your RAG solution up and running. Join our vibrant community of developers, researchers, and enthusiasts on Discord, where you can connect with like-minded individuals, get support, and stay up-to-date with the latest advancements in the RAG ecosystem. We can't wait to see the incredible applications you'll build with SciPhi! Share your thoughts, ask questions, and let us know how we can help you make the best RAG pipeline. Happy building! 🛠️

@jgani - To answer your question, yes! I recommend taking a look at the docs core-features, starting here [https://r2r-docs.sciphi.ai/core-...]. Also, there is a SciPhi assistant that can be toggled in the bottom right of the docs / web app that can answer questions such as this. The reply it gave to your prompt above was - ` SciPhi provides customization primarily through the config.json file, where you can specify various settings including vector database providers, embedding settings, language model providers, and more. This file serves as the central point for tailoring your RAG pipeline to your specific needs. Additionally, SciPhi offers a range of RAG pipeline templates that serve as starting points for building RAG pipelines with different capabilities and configurations, which include customization options for vector database provider, evaluation settings, embedding settings, text splitter settings, and language model provider. ... `

Owen Colegrove

R2R

Maker

📌

1yr ago

Dimitrie Baitanciuc

Brizy

I'm curious about its ease of use and how it handles complex deployments, good luck

@dimitrie_baitanciuc Take it for a spin and let us know how it works for you

Jonni Gani

Unofficial Product Hunt Chrome Plugin

Congrats on the launch @emrgnt_cmplxty 🚀 Does SciPhi support other customization options beyond configuration files for flexibility e.g. script files? All the best with the launch Owen

SciPhi

One-click RAG deployment for developers

One-click RAG deployment for developers

SciPhi

One-click RAG deployment for developers

One-click RAG deployment for developers

Do you use SciPhi?

Do you use SciPhi?