Research Idea Generation via PDF Content Gap Analysis - n8n Workflow

• Researchers and Academics needing to identify novel research directions.
• Content Strategists looking to find structural gaps in competitor or internal documentation.
• Users of n8n seeking advanced retrieval-augmented generation (RAG) implementation examples.
• Automation engineers looking for powerful n8n templates involving file processing and complex external APIs.

Generating truly novel ideas from large bodies of text can be challenging using traditional AI methods, which often lead to generic responses. This sophisticated n8n workflow leverages the power of InfraNodus GraphRAG technology to overcome this limitation. By building a knowledge graph from your uploaded PDF documents, the system identifies structural gaps—concepts that appear in the text but are not yet connected.

This specific n8n workflow then automatically generates a research question designed to bridge that content gap, followed by an informed, text-based response. This process ensures the ideas generated are relevant to your source material yet inherently innovative. It demonstrates how powerful an n8n automation solution can be when combining file handling, custom scripting, and intelligent external services.

This n8n workflow is triggered by an interactive form submission where users upload one or more PDF files.

1. Trigger and Conversion: The On form submission n8n trigger captures the uploaded files. A subsequent Code n8n node (Convert binary files to PDF) prepares the incoming binary data, adding a filename key necessary for the next step.


2. Text Extraction: The Extract text from PDF files n8n node reads the binary data and converts all content into raw, searchable text strings.


3. Data Preparation: The next Code n8n node (Prepare for InfraNodus) aggregates all extracted text from the multiple PDFs into a single, large text string. It also calculates a random 'gap depth' parameter needed for the InfraNodus API call.


4. Question Generation (GraphRAG): The InfraNodus GraphRAG Question Generator (an HTTP Request n8n node) sends the aggregated text to the InfraNodus API. The service analyzes the text, builds a knowledge graph, identifies the largest structural content gap, and generates a corresponding research question.


5. Response Generation: The InfraNodus GraphRAG Response Generator n8n node takes the newly generated question as a prompt and queries the source text again to formulate a preliminary response or idea related to bridging that gap.


6. User Display: Finally, the Display on the Form to the User n8n node presents both the novel research question and the generated response back to the user via the initial form interface, concluding this powerful n8n automation.

To deploy this advanced n8n workflow, follow these steps:

1. Import the JSON: Copy the provided n8n workflow JSON and import it into your n8n instance.


2. Set up Credentials: You must configure two HTTP Bearer Authentication credentials for the InfraNodus API:

1. Activate the Trigger: Ensure the On form submission n8n trigger node is set to 'Active' and save the n8n workflow. You can then access the public URL of the form to begin uploading PDF files for analysis. This n8n template is now ready to run.

On form submission (n8n trigger): This is the entry point for the n8n workflow. It is configured to accept file uploads specifically of type .pdf. It makes the automation interactive by providing a web form for users.
Convert binary files to PDF (Code n8n node): Essential for file preparation. It iterates through the binary data uploaded by the n8n trigger and structures the data by adding unique filenames to ensure proper processing by the PDF extraction n8n node.
Extract text from PDF files (n8n node): Handles the core PDF processing, converting the binary data of the uploaded PDFs into accessible text strings.
Prepare for InfraNodus (Code n8n node): Aggregates text from all incoming items into one large string (plainText) and calculates a random gap depth (randomNum) parameter, preparing the data payload for the external API call. This custom n8n node logic is crucial for successful API interaction.
InfraNodus GraphRAG Question Generator (HTTP Request n8n node): Configured for a POST request to the InfraNodus API. It uses the text field (containing all PDF content) and sets requestMode to question and utilizes the dynamically generated gapDepth to find and articulate a highly specific research question based on structural gaps.
InfraNodus GraphRAG Response Generator (HTTP Request n8n node): Another HTTP Request n8n node, it takes the question generated in the previous step (mapped via expression: {{ $json.aiAdvice[0].text }}) and the original source text to generate a corresponding response based on the content available.

• Display on the Form to the User (Form n8n node): The final action, which displays the results back to the initiating user, completing the fully encapsulated n8n workflow.