📖 Answer HR policy questions in Telegram with Groq, Gemini and Google Drive
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Description
Quick overview
This workflow indexes an HR policy PDF from Google Drive into an in-memory vector store using Google Gemini embeddings, then answers employee questions sent via Telegram using a Groq chat model with retrieval-augmented generation.
How it works
- Manually runs to download the HR policy PDF from Google Drive.
- Splits and loads the PDF content, generates embeddings with Google Gemini, and inserts the chunks into an in-memory vector store.
- Triggers when a new Telegram message is received by your bot.
- Uses a Groq chat model with per-chat conversation memory and a vector-store search tool to retrieve relevant HR policy passages and generate a grounded response.
- Sends the generated answer back to the originating Telegram chat.
Setup
- Create a Telegram bot with @BotFather and add your bot token as Telegram credentials in n8n.
- Add Google Drive OAuth credentials and select the HR policy PDF file to download.
- Add a Google Gemini API key for embeddings and a Groq API key for the chat model.
- Run the manual “Load knowledge base” trigger once to index the PDF, and re-run it whenever the document changes or n8n restarts (the in-memory store resets).
Requirements
- • Telegram bot token (from @BotFather)
- • Google Drive account with your HR policy PDF
- • Google Gemini API key (embeddings)
- • Groq API key (chat model)
Customization
- • Edit the system message in the “HR Policy Agent” node to change the tone, language or word limit.
- • Replace the PDF with any other document, such as an employee handbook, IT FAQ or product documentation.
- • Swap the Groq model for OpenAI, Anthropic or any other chat model node.
- • Replace the in-memory vector store with Pinecone, Qdrant, Supabase or PGVector for persistent production use.
Additional info
The in-memory vector store is cleared when n8n restarts. Re-run the “Load knowledge base” trigger after a restart, or switch to a persistent vector store. Use the same embedding model for inserting and retrieving documents.
🔗 Nodes Used
Telegram, Telegram Trigger, Google Drive, AI Agent, Simple Memory, Simple Vector Store
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File