Multi-Source RAG System with GPT-4 Turbo, News & Academic Papers Integration

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Built by vinci-king-01 vinci-king-01
Created on June 05, 2026

Description

Multi-Source RAG System with GPT-4 Turbo, News & Academic Papers Integration

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

Form Input - Collects user queries with customizable search scope, response style, and language preferences
Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents)
Data Aggregation - Unifies and processes information from multiple sources with quality scoring
AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses
Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.)
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
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

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

Keep detailed configuration notes in sticky notes inside your workflow

Nodes Used (3)

Code
n8n-nodes-base.code
HTTP Request
n8n-nodes-base.httpRequest
OpenAI
n8n-nodes-base.openAi