galafis/Natural-Language-Processing-Suite
Comprehensive NLP toolkit with text classification, named entity recognition, sentiment analysis, and text summarization. Built with transformers, spaCy, and custom models.
What's novel
Comprehensive NLP toolkit with text classification, named entity recognition, sentiment analysis, and text summarization. Built with transformers, spaCy, and custom models.
Code Analysis
15 files read · 4 roundsA from-scratch Python NLP library implementing 7 text processing algorithms (tokenization, stemming, stop words, TF-IDF, sentiment, Naive Bayes, word frequency) with a non-functional Flask backend stub and generic frontend that do not actually use the NLP modules.
Strengths
The 7 NLP modules are genuine from-scratch implementations with correct algorithms (Porter stemmer with VC measure, log-space Naive Bayes with Laplace smoothing, proper TF-IDF), clean consistent API design, and 35+ meaningful tests covering edge cases.
Weaknesses
The backend is a complete stub that uppercases text and returns hardcoded data without importing any NLP module; the frontend is a generic UI scaffold; the R analytics is a standalone 3-method class; the README presents these as an integrated system when they are disconnected components.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
25
Contributors
2
Files
27
Active weeks
7
Repository
Language
Python
Stars
1
Forks
0
License
MIT