import gradio as gr
import re
from transformers import pipeline

# โหลดโมเดลจาก Hugging Face Hub
ner_pipeline = pipeline(
    task="ner",
    model="Nucha/Nucha_ITSkillNER_BERT",
    aggregation_strategy="simple"
)

examples = [
                "Responsibilities Develop and maintain web applications using C#.NET, ReactJS , and PHP frameworks . Collaborate with the team and clients to gather and analyze business needs. Implement solutions and integrate automated testing within the development process using CICD tools . Contribute to the design and development of largescale applications . Provide and receive constructive feedback on projects. Qualifications Bachelors degree in Computer Science , Software Engineering , or a related field preferred but not required. Minimum of 1+ years of experience in C#.NET and ReactJS , or a strong willingness to learn. Experience using JIRA for project management. Skilled in writing API documentation using Paw . Experience working with RESTful web services . knowledge of AWS is an advantage."
        ]

def preprocess_text(text):
    return text.replace(",", " ")
    
# ฟังก์ชันประมวลผลข้อความ
def extract_skills(text):
    text=preprocess_text(text)
    entities = ner_pipeline(text)
    for result in entities:
        if result.get("entity_group"):
            result["entity"] = result["entity_group"]
            del result["entity_group"]
    print(entities)
    return {"text": text, "entities": entities}


# UI ของ Gradio
demo = gr.Interface(
    fn=extract_skills,
    inputs=gr.Textbox(lines=5, placeholder="พิมพ์ข้อความเกี่ยวกับ IT job description ที่นี่..."),
    outputs=["highlight"],
    title="IT Skill NER Extractor",
    description="โมเดลสำหรับแยกทักษะด้านไอทีจากข้อความประกาศงาน",
    examples=examples
)

if __name__ == "__main__":
    demo.launch()