Building a Retrieval-Augmented Generation Chatbot with SvelteKit and Xata Vector Search

• xata-rag-chatbot

  1 2 5.0 TypeScript

  A demo of your own RAG Chatbot with Xata, SvelteKit, LiteLLM, OpenAI and Vercel.

Resource Link GitHub Repo https://github.com/rishi-raj-jain/xata-rag-chatbot SvelteKit with Xata https://xata.io/docs/getting-started/sveltekit Xata Vector Search https://xata.io/docs/sdk/vector-search How to Prompt Llama 2 https://huggingface.co/blog/llama2#how-to-prompt-llama-2 SvelteKit AI SDK https://sdk.vercel.ai/docs/guides/frameworks/sveltekit

• ai

  18 8,226 9.8 TypeScript

  Build AI-powered applications with React, Svelte, Vue, and Solid

  

import { experimental_buildLlama2Prompt } from 'ai/prompts'; // Now use Replicate LLAMA 70B streaming to perform the autocompletion with context const response = await replicate.predictions.create({ // You must enable streaming. stream: true, // The model must support streaming. See https://replicate.com/docs/streaming model: 'meta/llama-2-70b-chat', // Format the message list into the format expected by Llama 2 // @see https://github.com/vercel/ai/blob/99cf16edf0a09405d15d3867f997c96a8da869c6/packages/core/prompts/huggingface.ts#L53C1-L78C2 input: { prompt: experimental_buildLlama2Prompt([ { // create a system content message to be added as // the llama2prompt generator will supply it as the context with the API role: 'system', content: systemContext }, { // create a system instruction // make sure to wrap code blocks with ``` {% endraw %} so that the svelte markdown picks it up correctly role: 'assistant', content: {% raw %}`When creating repsonses sure to wrap any code blocks that you output as code blocks and not text so that they can be rendered beautifully.`{% endraw %} }, // also, pass the whole conversation! ...messages ]) } }); {% raw %}

• SurveyJS

  surveyjs.io featured

  Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

  

• pgzx

  7 344 8.6 Zig

  Create PostgreSQL extensions using Zig.

  

Resource Link GitHub Repo https://github.com/rishi-raj-jain/xata-rag-chatbot SvelteKit with Xata https://xata.io/docs/getting-started/sveltekit Xata Vector Search https://xata.io/docs/sdk/vector-search How to Prompt Llama 2 https://huggingface.co/blog/llama2#how-to-prompt-llama-2 SvelteKit AI SDK https://sdk.vercel.ai/docs/guides/frameworks/sveltekit

• vercel

  491 12,309 9.8 TypeScript

  Develop. Preview. Ship.

  

A Vercel Account

• replicate-javascript

  8 422 8.9 TypeScript

  Node.js client for Replicate

  

import { experimental_buildLlama2Prompt } from 'ai/prompts'; // Now use Replicate LLAMA 70B streaming to perform the autocompletion with context const response = await replicate.predictions.create({ // You must enable streaming. stream: true, // The model must support streaming. See https://replicate.com/docs/streaming model: 'meta/llama-2-70b-chat', // Format the message list into the format expected by Llama 2 // @see https://github.com/vercel/ai/blob/99cf16edf0a09405d15d3867f997c96a8da869c6/packages/core/prompts/huggingface.ts#L53C1-L78C2 input: { prompt: experimental_buildLlama2Prompt([ { // create a system content message to be added as // the llama2prompt generator will supply it as the context with the API role: 'system', content: systemContext }, { // create a system instruction // make sure to wrap code blocks with ``` {% endraw %} so that the svelte markdown picks it up correctly role: 'assistant', content: {% raw %}`When creating repsonses sure to wrap any code blocks that you output as code blocks and not text so that they can be rendered beautifully.`{% endraw %} }, // also, pass the whole conversation! ...messages ]) } }); {% raw %}

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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