Automate PDF Q&A System with LlamaIndex, OpenAI, and Pinecone
This workflow automates the process of parsing, normalizing, and storing PDF content for Retrieval-Augmented Generation (RAG) using LlamaIndex, OpenAI embeddings, and Pinecone. Ideal for developers and teams handling structured documents like insurance policies.
The workflow monitors a Google Drive folder for new PDFs, uploads them to LlamaIndex Cloud for parsing, normalizes the text by removing unnecessary elements, and splits it into manageable chunks. These chunks are then embedded using OpenAI and stored in Pinecone for efficient semantic search. A Chat Agent can query Pinecone to retrieve precise answers from the document vector database, making it perfect for creating chatbots or Q&A systems for structured documents.
- Platform
- n8n
- Category
- AI & Machine Learning
- Price
- $14.99
- Creator
- Leo Novak
- if
- code
- wait
- stickyNote
- googleDrive
- httpRequest
- googleDriveTrigger
- embeddingsOpenAi
- vectorStorePinecone
- documentDefaultDataLoader
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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