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app.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 
+
+load_dotenv()
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+def get_gemini_response(input, pdf_content, prompt):
+    model = genai.GenerativeModel('gemini-1.5-flash')
+    response=model.generate_content([input, pdf_content[0], prompt])
+    return response.text
+
+# now to convert the uploaded pdf file into img that gemini pro can understant it and process it
+# def input_pdf_setup(uploaded_pdf):
+#     if uploaded_pdf is not None:
+#         images = pdf2image.convert_from_bytes(uploaded_pdf.read()) # convet pdf to image
+#         first_page = images[0]
+
+#         # t convert into bytes
+#         img_byte_arr = io.BytesID()
+#         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() # encode to base64
+
+#             }
+#         ]
+
+#         return pdf_parts
+#     else:
+#         raise FileNotFoundError("File not Uploaded")
+
+def input_pdf_setup(uploaded_pdf):
+    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 (no need to save the image)
+        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("File not Uploaded")
+
+
+
+#-------------- streamlit app -----------------
+
+#-------------- Streamlit App -----------------
+
+st.set_page_config(page_title="ATS System")
+
+# Sidebar: Upload Resume, File Upload Success, and Buttons for Prompts
+with st.sidebar:
+    
+    field = st.text_input("Enter your job filed")
+
+    uploaded_file = st.file_uploader("Upload your Resume", type=["pdf"])
+
+    if uploaded_file is not None:
+        st.toast("File uploaded successfully!", icon="✅")
+        
+    
+    submit1 = st.button("Tell me about the resume")
+    submit4 = st.button("How much is the percentage match?")
+
+# Main Area: Job Description and Bot Response
+st.header("ATS System - Resume Evaluation")
+
+input_text = st.text_area("Job Description:", key="input")
+
+
+# Define Prompts
+input_prompt1 = """
+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 = """
+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.
+"""
+
+# Handle button clicks and generate responses
+if submit1:
+    if uploaded_file is not None:
+        pdf_content = input_pdf_setup(uploaded_file)
+        response = get_gemini_response(input_prompt1, pdf_content, input_text)
+        st.markdown(
+            f"""
+            <div style="background-color:#f0f0f0; padding: 15px; border-radius: 8px; margin-top: 20px;">
+                <h3>Response:</h3>
+                <p>{response}</p>
+            </div>
+            """, 
+            unsafe_allow_html=True
+        )
+    else:
+        st.write("Please upload your Resume.")
+
+if submit4:
+    if uploaded_file is not None:
+        pdf_content = input_pdf_setup(uploaded_file)
+        response = get_gemini_response(input_prompt4, pdf_content, input_text)
+        st.markdown(
+            f"""
+            <div style="background-color:#f0f0f0; padding: 15px; border-radius: 8px; margin-top: 20px;">
+                <h3>Response:</h3>
+                <p>{response}</p>
+            </div>
+            """, 
+            unsafe_allow_html=True
+        )
+    else:
+        st.write("Please upload your Resume.")

plan.txt

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+1. field to put my job discription
+2. upload pdf
+3. pdf to image --> processing --> google gemini processing
+4. Prompts Templates for execution [multiple prompts]

requirements.txt

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