AGENT SKILL

vertex-infra-expert

Terraform infrastructure specialist for Vertex AI services and Gemini deployments. Provisions Model Garden, endpoints, vector search, pipelines, and enterprise AI infrastructure. Triggers: "vertex ai terraform", "gemini deployment terraform", "model garden infrastructure", "vertex ai endpoints"

使用场景运维与部署
License 许可
MIT
最近更新
2026-06-24
Stars
★ 67
Forks
24

01 前言 Front Matter

name
vertex-infra-expert
version
1.0.0
description
Terraform infrastructure specialist for Vertex AI services and Gemini deployments. Provisions Model Garden, endpoints, vector search, pipelines, and enterprise AI infrastructure. Triggers: "vertex ai terraform", "gemini deployment terraform", "model garden infrastructure", "vertex ai endpoints"
allowed-tools
Read, Write, Edit, Grep, Glob, Bash

03 SKILL.md 正文

What This Skill Does

Expert in provisioning Vertex AI infrastructure including Model Garden, Gemini endpoints, vector search, ML pipelines, and production AI services.

When This Skill Activates

Triggers: "vertex ai terraform", "deploy gemini terraform", "model garden infrastructure", "vertex ai endpoints terraform", "vector search terraform"

Core Terraform Modules

Gemini Model Endpoint

resource "google_vertex_ai_endpoint" "gemini_endpoint" {
  name         = "gemini-25-flash-endpoint"
  display_name = "Gemini 2.5 Flash Production"
  location     = var.region

  encryption_spec {
    kms_key_name = google_kms_crypto_key.vertex_key.id
  }
}

resource "google_vertex_ai_deployed_model" "gemini_deployment" {
  endpoint = google_vertex_ai_endpoint.gemini_endpoint.id
  model    = "publishers/google/models/gemini-2.5-flash"

  dedicated_resources {
    min_replica_count      = 1
    max_replica_count      = 10
    machine_spec {
      machine_type = "n1-standard-4"
    }
  }

  automatic_resources {
    min_replica_count = 1
    max_replica_count = 5
  }
}

Vector Search Index

resource "google_vertex_ai_index" "embeddings_index" {
  display_name = "production-embeddings"
  location     = var.region

  metadata {
    contents_delta_uri = "gs://${google_storage_bucket.embeddings.name}/index"
    config {
      dimensions                  = 768
      approximate_neighbors_count = 150
      distance_measure_type       = "DOT_PRODUCT_DISTANCE"

      algorithm_config {
        tree_ah_config {
          leaf_node_embedding_count    = 1000
          leaf_nodes_to_search_percent = 10
        }
      }
    }
  }
}

Tool Permissions

Read, Write, Edit, Grep, Glob, Bash - AI infrastructure provisioning

References

04 同仓库更多 Skills