How pavitraseelam/iphone-sentiment-analysis works
This Flask application analyzes product reviews individually or from CSV, returning sentiment, confidence, and issue-specific suggestions for a browser dashboard. The main flow runs from browser input through Flask orchestration to sentiment and suggestion processing, then displays results and aggregate charts. The README is empty, so capabilities are based on the sampled source and file tree; template details and other unsampled implementation are not inferred.
Main entry points: app.py Flask application · script.js UI interactions · index.html Review dashboard · sentiment_model.py Sentiment analysis
Components 10
Browser interface
- Review dashboard
templates/index.html - UI interactions
static/script.js
Flask endpoints
- Flask application
app.py
Review analysis
- Sentiment analysis
sentiment_model.py - Issue suggestions
suggestion_engine.py
External libraries
- CSV parsing
- Hugging Face model
- Chart.js
Other components
- Reviewer
- CSV file
Connections 11
- Reviewer → Review dashboard: uses
- CSV file → UI interactions: selects for upload
- Review dashboard → UI interactions: hosts interface
- UI interactions → Flask application: posts reviews
- Flask application → Review dashboard: serves template
- Flask application → CSV parsing: parses upload
- Flask application → Sentiment analysis: analyzes text
- Flask application → Issue suggestions: requests suggestion
- Sentiment analysis → Hugging Face model: predicts with
- Flask application → UI interactions: returns results
- UI interactions → Chart.js: renders charts