Flask wrappers for different models from deepcubes package
Just several examples of usage
POST query with config field as json string representaion:
{
"lang": string, # now just "rus" or "eng"
"not_understand_label": string, # any string that corresponds to `not understand` label
"labels_settings": [
{
"label": string, # unique label name
"patterns": [string], # list with regexps, example: ["нет", "нет.*"]
"generics": [string], # list with generics, possible:
# ["yes", "no", "repeat", "no"questions"]
"intent_phrases": [string], # list with intent phrases for ML
},
...
]
}
Returns json string with model_id (int).
POST query with model_id (int) field (returned by /train) and query (string) field as user input text. Additionall labels ([array representation]) field can be specified, in this case model returns probabilities only for specified labels.
Returns collection of labels sorted decreasingly according probabilities.
[
{
"label": string,
"proba": float
},
...
]
POST query with tokens ([[string, string, ...], [string, string, ...], ...]) fields.
Returns json string with vectors field, lists of floats with embedding vectors components.
- Dmitry Ischenko
- Svyatoslav Nevyantsev