Mauna SDK
Project description
Mauna SDK
Installation and usage
Build
poetry install
poetry run codegen
poetry build
Install
pip install mauna_sdk
Usage
from mauna_sdk import Mauna
from mauna_sdk.api.parse_ace import parseACE
from mauna_sdk.api.enum.a_c_e_output_type import ACEOutputType
developer_id = <int> # Check your profile on the dashboard for this.
api_key = "<64 letter api key available on your mauna dashboard>"
client = Mauna(api_key, developer_id)
result = parseACE.execute(client, text="John walks.", format=ACEOutputType.drs)
print(result)
API list
api.parseContext
Takes a list of turns ({ content: string }
) and parses them to produce a semantic frames-based context object.
api.parseContext: (turns: [{ content: string }]) => {
context {
mentions [
{
evokes,
phrase
}
]
}
}
api.paraphraseSentence
Takes an english sentence and produces paraphrased versions of it that retain the semantic meaning of the original.
api.paraphraseSentence: (sentence: string, count: Int = 3) => {
paraphrases
}
api.predictNextTurn
Takes a list of utterances as history and a list of possible alternatives that can be replied with. Returns the most likely alternative and confidence in that prediction.
api.predictNextTurn: (history: [string], alternatives: [string]) => {
nextTurn,
confidence
}
api.matchIntent
Takes a list of intents (with slots) and a user input. Performs structured information extraction to find the correct intent and fill the corresponding slots.
api.matchIntent: (
input: string,
intent: [string],
threshold: Float = 0.7
) => {
matches [
{
intent,
confidence,
slots: [
{
slot,
value,
match_type,
confidence
}
]
}
]
}
api.measureSimilarity
Takes a target sentence and a list of other sentences to compare with for similarity. Returns an array of pairwise similarity scores.
api.measureSimilarity: (sentence: string, compareWith: [string]) => {
result {
score,
sentencePair
}
}
api.resolveCoreferences
api.resolveCoreferences: (text: string) => {
coref: {
detected,
resolvedOutput, // Rewritten input with all the coreferences resolved
clusters: [
{
mention, // token(s) detected as a mention of an entity
references: [
{
match,
score
}
]
}
]
}
}
api.toVec
Takes an English text as an input and returns vector representation for passage, its sentences and entities if found.
api.toVec: (text: string) => {
has_vector,
vector,
vector_norm,
sentences: {
has_vector,
vector_norm,
vector,
text
}
entities: {
text,
has_vector,
vector_norm,
vector
}
}
api.getSentiment
Takes plain English input and returns overall and sentence-level sentiment information. Represents positivity or negativity of the passage as a floating point value.
api.getSentiment: (text: string) => {
sentiment,
sentences: {
text,
sentiment,
}
}
api.parseText
Takes some plain English input and returns parsed categories, entities and sentences.
api.parseText: (text: string) => {
categories: {
label,
score
},
entities: {
label,
lemma,
text
},
sentences: {
text,
label,
lemma
}
}
api.extractNumericData
Takes some text and extracts numeric references as a list of tokens with numeric annotations.
api.extractNumericData: (text: string) => {
tokens: [
{
numeric_analysis: {
data, // numeric data
has_numeric // does this token have numeric info?
}
}
]
}
api.parseTextTokens
Takes some plain English string as input and returns a list of its tokens annotated with linguistic information.
api.parseTextTokens: (text: string) => {
tokens: [
{
dependency, // Type of dependency: PNP, VB ...
entity_type, // Type of entity: PERSON ...
is_alpha,
is_currency,
is_digit,
is_oov, // is out of vocabulary
is_sent_start,
is_stop,
is_title,
lemma,
like_email,
like_num,
like_url,
part_of_speech, // verb, noun ...
prob,
tag,
text
}
]
}
api.renderCSS
Takes ssml and corresponding styles as a css string. Returns base64 encoded audio.
api.renderCSS: (ssml: string, css: string) => {
result // base64 encoded audio
}
api.speechToText
Takes base64 encoded audio as input and returns a list of possible transcripts (sorted in order of decreasing confidence).
api.speechToText: (audio: string) => {
transcript: [
{
text
}
]
}
api.textToSpeech
Takes text (string
) as input and returns audio encoded as a base64 string.
api.textToSpeech: (text: string) => {
audio // base64 encoded audio
}
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