import gradio as gr
from huggingface_hub import InferenceClient

client = InferenceClient("Qwen/Qwen2.5-3B-Instruct")

SYSTEM_PROMPT = """You are a brutally honest but helpful senior hiring manager with 15 years of experience.
Your job is to tell candidates EXACTLY why they will be rejected — not a vague match score, but a specific, actionable rejection explanation.

You must output your response in this exact structure:

## ❌ Why You Will Likely Be Rejected
[2-3 specific, direct sentences about the core mismatch]

## 🔍 Top 3 Skill Gaps
1. [Gap 1 — specific technology or skill missing]
2. [Gap 2]
3. [Gap 3]

## 📂 Missing Projects/Experience
- [What kind of project would fill this gap]
- [Another project]
- [Another project]

## 🔑 Missing Keywords (for ATS systems)
[comma-separated list of keywords from the job description not present in the resume]

## 📅 30-Day Improvement Plan
**Week 1:** [Specific action]
**Week 2:** [Specific action]
**Week 3:** [Specific action]
**Week 4:** [Specific action — ideally a project to show]

## 💡 One Honest Verdict
[One sentence: should they apply now, in 3 months, or pivot entirely?]

Be specific. Name actual technologies. Do not be vague. Do not be encouraging unless there is a real reason to be."""


def analyze(resume_text, job_description):
    if not resume_text.strip() or not job_description.strip():
        return "⚠️ Please paste both your resume and the job description."

    user_message = f"""Here is the candidate's resume:
---
{resume_text}
---

Here is the job description they want to apply to:
---
{job_description}
---

Tell them exactly why they will be rejected and what to do about it."""

    response = client.chat_completion(
        messages=[
            {"role": "system", "content": SYSTEM_PROMPT},
            {"role": "user", "content": user_message}
        ],
        max_tokens=1024,
        temperature=0.7,
    )
    return response.choices[0].message.content


EXAMPLE_RESUME = """Name: Priya Sharma
Education: M.S. Computer Science, 2024

Skills: Python, PyTorch, NLP, Transformers, BERT fine-tuning, HuggingFace, scikit-learn, pandas, numpy

Projects:
- Sentiment analysis model on Twitter data using BERT
- Named Entity Recognition system for biomedical text
- Research paper: "Improving low-resource NER with cross-lingual transfer"

Experience:
- ML Research Intern, university NLP lab (6 months)
- TA for Introduction to Machine Learning course"""

EXAMPLE_JD = """Senior ML Engineer — Infrastructure
Company: CloudScale Inc.

Requirements:
- 3+ years deploying ML models at scale in production
- Strong knowledge of Kubernetes, Docker, MLflow
- Experience with distributed training (Horovod, DeepSpeed)
- Familiarity with AWS SageMaker or GCP Vertex AI
- Python, Go, or Rust for systems-level work
- Experience with data pipelines: Spark, Kafka, Airflow
- Nice to have: ONNX optimization, TensorRT, model quantization"""


with gr.Blocks(
    theme=gr.themes.Soft(),
    title="Rejected Before Applying",
    css="""
    .header { text-align: center; margin-bottom: 20px; }
    .warning-box { background: #fff3cd; border-left: 4px solid #ff6b35; padding: 12px; border-radius: 6px; }
    """
) as demo:
    gr.HTML("""
    <div class='header'>
        <h1>💔 Rejected Before Applying</h1>
        <p style='font-size:1.1em; color:#666;'>
            Find out <b>exactly why</b> your resume won't make it — before you waste the application.
        </p>
        <p style='color:#888; font-size:0.9em;'>Powered by Qwen2.5-3B • No data stored • Brutal honesty guaranteed</p>
    </div>
    """)

    with gr.Row():
        with gr.Column():
            resume_input = gr.Textbox(
                label="📄 Your Resume (paste as plain text)",
                placeholder="Paste your resume here — skills, experience, education, projects...",
                lines=15,
                value=EXAMPLE_RESUME
            )
        with gr.Column():
            jd_input = gr.Textbox(
                label="💼 Job Description (paste the full JD)",
                placeholder="Paste the job description here...",
                lines=15,
                value=EXAMPLE_JD
            )

    analyze_btn = gr.Button("🔍 Analyse My Rejection", variant="primary", size="lg")

    output = gr.Markdown(label="Your Rejection Report")

    analyze_btn.click(
        fn=analyze,
        inputs=[resume_input, jd_input],
        outputs=output
    )

    gr.HTML("""
    <div style='text-align:center; margin-top:20px; color:#aaa; font-size:0.85em;'>
        Built for the 🤗 Build Small Hackathon • Small model, real talk
    </div>
    """)

demo.launch()