Skip to main content

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
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mauna_sdk-0.1.1.tar.gz (30.1 kB view hashes)

Uploaded Source

Built Distribution

mauna_sdk-0.1.1-py3-none-any.whl (49.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page