Add Data Lab and Data Center Specialist AI role

[GYFX35]

Enhanced the AI assistant with a new role: Data Lab and Data Center Specialist. This role provides expert advice on data lab development, data center infrastructure, scalability, and energy efficiency. The change includes backend logic, API endpoints, frontend UI components, and updated translations for English and Spanish.

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PR created automatically by Jules for task 6415144017764756467 started by @GYFX35

Summary by Sourcery

Add a new Data Lab & Data Center Specialist AI capability across backend and frontend.

New Features:

• Introduce a Vertex AI-powered Data Lab & Data Center Specialist assistant for guidance on data labs, data center infrastructure, scalability, and energy efficiency.
• Expose a protected REST API endpoint for requesting Data Lab & Data Center assistance.
• Add a dedicated UI section and interaction flow for submitting Data Lab & Data Center queries and viewing responses.

Enhancements:

• Extend English and Spanish translations to cover the new Data Lab & Data Center Specialist role and interface text.

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[sourcery-ai]

Reviewer's Guide

Adds a new "Data Lab & Data Center Specialist" AI capability end-to-end, including backend Vertex AI integration, a secured REST endpoint, frontend UI section with input/response handling, and English/Spanish i18n strings.

Sequence diagram for Data Lab and Data Center Specialist assistance flow

sequenceDiagram
    actor User
    participant Browser
    participant FlaskApp
    participant GoogleAI
    participant VertexAI

    User->>Browser: Click data_lab_center_btn
    Browser->>Browser: Collect prompt from data_lab_center_input
    Browser->>User: Prompt for API key
    User-->>Browser: Enter API key
    Browser->>FlaskApp: POST /api/v1/data-lab-center/assistance
    activate FlaskApp
    FlaskApp->>FlaskApp: require_api_key validation
    FlaskApp->>FlaskApp: Parse JSON and validate prompt
    FlaskApp->>GoogleAI: provide_data_lab_center_assistance(prompt)
    activate GoogleAI
    GoogleAI->>VertexAI: GenerativeModel.generate_content(generation_prompt)
    activate VertexAI
    VertexAI-->>GoogleAI: Generated content
    deactivate VertexAI
    GoogleAI-->>FlaskApp: message
    deactivate GoogleAI
    FlaskApp-->>Browser: JSON { status, message }
    deactivate FlaskApp
    Browser->>Browser: Extract message from JSON
    Browser-->>User: Render message in data-lab-center-response

    alt Error case
        Browser-->>User: Display error message in data-lab-center-response
    end

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File-Level Changes

Change	Details	Files
Wire up frontend interaction for the Data Lab & Data Center Specialist tool.	Add DOM bindings for the new button, input textarea, and response container dedicated to data lab & data center assistance. On click, collect the user prompt, request an API key via the existing helper, and POST it to the new backend endpoint. Handle API errors by surfacing a user-friendly error message, and display successful responses in the response container.	frontend/static/js/script.js
Introduce a Vertex AI-backed provider for data lab and data center assistance.	Create a new helper that instantiates the gemini-1.5-flash GenerativeModel and crafts a role-specific, detailed system prompt for data lab and data center guidance. Generate content using the composed prompt and return the stripped text body to callers. Catch and log any exceptions and surface them as error strings to the caller.	google_ai.py
Expose the Data Lab & Data Center Specialist as a dedicated UI section.	Add a new card in the services overview that advertises the Data Lab & Data Center Specialist role and its scope. Create a new section with textarea, submit button, and preformatted response block wired to the JS handlers via element IDs. Ensure all static text uses the translation function for localization.	frontend/templates/index.html
Add a protected REST API endpoint for data lab & data center assistance.	Define a new POST /api/v1/data-lab-center/assistance route guarded by the existing API key decorator. Validate the presence of a prompt in the JSON body and return a 400 with a localized error if missing. Delegate to the new google_ai provider and wrap the result in a standard JSON success payload.	app.py
Localize the new Data Lab & Data Center Specialist UI text in English and Spanish.	Update the base message catalog with keys for the new role name, description, input placeholder, and validation messages as needed. Provide English translations for all new messages. Provide Spanish translations for all new messages.	messages.pot translations/en/LC_MESSAGES/messages.po translations/es/LC_MESSAGES/messages.po

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Status	Name	Latest Commit	Updated (UTC)
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[sourcery-ai]

Hey - I've left some high level feedback:

• The new data-lab-center endpoint, service function, and frontend handler closely mirror the existing role-specific flows; consider extracting a shared helper for role-based AI assistance to reduce duplication and keep behavior consistent across roles.
• In the Data Lab & Data Center frontend handler, response.json() is called unconditionally on non-OK responses; it may be safer to guard this with a try/catch or response.headers.get('Content-Type') check and fall back to a generic message if the response body is not valid JSON.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- The new `data-lab-center` endpoint, service function, and frontend handler closely mirror the existing role-specific flows; consider extracting a shared helper for role-based AI assistance to reduce duplication and keep behavior consistent across roles.
- In the Data Lab & Data Center frontend handler, `response.json()` is called unconditionally on non-OK responses; it may be safer to guard this with a try/catch or `response.headers.get('Content-Type')` check and fall back to a generic message if the response body is not valid JSON.

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