import gradio as gr
from openai import OpenAI
import time

# Predefined examples
SETUP_EXAMPLES = [
    ["AI Engineer", "Mid-level"],
    ["Data Scientist", "Senior"],
    ["ML Engineer", "Entry-level"]
]

PRACTICE_EXAMPLES = [
    [
        # Sample Questions
        """Technical Questions:
1. Can you explain the difference between supervised and unsupervised learning?
2. How do you handle imbalanced datasets in machine learning?
3. Can you describe a project where you used deep learning techniques?
4. How do you evaluate the performance of a machine learning model?
5. Can you explain the concept of overfitting and how to prevent it?

Behavioral Questions:
1. Can you describe a time when you had to work on a project with a tight deadline?
2. Tell me about a time when you faced a technical challenge during a project.
3. Can you give an example of teamwork experience?""",
        
        # Sample Answer
        """### 1. **Supervised vs Unsupervised Learning**
Supervised learning uses labeled data to train models, while unsupervised learning finds patterns in unlabeled data...

### 2. **Handling Imbalanced Data**
Techniques include resampling, class weighting, and using appropriate evaluation metrics...

[Rest of the sample answer...]"""
    ]
]

FEEDBACK_EXAMPLE = [
    """**Feedback on Candidate's Answers**
**1. Supervised vs Unsupervised Learning**
Clarity: Clear explanation with good examples...
[Rest of the sample feedback...]"""
]

def generate_questions(api_key, role, experience):
    if not api_key:
        return "[ERROR] Please enter your OpenRouter API key"
    
    client = OpenAI(
        base_url="https://openrouter.ai/api/v1",
        api_key=api_key,
    )
    
    try:
        completion = client.chat.completions.create(
            extra_headers={
                "HTTP-Referer": "http://localhost:7860",
                "X-Title": "AI Mock Interview",
            },
            model="deepseek/deepseek-v3-base:free",
            messages=[
                {
                    "role": "system",
                    "content": "You are a professional interview coach. Generate relevant interview questions.",
                },
                {
                    "role": "user",
                    "content": f"Act as an interviewer for a {role} position requiring {experience} experience. Generate 5 technical questions and 3 behavioral questions. Present them in a numbered list."
                }
            ]
        )
        return completion.choices[0].message.content
    except Exception as e:
        return f"[ERROR] API call failed: {str(e)}"

def get_feedback(api_key, questions, answer):
    if not api_key:
        return "[ERROR] Please enter your OpenRouter API key"
    
    client = OpenAI(
        base_url="https://openrouter.ai/api/v1",
        api_key=api_key,
    )
    
    try:
        completion = client.chat.completions.create(
            extra_headers={
                "HTTP-Referer": "http://localhost:7860",
                "X-Title": "AI Mock Interview",
            },
            model="deepseek/deepseek-v3-base:free",
            messages=[
                {
                    "role": "system",
                    "content": "You are an interview coach analyzing candidate responses.",
                },
                {
                    "role": "user",
                    "content": f"Interview questions:\n{questions}\n\nCandidate answer:\n{answer}\n\nProvide constructive feedback focusing on: clarity, relevance, technical accuracy, and suggestions for improvement. Structure your feedback with clear sections."
                }
            ]
        )
        return completion.choices[0].message.content
    except Exception as e:
        return f"[ERROR] API call failed: {str(e)}"

with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# AI Mock Interview Practice 🤖💼")
    
    with gr.Row():
        api_key = gr.Textbox(
            label="OpenRouter API Key",
            placeholder="Enter your API key here",
            type="password"
        )
    
    with gr.Tab("Interview Setup"):
        with gr.Row():
            with gr.Column():
                role = gr.Textbox(label="Desired Job Role")
                experience = gr.Dropdown(
                    label="Experience Level",
                    choices=["Entry-level", "Mid-level", "Senior", "Executive"],
                    value="Mid-level"
                )
                generate_btn = gr.Button("Generate Questions")
                
                # Setup examples
                gr.Examples(
                    examples=SETUP_EXAMPLES,
                    inputs=[role, experience],
                    label="Click any example to load setup:"
                )

    with gr.Tab("Practice Session"):
        with gr.Row():
            with gr.Column():
                questions = gr.Textbox(label="Generated Questions", lines=10, interactive=False)
                answer = gr.Textbox(label="Your Answer", lines=8, placeholder="Type your response here...")
                feedback_btn = gr.Button("Get Feedback")
                
                # Practice examples
                gr.Examples(
                    examples=PRACTICE_EXAMPLES,
                    inputs=[questions, answer],
                    label="Click to load example Q&A:"
                )

    with gr.Tab("Feedback"):
        with gr.Row():
            feedback = gr.Textbox(label="Expert Feedback", lines=12, interactive=False)
            
            # Feedback example
            gr.Examples(
                examples=FEEDBACK_EXAMPLE,
                inputs=[feedback],
                label="Example Feedback:"
            )

    generate_btn.click(
        fn=generate_questions,
        inputs=[api_key, role, experience],
        outputs=questions
    )
    
    feedback_btn.click(
        fn=get_feedback,
        inputs=[api_key, questions, answer],
        outputs=feedback
    )

if __name__ == "__main__":
    demo.launch()