Update app.py

app.py

@@ -1,49 +1,53 @@
+import os
 import io
-from dotenv import load_dotenv
-
-load_dotenv()
-
 import streamlit as st
-import os
-from PIL import Image
-import pdf2image
+from dotenv import load_dotenv
+import fitz  # PyMuPDF
 import base64
 import google.generativeai as genai
 
-genai.configure(api_key=os.getenv("API_KEY"))
+
+# Load environment variables
+load_dotenv()
+
+# Configure your application, for example, with an API key for a service
+# api_key = os.getenv("API_KEY")
 
 def get_gemini_response(input, pdf_content,prompt):
     model = genai.GenerativeModel('gemini-pro-vision')
     response = model.generate_content([input,pdf_content[0],prompt])
     return response.text
 
+def extract_text_from_first_page(pdf_path):
+    """Extract text from the first page of a PDF file using PyMuPDF (fitz)."""
+    doc = fitz.open(pdf_path)
+    first_page_text = doc[0].get_text()
+    doc.close()
+    return first_page_text
+
 def input_pdf_setup(upload_file):
+    """Save uploaded file to disk and extract text from the first page."""
     if upload_file is not None:
-                images=pdf2image.convert_from_bytes(upload_file.read())
-
-                first_page = images[0]
-
-                img_byte_arr = io.BytesIO()
-                first_page.save(img_byte_arr, format='JPEG')
-                img_byte_arr = img_byte_arr.getvalue()
-
-                pdf_parts = [
-                {
-                    "mime_type": "image/jpeg",
-                        "data": base64.b64encode(img_byte_arr).decode()
-                }
-                ]
-                return pdf_parts
+        # Save the uploaded PDF to a temporary file
+        with open("temp_uploaded.pdf", "wb") as f:
+            f.write(upload_file.getbuffer())
+        
+        # Extract text from the first page
+        extracted_text = extract_text_from_first_page("temp_uploaded.pdf")
+        return extracted_text
     else:
-         raise FileNotFoundError("No File uploaded")
+        raise FileNotFoundError("No File uploaded")
 
+# Streamlit UI setup
 st.set_page_config(page_title="Resume Parser")
 st.header("Mock ATS")
-input_text = st.text_area("Paste the job description here: ",key="input")
+
+# User inputs
+input_text = st.text_area("Paste the job description here:", key="input")
 uploaded_file = st.file_uploader("Upload your resume (only PDFs are supported)...", type="pdf")
 
 if uploaded_file is not None:
-    st.write("Resume uploaded successfully")
+    st.write("Resume uploaded successfully.")
  
 submit1=st.button("Tell me about the resume")
 
@@ -78,5 +82,3 @@ elif submit2:
         st.write(response)
     else:
         st.write("Please uplaod the resume")
-
-