app.py

import os
import re
import markdown
import gradio as gr
from weasyprint import HTML
from markitdown import MarkItDown
from cerebras.cloud.sdk import Cerebras

# Dapatkan API key dari environment variables
api_key = os.environ.get("CEREBRAS_API_KEY")

# Inisialisasi MarkItDown
md_converter = MarkItDown()

def create_prompt(resume_string: str, jd_string: str) -> str:
    """
    Membuat prompt detail untuk AI agar melakukan optimasi resume
    berdasarkan job description.
    """
    return f"""
You are a professional resume optimization expert specializing in tailoring resumes to specific job descriptions. Your goal is to optimize my resume and provide actionable suggestions for improvement to align with the target role.

### Guidelines:
1. **Relevance**:  
   - Prioritize experiences, skills, and achievements **most relevant to the job description**.  
   - Remove or de-emphasize irrelevant details to ensure a **concise** and **targeted** resume.
   - Limit work experience section to 2-3 most relevant roles
   - Limit bullet points under each role to 2-3 most relevant impacts

2. **Action-Driven Results**:  
   - Use **strong action verbs** and **quantifiable results** (e.g., percentages, revenue, efficiency improvements) to highlight impact.  

3. **Keyword Optimization**:  
   - Integrate **keywords** and phrases from the job description naturally to optimize for ATS (Applicant Tracking Systems).  

4. **Additional Suggestions** *(If Gaps Exist)*:  
   - If the resume does not fully align with the job description, suggest:  
     1. **Additional technical or soft skills** that I could add to make my profile stronger.  
     2. **Certifications or courses** I could pursue to bridge the gap.  
     3. **Project ideas or experiences** that would better align with the role.  

5. **Formatting**:  
   - Output the tailored resume in **clean Markdown format**.  
   - Include an **"Additional Suggestions"** section at the end with actionable improvement recommendations.  

---

### Input:
- **My resume**:  
{resume_string}

- **The job description**:  
{jd_string}

---

### Output:  
1. - A resume in **Markdown format** that emphasizes relevant experience, skills, and achievements.  
   - Incorporates job description **keywords** to optimize for ATS.  
   - Uses strong language and is no longer than **one page**.

2. **Additional Suggestions** *(if applicable)*:  
   - List **skills** that could strengthen alignment with the role.  
   - Recommend **certifications or courses** to pursue.  
   - Suggest **specific projects or experiences** to develop.
"""

def get_resume_response(prompt: str, api_key: str, model: str = "llama-3.3-70b", temperature: float = 0.7) -> str:
    """
    Mengirim prompt ke model Cerebras (LLM) dan mengembalikan hasil streaming response.
    """
    client = Cerebras(api_key=api_key)
    stream = client.chat.completions.create(
        messages=[
            {"role": "system", "content": "Expert resume writer"},
            {"role": "user", "content": prompt}
        ],
        model=model,
        stream=True,
        temperature=temperature,
        max_completion_tokens=1024,
        top_p=1
    )

    response_string = ""
    for chunk in stream:
        response_string += chunk.choices[0].delta.content or ""
    return response_string

def remove_unwanted_headings(markdown_text: str) -> str:
    pattern = r'^#+.*\b(?:[Rr]esume|[Oo]ptimized)\b.*$'
    return re.sub(pattern, '', markdown_text, flags=re.MULTILINE)

def fix_jobsdesk_bullets(text: str) -> str:
    """
    Mengubah semua baris yang dimulai dengan tanda '-' (opsional dengan spasi)
    menjadi format bullet list Markdown standar.
    """
    return re.sub(r'^\s*-\s+', '- ', text, flags=re.MULTILINE)

def process_resume(resume, jd_string):
    # Cek ekstensi dan konversi dokumen menggunakan MarkItDown
    supported_extensions = ('.pptx', '.docx', '.pdf', '.jpg', '.jpeg', '.png', '.xlsx')
    if resume.name.lower().endswith(supported_extensions):
        result = md_converter.convert(resume.name)
        resume_string = result.text_content
    else:
        return "File format not supported for conversion to Markdown.", "", "", "", ""
    
    prompt = create_prompt(resume_string, jd_string)
    response_string = get_resume_response(prompt, api_key)
    
    response_list = response_string.split("## Additional Suggestions")
    new_resume = response_list[0].strip()
    new_resume = re.sub(r'^\* ', '- ', new_resume, flags=re.MULTILINE)
    suggestions = "## Additional Suggestions\n\n" + response_list[1].strip() if len(response_list) > 1 else ""
    
    new_resume = new_resume.replace("# Optimized Resume", "")
    new_resume = new_resume.replace("## Optimized Resume", "")
    new_resume = new_resume.replace("Optimized Resume", "")
    new_resume = new_resume.replace("# Resume", "")
    new_resume = new_resume.replace("## Resume", "")
    new_resume = re.sub(r'^#+\s*Resume\s*', '', new_resume, flags=re.MULTILINE)
    new_resume = remove_unwanted_headings(new_resume)
    new_resume = fix_jobsdesk_bullets(new_resume)  # Ubah tanda '-' menjadi bullet list
    
    original_resume_path = "resumes/original_resume.md"
    with open(original_resume_path, "w", encoding='utf-8') as f:
        f.write(resume_string)
    
    optimized_resume_path = "resumes/optimized_resume.md"
    with open(optimized_resume_path, "w", encoding='utf-8') as f:
        f.write(new_resume)
    
    return resume_string, new_resume, original_resume_path, optimized_resume_path, suggestions

def export_resume(new_resume):
    try:
        html_content = markdown.markdown(new_resume, extensions=['extra', 'nl2br'])
        output_pdf_file = "resumes/optimized_resume.pdf"
        HTML(string=html_content).write_pdf(
            output_pdf_file,
            stylesheets=["resumes/style.css"]
        )
        return output_pdf_file
    except Exception as e:
        return f"Failed to export resume: {str(e)} 💔"

# Bagian aplikasi Gradio (sama seperti kode Anda)
with gr.Blocks() as app:
    gr.Markdown("# Resume Optimizer 📄")
    gr.Markdown("Upload your resume, paste the job description, and get actionable insights!")
    
    with gr.Row():
        resume_input = gr.File(label="Upload Your Resume")    
        jd_input = gr.Textbox(
            label="Paste the Job Description Here",
            lines=9,
            interactive=True,
            placeholder="Paste job description..."
        )
    
    run_button = gr.Button("Optimize Resume 🤖")
    
    with gr.Row():
        before_md = gr.Markdown(label="Original Resume (Before)")
        after_md = gr.Markdown(label="Optimized Resume (After)")
        output_suggestions = gr.Markdown(label="Suggestions")
    
    with gr.Row():
        download_before = gr.File(label="Download Original Resume")
        download_after = gr.File(label="Download Optimized Resume")
        
    export_button = gr.Button("Export Optimized Resume as PDF 🚀")
    export_result = gr.File(label="Download PDF")
    
    run_button.click(
        process_resume,
        inputs=[resume_input, jd_input],
        outputs=[before_md, after_md, download_before, download_after, output_suggestions]
    )
    
    export_button.click(
        export_resume,
        inputs=[after_md],
        outputs=[export_result]
    )
    
app.launch()