IT support chatbot with Google Drive, Pinecone & Gemini | AI doc processing

This n8n template empowers IT support teams by automating document ingestion and instant query resolution through a conversational AI. It integrates Google Drive, Pinecone, and a Chat AI agent (using Google Gemini/OpenRouter) to transform static support documents into an interactive, searchable knowledge base. With two interlinked workflows—one for processing support documents and one for handling chat queries—employees receive fast, context-aware answers directly from your support documentation.

Overview

Document Ingestion Workflow

• Google Drive Trigger: Monitors a specified folder for new file uploads (e.g., updated support documents).
• File Download & Extraction: Automatically downloads new files and extracts text content.
• Data Cleaning & Text Splitting: Utilizes a Code node to remove line breaks, trim extra spaces, and strip special characters, while a text splitter segments the content into manageable chunks.
• Embedding & Storage: Generates text embeddings using Google Gemini and stores them in a Pinecone vector store for rapid similarity search.

Chat Query Workflow

• Chat Trigger: Initiates when an employee sends a support query.
• Vector Search & Context Retrieval: Retrieves the top relevant document segments from Pinecone based on similarity scores.
• Prompt Construction: A Code node combines the retrieved document snippets with the user’s query into a detailed prompt.
• AI Agent Response: The constructed prompt is sent to an AI agent (using OpenRouter Chat Model) to generate a clear, step-by-step solution.

Key Benefits & Use Case

Imagine a large organization where every IT support document—from troubleshooting guides to system configurations—is stored in a single Google Drive folder. When an employee encounters an issue (e.g., “How do I reset my VPN credentials?”), they simply type the query into a chat interface. Instantly, the workflow retrieves the most relevant context from the ingested documents and provides a detailed, actionable answer. This process reduces resolution times, enhances support consistency, and significantly lightens the load on IT staff.

Prerequisites

• A valid Google Drive account with access to the designated folder.
• A Pinecone account for storing and retrieving text embeddings.
• Google Gemini (or OpenRouter) credentials to power the Chat AI agent.
• An operational n8n instance configured with the necessary nodes and credentials.

Workflow Details

1 Document Ingestion Workflow

• Google Drive Trigger Node:
  • Listens for file creation events in the specified folder.
• Google Drive Download Node:
  • Downloads the newly added file.
• Extract from File Node:
  • Extracts text content from the downloaded file.
• Code Node (Data Cleaning):
  • Cleans the extracted text by removing line breaks, trimming spaces, and eliminating special characters.
• Recursive Text Splitter Node:
  • Segments the cleaned text into manageable chunks.
• Pinecone Vector Store Node:
  • Generates embeddings (via Google Gemini) and uploads the chunks to Pinecone.

2 Chat Query Workflow

• Chat Trigger Node:
  • Receives incoming user queries.
• Pinecone Vector Store Node (Query):
  • Searches for relevant document chunks based on the query.
• Code Node (Context Builder):
  • Sorts the retrieved documents by relevance and constructs a prompt merging the context with the query.
• AI Agent Node:
  • Sends the prompt to the Chat AI agent, which returns a detailed answer.

How to Use

1. Import the Template:
   • Import the template into your n8n instance.
2. Configure the Google Drive Trigger:
   • Set the folder ID (e.g., 1RQvAHIw8cQbtwI9ZvdVV0k0x6TM6H12P) and connect your Google Drive credentials.
3. Set Up Pinecone Nodes:
   • Enter your Pinecone index details and credentials.
4. Configure the Chat AI Agent:
   • Provide your Google Gemini (or OpenRouter) API credentials.
5. Test the Workflows:
   • Validate the document ingestion workflow by uploading a sample support document.
   • Validate the chat query workflow by sending a test query and verifying the returned support information.

Additional Notes

• Ensure all credentials (Google Drive, Pinecone, and Chat AI) are correctly set up and tested before deploying the workflows in production.
• The template is fully customizable. Adjust the text cleaning, splitting parameters, or the number of document chunks retrieved based on your support documentation's size and structure.
• This template not only enhances IT support efficiency but also offers a scalable solution for managing and leveraging growing volumes of support content.