Create app.py

app.py

@@ -0,0 +1,71 @@
+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.Textbox(lines=10, 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()