bench get-app https://github.com/IBSLPUNE/Resume-Insights

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Resume Insights – Resume Parsing for ERPNext

Resume Insights is an ERPNext/Frappe app designed to simplify the recruitment process by automatically extracting key information from resumes uploaded by job applicants. It extracts Name, Email, and Phone Number from PDF or DOCX resumes and autofills the Job Applicant form — reducing manual data entry and speeding up hiring workflows.

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🔧 Features

• Upload resumes in PDF or DOCX formats.
• Parse resumes with a single click using the "Parse Resume" button in the Job Applicant form.
• Automatically extract and populate:
  • Name
  • Email
  • Phone Number
• Converts uploaded files into accessible URLs for parsing.
• Seamless integration with ERPNext Job Applicant DocType.
• User-friendly interface for recruiters and HR teams.

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✅ Version Compatibility

ERPNext Version	Frappe Version	Compatibility
v14.x	v14.x	✅ Fully Compatible
v15.x	v15.x	✅ Fully Compatible

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🔧 Job Applicant Configuration

To use resume parsing:

1. Go to Job Applicant in ERPNext.
2. You will see a Parse Resume button on the form.
3. Click the button to upload a resume (PDF or DOCX).
4. The system will process the uploaded file and populate the following fields automatically:

Field	Description
Name	Extracted full name from resume
Email	Extracted email address
Phone Number	Extracted phone number

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➕ Steps to Use

1. Navigate to Job Applicant DocType.
2. Click the Parse Resume button.
3. Upload your resume file in PDF or DOCX format.
4. Wait for the system to process the file.
5. The Name, Email, and Phone Number fields are automatically filled in the Job Applicant form.

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🖥️ Implementation Details

Frontend:

• Custom button in Job Applicant form triggers file upload dialog.

Backend:

• Python scripts using:
  • PyMuPDF (for PDF parsing)
  • python-docx (for DOCX parsing)
• Extracts Name, Email, and Phone Number using regular expressions.
• Updates Job Applicant DocType automatically.

Error Handling:

• Invalid file types are rejected.
• Unreadable or empty resumes return an error message.

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🛠️ Technologies Used

• ERPNext / Frappe Framework
• Python 3.x
• PyMuPDF (PDF parsing)
• python-docx (DOCX parsing)
• Regular Expressions
• Frappe Client & Server Scripts

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🧾 License

This project is licensed under the MIT License.