Build an Endless AI Interviewer with n8n and Langchain
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Automate in-depth interviews with an AI agent that dynamically generates questions and learns from user responses. This workflow leverages n8n and Langchain to create an engaging and insightful interview experience.
About This Workflow
This n8n workflow empowers you to create an intelligent, AI-driven interviewer that can conduct virtually endless interviews. Designed for gathering deep insights, it uses the power of Langchain to generate contextually relevant, follow-up questions based on user input. The workflow starts with a simple form to initiate the interview, then enters a loop where the AI poses questions and records the user's answers. This process continues until the user explicitly signals to stop, ensuring comprehensive data collection. Session data is managed for scalability and persistence, allowing for flexible deployment.
Key Features
- Dynamic AI Question Generation: An AI agent creates an unending series of open-ended and follow-on questions.
- Form-Based Interview Flow: User responses are captured through an integrated form trigger.
- Intelligent Answer Handling: Captures user answers and uses them to inform subsequent questions.
- Scalable Session Management: Utilizes Redis (via Upstash or standard) for robust session storage.
- Interview Control: Users can easily stop the interview by indicating their preference.
How To Use
- Setup Interview Trigger: Configure the
Start Interviewnode (Form Trigger) with your desired form title, description, and fields. This node acts as the entry point, collecting initial information like the interviewee's name. - Configure AI Researcher: Integrate the
AI Researchernode (Langchain Agent) to handle the dynamic question generation. Ensure it's set up to receive input from the previous node and output questions. - Conditional Interview Flow: Utilize the
Stop Interview?node (If node) to check if the user has indicated they want to end the interview. This is crucial for breaking the loop. - Record Interview Data: Use
Generate RowandGenerate Row1(Set nodes) to structure and store interview data. One path handles continuing the interview (recording question and answer), while the other handles the "stop" scenario. - Manage Session Data: Employ the
Clear For Next Interviewnode (Langchain Memory Manager) to manage session data, ensuring it's cleared appropriately after an interview or after a set period. - Send Reply: Configure the
Send Reply To Agentnode (Set node) to send the AI's generated answer or a concluding message back to the interviewee.
Apps Used
Workflow JSON
{
"id": "1ff5c06e-155c-4762-aaad-153bd36a37bd",
"name": "Build an Endless AI Interviewer with n8n and Langchain",
"nodes": 6,
"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: 1ff5c06e-155c...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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