Ask questions about a PDF using AI

Load data into database Fetch file from Google Drive, split it into chunks and insert into Pinecone index

Workflow Structure (13 nodes)
100%
Manual Trigger
When clicking 'Test Workflow' button
Set
Set Google Drive file URL
Google Drive
Google Drive
Langchain.embeddings Open Ai
Embeddings OpenAI
Langchain.vector Store Pinecone
Insert into Pinecone vector store
Langchain.document Default Data Loader
Default Data Loader
Langchain.chat Trigger
When clicking 'Chat' button below
Langchain.chain Retrieval Qa
Question and Answer Chain
Langchain.lm Chat Open Ai
OpenAI Chat Model
Langchain.retriever Vector Store
Vector Store Retriever
Langchain.text Splitter Recursive Character Text Splitter
Recursive Character Text Splitter
Langchain.embeddings Open Ai
Embeddings OpenAI2
Langchain.vector Store Pinecone
Read Pinecone Vector Store
Node Types:
action
logic
default
trigger
transform
Requires credentials

Prerequisites

Required Credentials (3)

Google Drive

Used by: Google Drive

Docs

OpenAI

Used by: Embeddings OpenAI, OpenAI Chat Model +1 more

Docs

Pinecone

Used by: Read Pinecone Vector Store, Insert into Pinecone vector store

Docs

Multiple services required

This workflow needs 3 different credentials. Make sure you have accounts for all services before importing.

Complexity

Complex

Advanced features used. Requires n8n experience.

Setup time: ~40 min
Score: 41/100

When to Use This Workflow

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

Time Savings

Replace repetitive manual tasks with reliable automation.

Reclaim hours every week for higher-value work.

Error Reduction

Eliminate human error from routine processes with consistent automation.

Improve accuracy and reliability across your workflows.

workflow.json
{
  "meta": {
    "instanceId": "62b3b6db4f4d3641a1fa1da6dfb9699a19380a1f60cbc18fc75d6d145f35552b"
  },
  "nodes": [
    {
      "id": "40bb5497-d1d2-4eb7-b683-78b88c8d9230",
      "name": "Google Drive",
      "type": "n8n-nodes-base.googleDrive",
      "position": [
        496.83478320435574,
        520
      ],
      "parameters": {
        "fileId": {
          "__rl": true,
          "mode": "url",
          "value": "https://drive.google.com/file/d/11Koq9q53nkk0F5Y8eZgaWJUVR03I4-MM/view"
        },
        "options": {},
...

Workflow Details

Nodes
16
Trigger
Event
Source
awesome
Added
Dec 4, 2025

Need Help?

Check out the official n8n documentation for detailed guides.

Related Workflows

Supabase Insertion & Upsertion & Retrieval

INSERTING - it's important to use the same embedding model when for any interaction with your vector database (inserting...

Google-drive
Documentdefaultdataloader
Chainretrievalqa
Lmchatopenai
21 nodesEvent
Curated

Chat with PDF docs using AI (quoting sources)

1. Setup: Fetch file from Google Drive, split it into chunks and insert into a vector database Note that running this pa...

Embeddingsopenai
Documentdefaultdataloader
Google-drive
Chat
22 nodesEvent
Curated

Advanced AI Demo (Presented at AI Developers #14 meetup)

![h](https://i.postimg.cc/9XLvL5dL/slide-sf-talk.pngfull-width)

Slack
Textsplitterrecursivecharactertextsplitter
Embeddingsopenai
Documentdefaultdataloader
39 nodesEvent
Curated

Chat with GitHub OpenAPI Specification using RAG (Pinecone and OpenAI)

Indexing content in the vector database This part of the workflow is responsible for extracting content, generating embe...

Http-request
Vectorstorepinecone
Documentdefaultdataloader
Textsplitterrecursivecharactertextsplitter
17 nodesEvent
Curated

RAG on living data

Switch trigger (optional) If you are on the cloud plan, consider switching to the Notion Trigger Node instead, to save o...

Embeddingsopenai
Textsplittertokensplitter
Chainretrievalqa
Retrievervectorstore
34 nodesEvent
Curated

Telegram RAG pdf

Load data into database Fetch file from Telegram, split it into chunks and insert into Pinecone index, a message from Te...

Telegram
Embeddingsopenai
Documentdefaultdataloader
Textsplitterrecursivecharactertextsplitter
20 nodesEvent
Curated