How sahilbehera6531/hireready-nexus works
HireReady-Nexus is a Flask interview-preparation app. Candidates use its browser UI to submit text or recorded answers; the server evaluates them, updates interview state, and returns feedback, scores, and a next question. Audio answers additionally pass through confidence scoring and transcription. A separate group-discussion feature generates speaker turns and evolves its topic. The graph includes the documented discussion UI capability, though its client wiring is not shown in the excerpts; edges are limited to visible calls or explicit documentation.
Main entry points: server.py Interview Server · model.py Audio Pipeline · script.js Browser Client · train_model.py Model Training
Components 18
Mock Interview
- Interview UI
templates - Browser Client
static/script.js - Interview Server
server.py - Interview Logic
gen.py - Interview State
server.py
Audio Evaluation
- Audio Capture
static/script.js - Audio Upload
server.py - Audio Pipeline
model.py - FFmpeg
- Speech Recognition
Group Discussion
- Discussion Flow
server.py - Discussion UI
templates
Confidence Model
- Model Training
train_model.py - RAVDESS Audio
RAVDESS_dataset - Random Forest
rf_model.pkl
Other components
- Candidate
- Groq LLM
- Discussion Participant
Connections 19
- Candidate → Interview UI: uses
README.md - Interview UI → Browser Client: loads
- Browser Client → Interview Server: posts answers
static/script.js - Interview Server → Interview Logic: evaluates and generates
server.py - Interview Server → Interview State: updates
server.py - Interview Server → Browser Client: returns results
server.py - Browser Client → Audio Capture: records audio
static/script.js - Audio Capture → Audio Upload: uploads recording
static/script.js - Audio Upload → Audio Pipeline: runs analysis
server.py - Audio Pipeline → FFmpeg: converts audio
model.py - Audio Pipeline → Random Forest: predicts confidence
model.py - Audio Pipeline → Speech Recognition: transcribes audio
model.py - Audio Upload → Interview Logic: scores transcript and generates feedback
server.py - Audio Upload → Interview State: updates
server.py - Discussion Participant → Discussion UI: participates
README.md - Discussion UI → Discussion Flow: sends discussion input
- Discussion Flow → Groq LLM: generates turns and topic
server.py - Model Training → RAVDESS Audio: extracts training samples
train_model.py - Model Training → Random Forest: saves trained model
train_model.py