Upload 5 files

ProjectFlow.tldr

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README.md

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----
-title: Simple ResumeATSTracking
-emoji: 📊
-colorFrom: gray
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.34.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Simple Resume ATS Tracking
+
+## Project Flow
+
+![Project Flow](ATS%20Resume%20Tracker%20Project%20flow%20TLDR.png)
+1. **PDF Text:** The application starts by extracting text from a PDF file. This is done using the PyPDF2 library.
+
+2. **API Response:** The extracted text is then sent to the Gemini API. The API processes the text and returns a response.
+
+3. **PyPDF2 to Text:** The PyPDF2 library converts the PDF file into text. This text is then processed further.
+
+4. **Gemini Using:** The processed text is sent to the Gemini API for further analysis.
+
+## Technologies Used
+
+- **Streamlit:** Streamlit is used for creating the web application. It provides an easy way to create beautiful, interactive web applications.
+
+- **PyPDF2:** PyPDF2 is used for extracting text from PDF files. It provides a simple and efficient way to handle PDF files in Python.
+
+- **Gemini:** Gemini is used for processing the text extracted from the PDF files. It provides powerful text analysis capabilities.
+
+## Getting Started
+
+To start this project, clone the repository and install the required dependencies.
+
+```bash
+git clone https://github.com/RahulSainy/GEN-AI-Projects.git
+cd Simple Resume ATS Tracking
+pip install -r requirements.txt
+streamlit run app.py

app.py

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+import streamlit as st
+import google.generativeai as genai
+import os
+from PyPDF2 import PdfReader
+import json
+from dotenv import load_dotenv
+load_dotenv()
+
+genai.configure(api_key=os.getenv('Google_API_KEY'))
+
+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":""}}
+"""
+def get_gemini_response(input):
+    model = genai.GenerativeModel('gemini-pro')
+    response = model.generate_content(input)
+    return response.text
+
+def input_pdf_text(uploaded_file):
+    reader = PdfReader(uploaded_file)
+    text = ''
+    for page in reader.pages:
+        text += str(page.extract_text())
+    return text
+
+
+
+# Set page configuration
+st.set_page_config(
+    page_title="Resume ATS Tracking",
+    page_icon="📄",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+sidebar = st.sidebar
+sidebar.title('Navigation')
+sidebar.markdown('Use this panel to navigate through the application and input your data.')
+# Add a title and a subtitle
+st.title('Resume ATS Tracking')
+st.subheader('Upload your resume and paste the job description to get the ATS tracking response')
+
+jd = st.text_area('Paste the Job Description')
+uploaded_file = sidebar.file_uploader('Upload Resume', type=['pdf'])
+
+submit = st.button('Submit')
+
+# Process the uploaded file and job description when the submit button is clicked
+if submit:
+    if uploaded_file is not None:
+        text = input_pdf_text(uploaded_file)
+        # input = input_prompt.format(text=text,jd=jd)
+        response = get_gemini_response(input_prompt)
+        response = response[1:-1]
+
+        # Convert the response to a dictionary
+        response_dict = json.loads(response)
+
+        # Display the response in a structured way
+        st.subheader('ATS Tracking Response:')
+        st.markdown(f"**JD Match:** {response_dict['JD Match']}")
+        st.markdown(f"**Missing Keywords:** {', '.join(response_dict['MissingKeywords'])}")
+        st.markdown(f"**Profile Summary:** {response_dict['Profile Summary']}")

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+PyPDF2
+google.generativeai
+python-dotenv