Automate RAG Chatbot for Company Documents with Google Drive and Gemini
This workflow automates a Retrieval Augmented Generation (RAG) chatbot that answers employee questions using company documents stored in Google Drive. It indexes documents in a Pinecone vector database, ensuring the chatbot provides accurate and up-to-date responses using Google's Gemini AI.
The workflow leverages Google Drive triggers to detect new or updated documents, which are then processed and indexed in Pinecone. Google's Gemini AI generates embeddings and responses, enabling the chatbot to deliver precise answers based on the most current document information. This setup enhances employee access to company knowledge, streamlining information retrieval.
- Platform
- n8n
- Category
- AI
- Price
- $14.99
- Creator
- Chiara Romano
- stickyNote
- googleDrive
- agent
- googleDriveTrigger
- chatTrigger
- toolVectorStore
- lmChatGoogleGemini
- memoryBufferWindow
- vectorStorePinecone
- embeddingsGoogleGemini
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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