1️⃣: DETECT ENTITIES (BACK-END) =======================

📋 ACTION DESCRIPTION
--------------------------------
DETECT ENTITIES (BACK-END) inspects text for entities, and returns information such as entity type (for instance a location, organization, date, person name, event and much more), the associated text, MIB code and metadata such as Wikipedia link when available.

🔧 STEP-BY-STEP SETUP
--------------------------------
ℹ️ The steps from 0) to 1) can be automatically performed by logging in into your Google Cloud Console, opening the Cloud Shell (top right corner of your page) and copy pasting this command and press enter:

wget -q https://storage.googleapis.com/bubblegcpdemo/demo-assets/wiseable-gcp-language.py && python3 wiseable-gcp-language.py

Otherwise, follow these manual steps:

0) Set-up a project from Google Cloud Console : https://cloud.google.com/vision/docs/setup
 - Create or select a project
 - Enable the CLOUD NATURAL LANGUAGE API for that project
 - Create a service account
 - Download a private key as JSON.

1) Open the private key JSON file with a text editor, copy/paste the following parameters from your file to the Plugin settings:
 - CLIENT_EMAIL
 - PROJECT_ID
 - PRIVATE_KEY, including the -----BEGIN PRIVATE KEY-----\\n prefix and \\n-----END PRIVATE KEY-----\\n suffix.

2) Set up the action "DETECT ENTITIES (BACK-END)" in the workflow.
   Inputs Fields:
     - TEXT: A UTF-8 text string. Each string must contain fewer than 1,000,000 bytes of UTF-8 encoded characters.
     - RESULT DATA TYPE: Returned type, must always be set to "RESULT (ANALYTICS)".
   Output Fields:
     - RESULTS: Returns a list of entities identified in the input text and the detected language. For each entity, the response provides the entity type (for instance a location, organization, date, person name, event and much more), the associated text, MIB code and metadata such as Wikipedia link when available. The returned language code conform to ISO-639-1 or BCP-47 identifiers.

⚠️ Note that for back-end actions, the maximum retrievable result set is capped at 30 seconds duration time.

2️⃣: GOOGLE CLOUD NLP TEXT ANALYTICS (FRONT-END)
==========================

📋 ELEMENT DESCRIPTION
--------------------------------
GOOGLE CLOUD NLP TEXT ANALYTICS (FRONT-END) provides a visual element with the DETECT ENTITIES (FRONT-END) action to analyze text for entities. The front-end element is suitable for applications when reactivity is desired.

🔧 STEP-BY-STEP SETUP
--------------------------------
ℹ️ The steps from 0) to 1) can be automatically performed by logging in into your Google Cloud Console, opening the Cloud Shell (top right corner of your page) and copy pasting this command and press enter:

wget -q https://storage.googleapis.com/bubblegcpdemo/demo-assets/wiseable-gcp-language.py && python3 wiseable-gcp-language.py

0) Set-up a project from Google Cloud Console : https://cloud.google.com/vision/docs/setup
 - Create or select a project
 - Enable the CLOUD NATURAL LANGUAGE API for that project
 - Create a service account
 - Download a private key as JSON.

1) Open the private key JSON file with a text editor, copy/paste the following parameters from your file to the Plugin settings:
 - CLIENT_EMAIL
 - PROJECT_ID
 - PRIVATE_KEY, including the -----BEGIN PRIVATE KEY-----\\n prefix and \\n-----END PRIVATE KEY-----\\n suffix.

2) Register on plugins.wiseable.io. Create a new Credential which associates your BUBBLE APP URL, GCP PROJECT_ID, CLIENT_EMAIL & PRIVATE_KEY.
The registration service will generate your PUBLIC ACCESS KEY. This key serves as a secure proxy for your real API key. It allows your application to communicate with the service without exposing your real API key. Since this PUBLIC ACCESS KEY is explicitly tied to your registered BUBBLE APP URL, it can only be used from that domain, ensuring that even if the key is publicly visible, it remains safe and cannot be misused by unauthorized sources.

3) Enter in the PLUGIN SETTINGS your PUBLIC ACCESS KEY (used for front-end element only).

4) Add the GOOGLE CLOUD NLP TEXT ANALYTICS (FRONT-END) element to the page on which the text analysis feature must be integrated. Select the RESULT DATA TYPE as Returned type, must always be set to "RESULT (ANALYTICS)".

5) Integrate the logic into your application using the following GOOGLE CLOUD NLP TEXT ANALYTICS (FRONT-END) element's states and actions:

FIELDS:
- RESULT DATA TYPE: Returned type, must always be set to "RESULT (ANALYTICS)".  

EVENTS:
- SUCCESS: Event triggered upon success
- ERROR: Event triggered upon error

EXPOSED STATES:
Use any element able to show/process the data of interest (such as a Group with a Text field) stored within the result of the following states of the GOOGLE CLOUD NLP TEXT ANALYTICS (FRONT-END) element:
- RESULTS: Populated upon SUCCESS event. Returns a list of entities identified in the input text and the detected language.
- ERROR MESSAGE: Populated upon ERROR event.
- IS PROCESSING: Set to true when processing is in progress, false otherwise.

ELEMENT ACTIONS - TRIGGERED IN WORKFLOW:
- DETECT ENTITIES (FRONT-END): Analyze text for entities. Populate RESULTS state upon completion.

Inputs Fields:
 - TEXT: A UTF-8 text string. Each string must contain fewer than 1,000,000 bytes of UTF-8 encoded characters.

🔍 IMPLEMENTATION EXAMPLE
======================
Feel free to browse the app editor in the Service URL for an implementation example.

ℹ️ ADDITIONAL INFORMATION
======================
> Supported languages: https://cloud.google.com/natural-language/docs/languages

> GOOGLE NATURAL LANGUAGE PROCESSING service limits: https://cloud.google.com/natural-language/quotas

⚠️ TROUBLESHOOTING
================
Any plugin related error will be posted to the Logs tab, "Server logs" section of your App Editor.
Make sure that "Plugin server side output" and "Plugin client side output" is selected in "Show Advanced".

For front-end actions, you can also open your browser's developer console (F12 or Ctrl+Shift+I in most browsers) to view detailed error messages and logs.

Always check the ERROR MESSAGE state of the element and implement error handling using the ERROR event to provide a better user experience.

> Server Logs Details: https://manual.bubble.io/core-resources/bubbles-interface/logs-tab#server-logs

⚡ PERFORMANCE CONSIDERATIONS
===========================

⏱️ BACK-END ACTION START DELAY
-----------------------------------------------
Each time a server-side action is called, Bubble initializes a small virtual machine to execute the action. If the same action is called shortly after, the caching mechanism kicks in, resulting in faster execution on subsequent calls.

A useful workaround is to fire a dummy execution at page load, which pre-warms the Bubble engine for the next few minutes, reducing the impact of cold starts for your users.

❓ QUESTIONS?
===========
Contact us at [email protected] for any additional feature you would require or support question.