firebase-vertex-ai

仓库: jeremylongshore/claude-code-plugins-plus-skills
安装量: 42
排名: #17274

安装

npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill firebase-vertex-ai

Operate Firebase projects end-to-end (Auth, Firestore, Functions, Hosting) and integrate Gemini/Vertex AI safely for AI-powered features.

Overview

Use this skill to design, implement, and deploy Firebase applications that call Vertex AI/Gemini from Cloud Functions (or other GCP services) with secure secrets handling, least-privilege IAM, and production-ready observability.

Prerequisites

  • Node.js runtime and Firebase CLI access for the target project

  • A Firebase project (billing enabled for Functions/Vertex AI as needed)

  • Vertex AI API enabled and permissions to call Gemini/Vertex AI from your backend

  • Secrets managed via env vars or Secret Manager (never in client code)

Instructions

  • Initialize Firebase (or validate an existing repo): Hosting/Functions/Firestore as required.

  • Implement backend integration:

add a Cloud Function/HTTP endpoint that calls Gemini/Vertex AI

  • validate inputs and return structured responses

  • Configure data and security:

Firestore rules + indexes

  • Storage rules (if applicable)

  • Auth providers and authorization checks

  • Deploy and verify:

deploy Functions/Hosting

  • run smoke tests against deployed endpoints

  • Add ops guardrails:

logging/metrics

  • alerting for error spikes

  • basic cost controls (budgets/quotas) where appropriate

Output

  • A deployable Firebase project structure (configs + Functions/Hosting as needed)

  • Secure backend code that calls Gemini/Vertex AI (with secrets handled correctly)

  • Firestore/Storage rules and index guidance

  • A verification checklist (local + deployed) and CI-ready commands

Error Handling

  • Auth failures: identify the principal and missing permission/role; fix with least privilege.

  • Billing/API issues: detect which API or quota is blocking and provide remediation steps.

  • Firestore rule/index problems: provide minimal repro queries and rule fixes.

  • Vertex AI call failures: surface model/region mismatches and add retries/backoff for transient errors.

Examples

Example: Gemini-backed chat API on Firebase

  • Request: “Deploy Hosting + a Function that powers a Gemini chat endpoint.”

  • Result: /api/chat function, Secret Manager wiring, and smoke tests.

Example: Firestore-powered RAG

  • Request: “Build a RAG flow that embeds docs and answers with citations.”

  • Result: ingestion plan, embedding + index strategy, and evaluation prompts.

Resources

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