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| import os | |
| import gradio as gr | |
| from dotenv import load_dotenv | |
| import google.generativeai as genai | |
| # Load your Gemini API key from .env | |
| load_dotenv() | |
| api_key = os.getenv("GEMINI_API_KEY") | |
| # Configure Gemini with your API key | |
| genai.configure(api_key=api_key) | |
| # Use the Gemini 1.5 Flash model (fast & free) | |
| model = genai.GenerativeModel("gemini-2.0-flash") | |
| # Main function to generate interview prep | |
| def generate_interview_prep(role): | |
| prompt = f""" | |
| You are a Google-level interviewer preparing candidates for the job role: {role}. | |
| Please provide: | |
| 1. Three real-world interview questions for this role | |
| 2. One sample answer | |
| 3. One practical interview tip | |
| Respond clearly and in numbered format. | |
| """ | |
| try: | |
| response = model.generate_content(prompt) | |
| return response.text | |
| except Exception as e: | |
| return f" Error: {e}" | |
| # Gradio UI | |
| demo = gr.Interface( | |
| fn=generate_interview_prep, | |
| inputs=gr.Textbox(label="Enter Job Role", placeholder="e.g., Prompt Engineer"), | |
| outputs=gr.Textbox(label="AI Interview Prep"), | |
| title=" Gemini-Powered Interview Prep", | |
| description="Enter a job title to receive 3 questions, a sample answer, and one practical tip.", | |
| article=" Made with ❤️ by Mantasha Idrisi • GitHub: [imantasha](https://github.com/imantasha) • Portfolio: [imantasha.github.io](https://imantasha.github.io)" | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| demo.launch() | |