Update app.py

app.py

@@ -1,11 +1,25 @@
 import gradio as gr
 import openai
 import os
+import fitz  # PyMuPDF
 
 # Set OpenAI API key
-openai.api_key = os.getenv("OPENAI_API_KEY")
+openai.api_key = os.getenv("sk-1E6ExsyFb-cdU8jPNDP1dsEq_ra_bazU-EXQZQ86pJT3BlbkFJ4zURsV0t--3qNM7A-P57NUqZIBosrL7POwzpjR5EQA")
+
+def extract_text_from_pdf(pdf_file):
+    # Open the PDF file
+    document = fitz.open(pdf_file)
+    text = ""
+    # Extract text from each page
+    for page_num in range(len(document)):
+        page = document.load_page(page_num)
+        text += page.get_text()
+    return text
+
+def evaluate_resume(pdf_file, job_description):
+    # Extract text from PDF
+    resume_text = extract_text_from_pdf(pdf_file)
 
-def evaluate_resume(resume, job_description):
     prompt = f"""
     As an experienced Applicant Tracking System (ATS) analyst,
     with profound knowledge in technology, software engineering, data science,
@@ -13,7 +27,7 @@ def evaluate_resume(resume, job_description):
     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:{resume}
+    resume:{resume_text}
     description:{job_description}
     I want the response in one single string having the structure
     {{"Job Description Match":"%","Missing Keywords":"","Candidate Summary":"","Experience":""}}
@@ -32,7 +46,7 @@ def evaluate_resume(resume, job_description):
 iface = gr.Interface(
     fn=evaluate_resume,
     inputs=[
-        gr.inputs.Textbox(lines=10, label="Resume"),
+        gr.File(label="Upload Resume PDF"),
         gr.inputs.Textbox(lines=10, label="Job Description")
     ],
     outputs="text",