Upstash

Reddit sentiment analysis for the US 2024 Presidential Election ????? We periodically parse the latest Reddit posts using QStash and ask OpenAI to score them. An Open Source Project by Upstash: https://lnkd.in/d6ERUWce

RAG chatbot is an assistant designed to help affiliates on IG. Introducing mangosqueezy.com Find and onboard affiliates automatically We help SaaS businesses by finding affiliates, creating links, and tracking results for you. Just pick a product to promote, and we handle everything, so you can focus on growing your business. Benefit - As a business, you can easily save up to 4-5 weeks. Stack used for RAG chatbot implementation: - Vercel /ai SDK - Upstash workflow for sending IG messages - Supabase for vector storage - dubdotco for creating affiliate links - Resend for messaging affiliates - honojs to create an API, deployed on @vercel Source code: https://git.new/iQ7MgSA

Upstash is now closer to Indian Developers! Introducing our new Mumbai region for globally fast Redis: ◆ Faster reads & writes for Indian users ◆ Improved latency across the region Can be used with new or existing databases in seconds.

Learn how to build a community platform with a focus on user onboarding using NextJs, Prisma, Neon, Clerk.com, and Upstash workflows. https://lnkd.in/gR--FkPm

I've just published a blog on upstash.com where I show you how to build an app that can summarize hundreds of online articles simultaneously using QStash's LLM integration and Django. ??? In this project, I demonstrate: 1. How to handle API rate limits effortlessly 2. Using Upstash-hosted models for article summarization 3. Building scalable solutions with parallel processing and automatic retries with QStash ?? Read the full blog: [https://lnkd.in/dxxeiZVp] Big thanks to Upstash for making the process seamless. ?? #WebDevelopment #QStash #Upstash #Django

https://upsta.sh/ ?? Thanks to Dub.co team!

Thank you Steven Tey ! We are glad to hear that!

Come visit our booth in #nextjsconf. Looking forward to it!

To prove how scalable Upstash Vector is, we indexed the entire Wikipedia in 11 languages (144 million vectors) in a single Vector DB. ◆ Over 700GB of data ◆ Fast semantic search ◆ Chat with Wikipedia here: https://lnkd.in/dFzRm5x3 Blog post with all the details and the code: https://lnkd.in/dEPzTpUZ

New Course Drop! And it's free. Learn how to build AI-Driven Apps with Python, LangChain, OpenAI, FastAPI and Upstash Vector! LangChain is a tool that makes it easier to load large datasets (e.g. far beyond what you can upload to ChatGPT directly) and quickly switch between different Large Language Models, different prompts, and even deploy all of it as a Rest API app via FastAPI. Tools You'll Learn: - OpenAI's state-of-the-art models for LLMs and embeddings - Upstash Vector Database for fast and efficient embedding data storage and retrieval - FastAPI for high-performance, yet simple, backend development - Upstash Redis for lightning-fast request rate limiting and activity tracking It's an exciting time to build out powerful AI-based apps. Big thanks to Upstash for partnering with me on this course! Video & code ?? in comments ??