Upstash RAG Chat Integration

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Introduction

Upstash RAG Chat is a TypeScript toolkit for building powerful retrieval-augmented generation (RAG) applications. This integration with Helicone allows you to leverage advanced observability tools for your RAG Chat applications, providing deeper insights into your LLM operations.

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Key Features

• Framework Compatibility: Seamlessly integrates with Next.js, Svelte, Nuxt.js, and Solid.js.
• Diverse Data Ingestion: Ingest websites by URL, text files, CSVs, PDFs, and more out of the box.
• Real-time Streaming: Stream AI-generated content in real time.
• Built-in Vector Store: Efficiently manage your knowledge base.
• Optional Redis Integration: Store chat messages for persistent conversations.
• Flexible Chat Sessions: Support for maintaining context across interactions.
• Customizable Prompts: Fully customizable prompts for tailored experiences.
• Pure LLM Chat Mode: Option to use without RAG for traditional LLM interactions.

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Integration Steps

npm i @upstash/rag-chat
# or
pnpm add @upstash/rag-chat
# or
yarn add @upstash/rag-chat

import { RAGChat, openai } from "@upstash/rag-chat";

const ragChat = new RAGChat({
  model: openai("gpt-3.5-turbo", {
    apiKey: process.env.OPENAI_API_KEY!,
    analytics: { name: "helicone", token: process.env.HELICONE_API_KEY },
  }),
});

By integrating Upstash RAG Chat with Helicone, you can build advanced RAG applications with comprehensive observability, allowing you to optimize your LLM operations and deliver more efficient, context-aware AI interactions.

For more details on RAG Chat features and usage, visit the Upstash RAG Chat documentation.