AI-powered job analysis and resume coaching tool using GPT. Analyzes job postings and provides personalized recommendations to job seekers for improving their resumes.
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[ENHANCEMENT] ✨ Enhance Resume Handling and Analysis 📄🔍 #69
Currently, our application handles user resumes by storing them locally in a data file. This approach has limitations and restricts us from performing in-depth analysis and comparisons. We aim to enhance the resume handling process by:
Taking users' resumes directly from the Streamlit application.
Saving the resumes in an SQLite database.
Designing a schema for the new resume table.
Updating the front-end code to seamlessly accept user resumes and store them in the database.
Modifying the code responsible for resume similarity analysis, which currently reads resumes from local files.
Implementing a feature that allows users to select which resume they want to analyze against job listings.
Details:
Current Resume Handling: Resumes are currently stored locally in a data file, which limits our ability to perform dynamic analysis and comparisons.
Proposed Enhancements:
Database Table for Resumes: Create a new table in the SQLite database dedicated to storing user resumes. Design the schema for this table.
Front-End Integration: Update the front-end code to seamlessly accept user resumes through the Streamlit application and store them in the newly created database table.
Resume Similarity Analysis: Modify the code responsible for resume similarity analysis to read resumes from the database rather than local files.
User Resume Selection: Implement a user-friendly feature that allows users to select which resume they want to analyze against job listings, enhancing the user experience.
Expected Benefits:
Users can upload and manage their resumes directly within the application, making it more user-friendly and efficient. 📁🚀
The enhanced system will enable more dynamic and sophisticated resume analysis and comparison against job listings. 🔍📈
Proposed Steps:
Design the schema for the new resume table in the SQLite database.
Update the front-end code to include resume upload functionality.
Modify the resume similarity analysis code to work with the new database storage.
Implement the resume selection feature to allow users to choose the resume for analysis.
Test the entire workflow to ensure proper integration and functionality.
espin086
commented
11 months ago
Currently, our application handles user resumes by storing them locally in a data file. This approach has limitations and restricts us from performing in-depth analysis and comparisons. We aim to enhance the resume handling process by:
Details:
Current Resume Handling: Resumes are currently stored locally in a data file, which limits our ability to perform dynamic analysis and comparisons.
Proposed Enhancements:
Expected Benefits:
Proposed Steps: