CV/Resume Analyser

The script analyses CVs/resumes for the presence of specified keywords and extracts the candidate's name and relevant experiences. It uses the OpenAI API to perform the analysis and provides a Gradio interface for user interaction.

Features

• Extracts text from PDF CVs/resumes
• Analyses CVs/resumes for the presence of specified keywords
• Extracts candidate's name and relevant experiences
• Provides a list of the top three candidates based on the analysis
• Offers a user-friendly Gradio interface for uploading CVs/resumes and viewing the analysis results

Dependencies

• OpenAI
• PyPDF2
• Gradio

Usage

1. Set the OPENAI_KEY environment variable with your OpenAI API key: export OPENAI_KEY="your_api_key"

2. Install the required dependencies using pip install -r requirements.txt

    ## Prerequisites
    python3 -m venv .venv
    source .venv/bin/activate
    pip3 install -r requirements.txt
    python3 -m pip install --upgrade pip
   

3. Run the script using python3 cv_analyser.py.

4. Access the Gradio interface in your web browser: http://localhost:7860

5. Upload the CVs/resumes (maximum 10) in PDF format.

6. Click the Submit button to analyse the CVs/resumes.

7. View the analysis results, including the top three candidates' names, relevant keywords, and standout experiences.

Processing Time

Number of CVs/Resumes	Processing Time
10	49.9 seconds

Customisation

• Modify the keywords list in the use_gradio_interface() function to specify the desired keywords for cv/resume analysis.
• Adjust the prompts in the analyse_cv() and analyse_cvs() methods to customise the analysis and output format.

License

This project is licensed under the MIT License.

Acknowledgements

• Thank you, Yas. 🙏🏽 Maybe make it a microservice? 😎 — Rebel Recruiters
• OpenAI for providing the powerful GPT-3.5-turbo language model
• PyPDF2 for simplifying the extraction of text from PDF documents
• Gradio for enabling the creation of interactive web interfaces

Copyright

(c) 2024 Finbarrs Oketunji.

Developed at LincolnHack 2024 in collaboration with Digital Lincoln — Lincolnshire 🇬🇧