Delete app.py

app.py

@@ -1,118 +0,0 @@
-from dotenv import load_dotenv
-
-load_dotenv()
-import base64
-import streamlit as st
-import os
-import io
-from PIL import Image 
-import pdf2image
-import google.generativeai as genai
-
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-
-def get_gemini_response(input,pdf_cotent,prompt):
-    model=genai.GenerativeModel('gemini-pro-vision')
-    response=model.generate_content([input,pdf_content[0],prompt])
-    return response.text
-
-def input_pdf_setup(uploaded_file):
-    if uploaded_file is not None:
-        ## Convert the PDF to image
-        images=pdf2image.convert_from_bytes(uploaded_file.read())
-
-        first_page=images[0]
-
-        # Convert to bytes
-        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()  # encode to base64
-            }
-        ]
-        return pdf_parts
-    else:
-        raise FileNotFoundError("No file uploaded")
-
-## Streamlit App
-
-st.set_page_config(page_title="ATS Resume EXpert")
-st.header("ATS Tracking System")
-input_text=st.text_area("Job Description: ",key="input")
-with st.sidebar:
-        st.title("Menu:")
-        uploaded_file=st.file_uploader("Upload your resume(PDF)...",type=["pdf"])
-        if uploaded_file is not None:
-           st.success("Done")
-
-
-submit1 = st.button("Tell Me About the Resume")
-
-#submit2 = st.button("How Can I Improvise my Skills")
-
-submit3 = st.button("Percentage match")
-
-input_prompt1 = """
- You are an experienced Technical Human Resource Manager,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_prompt3 = """
-You are an skilled ATS (Applicant Tracking System) scanner with a deep understanding of data science 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 and then keywords missing and last final thoughts.
-"""
-
-if submit1 and uploaded_file is not None and input_text:
-    pdf_content=input_pdf_setup(uploaded_file)
-
-    response=get_gemini_response(input_text,pdf_content,input_prompt1)
-
-    st.subheader("Evaluation of the Resume")
-
-    selected_option = "Clear Uploaded Files"
-
-    uploaded_file = None
- 
-    st.write(response)
-    st.write("Uploaded files cleared. Because While Rendersing Response It will Automatically Clear")
-
-elif submit3 and uploaded_file is not None and input_text:
-    pdf_content=input_pdf_setup(uploaded_file)
-
-    response=get_gemini_response(input_text,pdf_content,input_prompt3)
-
-    st.subheader("Matching Percentage and Analysis")
-
-    selected_option = "Clear Uploaded Files"
-
-
-    uploaded_file = None
-
-    st.write(response)
-    st.write("Uploaded files cleared. Because While Rendersing Response It will Automatically Clear")
-else:
-    st.write("Please upload the resume and provide the job description.")
-
-st.sidebar.markdown("### Additional Options:")
-selected_option = st.sidebar.selectbox("Select an option", ["View Uploaded Resume", "Clear Uploaded Files"])
-
-
-if selected_option == "View Uploaded Resume" and uploaded_file is not None:
-    st.markdown("### Uploaded Resume")
-    # Store the PDF content
-    pdf_content = uploaded_file.read()
-    # Convert the PDF to images
-    images = pdf2image.convert_from_bytes(pdf_content)
-    # Display each page as an image
-    for i, page in enumerate(images):
-        st.image(page, caption=f"Page {i+1}", use_column_width=True)
-
-elif selected_option == "Clear Uploaded Files":
-    st.write("Uploaded files cleared.")
-    uploaded_file = None