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app2.py

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+from dotenv import load_dotenv
+import streamlit as st
+import os
+from PIL import Image
+import pdf2image
+import google.generativeai as genai
+import io
+import base64
+import fitz
+import re
+
+load_dotenv()
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+def get_gemini_response(input, pdf_content, prompt):
+    try:
+        model = genai.GenerativeModel('gemini-1.5-flash')
+        response = model.generate_content([input, pdf_content[0], prompt])
+        return response.text
+    except Exception as e:
+        st.error(f"Error in generating response: {str(e)}")
+        return ""
+
+def input_pdf_setup(uploaded_pdf):
+    try:
+        if uploaded_pdf is not None:
+            doc = fitz.open(stream=uploaded_pdf.read(), filetype="pdf")
+
+            # Convert the first page to an image (0-indexed)
+            first_page = doc.load_page(0)
+            pix = first_page.get_pixmap()
+
+            # Convert pixmap to bytes
+            img_byte_arr = io.BytesIO()
+            img_byte_arr.write(pix.tobytes("jpeg"))
+            img_byte_arr.seek(0)  # Go to the start of the byte stream
+
+            # Encode the image to base64
+            pdf_parts = [
+                {
+                    "mime_type": "image/jpeg",
+                    "data": base64.b64encode(img_byte_arr.read()).decode()  # Encode to base64
+                }
+            ]
+            return pdf_parts
+        else:
+            raise FileNotFoundError("No file uploaded")
+    except Exception as e:
+        st.error(f"Error processing PDF file: {str(e)}")
+        return []
+
+def extract_percentage(response):
+    try:
+        match = re.search(r'(\d+(\.\d+)?)%', response)
+        if match:
+            return float(match.group(1))
+        return 0.0
+    except Exception as e:
+        st.error(f"Error extracting percentage: {str(e)}")
+        return 0.0
+
+#-------------- Streamlit App -----------------
+
+st.set_page_config(page_title="ATS System")
+
+with st.sidebar:
+    field = st.text_input("Enter your job field")
+
+    # Upload multiple resumes
+    uploaded_files = st.file_uploader("Upload Resumes (multiple)", type=["pdf"], accept_multiple_files=True)
+
+    if uploaded_files:
+        st.toast(f"{len(uploaded_files)} files uploaded successfully!", icon="✅")
+
+    submit1 = st.button("Tell me about the resumes")
+    submit4 = st.button("How much is the percentage match?")
+
+st.header("ATS System - Resume Evaluation")
+
+input_text = st.text_area("Job Description:", key="input")
+
+input_prompt1 = f"""
+You are an experienced Technical Human Resource Manager and an expert in {field}, your task is to review the provided resume  against the job description. 
+Please share your professional evaluation on whether the candidate's profile aligns with the role. 
+Highlight the strengths and weaknesses of the applicant in relation to the specified job requirements.
+"""
+
+input_prompt4 = f"""
+You are a skilled ATS (Applicant Tracking System) scanner with a deep understanding of {field} and ATS functionality, 
+your task is to evaluate the resume against the provided job description. Give me the percentage of match if the resume matches
+the job description. First, the output should come as percentage, then keywords missing, and last final thoughts.
+"""
+
+comparison_results = []
+
+if submit1 or submit4:
+    if uploaded_files:
+        if not input_text:
+            st.error("Please! provide the job description")
+        if not field:
+            st.error("Please! Enter your field of job")
+        for uploaded_file in uploaded_files:
+            pdf_content = input_pdf_setup(uploaded_file)
+
+            if pdf_content:  # Only proceed if PDF content is valid
+                if submit1:
+                    response = get_gemini_response(input_prompt1, pdf_content, input_text)
+                elif submit4:
+                    response = get_gemini_response(input_prompt4, pdf_content, input_text)
+
+                if response:
+                    comparison_results.append({
+                        "file_name": uploaded_file.name,
+                        "response": response
+                    })
+
+        if comparison_results:
+            for result in comparison_results:
+                st.markdown(
+                    f"""
+                    <div style="background-color:#f0f0f0; padding: 15px; border-radius: 8px; margin-top: 20px;">
+                        <h3>{result['file_name']}</h3>
+                        <p>{result['response']}</p>
+                    </div>
+                    """, 
+                    unsafe_allow_html=True
+                )
+
+            if submit4:
+                try:
+                    best_match = max(
+                        comparison_results, 
+                        key=lambda x: extract_percentage(x['response'])
+                    )
+                    st.markdown(
+                        f"""
+                        <div style="background-color: #d3f8d3; padding: 15px; border-radius: 8px; margin-top: 20px; color: black;">
+                            <h3><strong>Best Match:</strong> {best_match['file_name']}</h3>
+                            <p>{best_match['response']}</p>
+                        </div>
+                        """, 
+                        unsafe_allow_html=True
+                    )
+                except ValueError:
+                    st.error("Could not extract a valid percentage match.")
+        else:
+            st.write("No valid responses generated.")
+    else:
+        st.write("Please upload at least one resume.")

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv
+pdf2image
+pymupdf