example yaml

swagger: '2.0'
info:
  description: >-
    This API implments some simple natural language processing tasks like
    tokenization, sentiment analysis, finding the most common words, and
    retrieving parts of speech from text.
  version: 2017.06.14
  title: Natural Language Processing with Anaconda
  termsOfService: ''
  contact:
    email: [email protected]
  license:
    name: Apache 2.0
    url: 'http://www.apache.org/licenses/LICENSE-2.0.html'
host: 'https://enterprise.demo.continuum.io:XXXXX'
basePath: /
tags:
  - name: tokenize
    description: Tokenize text.
  - name: sentiment
    description: Sentiment analysis of text.
  - name: parts_of_speech
    description: Retrieve parts of speech from text.
  - name: top_k
    description: Get the k most common words from a collection of text.
  - name: topics
    description: Perform Latent Dirichlet Allocation on a collection on text.
schemes:
  - http
  - https
paths:
  /tokenize:
    get:
      tags:
        - tokenize
      summary: Get tokens from text.
      description: ''
      consumes:
        - application/json
        - text/plain
      produces:
        - application/json
      parameters:
        - in: body
          name: data
          description: Text to be tokenized.
          required: true
          schema:
            type: object
            properties:
              data:
                type: string
        - name: unique
          in: query
          description: Only return unique tokens?
          required: false
          type: string
        - name: library
          in: query
          description: >-
            Which library to use for tokenization? Options are textblob, gensim,
            nltk, or spacy
          required: false
          type: string
      responses:
        '200':
          description: OK
          schema:
            type: object
            properties:
              library:
                type: string
                description: The library used for tokenization.
                example: textblob
              tokens:
                type: array
                description: The array of tokens in the text.
                example:
                  - anaconda
                  - is
                  - awesome
        '405':
          description: Invalid data type
  /sentiment:
    get:
      tags:
        - sentiment
      summary: Get the sentiment score from input text.
      description: ''
      consumes:
        - application/json
        - text/plain
      produces:
        - application/json
      parameters:
        - in: body
          name: data
          description: Text to be analyzed.
          required: true
          schema:
            type: object
            properties:
              data:
                type: string
        - name: type
          in: query
          description: >-
            The type of sentiment analyzer to use. Type = 1 (the default) uses
            the implmentation from the pattern library. Type = 2 uses a Naive
            Bayes classifier trained on movie reviews from nltk.
          required: false
          type: integer
      responses:
        '200':
          description: OK
          schema:
            type: object
            properties:
              classifier_type:
                type: integer
                example: 1
                description: Classifier type used in the sentiment analysis.
              sentiment_score:
                type: string
                example: -0.6
                description: >-
                  If type = 1, returns the sentiment score. Ranges from -1 (very
                  negative) to 1 (very positive). If type = 2, returns whether
                  the text is predicted to be positive or negative, the
                  probability that the text is positive, and the probability
                  that the text is negative.
        '405':
          description: Invalid data type
  /top_k:
    get:
      tags:
        - top_k
      summary: Get the top k most common tokens from a collection of texts.
      description: ''
      consumes:
        - application/json
        - text/plain
      produces:
        - application/json
      parameters:
        - in: body
          name: data
          description: Text to be analyzed.
          required: true
          schema:
            type: object
            properties:
              data:
                type: string
        - in: query
          name: library
          description: >-
            Library to use for tokenization. Options are textblob (the default),
            nltk, gensim, and spacy.
          required: false
          type: string
        - in: query
          name: k
          type: integer
          description: Find the top k most common tokens in all the text passed.
          required: false
      responses:
        '200':
          description: OK
          schema:
            type: object
            properties:
              k:
                type: integer
                description: Returning the top k most common words.
                example: 1
              library:
                type: string
                description: The library used for tokenization.
                example: nltk
              top_k:
                type: array
                description: >-
                  List of the most popular words in the collection of strings
                  passed, in the format ["token", count].
                example:
                  - anaconda
                  - 5
        '405':
          description: Invalid data type
  /parts_of_speech:
    get:
      tags:
        - parts_of_speech
      summary: Gets the parts of speech from text.
      description: ''
      consumes:
        - application/json
        - text/plain
      produces:
        - application/json
      parameters:
        - in: body
          name: data
          description: Text to be analyzed.
          required: true
          schema:
            type: object
            properties:
              data:
                type: string
      responses:
        '200':
          description: OK
          schema:
            type: object
            properties:
              nouns:
                type: array
                description: List of nouns.
                example:
                  - brown
                  - fox
                  - dog
              adverbs:
                type: array
                description: List of adverbs.
                example: []
              verbs:
                type: array
                description: List of verbs.
                example:
                  - jumped
              number:
                type: array
                description: 'List of any numbers (e.g. three, 11) in the text.'
                example: []
              adjectives:
                type: array
                description: List of adjectives.
                example:
                  - quick
                  - lazy
        '405':
          description: Invalid data type
  /topics:
    get:
      tags:
        - topics
      summary: Perform Latent Dirichlet Allocation on a collection of text.
      description: ''
      consumes:
        - application/json
        - text/plain
      produces:
        - application/json
      parameters:
        - in: body
          name: data
          description: Text to be analyzed.
          required: true
          schema:
            type: object
            properties:
              data:
                type: string
        - in: query
          name: num_topics
          description: Number of topics to return.
          required: false
          type: string
      responses:
        '200':
          description: OK
          schema:
            type: object
            properties:
              number_of_topics:
                type: integer
                description: The number of topics the LDA analysis returns.
                example: 5
              topics:
                type: array
                description: List of topics output by the analysis.
        '405':
          description: Invalid data type
securityDefinitions:
  APIKey:
    type: apiKey
    in: header
    name: TOKEN