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Update app.py
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app.py
CHANGED
@@ -2,6 +2,46 @@ import gradio as gr
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from openai import OpenAI
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import time
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def generate_questions(api_key, role, experience):
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if not api_key:
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return "[ERROR] Please enter your OpenRouter API key"
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@@ -75,23 +115,48 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Tab("Interview Setup"):
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with gr.Tab("Practice Session"):
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with gr.Tab("Feedback"):
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generate_btn.click(
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fn=generate_questions,
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inputs=[api_key, role, experience],
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from openai import OpenAI
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import time
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# Predefined examples
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SETUP_EXAMPLES = [
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["AI Engineer", "Mid-level"],
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["Data Scientist", "Senior"],
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["ML Engineer", "Entry-level"]
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]
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PRACTICE_EXAMPLES = [
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[
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# Sample Questions
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"""Technical Questions:
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1. Can you explain the difference between supervised and unsupervised learning?
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2. How do you handle imbalanced datasets in machine learning?
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3. Can you describe a project where you used deep learning techniques?
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4. How do you evaluate the performance of a machine learning model?
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5. Can you explain the concept of overfitting and how to prevent it?
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Behavioral Questions:
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1. Can you describe a time when you had to work on a project with a tight deadline?
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2. Tell me about a time when you faced a technical challenge during a project.
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3. Can you give an example of teamwork experience?""",
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# Sample Answer
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"""### 1. **Supervised vs Unsupervised Learning**
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Supervised learning uses labeled data to train models, while unsupervised learning finds patterns in unlabeled data...
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### 2. **Handling Imbalanced Data**
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Techniques include resampling, class weighting, and using appropriate evaluation metrics...
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[Rest of the sample answer...]"""
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]
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]
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FEEDBACK_EXAMPLE = [
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"""**Feedback on Candidate's Answers**
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**1. Supervised vs Unsupervised Learning**
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Clarity: Clear explanation with good examples...
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[Rest of the sample feedback...]"""
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]
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def generate_questions(api_key, role, experience):
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if not api_key:
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return "[ERROR] Please enter your OpenRouter API key"
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)
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with gr.Tab("Interview Setup"):
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with gr.Row():
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with gr.Column():
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role = gr.Textbox(label="Desired Job Role")
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experience = gr.Dropdown(
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label="Experience Level",
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choices=["Entry-level", "Mid-level", "Senior", "Executive"],
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value="Mid-level"
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)
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generate_btn = gr.Button("Generate Questions")
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# Setup examples
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gr.Examples(
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examples=SETUP_EXAMPLES,
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inputs=[role, experience],
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label="Click any example to load setup:"
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)
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with gr.Tab("Practice Session"):
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with gr.Row():
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with gr.Column():
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questions = gr.Textbox(label="Generated Questions", lines=10, interactive=False)
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answer = gr.Textbox(label="Your Answer", lines=8, placeholder="Type your response here...")
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feedback_btn = gr.Button("Get Feedback")
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# Practice examples
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gr.Examples(
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examples=PRACTICE_EXAMPLES,
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inputs=[questions, answer],
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label="Click to load example Q&A:"
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)
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with gr.Tab("Feedback"):
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with gr.Row():
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feedback = gr.Textbox(label="Expert Feedback", lines=12, interactive=False)
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# Feedback example
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gr.Examples(
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examples=FEEDBACK_EXAMPLE,
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inputs=[feedback],
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label="Example Feedback:"
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)
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generate_btn.click(
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fn=generate_questions,
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inputs=[api_key, role, experience],
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