An AI-powered interview practice platform built with ElevenLabs Conversational AI SDK.
ai-mock-interview-demo.mp4
- 🎯 Any interview topic and difficulty level
- ⚡️ Instant feedback on your answers
- ✨ Personalized suggestions to improve your answers
- 📊 Final score and a detailed report of your interview
- Node.js 16 or higher
- pnpm installed globally
- An ElevenLabs account
- Set-up a Conversational AI agent in ElevenLabs Guide.
- Enable overrides in agent Settings => Security => Enable overrides.
- Add the following client-tools:
-
name:
triggerName- Description: When the person tells you their name, call this function to store in memory.
- Parameter 1:
- Data type: String
- Identifier: name
- Description: The name of the user.
-
name:
triggerQuestionAsked- Description: When you ask a new interview question, call this function.
- Parameter 1:
- Data type: String
- Identifier: questionId
- Description: A unique identifier for the question (e.g., "q1").
- Parameter 2:
- Data type: String
- Identifier: questionText
- Description: The full text of the question being asked.
-
name:
triggerAnswerFeedback- Description: After getting an answer from the user, call this function.
- Parameter 1:
- Data type: String
- Identifier: questionId
- Description: The ID of the question being answered.
- Parameter 2:
- Data type: String
- Identifier: answer
- Description: The answer provided by the user.
- Parameter 3:
- Data type: String
- Identifier: feedback
- Description: Your feedback on the answer.
- Parameter 4:
- Data type: Number
- Identifier: score
- Description: A score from 1-10 for the answer.
- Parameter 5:
- Data type: Array
- Identifier: suggestions
- Description: Specific suggestions for improving the answer.
- Array items:
- Data type: String
- Description: A suggestion for improving the answer.
-
name:
triggerInterviewComplete- Description: When providing the final assessment, call this function.
- Parameter 1:
- Data type: Number
- Identifier: overallScore
- Description: The overall interview score (1-10).
- Parameter 2:
- Data type: Array
- Identifier: strengths
- Description: Key strengths demonstrated during the interview.
- Array items:
- Data type: String
- Description: A strength demonstrated by the candidate.
- Parameter 3:
- Data type: Array
- Identifier: areasForImprovement
- Description: Areas where the candidate needs improvement.
- Array items:
- Data type: String
- Description: An area where the candidate needs improvement.
- Parameter 4:
- Data type: Array
- Identifier: nextSteps
- Description: Recommended next steps for preparation.
- Array items:
- Data type: String
- Description: A recommended next step for preparation.
pnpm installcp .env.example .env- Add your
AGENT_ID&XI_API_KEYto the.envfile pnpm run dev
This project is licensed under the MIT License - see the LICENSE file for details.