import gradio as gr
import requests
import os
import docx2txt
import PyPDF2 as pdf




def generate_response_from_jabir(resume_text, job_description):
    base_url = "https://api.jabirproject.org/generate"
    headers = {"apikey": os.getenv("7471142a-deb4-4a70-8ee3-6603e21bcc1d")}
    input_prompt_template = """
    As an experienced Applicant Tracking System (ATS) analyst,
    with profound knowledge in technology, software engineering, data science, 
    and big data engineering, your role involves evaluating resumes against job descriptions.
    Recognizing the competitive job market, provide top-notch assistance for resume improvement.
    Your goal is to analyze the resume against the given job description, 
    assign a percentage match based on key criteria, and pinpoint missing keywords accurately.
    resume:{text}
    description:{job_description}
    I want the response in one single string having the structure
    {{"Job Description Match":"%","Missing Keywords":"","Candidate Summary":"","Experience":""}}
    """
    prompt = input_prompt_template.format(text=resume_text, job_description=job_description)
    data = {
        "messages": [{"role": "user", "content": prompt}]
    }
    response = requests.post(base_url, headers=headers, json=data)
    
    if response.ok:
        response_text = response.json()["choices"][0]["message"]["content"]
        match_percentage_str = response_text.split('"Job Description Match":"')[1].split('"')[0]
        match_percentage = float(match_percentage_str.rstrip('%'))
        
        if match_percentage >= 80:
            recommendation = "Move forward with hiring"
        else:
            recommendation = "Not a Match"
        
        return response_text, recommendation
    else:
        return f"Error: {response.status_code}, {response.text}", None

def extract_text_from_file(uploaded_file):
    if uploaded_file.name.endswith('.pdf'):
        pdf_reader = pdf.PdfReader(uploaded_file)
        text_content = ""
        for page in pdf_reader.pages:
            text_content += str(page.extract_text())
        return text_content
    elif uploaded_file.name.endswith('.docx'):
        return docx2txt.process(uploaded_file)
    else:
        return "Unsupported file format"

def process_file(uploaded_file, job_description):
    if uploaded_file is not None:
        resume_text = extract_text_from_file(uploaded_file)
        return generate_response_from_jabir(resume_text, job_description)
    else:
        return "No file uploaded", None

iface = gr.Interface(
    fn=process_file,
    inputs=[gr.File(type="filepath", label="resume") ,gr.Textbox(lines=10, label="Job Description")],
    outputs=[gr.Textbox(label="ATS Evaluation Result"), gr.Textbox(label="Recommendation")],
    title="Intelligent ATS-Enhance Your Resume ATS"
)

iface.launch()