إعداد GCP

from dataclasses import dataclass, field
from typing import List, Dict

# ─── محاكاة Google Cloud SDK ───────────────────────────────
@dataclass
class GCPProject:
    project_id:   str
    display_name: str
    region:       str = "us-central1"
    enabled_apis: List[str] = field(default_factory=list)
    resources:    List[str] = field(default_factory=list)

    def enable_api(self, api: str):
        self.enabled_apis.append(api)
        print(f"  ✅ API enabled: {api}")

    def add_resource(self, kind: str, name: str):
        self.resources.append(f"{kind}/{name}")

class GCPClient:
    REGIONS = {
        "us-central1":     "Iowa, USA",
        "europe-west4":    "Netherlands",
        "asia-southeast1": "Singapore",
        "me-west1":        "Tel Aviv (Middle East)",
    }
    REQUIRED_APIS = {
        "vertex-ai":    "aiplatform.googleapis.com",
        "gemini":       "generativelanguage.googleapis.com",
        "cloud-run":    "run.googleapis.com",
        "bigquery":     "bigquery.googleapis.com",
        "storage":      "storage.googleapis.com",
    }
    COMPUTE_TIERS = {
        "n1-standard-4": {"vCPUs": 4,  "RAM": "15 GB", "GPU": "None",   "price_hr": 0.19},
        "n1-highmem-8":  {"vCPUs": 8,  "RAM": "52 GB", "GPU": "None",   "price_hr": 0.473},
        "a2-highgpu-1g": {"vCPUs": 12, "RAM": "85 GB", "GPU": "A100",   "price_hr": 3.67},
        "tpu-v4-8":      {"vCPUs": 0,  "RAM": "240 GB","GPU": "TPU v4", "price_hr": 5.60},
    }

    def __init__(self):
        self.projects: Dict[str, GCPProject] = {}

    def create_project(self, project_id: str, name: str, region: str = "us-central1") -> GCPProject:
        p = GCPProject(project_id, name, region)
        self.projects[project_id] = p
        loc = self.REGIONS.get(region, region)
        print(f"  ✅ Project: {project_id} ({loc})")
        return p

    def list_compute(self):
        print(f"\n💻 خيارات Compute على GCP:")
        print(f"  {'Machine Type':<18} {'vCPUs':>6} {'RAM':>8} {'GPU':>10} {'Price/hr':>10}")
        print("  " + "-"*56)
        for mtype, spec in self.COMPUTE_TIERS.items():
            price_s = "$" + f"{spec['price_hr']:.2f}"
            print(f"  {mtype:<18} {spec['vCPUs']:>6} {spec['RAM']:>8} {spec['GPU']:>10} {price_s:>10}")

# ─── إعداد GCP للـ AI ──────────────────────────────────────
print("🌐 إعداد Google Cloud Platform للذكاء الاصطناعي:")
print("=" * 55)

gcp = GCPClient()

# إنشاء المشاريع
print("\n1️⃣  إنشاء المشاريع:")
prod = gcp.create_project("my-ai-prod",   "AI Production",  "us-central1")
dev  = gcp.create_project("my-ai-dev",    "AI Development", "europe-west4")

# تفعيل APIs
print("\n2️⃣  تفعيل APIs الضرورية:")
for api_name, api_id in gcp.REQUIRED_APIS.items():
    prod.enable_api(api_id)

# إضافة موارد
print("\n3️⃣  إنشاء الموارد:")
for name, kind in [
    ("vertex-endpoint",   "aiplatform.googleapis.com/Endpoint"),
    ("gemini-deployment",  "aiplatform.googleapis.com/Model"),
    ("data-lake",          "storage.googleapis.com/Bucket"),
    ("ml-pipeline",        "aiplatform.googleapis.com/Pipeline"),
]:
    prod.add_resource(kind, name)
    print(f"  📦 {kind.split('/')[1]}: {name}")

# خيارات Compute
gcp.list_compute()

# ملخص المشاريع
print(f"\n\n📊 ملخص المشاريع:")
for pid, p in gcp.projects.items():
    loc = gcp.REGIONS.get(p.region, p.region)
    print(f"  [{pid}] — {loc}")
    print(f"   APIs: {len(p.enabled_apis)} | Resources: {len(p.resources)}")

# gcloud CLI
print(f"\n💻 أوامر gcloud الأساسية:")
cmds = [
    ("تسجيل الدخول",     "gcloud auth login"),
    ("تعيين المشروع",    "gcloud config set project my-ai-prod"),
    ("تفعيل API",        "gcloud services enable aiplatform.googleapis.com"),
    ("Service Account",  "gcloud iam service-accounts create ai-sa --display-name 'AI SA'"),
    ("تحميل المفتاح",    "gcloud iam service-accounts keys create key.json --iam-account ai-sa@..."),
]
for desc, cmd in cmds:
    print(f"  # {desc}")
    print(f"  $ {cmd}")
    print()
print("✅ GCP جاهز للاستخدام!")