Wolfram|Alpha LLM Conversational Query

arazzo: 1.0.1
info:
  title: Wolfram|Alpha LLM Conversational Query
  summary: Gate a conversational turn through the recognizer, then answer it with the LLM API.
  description: >-
    Wolfram|Alpha does not expose a dedicated Conversational API in these
    descriptions; the LLM API is the surface purpose-built for AI chat and large
    language model consumption, returning query interpretation, a computed
    result, and a link to the full results page. This workflow adapts the
    requested conversational pattern to that surface: it first uses the Fast
    Query Recognizer (in Voice-or-Default mode) to decide whether a chat turn is
    something Wolfram|Alpha can usefully answer, and when accepted it calls the
    LLM API to produce a structured, chat-ready answer for the assistant to
    speak back. Every step spells out its request inline so the flow can be read
    and executed without opening the underlying OpenAPI descriptions.
  version: 1.0.0
sourceDescriptions:
- name: fastQueryRecognizerApi
  url: ../openapi/wolframalpha-fast-query-recognizer-api-openapi.yml
  type: openapi
- name: llmApi
  url: ../openapi/wolframalpha-llm-api-openapi.yml
  type: openapi
workflows:
- workflowId: llm-conversational-query
  summary: Recognize a chat turn, then answer accepted turns with the LLM API.
  description: >-
    Classifies the conversational query with the Fast Query Recognizer and, when
    accepted, requests a structured chat-ready answer from the LLM API. When the
    turn is not accepted the flow ends so the assistant can decline gracefully.
  inputs:
    type: object
    required:
    - appid
    - input
    properties:
      appid:
        type: string
        description: Wolfram|Alpha AppID used to authenticate every request.
      input:
        type: string
        description: The conversational query / chat turn to answer.
      mode:
        type: string
        description: Recognizer mode, either Default for typed turns or Voice for spoken turns.
      maxchars:
        type: integer
        description: Maximum number of characters in the LLM API response.
      units:
        type: string
        description: Measurement system preference, either metric or imperial.
  steps:
  - stepId: recognizeTurn
    description: >-
      Classify the conversational turn with the Fast Query Recognizer to decide
      whether Wolfram|Alpha can usefully answer it before calling the LLM API.
    operationId: recognizeQuery
    parameters:
    - name: appid
      in: query
      value: $inputs.appid
    - name: mode
      in: query
      value: $inputs.mode
    - name: i
      in: query
      value: $inputs.input
    - name: output
      in: query
      value: json
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      accepted: $response.body#/query/accepted
      domain: $response.body#/query/domain
    onSuccess:
    - name: turnAccepted
      type: goto
      stepId: answerWithLlm
      criteria:
      - context: $response.body
        condition: $.query.accepted == true
        type: jsonpath
    - name: turnRejected
      type: end
      criteria:
      - context: $response.body
        condition: $.query.accepted == false
        type: jsonpath
  - stepId: answerWithLlm
    description: >-
      Send the accepted turn to the LLM API to get a chat-ready structured
      answer with interpretation, result, and a link to full results.
    operationId: queryLlmApi
    parameters:
    - name: appid
      in: query
      value: $inputs.appid
    - name: input
      in: query
      value: $inputs.input
    - name: maxchars
      in: query
      value: $inputs.maxchars
    - name: units
      in: query
      value: $inputs.units
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      inputInterpretation: $response.body#/inputInterpretation
      result: $response.body#/result
      link: $response.body#/link
  outputs:
    accepted: $steps.recognizeTurn.outputs.accepted
    result: $steps.answerWithLlm.outputs.result
    link: $steps.answerWithLlm.outputs.link