Build Your Own AI-Powered Q&A System with n8n and LangChain
detail.loadingPreview
Effortlessly create an intelligent Q&A system that can answer questions based on your documents. This workflow leverages n8n and LangChain to ingest data, create vector embeddings, and provide instant, relevant answers to user queries.
About This Workflow
Unlock the power of AI for your data with this comprehensive n8n workflow. It automates the process of setting up a Q&A system that can understand and respond to queries based on a provided PDF document. The workflow begins by fetching a PDF from Google Drive, intelligently splitting it into manageable chunks, and then embedding these chunks into a Qdrant vector store using OpenAI's embedding models. When a user sends a question via webhook, the workflow retrieves relevant information from the vector store and uses an OpenAI language model to generate a concise and accurate answer, which is then returned via webhook. This solution is perfect for building internal knowledge bases, customer support bots, or any application requiring intelligent document analysis.
Key Features
- Automated Document Ingestion: Seamlessly fetch and process documents from Google Drive.
- Intelligent Text Chunking: Efficiently break down large documents for optimal AI processing.
- Vector Database Integration: Store and retrieve document information using Qdrant for fast and accurate Q&A.
- AI-Powered Question Answering: Leverage OpenAI models to understand queries and generate relevant answers.
- Webhook Integration: Easily connect with other applications for sending and receiving data.
How To Use
- Start with the YouTube Tutorial: Watch the provided YouTube video to get a step-by-step walkthrough.
- Configure Google Drive: Set up your Google Drive credentials in n8n and specify the PDF file ID you want to use.
- Set up Qdrant: Ensure your Qdrant instance is running and accessible. Configure the Qdrant API credentials in n8n and define the collection name (e.g., 'crowd').
- Configure OpenAI: Provide your OpenAI API key in n8n to access embedding models and chat models.
- Trigger the Workflow: Manually execute the workflow to ingest the document into the Qdrant vector store.
- Send a Question: Use the provided webhook endpoint (found in the 'Webhook' node) to send user questions. Include an 'input' field in the POST request body.
- Receive the Answer: The workflow will process the question and send the answer back to your webhook.
Apps Used
Workflow JSON
{
"id": "ca92db90-83f0-4a1a-ba4b-6026875f245e",
"name": "Build Your Own AI-Powered Q&A System with n8n and LangChain",
"nodes": 16,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: ca92db90-83f0...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
Statistics
Related Workflows
Discover more workflows you might like
Effortless Bug Reporting: Slack Slash Command to Linear Issue
Streamline your bug reporting process by instantly creating Linear issues directly from Slack using a simple slash command. This workflow enhances team collaboration by providing immediate feedback and a structured approach to logging defects, saving valuable time for development and QA teams.
Automated PR Merged QA Notifications
Streamline your QA process with this automated workflow that notifies your team upon successful Pull Request merges. Leverage AI and vector stores to enrich notifications and ensure seamless integration into your development pipeline.
Visualize Your n8n Workflows: Interactive Dashboard with Mermaid.js
Gain unparalleled visibility into your n8n automation landscape. This workflow transforms your n8n instance into a dynamic, interactive dashboard, leveraging Mermaid.js to visualize all your workflows in one accessible place.