AI-Powered Knowledge Base & Smart Job Data Processing
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This workflow automates the creation of an AI-powered knowledge base by extracting and vectorizing documents from Google Drive using OpenAI and Supabase. It also enables intelligent processing of job links received via Telegram, preparing data for AI extraction and potentially enriching it with context from the knowledge base.
About This Workflow
This n8n workflow offers a powerful solution for automating knowledge management and intelligent data processing. It seamlessly integrates Google Drive, OpenAI, and Supabase to build a dynamic, vector-based knowledge base. Documents from a specified Google Drive folder are automatically retrieved, processed, split into manageable chunks, embedded using OpenAI, and stored in a Supabase vector database. This creates a robust semantic search index. Additionally, the workflow can ingest job links from Telegram, preparing them for AI extraction of details like job type and categories, and can potentially leverage the established knowledge base for deeper insights into related company information. This dual functionality transforms raw data into actionable intelligence, streamlining both document management and smart content analysis.
Key Features
- Automated Google Drive Document Ingestion: Automatically searches for and downloads documents from a specified Google Drive folder.
- AI-Powered Text Vectorization: Utilizes OpenAI Embeddings to convert document content into vector representations for advanced semantic search.
- Supabase Vector Store Integration: Stores document chunks and their embeddings in a Supabase database, forming a scalable and queryable knowledge base.
- Smart Document Chunking: Employs a Recursive Character Text Splitter to optimize document processing for effective embedding and retrieval.
- Telegram-Triggered Job Link Processing: Initiates the workflow automatically upon receiving new job links or messages via Telegram, preparing them for further analysis.
- Dynamic Data Mapping: Maps extracted job categories and types to predefined IDs, likely after an AI model has processed the job description (implied by connected nodes).
How To Use
- Configure Google Drive: Set up your Google Drive credentials and specify the folder ID (e.g., 'GPT') where your source documents are located in the 'Search File' node.
- Set Up OpenAI: Provide your OpenAI API credentials in the 'Embeddings OpenAI' nodes for generating text embeddings.
- Integrate Supabase: Configure your Supabase API credentials in both 'Supabase Vector Store' nodes and ensure the
documentstable exists in your database to store the vectors. - Activate Telegram Trigger: Set up your Telegram Bot credentials for the '📥 New Job Link via Telegram' node and deploy the webhook to start receiving messages.
- Adjust Job Data Mapping: Review and customize the JavaScript code within the '🧮 Map Job Type & Category IDs' node to align with your specific category and job type IDs, referencing the output of your upstream AI extraction node (e.g., '🧠 Extract Job Data with GPT').
- Run the Workflow: Manually execute the Google Drive ingestion path (nodes: 'Search File' -> 'Loop Over Items' -> 'Get Data' -> 'Default Data Loader' -> 'Recursive Character Text Splitter' -> 'Embeddings OpenAI' -> 'Supabase Vector Store') to initially populate your knowledge base. The Telegram branch will run automatically upon receiving messages.
Apps Used
Workflow JSON
{
"id": "0b7c42ba-f886-4e06-8603-efa1012b632e",
"name": "AI-Powered Knowledge Base & Smart Job Data Processing",
"nodes": 14,
"category": "Operations",
"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: 0b7c42ba-f886...
About the Author
SaaS_Connector
Integration Guru
Connecting CRM, Notion, and Slack to automate your life.
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