Get Started with Upstage AI's Solar LLM in 10 Minutes

About this video

Creating a Retrieval-Augmented Generation (RAG) Workflow with Upstage AI Upstage Console Link: https://go.upstage.ai/SOLAR_DEV_DIGEST Credit Redeem Coupon Code: SOLAR_DEV_DIGEST_2408 Start registering for the coupon: August 15, 2024, 12:00 AM (UTC) End of coupon registration: September 15, 2024, 12:00 AM (UTC) Credit expiration date: November 1, 2024, 12:00 AM (UTC) Credit amount: $30 Console: https://console.upstage.ai/ Repo: https://git.new/answr In this informative video, I showcase the various services offered by Upstage AI, demonstrating how to integrate their embeddings and Solar LLM models into your LLM applications from scratch. The video provides a detailed walkthrough, including vector storage setup, similarity search, chunking, and combining these elements for retrieval-augmented generation. Additionally, a brief overview of the Upstage console and its user-friendly features, such as document OCR and key information extraction, is also shared. Follow along as I code a complete reg workflow without utilizing any frameworks, ensuring ease of understanding in every step. 00:00 Introduction to Upstage AI Services 00:29 Setting Up from Scratch: No Frameworks Needed 01:01 Exploring the Upstage Console 01:58 Document AI Features and Benefits 03:05 Combining Chat and Embeddings for RAG Applications 04:46 Coding the RAG Application 08:05 Performing Similarity Search and Chat Completion 11:10 Conclusion and Final Thoughts