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ats.py

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+import streamlit as st
+import google.generativeai as genai
+import os
+import PyPDF2 as pdf
+from dotenv import load_dotenv
+import json
+import re
+import ast
+
+load_dotenv() ## load all our environment variables
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+def get_gemini_repsonse(input):
+    model=genai.GenerativeModel('gemini-pro')
+    response=model.generate_content(input)
+    return response.text
+
+def input_pdf_text(uploaded_file):
+    reader=pdf.PdfReader(uploaded_file)
+    text=""
+    for page in range(len(reader.pages)):
+        page=reader.pages[page]
+        text+=str(page.extract_text())
+    return text
+
+#Prompt Template
+
+input_prompt="""
+Hey Act Like a skilled or very experience ATS(Application Tracking System)
+with a deep understanding of tech field,software engineering,data science ,data analyst
+and big data engineer. Your task is to evaluate the resume based on the given job description.
+You must consider the job market is very competitive and you should provide 
+best assistance for improving thr resumes. Assign the percentage Matching based 
+on Jd and
+the missing keywords with high accuracy
+resume:{text}
+description:{jd}
+
+I want the response in one single string having the structure
+{{"JD Match":"%","MissingKeywords:[]","Profile Summary":""}}
+"""
+
+## streamlit app
+st.title("Applicant Tracking System (ATS)")
+st.text("Improve Your Resume ATS")
+jd=st.text_area("Paste the Job Description")
+uploaded_file=st.file_uploader("Upload Your Resume",type="pdf",help="Please uplaod the pdf")
+
+submit = st.button("Submit")
+
+if submit:
+    if uploaded_file is not None:
+        text=input_pdf_text(uploaded_file)
+        response_string=get_gemini_repsonse(input_prompt)
+       
+        # Extract JD match percentage
+        jd_match = int(re.search(r'"JD Match":"(\d+)%?"', response_string).group(1))
+
+        # Extract missing keywords
+        missing_keywords = re.search(r'"MissingKeywords":(.*?)]', response_string).group(1) + ']'
+        missing_keywords = eval(missing_keywords)  # Convert string representation of list to actual list
+
+        # Extract profile summary
+        profile_summary = re.search(r'"Profile Summary":"(.*?)"', response_string).group(1)
+
+        # Streamlit app
+        st.title("Resume Evaluation Result")
+        st.write("JD Match:", f"{str(jd_match)}%")
+        st.write("Missing Keywords:", missing_keywords)
+        st.write("Profile Summary:", profile_summary)
+
+        # If JD match percentage is more than 80%, display balloons
+        if jd_match >= 80:
+            st.balloons()

requirements.txt

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+streamlit
+PyPDF2
+google.generativeai
+python-dotenv