import os
import gradio as gr
import openai

# Fix Matplotlib permission issues
os.environ['MPLCONFIGDIR'] = '/tmp/matplotlib'

# Initialize OpenAI
openai.api_key = os.environ.get("OPENAI_API_KEY", "your-api-key")

def generate_prompt(manager, peer, self_review):
    return f"""
Act as an expert HR coach analyzing 360° feedback. Generate a structured development report with these sections:
1. Key Strengths (3-5 bullet points) 💪
2. Growth Areas (3-5 actionable items) 📈
3. Development Plan (2-3 concrete suggestions) 🚀

Feedback Sources:
Manager: {manager or 'No input'}
Peer: {peer or 'No input'}
Self: {self_review or 'No input'}

Guidelines:
- Use empathetic, professional tone
- Connect insights across feedback sources
- Focus on measurable improvements
- Include both technical and soft skills
- Highlight 1 'quick win' priority
- Avoid generic advice - be specific
- Format in markdown with emojis
- Keep output under 300 words
"""

def generate_feedback(manager, peer, self_review):
    """Generate AI feedback summary from all inputs"""
    try:
        prompt = generate_prompt(manager, peer, self_review)
        
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[{"role": "user", "content": prompt}],
            temperature=0.7,
            max_tokens=500
        )
        
        return response.choices[0].message.content
    except Exception as e:
        return f"⚠️ Error generating feedback: {str(e)}"

with gr.Blocks(theme=gr.themes.Soft(), title="360° Feedback AI Coach") as app:
    gr.Markdown("# 🚀 360° Feedback AI Coach")
    gr.Markdown("Get personalized development insights from manager, peer, and self feedback")
    
    with gr.Row():
        with gr.Column():
            manager_input = gr.Textbox(label="Manager Feedback", lines=5, placeholder="Manager's comments...")
            peer_input = gr.Textbox(label="Peer Feedback", lines=5, placeholder="Peer's comments...")
            self_input = gr.Textbox(label="Self Review", lines=5, placeholder="Your self-assessment...")
            
        with gr.Column():
            output = gr.Markdown(label="AI Feedback Summary")
            with gr.Row():
                submit_btn = gr.Button("Generate Report", variant="primary")
                clear_btn = gr.Button("Clear")
    
    gr.Examples(
        examples=[
            ["Strong technical skills but needs improvement in communication", "Always helpful with technical problems", "I need to work on presentation skills"],
            ["Excellent leadership, should delegate more", "Great team player", "Want to improve time management"],
        ],
        inputs=[manager_input, peer_input, self_input],
        label="Example Inputs"
    )
    
    submit_btn.click(
        fn=generate_feedback,
        inputs=[manager_input, peer_input, self_input],
        outputs=output
    )
    
    clear_btn.click(lambda: [None, None, None, None], None, [manager_input, peer_input, self_input, output])

if __name__ == "__main__":
    app.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))