backend.py

import os
import docx2txt
import docx
from docx import Document
import openai
from dotenv import load_dotenv
import json
import tempfile
import re

# Add these imports for PDF support
import PyPDF2
import io

# Load environment variables
load_dotenv()

# Set up OpenAI API key
openai.api_key = os.getenv("OPENAI_API_KEY")

# Default model
DEFAULT_MODEL = "gpt-4o"
current_model = DEFAULT_MODEL

# Function to set OpenAI API key
def set_openai_api_key(api_key=None):
    """

    Set the OpenAI API key from the provided key or environment variable.

    

    Args:

        api_key: Optional API key to use. If None, will use the environment variable.

        

    Returns:

        bool: True if API key is set, False otherwise

    """
    if api_key:
        openai.api_key = api_key
        return True
    else:
        env_api_key = os.getenv("OPENAI_API_KEY")
        if env_api_key:
            openai.api_key = env_api_key
            return True
        return False

# Function to set OpenAI model
def set_openai_model(model_name="gpt-4o"):
    """

    Set the OpenAI model to use for API calls.

    

    Args:

        model_name: Name of the model to use (e.g., "gpt-4o", "gpt-4o-mini")

        

    Returns:

        str: The name of the model that was set

    """
    global current_model
    current_model = model_name
    return current_model

# Set up OpenAI API key from environment variable initially
set_openai_api_key()

def extract_text_from_document(file_path):
    """

    Extract text from a document file (DOCX or PDF).

    

    Args:

        file_path: Path to the document file

        

    Returns:

        str: Extracted text from the document

    """
    try:
        # Check file extension
        if file_path.lower().endswith('.docx'):
            # Extract text from DOCX
            return docx2txt.process(file_path)
        elif file_path.lower().endswith('.pdf'):
            # Extract text from PDF
            text = ""
            with open(file_path, 'rb') as file:
                pdf_reader = PyPDF2.PdfReader(file)
                for page_num in range(len(pdf_reader.pages)):
                    page = pdf_reader.pages[page_num]
                    text += page.extract_text() + "\n\n"
            return text
        else:
            raise ValueError(f"Unsupported file format: {os.path.splitext(file_path)[1]}")
    except Exception as e:
        print(f"Error extracting text from document: {e}")
        return None

def parse_resume(file_path):
    """

    Parse a resume file and extract its content.

    

    Args:

        file_path: Path to the resume file

        

    Returns:

        str: Extracted text from the resume

    """
    try:
        return extract_text_from_document(file_path)
    except Exception as e:
        print(f"Error parsing resume: {e}")
        return None

def analyze_resume_job_match(resume_text, job_description, creativity_level=30):
    """

    Analyze the match between a resume and job description using GPT-4o.

    

    Args:

        resume_text: Raw text of the resume

        job_description: Job description text

        creativity_level: Level of creativity/modification allowed (0-100)

        

    Returns:

        dict: Analysis results including match percentage, gaps, and suggestions

    """
    try:
        print(f"Analyzing resume match with creativity level: {creativity_level}")
        print(f"Resume text length: {len(resume_text)}")
        print(f"Job description length: {len(job_description)}")
        
        # Adjust system message based on creativity level
        if creativity_level < 20:
            system_message = "You are a conservative resume analyzer. Focus only on exact matches between the resume and job description. Be strict in your evaluation."
        elif creativity_level < 50:
            system_message = "You are a balanced resume analyzer. Evaluate the resume against the job description with a moderate level of flexibility, recognizing transferable skills."
        elif creativity_level < 80:
            system_message = "You are a creative resume analyzer. Be generous in your evaluation, recognizing potential and transferable skills even when not explicitly stated."
        else:
            system_message = "You are an optimistic resume analyzer. Focus on potential rather than exact matches. Be very generous in your evaluation and provide ambitious suggestions for improvement."
        
        prompt = f"""

        Analyze the following resume and job description:

        

        RESUME:

        {resume_text}

        

        JOB DESCRIPTION:

        {job_description}

        

        CREATIVITY LEVEL: {creativity_level}% (where 0% means strictly factual and 100% means highly creative)

        

        Provide a detailed analysis in JSON format with the following structure:

        1. "match_percentage": A numerical percentage (0-100) representing how well the resume matches the job description. Use job skills keyword used in job description to match with the contents of the resume to come up with the match percentage.

        2. "key_matches": List of skills and experiences in the resume that match the job requirements.

        3. "gaps": List of skills or experiences mentioned in the job description that are missing from the resume.

        4. "suggestions": Specific suggestions to improve the resume for this job. Ensure the suggestions are based on the job description and the resume and contain the exact keywords from the job description.

        5. "summary": A brief summary of the overall match and main recommendations.

        6. "skill_breakdown": An object containing categories of skills from the job description and how well the candidate matches each category:

           - "technical_skills": Assessment of technical skills match (percentage and comments)

           - "experience": Assessment of experience requirements match (percentage and comments)

           - "education": Assessment of education requirements match (percentage and comments)

           - "soft_skills": Assessment of soft skills/leadership match (percentage and comments)

        

        Adjust your analysis based on the creativity level. Higher creativity means being more generous with matches and more ambitious with suggestions.

        

        IMPORTANT: For each resume, provide a unique and accurate match percentage based on the actual content. Do not use the same percentage for different resumes. The excellent match resume should have a high percentage (80-95%), good match should be moderate-high (65-80%), average match should be moderate (40-65%), and poor match should be low (below 40%).

        

        Return ONLY the JSON object without any additional text.

        """
        
        response = openai.chat.completions.create(
            model=current_model,
            messages=[
                {"role": "system", "content": system_message},
                {"role": "user", "content": prompt}
            ],
            response_format={"type": "json_object"}
        )
        
        analysis = json.loads(response.choices[0].message.content)
        print(f"Analysis complete. Match percentage: {analysis.get('match_percentage', 0)}%")
        return analysis
    
    except Exception as e:
        print(f"Error analyzing resume: {e}")
        return {
            "match_percentage": 0,
            "key_matches": [],
            "gaps": ["Error analyzing resume"],
            "suggestions": ["Please try again"],
            "summary": f"Error: {str(e)}",
            "skill_breakdown": {
                "technical_skills": {"percentage": 0, "comments": "Error analyzing resume"},
                "experience": {"percentage": 0, "comments": "Error analyzing resume"},
                "education": {"percentage": 0, "comments": "Error analyzing resume"},
                "soft_skills": {"percentage": 0, "comments": "Error analyzing resume"}
            }
        }

def tailor_resume(resume_text, job_description, template_path=None, creativity_level=30, verbosity="elaborate"):
    """

    Generate a tailored resume based on the job description using GPT-4o.

    

    Args:

        resume_text: Raw text of the original resume

        job_description: Job description text

        template_path: Optional path to a resume template

        creativity_level: Level of creativity/modification allowed (0-100)

        verbosity: Level of detail in the resume ('concise' or 'elaborate')

        

    Returns:

        str: Tailored resume content

    """
    try:
        # If a template is provided, read its structure
        template_structure = ""
        template_sections = []
        
        if template_path:
            # Extract the template structure and sections
            doc = Document(template_path)
            for para in doc.paragraphs:
                if para.text.strip():
                    template_structure += para.text + "\n"
                    # Identify section headings (usually in all caps or with specific styles)
                    if para.style.name.startswith('Heading') or para.text.isupper() or (para.runs and para.runs[0].bold):
                        template_sections.append(para.text.strip())
        
        # Adjust system message based on creativity level
        if creativity_level < 20:
            system_message = "You are a conservative resume editor. Only reorganize existing content to better match the job description. Do not add any new experiences or skills that aren't explicitly mentioned in the original resume."
        elif creativity_level < 50:
            system_message = "You are a balanced resume editor. Enhance existing content with better wording and highlight relevant skills. Make minor improvements but keep all content factual and based on the original resume."
        elif creativity_level < 80:
            system_message = "You are a creative resume editor. Significantly enhance the resume with improved wording and may suggest minor additions or extensions of existing experiences to better match the job description."
        else:
            system_message = "You are an aggressive resume optimizer. Optimize the resume to perfectly match the job description, including suggesting new skills and experiences that would make the candidate more competitive, while maintaining some connection to their actual background. Ensure exact keywords are included from the job description in the new resume. "
            
        # Adjust system message based on creativity level and verbosity
        if creativity_level < 20:
            base_message = "You are a conservative resume editor. Only reorganize existing content to better match the job description. Do not add any new experiences or skills that aren't explicitly mentioned in the original resume."
        elif creativity_level < 50:
            base_message = "You are a balanced resume editor. Enhance existing content with better wording and highlight relevant skills. Make minor improvements but keep all content factual and based on the original resume."
        elif creativity_level < 80:
            base_message = "You are a creative resume editor. Significantly enhance the resume with improved wording and may suggest minor additions or extensions of existing experiences to better match the job description."
        else:
            base_message = "You are an aggressive resume optimizer. Optimize the resume to perfectly match the job description, including suggesting new skills and experiences that would make the candidate more competitive, while maintaining some connection to their actual background. Ensure exact keywords are included from the job description in the new resume."
        
        # Add verbosity instructions to the system message
        if verbosity == "concise":
            system_message = base_message + " Create a concise resume with brief bullet points, focusing only on the most relevant information. Aim for a shorter resume that can be quickly scanned by recruiters."
        else:  # elaborate
            system_message = base_message + " Create a detailed resume that thoroughly explains experiences and skills, providing context and specific achievements. Use comprehensive bullet points to showcase the candidate's qualifications."
        
        prompt = f"""

        Create a tailored version of this resume to better match the job description:

        

        ORIGINAL RESUME:

        {resume_text}

        

        JOB DESCRIPTION:

        {job_description}

        

        {("TEMPLATE STRUCTURE TO FOLLOW:" + chr(10) + template_structure) if template_path else ""}

        

        {("TEMPLATE SECTIONS TO INCLUDE:" + chr(10) + chr(10).join(template_sections)) if template_sections else ""}

        

        CREATIVITY LEVEL: {creativity_level}% (where 0% means strictly factual and 100% means highly creative)

        VERBOSITY: {verbosity.upper()} (CONCISE means brief and to-the-point, ELABORATE means detailed and comprehensive)

        

        Create a tailored resume that:

        1. Highlights relevant skills and experiences that match the job description

        2. Uses keywords from the job description

        3. Quantifies achievements where possible

        4. Removes or downplays irrelevant information

        5. Adjusts content based on the specified creativity level

        

        IMPORTANT FORMATTING INSTRUCTIONS:

        - Format your response with clear section headings in ALL CAPS

        - Use bullet points (•) for listing items and achievements

        - If a template is provided, follow its exact section structure and organization

        - Maintain the same section headings as in the template when possible

        - For each section, provide content that matches the requested verbosity level:

          * CONCISE: Use 1-2 line bullet points, focus only on the most relevant achievements

          * ELABORATE: Use detailed bullet points with context and specific metrics

        

        Return the complete tailored resume content in a professional format.

        """
        
        response = openai.chat.completions.create(
            model=current_model,
            messages=[
                {"role": "system", "content": system_message},
                {"role": "user", "content": prompt}
            ]
        )
        
        tailored_resume = response.choices[0].message.content
        return tailored_resume
    
    except Exception as e:
        print(f"Error tailoring resume: {e}")
        return f"Error tailoring resume: {str(e)}"

def create_word_document(content, output_path, template_path=None):
    """

    Create a Word document with the given content, optionally using a template.

    

    Args:

        content: Text content for the document

        output_path: Path to save the document

        template_path: Optional path to a template document to use as a base

        

    Returns:

        bool: Success status

    """
    try:
        # If a template is provided, use it as the base document
        if template_path and os.path.exists(template_path):
            # Create a new document instead of modifying the template directly
            doc = Document()
            original_template = Document(template_path)
            
            # Copy all styles from the template to the new document
            for style in original_template.styles:
                if style.name not in doc.styles:
                    try:
                        doc.styles.add_style(style.name, style.type)
                    except:
                        pass  # Style might already exist or be built-in
            
            # Copy document properties and sections settings
            # We'll only add sections as needed, not at the beginning
            if len(original_template.sections) > 0:
                # Copy properties from the first section
                section = original_template.sections[0]
                # Use the existing first section in the new document
                new_section = doc.sections[0]
                new_section.page_height = section.page_height
                new_section.page_width = section.page_width
                new_section.left_margin = section.left_margin
                new_section.right_margin = section.right_margin
                new_section.top_margin = section.top_margin
                new_section.bottom_margin = section.bottom_margin
                new_section.header_distance = section.header_distance
                new_section.footer_distance = section.footer_distance
                
                # Copy additional sections if needed
                for i in range(1, len(original_template.sections)):
                    section = original_template.sections[i]
                    new_section = doc.add_section()
                    new_section.page_height = section.page_height
                    new_section.page_width = section.page_width
                    new_section.left_margin = section.left_margin
                    new_section.right_margin = section.right_margin
                    new_section.top_margin = section.top_margin
                    new_section.bottom_margin = section.bottom_margin
                    new_section.header_distance = section.header_distance
                    new_section.footer_distance = section.footer_distance
            
            # Copy complex elements like headers and footers
            copy_template_complex_elements(original_template, doc)
            
            # Split content by sections (using headings as delimiters)
            sections = []
            current_section = []
            lines = content.split('\n')
            
            for line in lines:
                line = line.strip()
                if not line:
                    continue
                    
                # Check if this is a heading (all caps or ends with a colon)
                if line.isupper() or (line.endswith(':') and len(line) < 50):
                    if current_section:
                        sections.append(current_section)
                    current_section = [line]
                else:
                    current_section.append(line)
            
            if current_section:
                sections.append(current_section)
            
            # Find template headings to match with our content sections
            template_headings = []
            template_heading_styles = {}
            for para in original_template.paragraphs:
                if para.style.name.startswith('Heading') or para.text.isupper() or (para.runs and para.runs[0].bold):
                    template_headings.append(para.text.strip())
                    template_heading_styles[para.text.strip()] = para.style.name
            
            # Add content to the document with appropriate formatting
            for section in sections:
                if not section:
                    continue
                    
                # First line of each section is treated as a heading
                heading = section[0]
                
                # Try to find a matching heading style from the template
                heading_style = 'Heading 1'  # Default
                for template_heading in template_headings:
                    if template_heading.upper() == heading.upper() or template_heading.upper() in heading.upper() or heading.upper() in template_heading.upper():
                        heading_style = template_heading_styles.get(template_heading, 'Heading 1')
                        break
                
                # Add the heading with the appropriate style
                p = doc.add_paragraph()
                try:
                    p.style = heading_style
                except:
                    p.style = 'Heading 1'  # Fallback
                
                run = p.add_run(heading)
                run.bold = True
                
                # Add the rest of the section content
                for line in section[1:]:
                    if line.startswith('•') or line.startswith('-') or line.startswith('*'):
                        # This is a bullet point
                        p = doc.add_paragraph(line[1:].strip(), style='List Bullet')
                    else:
                        p = doc.add_paragraph(line)
        else:
            # Create a new document with basic formatting
            doc = Document()
            
            # Split content by lines and add to document with basic formatting
            paragraphs = content.split('\n')
            for para in paragraphs:
                para = para.strip()
                if not para:
                    continue
                    
                # Check if this is a heading (all caps or ends with a colon)
                if para.isupper() or (para.endswith(':') and len(para) < 50):
                    p = doc.add_paragraph()
                    p.style = 'Heading 1'
                    run = p.add_run(para)
                    run.bold = True
                elif para.startswith('•') or para.startswith('-') or para.startswith('*'):
                    # This is a bullet point
                    p = doc.add_paragraph(para[1:].strip(), style='List Bullet')
                else:
                    doc.add_paragraph(para)
        
        doc.save(output_path)
        return True
    
    except Exception as e:
        print(f"Error creating Word document: {e}")
        return False

def get_available_templates():
    """

    Get a list of available resume templates from the current working directory.

    

    Returns:

        list: List of template file paths

    """
    # First, copy any templates from templates directory if they don't exist
    #copy_templates_to_current_directory()
    
    templates = []
    
    # Check current directory for templates
    for file in os.listdir("."):
        if file.endswith("_Template.docx") or file.endswith("Template.docx"):
            templates.append(file)
    
    print(f"Found templates in current directory: {templates}")
    return templates

def copy_templates_to_current_directory():
    """

    Copy templates from the templates directory to the current working directory

    if they don't already exist.

    

    Returns:

        list: List of copied template file paths

    """
    copied_templates = []
    templates_dir = "templates"
    
    # Check if templates directory exists
    if not os.path.exists(templates_dir):
        print(f"Templates directory '{templates_dir}' not found.")
        return copied_templates
    
    # Get list of template files in templates directory
    template_files = [f for f in os.listdir(templates_dir) if f.endswith(".docx")]
    
    # Copy each template file to current directory if it doesn't exist
    for template_file in template_files:
        source_path = os.path.join(templates_dir, template_file)
        dest_path = template_file
        
        if not os.path.exists(dest_path):
            try:
                import shutil
                shutil.copy2(source_path, dest_path)
                copied_templates.append(dest_path)
                print(f"Copied template '{template_file}' to current directory.")
            except Exception as e:
                print(f"Error copying template '{template_file}': {e}")
        else:
            print(f"Template '{template_file}' already exists in current directory.")
    
    return copied_templates

def copy_template_complex_elements(source_doc, target_doc):
    """

    Copy complex elements like headers and footers from source document to target document.

    

    Args:

        source_doc: Source Document object

        target_doc: Target Document object

    """
    try:
        # Copy headers and footers
        for i, section in enumerate(target_doc.sections):
            # Skip if source doesn't have this many sections
            if i >= len(source_doc.sections):
                break
                
            # Copy header
            if section.header.is_linked_to_previous == False:
                # Check if there's at least one paragraph in the header
                if len(section.header.paragraphs) == 0:
                    section.header.add_paragraph()
                
                # Copy text and style from source header paragraphs
                for j, para in enumerate(source_doc.sections[i].header.paragraphs):
                    if j < len(section.header.paragraphs):
                        section.header.paragraphs[j].text = para.text
                        try:
                            section.header.paragraphs[j].style = para.style
                        except Exception:
                            pass  # Style might not be compatible
                    else:
                        new_para = section.header.add_paragraph(para.text)
                        try:
                            new_para.style = para.style
                        except Exception:
                            pass
            
            # Copy footer
            if section.footer.is_linked_to_previous == False:
                # Check if there's at least one paragraph in the footer
                if len(section.footer.paragraphs) == 0:
                    section.footer.add_paragraph()
                
                # Copy text and style from source footer paragraphs
                for j, para in enumerate(source_doc.sections[i].footer.paragraphs):
                    if j < len(section.footer.paragraphs):
                        section.footer.paragraphs[j].text = para.text
                        try:
                            section.footer.paragraphs[j].style = para.style
                        except Exception:
                            pass  # Style might not be compatible
                    else:
                        new_para = section.footer.add_paragraph(para.text)
                        try:
                            new_para.style = para.style
                        except Exception:
                            pass
    except Exception as e:
        print(f"Error copying complex elements: {e}")

def create_tailored_resume_from_template(content, template_path, output_path):
    """

    Create a tailored resume by directly modifying a template document.

    This preserves all formatting, tables, and styles from the original template.

    

    Args:

        content: Structured content for the resume (text)

        template_path: Path to the template document

        output_path: Path to save the output document

        

    Returns:

        bool: Success status

    """
    try:
        if not os.path.exists(template_path):
            return False
            
        # Create a copy of the template
        doc = Document(template_path)
        
        # Parse the content into sections
        sections = {}
        current_section = None
        current_content = []
        
        for line in content.split('\n'):
            line = line.strip()
            if not line:
                continue
                
            # Check if this is a heading (all caps or ends with a colon)
            if line.isupper() or (line.endswith(':') and len(line) < 50):
                # Save the previous section
                if current_section and current_content:
                    sections[current_section] = current_content
                
                # Start a new section
                current_section = line
                current_content = []
            else:
                if current_section:
                    current_content.append(line)
        
        # Save the last section
        if current_section and current_content:
            sections[current_section] = current_content
        
        # Find all paragraphs in the template that are headings or potential section markers
        template_sections = {}
        for i, para in enumerate(doc.paragraphs):
            if para.style.name.startswith('Heading') or para.text.isupper() or para.runs and para.runs[0].bold:
                template_sections[para.text.strip()] = i
        
        # Create a new document to avoid duplicate content
        new_doc = Document()
        
        # Copy all styles from the template to the new document
        for style in doc.styles:
            if style.name not in new_doc.styles:
                try:
                    new_doc.styles.add_style(style.name, style.type)
                except:
                    pass  # Style might already exist or be built-in
        
        # Copy document properties and sections settings
        # We'll only add sections as needed, not at the beginning
        if len(doc.sections) > 0:
            # Copy properties from the first section
            section = doc.sections[0]
            # Use the existing first section in the new document
            new_section = new_doc.sections[0]
            new_section.page_height = section.page_height
            new_section.page_width = section.page_width
            new_section.left_margin = section.left_margin
            new_section.right_margin = section.right_margin
            new_section.top_margin = section.top_margin
            new_section.bottom_margin = section.bottom_margin
            new_section.header_distance = section.header_distance
            new_section.footer_distance = section.footer_distance
            
            # Copy additional sections if needed
            for i in range(1, len(doc.sections)):
                section = doc.sections[i]
                new_section = new_doc.add_section()
                new_section.page_height = section.page_height
                new_section.page_width = section.page_width
                new_section.left_margin = section.left_margin
                new_section.right_margin = section.right_margin
                new_section.top_margin = section.top_margin
                new_section.bottom_margin = section.bottom_margin
                new_section.header_distance = section.header_distance
                new_section.footer_distance = section.footer_distance
        
        # Copy complex elements like headers and footers
        copy_template_complex_elements(doc, new_doc)
        
        # Replace content in the template with our tailored content
        # First, create a mapping between our sections and template sections
        section_mapping = {}
        for our_section in sections.keys():
            best_match = None
            best_score = 0
            
            for template_section in template_sections.keys():
                # Calculate similarity between section headings
                if template_section.upper() == our_section.upper():
                    # Exact match
                    best_match = template_section
                    break
                elif template_section.upper() in our_section.upper() or our_section.upper() in template_section.upper():
                    # Partial match
                    score = len(set(template_section.upper()) & set(our_section.upper())) / max(len(template_section), len(our_section))
                    if score > best_score:
                        best_score = score
                        best_match = template_section
            
            if best_match and best_score > 0.5:
                section_mapping[our_section] = best_match
        
        # Add content to the new document based on the template structure
        for our_section, content_lines in sections.items():
            # Add section heading
            p = new_doc.add_paragraph()
            
            # Try to find a matching heading style from the template
            if our_section in section_mapping:
                template_section = section_mapping[our_section]
                section_index = template_sections[template_section]
                template_para = doc.paragraphs[section_index]
                
                try:
                    p.style = template_para.style.name
                except:
                    p.style = 'Heading 1'  # Fallback
                
                # Copy formatting from template paragraph
                for run in template_para.runs:
                    if run.text.strip():
                        p_run = p.add_run(our_section)
                        p_run.bold = run.bold
                        p_run.italic = run.italic
                        p_run.underline = run.underline
                        if run.font.name:
                            p_run.font.name = run.font.name
                        if run.font.size:
                            p_run.font.size = run.font.size
                        if run.font.color.rgb:
                            p_run.font.color.rgb = run.font.color.rgb
                        break
                else:
                    # If no runs with text, add a default run
                    p_run = p.add_run(our_section)
                    p_run.bold = True
            else:
                # No matching template section, use default formatting
                p.style = 'Heading 1'
                p_run = p.add_run(our_section)
                p_run.bold = True
            
            # Add section content
            for line in content_lines:
                if line.startswith('•') or line.startswith('-') or line.startswith('*'):
                    # This is a bullet point
                    p = new_doc.add_paragraph(line[1:].strip(), style='List Bullet')
                else:
                    p = new_doc.add_paragraph(line)
        
        new_doc.save(output_path)
        return True
        
    except Exception as e:
        print(f"Error creating tailored resume from template: {e}")
        return False

def convert_text_to_word(text_file_path, output_docx_path):
    """

    Convert a text file to a Word document.

    

    Args:

        text_file_path: Path to the text file

        output_docx_path: Path where the Word document will be saved

    

    Returns:

        bool: True if successful, False otherwise

    """
    try:
        # Read the text file
        with open(text_file_path, 'r', encoding='utf-8') as file:
            content = file.read()
        
        # Create a new Word document
        doc = Document()
        
        # Split the content by double newlines to identify paragraphs
        paragraphs = content.split('\n\n')
        
        # Process each paragraph
        for i, para_text in enumerate(paragraphs):
            # Skip empty paragraphs
            if not para_text.strip():
                continue
                
            # Check if this looks like a heading (all caps or ends with a colon)
            is_heading = para_text.isupper() or para_text.strip().endswith(':')
            
            # Add the paragraph to the document
            paragraph = doc.add_paragraph(para_text.strip())
            
            # Apply formatting based on position and content
            if i == 0:  # First paragraph is likely the name
                paragraph.style = 'Title'
            elif is_heading:
                paragraph.style = 'Heading 2'
            else:
                paragraph.style = 'Normal'
        
        # Save the document
        doc.save(output_docx_path)
        return True
        
    except Exception as e:
        print(f"Error converting text to Word: {e}")
        return False

def convert_sample_resumes():
    """

    Convert all sample text resumes to Word documents.

    

    Returns:

        list: Paths to the created Word documents

    """
    sample_files = [
        "excellent_match_resume.docx.txt",
        "good_match_resume.docx.txt",
        "average_match_resume.docx.txt",
        "poor_match_resume.docx.txt"
    ]
    
    created_files = []
    
    for text_file in sample_files:
        if os.path.exists(text_file):
            output_path = text_file.replace('.docx.txt', '.docx')
            print(f"Converting {text_file} to {output_path}...")
            if convert_text_to_word(text_file, output_path):
                created_files.append(output_path)
                print(f"Successfully created {output_path}")
            else:
                print(f"Failed to create {output_path}")
        else:
            print(f"Sample file not found: {text_file}")
    
    return created_files