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AI Chatbot With Pinecone Next.js RAG template interface with upload panel and citations
RAG Template

AI Chatbot With Pinecone

AI Chatbot With Pinecone is a production-style Next.js AI template for building retrieval-augmented chat applications on Pinecone. It includes document upload, server-side PDF parsing, sentence-aware chunking, OpenAI text embeddings, Pinecone vector upserts, semantic search, grounded answers, evidence previews, delete-by-metadata lifecycle handling, and a polished mobile responsive chat interface. Use it for knowledge-base assistants, customer support documentation bots, internal policy Q&A, research copilots, and document intelligence products.

Direct answer

AI Chatbot With Pinecone is a Next.js RAG chatbot template for document upload, OpenAI embeddings, Pinecone vector search, retrieval augmented generation, and cited AI answers. It is best for knowledge-base assistants, support documentation bots, internal policy Q&A, research copilots, and document intelligence SaaS prototypes.

Download on GitHub View repository Explore AI Lab
Pinecone Pinecone Documentation Pinecone TypeScript SDK OpenAI Embeddings Next.js

Features

PDF and text upload
Server-side PDF extraction
Sentence-aware chunking
OpenAI embeddings
Pinecone vector upserts
Pinecone semantic search
Grounded answers with citations
Evidence preview panel
Responsive mobile interface
Document vector deletion

Use cases

Knowledge base chatbotDocument intelligence appSupport documentation assistantInternal policy Q&AResearch copilotRAG SaaS prototype

Freshness and tested metadata

last Tested
2026-07-13
next Version
Next.js 16.2.1
node Version
Node.js 20+
runtime
Next.js App Router
deployment
Vercel-ready starter
license
MIT
status
Open Source

Architecture

Next.js App Router page for the upload, source list, chat thread, and evidence panel.
Server-side document upload route for file extraction and ingestion.
OpenAI embedding calls for document chunks and user questions.
Pinecone serverless index for vector storage, metadata, retrieval, and deletion.
Server-side chat route for grounded answer generation from retrieved chunks.
Tailwind CSS responsive interface with mobile-friendly chat and source controls.

Setup path

  1. 1Clone the GitHub repository linked above.
  2. 2Install dependencies with npm install.
  3. 3Create .env.local from .env.example.
  4. 4Add OPENAI_API_KEY and PINECONE_API_KEY.
  5. 5Run npm run dev and upload a PDF or text source.
  6. 6Ask grounded questions and inspect citations from retrieved Pinecone chunks.

Related AI template categories

Next.js AI chatbot templates RAG chatbot templates for Next.js OpenAI Agents SDK templates Next.js OpenAI templates ChatGPT clone templates Document Q&A AI templates OpenAI Agents SDK Next.js templates Next.js OpenAI starter templates

Internal template pathways

AI Templates RAG Chatbot Next.js RAG PDF Chatbot Creator

Frequently asked questions

What is AI Chatbot With Pinecone?

AI Chatbot With Pinecone is an open-source Next.js RAG chatbot template that uploads documents, creates OpenAI embeddings, stores vectors in Pinecone, retrieves relevant chunks, and answers with citations.

Which API keys does the Pinecone chatbot template need?

The template needs OPENAI_API_KEY for embeddings and answer generation, plus PINECONE_API_KEY for vector database operations.

Can I use this as a production knowledge base chatbot?

It is a strong production starter, but production deployments should add authentication, durable metadata storage, object storage, rate limits, tenant isolation, and observability.