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Alfredo

See exactly how TF-IDF, TextRank, and sentiment scoring work — with code you can read in 5 minutes — running at production speed.

Alfredo is not a wrapper around an LLM API. It's a self-contained, offline, dependency-light NLP toolkit built for two audiences at once: learners who want to see the actual math behind NLP tasks, and developers who want something fast enough to ship without API keys, network calls, or per-request costs.

Install

pip install -e ".[dev]"

Usage

import alfredo as nlp

nlp.summarize("Long article text...", num_sentences=2)
nlp.sentiment("This product is amazing!")
nlp.classify("Free money now!!!", labels=["spam", "not spam"])
nlp.extract_keywords("Machine learning is a subset of artificial intelligence...")

Why Alfredo

Goal Why it matters
No external AI API calls Works offline, no API key, no per-call cost, no network latency
Readable source code Every algorithm should be understandable in one sitting
Fast (NumPy-vectorized) Not "slow but educational" — usable in real projects
Documented reasoning docs/HOW_IT_WORKS.md explains the why, not just the what
Benchmarked Speed claims backed by numbers vs. nltk/spaCy/textblob

Benchmarks

Run python benchmarks/benchmark.py and paste real numbers here once available.

Task Alfredo nltk textblob
summarize
sentiment
extract_keywords

Development

pip install -e ".[dev]"
pytest tests/
python benchmarks/benchmark.py

License

MIT — see LICENSE.

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0.1.3

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