Intelligent Document Q&A with AI Agents and Vector Stores
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Unlock the power of your documents with this n8n workflow. It leverages AI agents and vector stores to enable natural language querying of your uploaded files. Easily extract information and get answers directly from your data.
About This Workflow
This n8n workflow automates the process of creating an intelligent Q&A system for your documents. It begins by ingesting files from Google Drive, processing them with recursive text splitting, and then embedding them using Cohere. These embeddings are stored in a Qdrant vector database for efficient similarity search. An AI Agent, powered by DeepSeek, is then configured with memory and the ability to search your vector store. This allows users to ask natural language questions and receive accurate answers derived directly from your documents. The workflow also includes steps for cleaning up previous collections and creating new documents, ensuring a seamless and repeatable process for building powerful knowledge bases.
Key Features
- AI-Powered Document Analysis: Utilize advanced AI agents to understand and process your documents.
- Vector Store Integration: Leverage Qdrant for efficient similarity searches and retrieval of relevant information.
- Natural Language Querying: Ask questions in plain English and get direct answers from your data.
- Google Drive Connectivity: Seamlessly integrate with Google Drive to source your documents.
- Configurable AI Memory: Enhance conversational context with simple memory buffering.
How To Use
- Trigger Setup: Configure the
File Creatednode to monitor your Google Drive for new files. - Document Ingestion: The
Google Drivenode will fetch the newly created file. - Text Splitting: The
Recursive Character Text Splitternode will break down the document into manageable chunks. - Embedding Generation: Use the
Embeddings Coherenode to convert text chunks into numerical vector representations. - Vector Storage: Store these embeddings in
Qdrant Vector Storefor efficient retrieval. - AI Agent Configuration: Set up the
AI AgentwithSimple Memoryand configureqdrant_searchas a tool. - Question Answering: The
Question and Answer Chainnode will process user queries, and theAI Agentwill use the vector store to find relevant information. - Response Generation: The
Responsenode will format the AI's answer. - Cleanup: The
Delete Collectionnode can be used to manage your Qdrant collections.
Apps Used
Workflow JSON
{
"id": "2e904cdc-b26e-4916-b780-50e9862e9240",
"name": "Intelligent Document Q&A with AI Agents and Vector Stores",
"nodes": 15,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 2e904cdc-b26e...
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