On mobile: use your PC's IP (shown in terminal when you run python app.py)
⚠ Model Server Offline
Place twitter_roberta_v2/ next to app.py
Run: pip install -r requirements.txt
Run: python app.py
Check terminal for your IP address, enter above
Tap Set — status will turn green
💡 Terminal shows: Running on http://192.168.x.x:5000
Use that IP on your mobile device
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Try:
Input Terminal — twitter_roberta_v2
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// Running neural inference...
// Sentiment
—
// Language
—
// Emojis
—
// Confidence Scores
Positive
0%
Negative
0%
Neutral
0%
// Extracted Aspects
// Reasoning Output
Analysis Log
Demo Dataset
PHRASES
Tap any phrase to load & analyze
🟢 Positive
🔴 Negative
🔵 Neutral
🌐 Multilingual
😀 Emoji-Aware
🎯 Aspect-Based
⚖️ Mixed / Tricky
System Info
ABOUT
// Model Specifications
Modeltwitter_roberta_v2
ArchitectureRoBERTa-base
TaskSentiment Classification
FormatSafeTensors
BackendFlask + PyTorch
InferenceCPU (local)
// Capabilities
Aspect-Based Sentiment Analysis
Automatically extracts key noun aspects (camera, battery, price) from the input text and highlights them as chips.
Multilingual Support
Detects and labels French 🇫🇷, Spanish 🇪🇸, German 🇩🇪, and Portuguese 🇧🇷 inputs automatically.
Emoji-Aware Processing
Extracts emojis from input and displays them separately, providing an additional sentiment signal beyond text.
Lexical Override
When model confidence is below 65% but strong negative signals are detected (profanity, threats), the system overrides to NEGATIVE with a warning note.
// NLP Pipeline
Preprocessing → URLs replaced with http, @mentions replaced with @user
Tokenization → RoBERTa BPE tokenizer, max 128 tokens
Inference → Softmax over logits → confidence scores
Post-processing → Language detect, emoji extract, aspect extract, lexical override
Dataset → Trained on Twitter/X sentiment data (Kaggle)
// Mobile Usage
Run python app.py on your PC. The terminal shows two IP addresses:
• 127.0.0.1:5000 → only works on the PC itself
• 192.168.x.x:5000 → works from any device on the same WiFi
On this mobile page, enter the 192.168.x.x:5000 address in the Server Address box on the Analyze tab and tap Set.