# Open.AI NLP Sentiment Analysis
#

# Account slugs:
#  - quickbase[jOder3V]: ChatGPT Application <None>
---
- META:
    name: Open.AI NLP Sentiment Analysis
    enabled: true
- TRIGGER quickbase[jOder3V] record on_create -> a:
    inputs-meta:
      export_fields: '"Question, Response, Related Components - Prompt" <6, 7, 10>'
      table: '"ChatGPT: Questions" <btd84fwy6>'
- ACTION json-handler json_source fetch_json_blob -> b:
    inputs-meta:
      body: "{\n  \"model\": \"text-davinci-003\",\n  \"prompt\": \"Interpret the\
        \ sentiment embedded within the user's statement: '{{a.question}}'. Scrutinize\
        \ the phrasing, tone, and inherent context to identify the dominant sentiment.\
        \ Allocate the sentiment to one of these classifications: positive, neutral,\
        \ negative, or mixed. Justify the classification succinctly, highlighting\
        \ specific linguistic indicators and emotional resonances found within the\
        \ statement.\",\n  \"temperature\": 0.4,\n  \"max_tokens\": 3500,\n  \"top_p\"\
        : 1,\n  \"frequency_penalty\": 0,\n  \"presence_penalty\": 0\n}"
      headers: 'Content-Type: application/json

        Authorization: PASTE OPENAI API KEY
      json_url: https://api.openai.com/v1/completions
      method_type: POST
- b<>QUERY json-handler json_object search -> c:
    inputs-meta:
      json_records_path: /choices
      json_schema_sample: "{\"text\": \"\\n\\nThis is indeed a test\",\n      \"index\"\
        : 0,\n      \"logprobs\": null,\n      \"finish_reason\": \"length\"\n   \
        \ }"
- c<>LOOP:
  - DO:
    - a<>ACTION quickbase record update -> d:
        inputs:
          response: '{{c.text}}'
...