/rag-chatbot-with-vercel-ai-sdk

Next.js AI RAG chatbot with Vercel AI SDK

Primary LanguageTypeScript

Basic ChatBot Example

RAG ChatBot setup with Next.js and Vercel AI SDK using the GROQ

RAG ChatBot with GROQ

Install The node modules

  • run npm install

Run the app

  • run npm run dev

Environment variables

  • Create a .env file and copy the conent from .env.example to this file
  • GROQ_API_KEY - Get your groq API key from Groq Console
  • UPSTASH_REDIS_REST_URL - Get your redis url from Upstash Console
  • UPSTASH_REDIS_REST_TOKEN - Get your redis token from Upstash Console
  • UPSTASH_VECTOR_REST_URL - Get your vector url from Upstash Console
  • UPSTASH_VECTOR_REST_TOKEN - Get your vector token from Upstash Console
  • GOOGLE_DRIVE_FOLDER_ID - Get your google drive folder id from Google Drive Console

Note:

  • Enable the Google Drive API that allows clients to access resources from Google Drive.
  • Make sure to Share the folder access with the service account email.
  • When creating you vector store - chose the 768 dimension with COSINE metric. 768/COSINE
  • When generating the embeddings - make sure the ollama is running locally and the model nomic-embed-text is installed, use the command ollama pull nomic-embed-text to pull the model. Nomic Embed Text