Query PDF Content Using Weaviate and OpenAI for Document Q&A
Upload a PDF and ask questions about its content using Weaviate and OpenAI in n8n. This workflow serves as a template for implementing Retrieval-Augmented Generation (RAG) over your documents.
This workflow facilitates the process of querying PDF documents by leveraging Weaviate's vector storage capabilities and OpenAI's language models. It allows users to upload a PDF, generate embeddings, and perform queries to retrieve contextually grounded answers. The workflow is designed to be extendable, enabling users to adapt it for more complex data pipelines or different document types. It requires a Weaviate cluster, OpenAI API keys, and a self-hosted n8n instance.
- Platform
- n8n
- Category
- AI
- Price
- $14.99
- Creator
- Lucas Dubois
- starter-docker-compose-file
- set
- stickyNote
- formTrigger
- extractFromFile
- chatTrigger
- lmChatOpenAi
- chainRetrievalQa
- embeddingsOpenAi
- vectorStoreWeaviate
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.
Related AI workflows
- Launch Your First AI-Powered Chatbot with Actionable Tools$9.99
- Automate AI Video Creation and YouTube Upload with Google Sheets$14.99
- Build a WhatsApp Assistant with Memory, Google Suite, Multi-AI, Research, and Imaging$24.99
- Automate Blog Post Creation and Publishing with GPT, Leonardo AI, and WordPress$14.99
- Email Agent$500.99
- Automate SEO Keyword Generation with ChatGPT from Google Sheets$3.99
More from Lucas Dubois
Need this deployed? We'll set it up for you.
Our automation experts deploy this workflow in your stack, connect your accounts, and verify it works — or build a custom solution from scratch.