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from nexcore_ai import Platform, ModelManager

# Initialize the AI platform
platform = Platform(
    api_key="your-api-key",
    region="us-east-1"
)

# Load pre-trained models
model_manager = ModelManager()
nlp_model = model_manager.load("nexcore-nlp-v3")
vision_model = model_manager.load("nexcore-vision-v2")

# Process text input
def analyze_text(text: str) -> dict:
    """Analyze text using NLP model."""
    result = nlp_model.predict(
        text,
        tasks=["sentiment", "entities", "summary"],
        language="multi"
    )
    return {
        "sentiment": result.sentiment,
        "entities": result.entities,
        "summary": result.summary
    }

# Process image input
def analyze_image(image_url: str) -> dict:
    """Analyze image using vision model."""
    result = vision_model.predict(
        image_url,
        tasks=["objects", "faces", "text"],
        confidence_threshold=0.85
    )
    return {
        "objects": result.objects,
        "faces": result.faces,
        "text": result.text_ocr
    }

module "nexcore_aws_infrastructure" {
  source  = "nexcore/infrastructure/aws"
  version = "2.1.0"
  
  # Environment configuration
  environment          = var.environment
  project_name         = "nexcore-platform"
  
  # VPC Configuration
  vpc_cidr            = "10.0.0.0/16"
  enable_nat_gateway  = true
  single_nat_gateway  = false
  
  # EKS Cluster
  eks_cluster_name    = "nexcore-production"
  eks_node_groups     = {
    general = {
      instance_types = ["m5.large", "m5.xlarge"]
      min_size       = 3
      max_size       = 10
      desired_size   = 5
    }
  }
  
  # RDS Configuration
  enable_rds          = true
  rds_engine          = "postgres"
  rds_engine_version  = "15.2"
  rds_instance_class  = "db.r6g.2xlarge"
  rds_multi_az        = true
  
  # ElastiCache
  enable_elasticache  = true
  elasticache_node_type = "r6g.xlarge"
  elasticache_engine  = "redis"
}