utils/ai_analyzer.py

import json
from config.settings import OPENAI_API_KEY, MODEL_NAME, TEMPERATURE, MAX_TOKENS


def analyze_resume_with_openai(resume_text):
    """
    Analyze resume using OpenAI API
    
    Args:
        resume_text: Extracted resume text
    
    Returns:
        Dictionary with analysis results
    """
    import openai
    
    if not OPENAI_API_KEY:
        # Return mock data if API key is not configured
        return get_mock_analysis()
    
    openai.api_key = OPENAI_API_KEY
    
    prompt = f"""Analyze the following resume and provide a detailed assessment. 
    Return your response as a JSON object with the following structure:
    {{
        "summary": "Brief overview of the candidate",
        "skills": {{
            "technical": ["list of technical skills"],
            "soft": ["list of soft skills"],
            "missing": ["important missing skills in this field"]
        }},
        "experience": {{
            "highlights": ["key achievements and experiences"],
            "concerns": ["any gaps or concerns in work history"]
        }},
        "education": {{
            "details": "education background description",
            "relevant": "how relevant is the education"
        }},
        "career_gaps": ["any identified gaps in career progression"],
        "recommendations": [
            "action items to improve resume",
            "skills to develop",
            "areas to strengthen"
        ],
        "overall_score": {{"rating": 0-100, "explanation": "brief explanation"}},
        "job_compatibility": {{
            "strengths": ["matched competencies"],
            "weaknesses": ["areas that need improvement for typical jobs"]
        }}
    }}
    
    Resume text:
    {resume_text}
    
    Provide ONLY valid JSON response, no additional text."""
    
    try:
        response = openai.ChatCompletion.create(
            model=MODEL_NAME,
            messages=[
                {"role": "system", "content": "You are an expert resume analyst and HR consultant."},
                {"role": "user", "content": prompt}
            ],
            temperature=TEMPERATURE,
            max_tokens=MAX_TOKENS
        )
        
        analysis_text = response.choices[0].message.content
        analysis = json.loads(analysis_text)
        return analysis
    
    except json.JSONDecodeError:
        # If JSON parsing fails, return mock data
        return get_mock_analysis()
    except Exception as e:
        print(f"Error calling OpenAI API: {e}")
        return get_mock_analysis()


def get_mock_analysis():
    """Return mock analysis data for demo purposes"""
    return {
        "summary": "Experienced professional with strong technical background and leadership skills. Shows good career progression with relevant certifications.",
        "skills": {
            "technical": ["Python", "JavaScript", "SQL", "Git", "Docker", "APIs"],
            "soft": ["Project Management", "Team Leadership", "Communication", "Problem-solving"],
            "missing": ["Cloud Architecture (AWS/Azure)", "Machine Learning", "Advanced DevOps"]
        },
        "experience": {
            "highlights": [
                "Led cross-functional team of 5+ developers",
                "Implemented automated testing increasing code coverage by 40%",
                "Reduced deployment time by 60% through CI/CD optimization"
            ],
            "concerns": ["Gap of 2 months between roles in 2021"]
        },
        "education": {
            "details": "Bachelor's degree in Computer Science with relevant coursework",
            "relevant": "Highly relevant to technical roles"
        },
        "career_gaps": [
            "Limited experience with emerging technologies",
            "No mention of continuous learning or certifications in last 2 years"
        ],
        "recommendations": [
            "Add quantifiable metrics to all achievements",
            "Include recent certifications or training",
            "Expand cloud platform experience section",
            "Consider adding GitHub profile or portfolio link",
            "Highlight specific results and ROI from projects"
        ],
        "overall_score": {
            "rating": 75,
            "explanation": "Strong foundational experience with room for growth in emerging technologies"
        },
        "job_compatibility": {
            "strengths": ["Solid programming fundamentals", "Team collaboration experience"],
            "weaknesses": ["Limited cloud platform experience", "No mention of recent projects"]
        }
    }


def format_analysis_for_display(analysis):
    """
    Format analysis dictionary for better display
    
    Args:
        analysis: Dictionary with analysis results
    
    Returns:
        Formatted analysis
    """
    return analysis