import spacy
from spacy.cli import download
import nltk
import os
import gradio as gr
import torch
from sentence_transformers import SentenceTransformer
import PyPDF2

# Ensure NLTK 'punkt' tokenizer is downloaded
try:
    nltk.data.find('tokenizers/punkt')
except LookupError:
    print("Downloading NLTK 'punkt' tokenizer...")
    nltk.download('punkt')

# Ensure spaCy 'en_core_web_sm' model is downloaded
try:
    nlp = spacy.load("en_core_web_sm")
except OSError:
    print("Downloading spaCy 'en_core_web_sm' model...")
    download("en_core_web_sm")
    nlp = spacy.load("en_core_web_sm")

# Load Sentence Transformer model
embedding_model = SentenceTransformer('all-MiniLM-L6-v2')

# Check for GPU availability
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"Running on: {device}")

# Function to extract text from PDF
def extract_text_from_pdf(file_path):
    try:
        with open(file_path, 'rb') as file:
            reader = PyPDF2.PdfReader(file)
            text = ''.join(page.extract_text() for page in reader.pages)
            return text
    except Exception as e:
        print(f"Error extracting PDF text: {e}")
        return ""

# Placeholder function for CV skill analysis
def analyze_cv_skills(cv_text):
    # Implement skill analysis and career recommendations
    return "Skill analysis and recommendations coming soon!"

# Function to process CV and provide recommendations
def cv_skill_assessment(cv_file):
    try:
        cv_text = extract_text_from_pdf(cv_file.name)
        if not cv_text.strip():
            with open(cv_file.name, 'r', encoding='utf-8') as f:
                cv_text = f.read()
        assessment = analyze_cv_skills(cv_text)
        return assessment
    except Exception as e:
        return f"Error processing CV: {str(e)}"

# Create Gradio Interface
def launch_cv_skill_assessment_app():
    demo = gr.Interface(
        fn=cv_skill_assessment,
        inputs=gr.File(label="Upload Your CV (PDF/Text)", type="file"),
        outputs=gr.Markdown(label="Career Recommendation Report"),
        title="🚀 CV Skills Assessment AI",
        description="""
        Discover your ideal career path based on your CV!

        - Upload your CV (PDF or Text file)
        - AI analyzes your skills and experience
        - Receive personalized career recommendations
        """,
    )
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)

# Run the application
if __name__ == "__main__":
    launch_cv_skill_assessment_app()