Automated Interview Scheduler with RAG Agent
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This n8n workflow automates interview scheduling by leveraging a Webhook Trigger, Langchain's RAG Agent, and Weaviate for vector storage. It processes incoming requests, retrieves relevant context, and logs the outcome to a Google Sheet.
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About This Workflow
Overview
This n8n workflow is designed to automate the process of scheduling interviews. It utilizes a RAG (Retrieval-Augmented Generation) Agent powered by Langchain to process incoming interview requests. The workflow starts with a Webhook Trigger that receives interview details. These details are then processed through a Text Splitter and Embeddings node before being stored in Weaviate, a vector database. When a new request comes in, the Weaviate Query and Vector Tool nodes retrieve relevant historical interview data. The RAG Agent then uses this retrieved context, along with Window Memory and a Chat Model, to generate an appropriate response or schedule the interview. Finally, the Append Sheet node logs the status to a Google Sheet, and a Slack Alert node is used for error notifications.
Key Features
- Automated Interview Scheduling: Streamlines the interview booking process.
- RAG Agent Integration: Utilizes Langchain's RAG capabilities for context-aware responses.
- Vector Database Integration: Employs Weaviate to store and retrieve interview-related data for better context.
- Webhook Trigger: Enables external systems to initiate the scheduling process.
- Google Sheets Logging: Automatically logs interview statuses for record-keeping.
- Slack Error Alerts: Notifies the team of any issues during the process.
How To Use
- Set up Credentials: Configure your OpenAI API and Weaviate API credentials within n8n.
- Configure Google Sheets: Ensure your Google Sheet is set up with a 'Log' sheet name and provide the correct
SHEET_ID. - Set up Webhook: Activate the
Webhook Triggerand use the provided URL to send interview request data. - Adjust Text Splitter and Embeddings: Fine-tune the
Text Splitterparameters (chunk size, overlap) and select the appropriate embedding model if needed. - Define Weaviate Index: Ensure the
indexNameinWeaviate InsertandWeaviate Querynodes matches your Weaviate index. - Customize RAG Agent Prompt: Modify the
RAG Agentnode'stextparameter andsystemMessageto suit your specific interview scheduling needs. - Test the Workflow: Send a test request to the webhook URL to verify the entire process from trigger to logging.
Apps Used
Workflow JSON
{
"id": "fb7afb16-c26a-4fa0-95ed-b16bfc6b7e23",
"name": "Automated Interview Scheduler with RAG Agent",
"nodes": 0,
"category": "Automation",
"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: fb7afb16-c26a...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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