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# Lets expand on this into a dev plan and for starters we are going to use a shared server, with c-panel and node.js app install capabilities, also has database capabilities and domain and dns management:

Phase P–R: AI-Powered Services
Google AI integration documentation is already present in the repo, giving a head start here .
P — AI Content Generation: Surface Gemini/GPT integrations into the page builder and dashboard for AI-assisted copywriting, image generation, and data summarization. The GOOGLE_AI_INTEGRATION.md doc already outlines the Gemini Studio setup

Phase P on your shared cPanel stack should be a **single AI service in the Node backend** that calls Gemini, with small, high-impact entry points in the page builder and dashboard: “write this for me”, “summarize this”, “explain this”.

***

## 1. Backend AI service (Node on cPanel)

**Goal:** one place that talks to Gemini/GPT; everything else calls into it.

1. Add env vars (in cPanel):
    - `GEMINI_API_KEY`
    - Optionally a model name: `GEMINI_MODEL=gemini-2.0-flash` (or similar).[^1][^2][^3]
2. Install client in your backend:
    - `npm install @google/genai` (or use plain `fetch` against `https://generativelanguage.googleapis.com/v1beta/...`).[^2][^4][^1]
3. Implement a small AI module:
    - `ai/gemini.ts`:
        - `generateText({ prompt, system, maxTokens })`
        - `summarize({ context, instructions })`
        - Later: `generateImage` via appropriate model/endpoint.

These follow the Gemini “generate content” pattern: send a system-style prompt and user content, get back `.text()` for the response.[^3][^1][^2]
4. Expose API endpoints:
    - `POST /api/ai/generate-copy`
    - `POST /api/ai/rewrite-copy`
    - `POST /api/ai/summarize-dashboard`

All are authenticated, tenant-scoped (use your existing auth + tenant middleware), and rate-limited to control spend.

***

## 2. Page builder: AI-assisted copywriting

Hook into the GrapesJS builder (Phase H) as a first UX surface.

**Features:**

- Per-block **“AI Assist”**:
    - For text-based blocks (hero, paragraph, CTA, features), add a button in the block settings: “Generate copy”, “Rewrite”, “Change tone”.
- Flow:

1. User selects a block (e.g. `HeroPrimary`).
2. Side panel shows brief + tone controls (e.g. product description, target audience, “professional / playful / concise”).
3. Frontend calls `POST /api/ai/generate-copy` with:
        - `blockType` (`hero-primary`, `pricing-table`, etc.).
        - Current props (if rewriting).
        - User’s brief and tone.
4. Backend builds a structured prompt:
        - System: “You are an expert SaaS copywriter for business automation platforms.”
        - User: description, tone, fields needed (headline, subheadline, CTA).
5. Gemini returns text; server normalizes into a props object; frontend previews and lets user accept.

This uses standard text-generation patterns: task instruction + context → generated copy.[^1][^2]

***

## 3. Dashboard: AI summarization and explanation

Use your existing dashboard APIs (summary, trends, processes, alerts) as context.

**Features:**

- “**Summarize this dashboard**” button:
    - Collects current KPI payloads (e.g., metrics from `/api/dashboard/:tenantId/summary`, trends, alerts).
    - Sends to `POST /api/ai/summarize-dashboard` with a short instruction (e.g., “Explain this in 3–5 bullets for an executive”).
- “**Explain this metric**” popovers:
    - For a selected metric card, call the same endpoint with just that metric’s history and metadata.
    - Gemini returns a human-readable explanation or “what changed since last period”.

Backend builds prompts like:

- System: “You are an analytics assistant for an automation platform. Be concise and non-technical.”
- User: JSON with metrics, trends, period (“last 30 days”), plus the question.

This follows Gemini’s standard summarization/insight use cases with structured context.[^5][^6][^1]

***

## 4. Image generation (later in Phase P)

Once text flows are stable:

- Add `POST /api/ai/generate-image` that:
    - Accepts brief + style (e.g. “illustration for automation dashboard hero”).
    - Calls the relevant Google model for image generation (via Vertex AI/Gen AI images), or another provider if preferred.[^6][^7]
    - Returns a URL or base64; the frontend inserts it into the hero block’s image slot.

Keep v1 small: a few stock hero/feature illustrations, not full custom art direction.

***

## 5. Multi-tenant, security, and limits

On a shared server:

- Store Gemini key only in backend env; **never** in frontend.
- Add per-tenant rate limits on `/api/ai/*` (e.g. `100` calls/day Starter, `1000` Pro/Enterprise).[^8][^9]
- Avoid sending PII; send aggregate metrics and generic descriptions.
- Gate features with RBAC flags:
    - `ai.builder_use`
    - `ai.dashboard_use`

***

## 6. Milestones

1. **P1 – Backend Gemini integration**
    - AI module + `/api/ai/generate-copy`.
    - Basic error handling and logging.
2. **P2 – Builder copy assist**
    - AI button for hero + paragraph blocks.
    - Generate + rewrite flows.
3. **P3 – Dashboard summarization**
    - “Summarize dashboard” and “Explain metric” features wired to metrics APIs.
4. **P4 – Rate limiting \& tuning**
    - Per-tenant quotas on AI calls.
    - Prompt tuning for tone and safety.

Once this is in place, Q (automated reporting) and R (AI business assistant) are largely about wrapping the same AI service with more workflow and chat UX rather than new core integration work.

Would you rather prioritize the builder’s AI copy assistance or the dashboard summarization in your first Gemini-powered release?

<div align="center">⁂</div>

[^1]: https://ai.google.dev/api/generate-content

[^2]: https://ai.google.dev/gemini-api/docs/text-generation

[^3]: https://ai.google.dev/gemini-api/docs

[^4]: https://github.com/googleapis/googleapis/blob/master/google/ai/generativelanguage/v1beta/generative_service.proto

[^5]: https://firebase.google.com/docs/ai-logic/generate-text

[^6]: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference

[^7]: https://github.com/GoogleCloudPlatform/vertex-ai-creative-studio

[^8]: https://dev.to/hamzakhan/api-rate-limiting-in-nodejs-strategies-and-best-practices-3gef

[^9]: https://github.com/express-rate-limit/express-rate-limit

