Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

How it works This workflow automates a full RAG ingestion pipeline. When a new OCR JSON file is added to a Google Drive folder, the workflow extracts lesson metadata, parses and cleans the Arabic t...

Best for

Document Extraction automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.googledrive, @n8n/n8n-nodes-langchain.documentdefaultdataloader, @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter, n8n-nodes-base.stickynote, n8n-nodes-base.googledrivetrigger, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.embeddingsopenai, @n8n/n8n-nodes-langchain.vectorstorepinecone

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by osama goda.

Original n8n.io source

1.1 Workflow description

Title: Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone
Workflow name: Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone

How it works

This workflow automates a full RAG ingestion pipeline. When a new OCR JSON file is added to a Google Drive folder, the workflow extracts lesson metadata, parses and cleans the Arabic text, generates semantic chunks, creates AI embeddings, and stores them in a Pinecone vector index. After processing, the file is automatically moved to an archive folder to prevent duplicates.

Set up steps

Follow the sticky notes inside the workflow for detailed instructions.

Connect your Google Drive credentials.
Replace the input folder ID and archive folder ID with your own.
Connect your OpenAI account for embeddings.
Connect your Pinecone API key and select your index.

The workflow is ready to run once credentials and folder paths are configured.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Download file

Type / Role: n8n-nodes-base.googleDrive - googleDrive
Config choices: Version 3

Block 2 - Default Data Loader

Type / Role: @n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices: Version 1.1

Block 3 - Recursive Character Text Splitter

Type / Role: @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - textSplitterRecursiveCharacterTextSplitter
Config choices: Version 1

Block 4 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Watch Drive Folder (new files)

Type / Role: n8n-nodes-base.googleDriveTrigger - googleDriveTrigger
Config choices: Version 1

Block 6 - Filename → Lesson Metadata

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 7 - Vision JSON → Clean Text Chunks

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 8 - Generate Embeddings (OpenAI)

Type / Role: @n8n/n8n-nodes-langchain.embeddingsOpenAi - embeddingsOpenAi
Config choices: Version 1.2

Block 9 - Insert into Pinecone Vector Store

Type / Role: @n8n/n8n-nodes-langchain.vectorStorePinecone - vectorStorePinecone
Config choices: Version 1.3

Block 10 - Move File to Archive

Type / Role: n8n-nodes-base.googleDrive - googleDrive
Config choices: Version 3

Block 11 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 12 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 13 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone
Complexity	intermediate
Nodes	14
Categories	Document Extraction, AI RAG
Author	osama goda
Published	10 Dec 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/11653/11653.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Document Extraction workflows AI RAG workflows

Frequently asked questions

What does Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI RAG use case.

osama goda

4 workflows

Nodes

n8n-nodes-base.googledrive @n8n/n8n-nodes-langchain.documentdefaultdataloader @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter n8n-nodes-base.stickynote n8n-nodes-base.googledrivetrigger n8n-nodes-base.code @n8n/n8n-nodes-langchain.embeddingsopenai @n8n/n8n-nodes-langchain.vectorstorepinecone

Complexity

intermediate

Published 10 Dec 2025

Likes 0

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Install path: /data/workflows/11653/11653.json

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Process OCR documents from Google Drive into searchable knowledge base with OpenAI & Pinecone

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How it works

Set up steps

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Download file

Block 2 - Default Data Loader

Block 3 - Recursive Character Text Splitter

Block 4 - Sticky Note

Block 5 - Watch Drive Folder (new files)

Block 6 - Filename → Lesson Metadata

Block 7 - Vision JSON → Clean Text Chunks

Block 8 - Generate Embeddings (OpenAI)

Block 9 - Insert into Pinecone Vector Store

Block 10 - Move File to Archive

Block 11 - Sticky Note1

Block 12 - Sticky Note2

Block 13 - Sticky Note3

Block 14 - Sticky Note4

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions