import gradio as gr
from langchain_community.chat_models import ChatOpenAI
from utils import process_file_with_dedoc, extract_text_from_all_levels, generate_formatted_resume, generate_json_structured_resume

ALLOWED_EXTENSIONS = {"jpg", "jpeg", "png", "docx", "pdf", "html", "doc"}

def allowed_file(filename):
    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS

def parse_resume(file_info, status):
    file_path, file = file_info
    filename = file_path.split("/")[-1]  # Extract the file name

    if not allowed_file(filename):
        return "Invalid file type. Allowed file types are: jpg, jpeg, png, docx, pdf, html, doc", None, filename

    status.update(f"Processing: {filename}")

    # Create instances of the chat model
    chat_llm_text = ChatOpenAI(model='gpt-3.5-turbo', temperature=0.0)
    chat_llm_json = ChatOpenAI(model='gpt-3.5-turbo', temperature=0.0)

    # Read and process the file
    text = process_file_with_dedoc(file)  # Ensure this is synchronous or adapted for async in Gradio
    status.update(f"Extracting text from: {filename}")
    text_f = extract_text_from_all_levels(text)  # Ensure this is synchronous or adapted for async in Gradio

    # Generate parsed resume and parsed JSON resume
    status.update(f"Generating formatted resume for: {filename}")
    parsed_resume = generate_formatted_resume(text_f, chat_llm_text)
    status.update(f"Generating structured JSON resume for: {filename}")
    parsed_json_resume = generate_json_structured_resume(text_f, chat_llm_json)

    return parsed_resume, parsed_json_resume, filename

# Define the Gradio interface
demo = gr.Interface(
    fn=parse_resume,
    inputs=[
        gr.File(label="Upload your resume"),
        gr.StatusTracker()
    ],
    outputs=[
        gr.Textbox(label="Formatted Resume"),
        gr.JSON(label="Structured JSON Resume"),
        gr.Textbox(label="File Name", lines=1)
    ],
    title="Resume Parser",
    description="Upload a resume to parse it into formatted text and structured JSON."
)

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