Generate Contextual Recommendations from Slack Using Pinecone

This advanced Retrieval-Augmented Generation (RAG) automation template for n8n enables contextual, real-time recommendations using Slack messages as input. The workflow extracts referenced documents from Google Drive, performs semantic retrieval from Pinecone, and generates next-step advice using GPT-4 - tailored specifically for executives and knowledge workers. Perfect for AI copilots, Slack-based assistants, or CEO coaching tools, this no-code RAG implementation gives you the building blocks to combine unstructured inputs with memory-augmented intelligence. **What This Template Does** - Triggers from a Slack Message or Mention Monitors a Slack channel using a bot, capturing user input in real-time. - Extracts Key Info from Message GPT-4 parses the message to identify the subject person and Google Drive link (if present). - Downloads File from Google Drive Automatically fetches and extracts PDF content using the built-in extractor. - Retrieves Metadata from Google Sheets & Pinecone Looks up user ID from Google Sheets and retrieves context from Pinecone based on embeddings and reranking. Contextual Response via GPT-4 (RAG) Combines user data and document context to generate a single, actionable next step using a tightly scoped GPT-4 prompt. - Auto-Fixes & Structures Output Ensures formatted response with recommended_action, rationale, and optional risk_note. - Sends Final Output Back to Slack Posts the recommendation directly to the channel as a reply. **Required Integrations** - Slack Bot with channels:history & app_mentions:read - Google Drive OAuth for file fetching - Google Sheets for ID mapping - Pinecone for vector document retrieval - Azure OpenAI or OpenAI GPT-4 for language processing - (Optional) Cohere for reranking results **Ideal Use Cases** - Executive coaching bots (e.g., for CEOs or founders) - Slack-based internal AI assistants - AI-powered document summarization with memory - Actionable recommendations based on real Slack conversations - Enterprise knowledge augmentation from vector DBs **Why This Template Stands Out** 1. Combines live Slack interaction, file ingestion, and Pinecone retrieval into a fully RAG-powered response system. 2. AI prompts are carefully scoped for actionable, context-aware, and time-bound responses. 3. No-code setup with modular components for scaling or adapting to new use cases (e.g., different roles or goals).