persimmon

FaceTomato is an AI assistant for job preparation. It provides resume analysis, resume optimization, face-to-face question bank, mock interview and interview reporting capabilities. Click "Runtime Settings" in the lower left corner to configure the model capabilities required for AI analysis. Configurable items: - Customize LLM API: Fill in Provider, API Key, Base URL, Model. - GLM OCR API Key: Used to analyze images or scanned PDF resumes. - Bean bag voice input: Used for simulated interview voice input. If you do not configure runtime settings, the application will use backend default environment variables; the default API Key in the current lazy cat package is empty, so real AI parsing usually needs to fill in the available Key here first. ##Resume Analysis Entrance: Navigation on the left-> Resume Analysis. ##Resume Optimization Entrance: Navigation on the left-> Resume Optimization. Usage steps: 1. First upload and analyze a resume in "Resume Analysis". 2. Enter "Resume Optimization". 3. The system generates an overview, risk points and modification suggestions based on the parsed structured resume. 4. You can further check the matching situation and optimization direction based on the target position JD. The following links were verified and accessible on 2026-06-29. Third-party links may change. If they fail, please switch to similar public examples. - Jake's Resume PDF, Overleaf template output: https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs.pdf - Isaac Newton CV, markdown-cv example: https://raw.githubusercontent.com/elipapa/markdown-cv/master/index.md - Official sample of JSON Resume: https://raw.githubusercontent.com/jsonresume/resume-schema/master/sample.resume.json