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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 |