I Built Deep Research That Beats Perplexity & OpenAI (free template) n8n tutorial

Summary

This video walks through the creation of an automated workflow for generating deep research reports using AI tools. It covers the process from gathering sources and generating content, to aggregating data in a Google Sheet and formatting it for a PDF report. The workflow involves content generation, table of contents creation, and email notifications, all while ensuring consistency in style. It also discusses system limitations and optimization opportunities to improve efficiency and reduce processing time, offering valuable insights into AI-powered automation for research report generation.

Takeaways

• 😀 The workflow starts by gathering research sources, processing them, and formatting the content into structured chapters within a Google Sheet.
• 😀 Each chapter's content is written in HTML format, ensuring consistency in styling throughout the report using a specific style guide.
• 😀 Sources for each chapter are dynamically numbered and formatted as clickable links in HTML, making them easy to reference in the final report.
• 😀 The system aggregates content from multiple sources and then formats it into clean HTML for easy merging and display in the final document.
• 😀 A major limitation of the workflow is its sequential nature, where each chapter must be completed before the next can begin, reducing efficiency.
• 😀 There is a hardcoded logic for assigning sources to chapters (5 sources per chapter), which could be made more dynamic to accommodate different numbers of sources.
• 😀 When updating the workflow or model, changes need to be manually applied across all sections, requiring extra maintenance effort.
• 😀 After content is merged into a Google Sheet, the system generates a PDF by converting the HTML content into a final downloadable document using an API.
• 😀 The PDF creation process includes customizing text sizes, headers, footers, and formatting to ensure the report looks professional and cohesive.
• 😀 Once the PDF is generated, it is sent to the requester via email, including a subject line and a brief message notifying them of the completion of the report.
• 😀 Although the workflow can be optimized for speed and cost-efficiency, it currently offers a functional first version that delivers a high-quality, comprehensive report.

Q & A

What is the main purpose of the automated system described in the video?

The system automates the process of generating detailed research reports, starting from gathering sources to formatting them into a consistent, styled HTML document and generating a PDF report.

How does the system ensure consistency in the styling of the report?

The system uses a style guide and applies it to all sections of the report, ensuring consistency in fonts, colors, and formatting across the entire document. The style guide is applied from the very beginning when creating the introduction and then throughout the rest of the report.

What are the limitations of the current system as mentioned in the video?

The main limitations include the sequential processing of chapters (where each chapter must finish before the next starts), the hardcoding of the logic for numbering sources, and the need to manually update branches if changes are made to one part of the workflow.

Why does the system process chapters sequentially instead of in parallel?

The system processes chapters sequentially to ensure that all the content for each chapter is gathered and merged properly. However, this approach could be more time-efficient if chapters were processed in parallel, allowing for faster report generation.

What is the role of the 'code node' in the system?

The 'code node' is used to structure and clean up the content, such as joining arrays into properly formatted lists and organizing sections in a readable manner. It ensures the content is ready for insertion into the Google Sheets and later for the PDF generation process.

How does the system handle the integration of sources into the report?

The system aggregates the sources for each chapter into a numbered list, formats them as clickable HTML links, and then adds them to the report. This process is automated for each chapter and is updated dynamically based on the data in the Google Sheet.

What happens after all five chapters have been populated into the Google Sheet?

Once the chapters are populated, the system combines all the content into one document. It then generates a table of contents, formats the content with consistent styling, and creates a PDF from the HTML using an API call to generate the final report.

How does the system generate the PDF report?

The system sends the formatted HTML content, including the table of contents, chapters, and sources, to a PDF generation API (template.io). This API converts the HTML into a PDF, which is then downloaded and sent as an email attachment to the user.

What is the advantage of using Claude 3.5 for this workflow?

Claude 3.5 offers high-quality writing capabilities, making it ideal for generating the content of the report. It is also cost-effective because it allows for unlimited executions with minimal expense, making it a great choice for automated content generation.

What are the potential optimizations for the system mentioned in the video?

Potential optimizations include processing chapters in parallel to speed up report generation, creating dynamic logic for numbering sources and handling different numbers of sources per chapter, and streamlining the workflow to reduce manual updates when changes are made.