AI Resume Analyzer #975

AI Resume Analyzer/Resume Analyzer Sentence Transformers/README.md

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+</br>
+
+![Screenshot (5313)](https://github.com/user-attachments/assets/ff312d66-7b70-4479-b1cf-06c9a871d853)
+
+</br>
+
+![Screenshot (5314)](https://github.com/user-attachments/assets/aed37f5f-361f-40e7-86a2-4ad77234db0d)
+
+</br>
+
+![Screenshot (5315)](https://github.com/user-attachments/assets/7ea6d358-40e3-4f57-908e-fd0a78d494b1)

AI Resume Analyzer/Resume Analyzer Sentence Transformers/app.py

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+
+
+import streamlit as st
+from resume_analyzer import ResumeAnalyzer
+import os
+
+def main():
+    st.set_page_config(page_title="Smart Resume Analyzer", layout="wide")
+    st.title("Smart Resume Analyzer")
+
+    job_description = st.text_area("Enter the Job Description", height=200)
+    st.write("Upload resumes as PDF files:")
+    uploaded_files = st.file_uploader("Upload PDF files", accept_multiple_files=True, type="pdf")
+
+    if st.button("Analyze Resumes") and uploaded_files:
+        resume_files = []
+        for uploaded_file in uploaded_files:
+            file_path = os.path.join("/tmp", uploaded_file.name)
+            with open(file_path, "wb") as f:
+                f.write(uploaded_file.getbuffer())
+            resume_files.append(file_path)
+
+        analyzer = ResumeAnalyzer()
+        analysis_results = analyzer.analyze_resumes(resume_files, job_description)
+
+        for result in analysis_results:
+            st.write(f"**Resume Name**: {result['Resume Name']}")
+            st.write(f"**Job Titles**: {result['Job Titles']}")
+            st.write(f"**Primary Skills**: {result['Primary Skills']}")
+            st.write(f"**Secondary Skills**: {result['Secondary Skills']}")
+            st.write(f"**Total Experience (Years)**: {result['Total Experience (Years)']}")
+            st.write(f"**Relevant Experience Duration (Years)**: {result['Relevant Experience Duration (Years)']:.2f}")
+            st.write(f"**Average Experience Relevance**: {result['Average Experience Relevance']:.2f}")
+            st.write(f"**Relevant Projects**: {result['Relevant Projects']}")
+            st.write(f"**Average Project Relevance**: {result['Average Project Relevance']:.2f}")
+            st.write(f"**Score**: {result['Score']:.2f}")
+            st.write("-" * 50)
+
+        report_path = analyzer.generate_ranking_report(analysis_results)
+        with open(report_path, "rb") as report_file:
+            st.download_button(
+                label="Download Analysis Report as PDF",
+                data=report_file,
+                file_name="resume_analysis_report.pdf",
+                mime="application/pdf"
+            )
+
+if __name__ == "__main__":
+    main()

AI Resume Analyzer/Resume Analyzer Sentence Transformers/requirements.txt

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+streamlit
+sentence-transformers
+PyMuPDF
+rapidfuzz
+fpdf
+python-dateutil
+spacy
+# en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz
+# pandas
+# spacy==3.5.0
+# https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.5.0/en_core_web_sm-3.5.0-py3-none-any.whl
+
+# python -m spacy download en_core_web_sm
+# # # # import nltk
+# # # # nltk.download('punkt')
+# # # # nltk.download('stopwords')

AI Resume Analyzer/Resume Analyzer Sentence Transformers/utils.py

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+
+import streamlit as st
+import spacy
+from sentence_transformers import SentenceTransformer
+
+# @st.cache_resource
+def load_nlp_model():
+    return spacy.load("en_core_web_sm")
+
+# @st.cache_resource
+def load_transformer_model():
+    return SentenceTransformer('all-MiniLM-L6-v2')

AI Resume Analyzer/Resume Analyzer With Gemini/Resume Application Tracking System(ATS)/README.md

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+
+
+# ATS Resume Expert
+
+ATS Resume Expert is a Streamlit-based web application that uses Google's Generative AI (Gemini) model to analyze resumes in PDF format against specific job descriptions. The application evaluates the resume content, providing insights and match percentages to help users understand how well their resume aligns with job requirements.
+
+## Features
+- **Resume Analysis**: Upload a PDF resume, and the AI evaluates it based on a provided job description.
+- **Job Match Scoring**: The AI provides a match percentage between the resume and job description, highlighting strengths, weaknesses, missing keywords, and more.
+- **Streamlit UI**: User-friendly interface with text input for job description and resume upload capability.
+
+## Getting Started
+
+### Prerequisites
+1. **Python**: Make sure you have Python 3.7+ installed.
+2. **Google API Key**: This project requires access to Google Generative AI's Gemini model. Obtain an API key and configure it in the environment.
+
+### Installation
+1. Clone this repository:
+   ```bash
+   git clone https://github.com/your-username/ATS-Resume-Expert.git
+   cd ATS-Resume-Expert
+   ```
+2. Install the required packages:
+   ```bash
+   pip install -r requirements.txt
+   ```
+   Here is a sample `requirements.txt`:
+   ```
+   streamlit
+   dotenv
+   pdf2image
+   pillow
+   google-generativeai
+   ```
+
+3. Install **poppler** (required for `pdf2image`):
+   - **Windows**: [Download Poppler for Windows](http://blog.alivate.com.au/poppler-windows/), extract, and add `poppler/bin` to your PATH.
+   - **Linux**: Run `sudo apt install poppler-utils`.
+   - **macOS**: Run `brew install poppler`.
+
+4. Create a `.env` file in the project root with your Google API key:
+   ```
+   GOOGLE_API_KEY=your_google_api_key
+   ```
+
+### Running the App
+1. Start the Streamlit app:
+   ```bash
+   streamlit run app.py
+   ```
+
+2. Open the provided local URL to access the ATS Resume Expert app.
+
+## Usage
+1. **Job Description**: Enter the job description in the text area.
+2. **Resume Upload**: Upload a PDF version of the resume.
+3. **Analyze Resume**:
+   - Click **Tell Me About the Resume** to get an evaluation of the resume based on job requirements.
+   - Click **Percentage Match** to receive a match score along with suggestions for improvement.
+
+## File Structure
+- **app.py**: Main application code.
+- **README.md**: Documentation for the app.
+- **requirements.txt**: List of required Python libraries.
+- **.env**: Environment file for API keys (not included in repository).
+
+## Troubleshooting
+1. **Poppler Installation**: Ensure Poppler is installed and accessible in your PATH if you encounter PDF processing errors.
+2. **API Errors**: Check your Google API key and usage limits if there are issues with the AI model responses.
+
+

AI Resume Analyzer/Resume Analyzer With Gemini/Resume Application Tracking System(ATS)/app.py

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+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("apikey"))
+
+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")
+uploaded_file=st.file_uploader("Upload your resume(PDF)...",type=["pdf"])
+
+
+if uploaded_file is not None:
+    st.write("PDF Uploaded Successfully")
+
+
+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:
+    if uploaded_file is not None:
+        pdf_content=input_pdf_setup(uploaded_file)
+        response=get_gemini_response(input_prompt1,pdf_content,input_text)
+        st.subheader("The Repsonse is")
+        st.write(response)
+    else:
+        st.write("Please uplaod the resume")
+
+elif submit3:
+    if uploaded_file is not None:
+        pdf_content=input_pdf_setup(uploaded_file)
+        response=get_gemini_response(input_prompt3,pdf_content,input_text)
+        st.subheader("The Repsonse is")
+        st.write(response)
+    else:
+        st.write("Please uplaod the resume")
+
+
+
+
+
+
+
+
+

AI Resume Analyzer/Resume Analyzer With Gemini/Resume Application Tracking System(ATS)/requirements.txt

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+streamlit
+google-generativeai
+python-dotenv
+langchain
+PyPDF2
+faiss-cpu
+langchain_google_genai