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Empower employees to instantly access and understand the company’s Code of Conduct via a Slack chatbot, powered by Retrieval-Augmented Generation (RAG) and LLMs.
This workflow is designed for:
This RAG-powered Slack chatbot answers user questions based on your uploaded Code of Conduct PDF using GPT-4 and embedded document chunks. Here's the flow:
Query Data Tool to retrieve relevant document chunks.Prepare your environment:
Upload the Code of Conduct PDF:
Deploy the chatbot:
@CodeBot Can I accept gifts from partners?)Monitor and iterate:
chat:write, users:read, commands)| What to Customize | How to Do It |
|---|---|
| 🔤 Prompt style | Edit the System & User prompts inside the Code Of Conduct Agent node |
| 📄 Document types | Upload additional policy PDFs and tag them differently in metadata |
| 🤖 Agent behavior | Tune GPT temperature or replace with different LLM |
| 💬 Slack interaction | Customize message formats or trigger phrases |
| 📁 Data Store engine | Swap to Pinecone, Weaviate, Supabase, etc. depending on use case |
| 🌐 Multilingual support | Preprocess text and support locale detection via Slack metadata |