The Adaptive AI Interview Assistant is a Streamlit-based application that conducts AI-driven interviews, evaluates responses using Google's Gemini API, and provides feedback with an ML-based similarity score.
- Adaptive Question Generation: Generates interview questions based on job title and confidence level.
- AI-Powered Answer Evaluation: Uses Google's Gemini API to evaluate answers.
- ML-Based Scoring: Calculates similarity scores using TF-IDF and cosine similarity.
- SQLite Database Integration: Stores interview details and responses for review.
- User-Friendly UI: Built with Streamlit for an interactive experience.
git clone https://github.com/yourusername/adaptive-ai-interview.git
cd adaptive-ai-interviewpython -m venv venv
source venv/bin/activate # On macOS/Linux
venv\Scripts\activate # On Windowspip install -r requirements.txtCreate a .env file in the project root and add:
GEMINI_API_KEY=your_google_gemini_api_key
streamlit run app.py├── app.py # Main Streamlit app
├── interview_system.py # AdaptiveInterviewSystem class
├── .env # Environment variables (excluded in Git)
├── .gitignore # Ignore sensitive files
├── requirements.txt # Required dependencies
├── README.md # Documentation
- Enter the Job Title and select Confidence Level.
- Answer generated questions.
- View AI evaluation and similarity score.
- Review interview rounds and save results.
- Ensure
.envis not committed to GitHub (already added in.gitignore). - Replace the placeholder
GEMINI_API_KEYwith a valid key.
- Multi-round interview customization.
- Speech-to-text for answer input.
- Integration with other AI models.
Feel free to fork this repo, create issues, or submit pull requests!
This project is licensed under the MIT License.