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# GPTC # GPTC
General-purpose text classifier in Python General-purpose text classifier in Python
GPTC provides both a CLI tool and a Python library. GPTC provides both a CLI tool and a Python library.
## CLI Tool ## CLI Tool
### Classifying text ### Classifying text
python -m gptc <modelfile> python -m gptc <modelfile>
@ -23,20 +25,28 @@ category:probability, ...}` to stdout.
python -m gptc <raw model file> -c|--compile <compiled model file> python -m gptc <raw model file> -c|--compile <compiled model file>
## Library ## Library
### `gptc.Classifier(model)` ### `gptc.Classifier(model)`
Create a `Classifier` object using the given *compiled* model (as a dict, not Create a `Classifier` object using the given *compiled* model (as a dict, not
JSON). JSON).
#### `Classifier.confidence(text)` #### `Classifier.confidence(text)`
Classify `text`. Returns a dict of the format `{category: probability, Classify `text`. Returns a dict of the format `{category: probability,
category:probability, ...}` category:probability, ...}`
#### `Classifier.classify(text)` #### `Classifier.classify(text)`
Classify `text`. Returns the category into which the text is placed (as a Classify `text`. Returns the category into which the text is placed (as a
string), or `None` when it cannot classify the text. string), or `None` when it cannot classify the text.
## `gptc.compile(raw_model)` ## `gptc.compile(raw_model)`
Compile a raw model (as a list, not JSON) and return the compiled model (as a Compile a raw model (as a list, not JSON) and return the compiled model (as a
dict). dict).
## Model format ## Model format
This section explains the raw model format, which is how you should create and This section explains the raw model format, which is how you should create and
edit models. edit models.
@ -55,6 +65,7 @@ in any way these Python objects can be. However, it is recommended to store
them in JSON format for compatibility with the command-line tool. them in JSON format for compatibility with the command-line tool.
## Example model ## Example model
An example model, which is designed to distinguish between texts written by An example model, which is designed to distinguish between texts written by
Mark Twain and those written by William Shakespeare, is available in `models`. Mark Twain and those written by William Shakespeare, is available in `models`.
The raw model is in `models/raw.json`; the compiled model is in The raw model is in `models/raw.json`; the compiled model is in