Create app.py

app.py

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+import streamlit as st
+import PyPDF2
+import google.generativeai as genai
+
+# Initialize Gemini Flash model with your API key
+genai.configure(api_key=os.environ.get("Google_API_KEY"))
+model = genai.GenerativeModel('gemini-1.5-flash')
+
+# Function to extract text from uploaded PDF
+def extract_text_from_pdf(pdf_file):
+    reader = PyPDF2.PdfReader(pdf_file)
+    text = ''
+    for page_num in range(len(reader.pages)):
+        page = reader.pages[page_num]
+        text += page.extract_text()
+    return text
+
+# Function to process the CV and job description
+def check_cv_match(cv_text, job_description):
+    prompt = (
+        f"You are an AI expert assisting with recruitment. "
+        f"Compare the following resume with the job description and determine if the resume matches the job requirements. "
+        f"Provide a detailed analysis and a match percentage:\n\n"
+        f"Job Description: {job_description}\n\n"
+        f"Resume: {cv_text}\n\n"
+        f"Give a score from 0% to 100% indicating how well the resume matches the job."
+    )
+    
+    response = model.generate_content([prompt])
+    return response.text
+
+
+st.title("CV and Job Description Matcher")
+
+uploaded_cv = st.file_uploader("Upload CV (PDF format)", type="pdf")
+
+if uploaded_cv is not None:
+    # Extract text from uploaded PDF
+    cv_text = extract_text_from_pdf(uploaded_cv)
+    st.text_area("Extracted CV Text", value=cv_text, height=300)
+
+# Input field for job description
+job_description = st.text_area("Enter the Job Description", height=300)
+
+if st.button("Check Match"):
+    if uploaded_cv and job_description:
+        match_result = check_cv_match(cv_text, job_description)
+        st.write("Match Analysis:")
+        st.write(match_result)
+    else:
+        st.error("Please upload a CV and enter the job description.")