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Enterprise knowledge search with GPT-4 Turbo, Google Drive & Academic APIs

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2/3/2026
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Enterprise Knowledge Search with GPT-4 Turbo, Google Drive & Academic APIs

This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo.

How it works

This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo.

Key Steps

  1. Form Input - Collects user queries with customizable search scope, response style, and language preferences
  2. Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents)
  3. Data Aggregation - Unifies and processes information from multiple sources with quality scoring
  4. AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses
  5. Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.)
  6. Multi-Channel Delivery - Delivers results via webhook, email, Slack, and optional PDF generation

Data Sources & AI Models

Search Sources

  • Web Search: Google, Bing, DuckDuckGo integration
  • Academic Papers: arXiv, PubMed, Google Scholar via Crossref API
  • News Articles: News API, RSS feeds, real-time news
  • Technical Documentation: GitHub, Stack Overflow, documentation sites
  • Internal Knowledge: Google Drive, Confluence, Notion integration

AI Models

  • GPT-4 Turbo: Primary language model for response generation
  • Embedding Models: For semantic search and similarity matching
  • Custom Prompts: Specialized prompts for different response styles

Set up steps

Setup time: 15-20 minutes

  1. Configure API credentials - Set up OpenAI API, News API, Google Drive, and other service credentials
  2. Set up search sources - Configure academic databases, news APIs, and internal knowledge sources
  3. Connect analytics - Link Google Sheets for usage tracking and performance monitoring
  4. Configure notifications - Set up Slack channels and email templates for automated alerts
  5. Test the workflow - Run sample queries to verify all components are working correctly

Keep detailed configuration notes in sticky notes inside your workflow

n8n Form Trigger with OpenAI and Conditional Logic

This n8n workflow demonstrates how to create an interactive form that triggers an OpenAI request based on user input, and then conditionally responds to the user.

Description

This workflow provides a basic example of using an n8n form to collect user input, process it with the OpenAI API, and then deliver a tailored response back to the user via the form. It showcases conditional logic to handle different scenarios based on the OpenAI response.

What it does

  1. Listens for Form Submissions: The workflow starts when a user submits data through an n8n form.
  2. Processes Input with OpenAI: It sends the submitted data to the OpenAI API (likely for text generation or analysis, although the specific prompt is not visible in the JSON).
  3. Applies Conditional Logic: It evaluates the response received from OpenAI using an "If" node.
  4. Responds to the User: Based on the outcome of the conditional logic, it sends a specific response back to the user who submitted the form.

Prerequisites/Requirements

  • n8n Instance: A running instance of n8n.
  • OpenAI API Key: An API key for OpenAI, configured as a credential in your n8n instance.

Setup/Usage

  1. Import the Workflow:
    • Copy the provided JSON code.
    • In your n8n instance, click "New" to create a new workflow.
    • Go to the "Workflows" menu, click "Import from JSON", and paste the workflow JSON.
  2. Configure Credentials:
    • Locate the "OpenAI" node.
    • Click on the "Credential" field and select your existing OpenAI API credential or create a new one if you haven't already.
  3. Configure the Form Trigger:
    • Open the "On form submission" node.
    • Define the fields you want in your form. Ensure the field names match what the OpenAI node expects as input.
  4. Configure OpenAI Node:
    • Open the "OpenAI" node.
    • Review and adjust the "Operation" (e.g., "Chat", "Completion") and the "Prompt" or "Messages" to suit your specific use case. This is where you define what question or task you're giving to OpenAI based on the form input.
  5. Configure the "If" Node:
    • Open the "If" node.
    • Define the conditions based on the expected output from the OpenAI node. For example, you might check if the OpenAI response contains a certain keyword or meets a length requirement.
  6. Configure "Respond to Webhook" Nodes:
    • Open each "Respond to Webhook" node (connected to the "True" and "False" branches of the "If" node).
    • Customize the "Response Data" to send back appropriate messages to the user based on whether the condition was met or not.
  7. Activate the Workflow:
    • Click the "Activate" toggle in the top right corner of the n8n editor to enable the workflow.
  8. Share the Form:
    • Go back to the "On form submission" node.
    • Copy the "Form URL" and share it with users. When they submit the form, the workflow will execute.

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