Multi-agent PDF-to-blog content generation

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

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

1. Workflow Overview

Purpose of workflow: The purpose of this workflow is to automatically transform complex, lengthy PDFs into concise, insightful blog posts. This process aims to make dense information more accessibl...

Best for

Content Creation automation workflows
Multimodal AI automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.merge, n8n-nodes-base.code, n8n-nodes-base.formtrigger, n8n-nodes-base.extractfromfile, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.ghost, n8n-nodes-base.splitout, @n8n/n8n-nodes-langchain.agent

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Multi-agent PDF-to-blog content generation
Workflow name: Multi-agent PDF-to-blog content generation

Purpose of workflow:

The purpose of this workflow is to automatically transform complex, lengthy PDFs into concise, insightful blog posts. This process aims to make dense information more accessible and understandable to a broader audience.

How it works:

Multi-agent team:

Working together to transform PDF to insightful blog

Content Analyst: Extracts key information and structure from the PDF.
Project Planner: Organizes the workflow and ensures efficient processing.
Writers: Multiple agents that craft engaging content based on the analyzed information.
Editor: Polishes the final output for accuracy, reliability, and readability.

Step by step

User inputs parameters via a n8n form (tone, word count, sections, PDF file).
System extracts text from the PDF.
Content Analyst AI agent analyzes the extracted text, identifying main topics and key points.
Project Planner AI agent organizes the workflow, creating a structure for the blog post.
Multiple Writer AI agents (based on the number of sections specified) each write a portion of the blog post.
Editor AI agent combines all sections and polishes the final draft.
Generates a title for the blog post.
Final content is uploaded to a publishing Ghost platform

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 - Merge chapters title and text

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 2.1

Block 2 - Final article text

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

Block 3 - n8n Form Trigger

Type / Role: n8n-nodes-base.formTrigger - formTrigger
Config choices: Version 2.1

Block 4 - Extract from File

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

Block 5 - OpenAI Chat Model1

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

Block 6 - Ghost

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

Block 7 - Delegate to Writers

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

Block 8 - Editor

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.6

Block 9 - Create title

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.4

Block 10 - OpenAI Chat Model

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

Block 11 - Content Analyst

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.6

Block 12 - Project Planner

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

Block 13 - Sticky Note

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

Block 14 - OpenAI Chat Model2

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

Block 15 - Sticky Note1

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

Block 16 - Sticky Note2

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

Block 17 - Sticky Note3

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

Block 18 - Sticky Note4

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

Block 19 - Writers

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.6

Block 20 - Sticky Note5

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

3. Summary Table

Workflow	Multi-agent PDF-to-blog content generation
Complexity	advanced
Nodes	20
Categories	Content Creation, Multimodal AI
Author	Derek Cheung
Published	09 Oct 2024

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2457/2457.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 Content Creation workflows Multimodal AI workflows

Frequently asked questions

What does Multi-agent PDF-to-blog content generation 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 Content Creation, Multimodal AI use case.

Derek Cheung

15 workflows

Nodes

n8n-nodes-base.merge n8n-nodes-base.code n8n-nodes-base.formtrigger n8n-nodes-base.extractfromfile @n8n/n8n-nodes-langchain.lmchatopenai n8n-nodes-base.ghost n8n-nodes-base.splitout @n8n/n8n-nodes-langchain.agent

Complexity

advanced

Published 09 Oct 2024

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/2457/2457.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Send daily LinkedIn post drafts with Tavily, Groq Llama 3.3 and Gmail

## Quick overview This workflow runs daily at 8 AM to rotate through a topic list, research it with Tavily web search, generate a LinkedIn post and image prompt with Groq (Llama 3.3 70B), create a Pollinations.ai image URL, and email you the post with the image attached via Gmail. ## How it works 1. Runs every day at 8:00 AM on a schedule. 2. Selects today’s topic from a rotating list based on the day of the year. 3. Searches the web with Tavily to fetch up-to-date results for the selected topic. 4. Uses a Groq-hosted Llama model to write a LinkedIn post and a matching image prompt grounded in the Tavily results. 5. Builds a Pollinations.ai image generation URL from the image prompt and downloads the generated image file. 6. Emails the post text with the image attached via Gmail, and sends a text-only fallback email if image generation or download fails. ## Setup 1. Add a Groq API credential to the Groq Chat Model node. 2. Create a Tavily API key and configure HTTP Header Auth with `Authorization: Bearer <YOUR_TAVILY_KEY>` for the Tavily Search request. 3. Connect a Gmail OAuth2 credential and update the recipient email address in both Gmail send steps. 4. Edit the topic list in the topic-selection code step if you want different rotating themes. ## Requirements - Groq API key (free tier available) - Tavily API key (free tier — 1,000 searches/month) - Gmail account (OAuth2) ## Customization - Edit the topic list inside the "Pick Today's Topic" code node to change what subjects the post rotates through. - Change the Groq model in the "Groq Chat Model" node if you want a different LLM (e.g. a smaller/faster or larger Groq model). - Adjust the schedule trigger if you want a different posting time, or swap the Gmail "send to" address to deliver the draft to someone else for review. ## Additional info This workflow emails you a draft for manual review before posting — it does not post to LinkedIn automatically. If image generation fails, a text-only fallback email is sent instead so you never miss the post text.

View

Generate VEO3 videos from form ideas with ChatGPT, fal.ai, Drive and Gmail

## Quick overview This workflow collects a video idea via an n8n Form, uses OpenAI to turn it into an optimized prompt, generates an 8-second VEO3 video with native audio via fal.ai, saves the MP4 to Google Drive, and emails the Drive link via Gmail. ## How it works 1. Receives a submission from an n8n Form with the requester’s email, a plain-English video idea, and a selected style. 2. Uses OpenAI (via an AI Agent) to convert the idea and style into a structured VEO3 title and detailed prompt returned as JSON. 3. Cleans and parses the AI JSON, creates a filename-safe title, and sets the generation parameters to 16:9 and 8 seconds. 4. Submits the prompt to fal.ai’s queue endpoint for the fal-ai/veo3 model and gets a request ID. 5. Polls fal.ai every 30 seconds until the job status returns COMPLETED. 6. Retrieves the final MP4 URL from fal.ai, downloads the video, uploads it to Google Drive, and emails the Google Drive web link to the requester via Gmail. ## Setup 1. Create a fal.ai account, generate an API key, and replace `YOUR_FAL_AI_API_KEY` in the fal.ai HTTP request headers. 2. Add an OpenAI API credential in the OpenAI Chat Model node and select the model you want to use. 3. Connect Google Drive OAuth2 and replace `YOUR_GDRIVE_FOLDER_ID` with the target folder ID where videos should be saved. 4. Connect Gmail OAuth2 for sending emails, then activate the workflow and use the Form URL (path `veo3-video-generator`) to submit requests.

View

Generate presentation decks from prompts with Encelade

## Quick overview This workflow starts a presentation generation job in Encelade from a prompt and outline hints, polls Encelade for completion, and outputs the finished deck link (or stops with an error if generation fails). ## How it works 1. Starts when you manually execute the workflow in n8n. 2. Sends the topic, slide count, audience, tone, theme settings, and outline hints to Encelade to generate a 6-slide presentation. 3. Waits 20 seconds and then checks the Encelade session status using the returned session ID. 4. If the session phase is not finished, it keeps waiting and rechecking until the phase changes. 5. When the phase is "done", it returns the generated deck link and project PID. 6. When the phase is "failed", it stops the workflow and raises an error with the failure details. ## Setup 1. Install and configure Encelade credentials in n8n for the Encelade node. 2. Update the generation inputs (topic, page count, outline hints, audience/tone, theme mode, and media provider) to match the deck you want to create. 3. Ensure the workflow has enough time to complete by adjusting the 20-second wait interval if your Encelade generations typically take longer.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Multi-agent PDF-to-blog content generation

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Merge chapters title and text

Block 2 - Final article text

Block 3 - n8n Form Trigger

Block 4 - Extract from File

Block 5 - OpenAI Chat Model1

Block 6 - Ghost

Block 7 - Delegate to Writers

Block 8 - Editor

Block 9 - Create title

Block 10 - OpenAI Chat Model

Block 11 - Content Analyst

Block 12 - Project Planner

Block 13 - Sticky Note

Block 14 - OpenAI Chat Model2

Block 15 - Sticky Note1

Block 16 - Sticky Note2

Block 17 - Sticky Note3

Block 18 - Sticky Note4

Block 19 - Writers

Block 20 - Sticky Note5

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