Build comprehensive literature reviews with GPT-4 and multi-database search

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Important notice

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

1. Workflow Overview

This workflow contains community nodes that are only compatible with the self hosted version of n8n. Comprehensive Literature Review Automation Automate your literature review process by searching ...

Best for

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

Tools used

n8n-nodes-base.stickynote, n8n-nodes-pdfvector.pdfvector, n8n-nodes-base.code, n8n-nodes-base.openai, n8n-nodes-base.writebinaryfile

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Build comprehensive literature reviews with GPT-4 and multi-database search
Workflow name: Build comprehensive literature reviews with GPT-4 and multi-database search

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

Comprehensive Literature Review Automation

Automate your literature review process by searching across multiple academic databases, parsing papers, and organizing findings into a structured review document.

Features:

Search multiple academic databases simultaneously (PubMed, ArXiv, Google Scholar, etc.)
Parse and analyze top papers automatically
Generate citation-ready summaries
Export to various formats (Markdown, Word, PDF)

Workflow Steps:

Input: Research topic and parameters
PDF Vector Search: Query multiple academic databases
Filter & Rank: Select top relevant papers
Parse Papers: Extract content from PDFs
Synthesize: Create literature review sections
Export: Generate final document

Use Cases:

PhD students conducting systematic reviews
Researchers exploring new fields
Grant writers needing background sections

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 - Start

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

Block 2 - PDF Vector - Search Papers

Type / Role: n8n-nodes-pdfvector.pdfVector - pdfVector
Config choices: Version 1

Block 3 - Sort by Citations

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

Block 4 - Select Top Papers

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

Block 5 - PDF Vector - Parse Papers

Type / Role: n8n-nodes-pdfvector.pdfVector - pdfVector
Config choices: Version 1

Block 6 - Synthesize Review

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

Block 7 - Combine Sections

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

Block 8 - Export Review

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

3. Summary Table

Workflow	Build comprehensive literature reviews with GPT-4 and multi-database search
Complexity	intermediate
Nodes	8
Categories	Document Extraction, Multimodal AI
Author	PDF Vector
Published	14 Aug 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/7354/7354.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 Multimodal AI workflows

Frequently asked questions

What does Build comprehensive literature reviews with GPT-4 and multi-database search 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, Multimodal AI use case.

PDF Vector

20 workflows

Nodes

n8n-nodes-base.stickynote n8n-nodes-pdfvector.pdfvector n8n-nodes-base.code n8n-nodes-base.openai n8n-nodes-base.writebinaryfile

Complexity

intermediate

Published 14 Aug 2025

Likes 0

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Install path: /data/workflows/7354/7354.json

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Build comprehensive literature reviews with GPT-4 and multi-database search

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Comprehensive Literature Review Automation

Features:

Workflow Steps:

Use Cases:

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Start

Block 2 - PDF Vector - Search Papers

Block 3 - Sort by Citations

Block 4 - Select Top Papers

Block 5 - PDF Vector - Parse Papers

Block 6 - Synthesize Review

Block 7 - Combine Sections

Block 8 - Export Review

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