components

var ProjectTemplates = map[string]ProjectTemplate{
	"custom": {
		Name:        "Custom",
		Description: "Select components manually",
		Components:  []string{},
	},
	"rag": {
		Name:        "RAG Application",
		Description: "Retrieval-augmented generation with vector search",
		Components:  []string{"llm", "embedding", "database", "vector", "cache"},
	},
	"chatbot": {
		Name:        "Chatbot Application",
		Description: "Create conversational AI interfaces",
		Components:  []string{"llm", "database", "cache"},
	},
	"fullstack": {
		Name:        "Full Stack App",
		Description: "Complete application with all necessary components",
		Components:  []string{"llm", "database", "cache", "queue", "storage"},
	},
	"simple": {
		Name:        "Simple LLM",
		Description: "Just language model, no additional services",
		Components:  []string{"llm"},
	},
}

var Registry = map[string]Component{
	"llm": {
		ID:          "llm",
		Name:        "LLM (Text generation)",
		Description: "Large language models for text generation, chat, and completion",
		Category:    "ai",
		Services:    []string{"ai"},
		Models: []Model{
			{Name: "qwen2.5:3b", Size: "2.3GB", RAM: 4 * GB, Default: true},
			{Name: "llama3.2:3b", Size: "2.0GB", RAM: 4 * GB},
			{Name: "deepseek-coder:1.3b", Size: "1.5GB", RAM: 3 * GB},
			{Name: "phi3:mini", Size: "2.3GB", RAM: 4 * GB},
			{Name: "gemma2:2b", Size: "1.6GB", RAM: 3 * GB},
		},
		MinRAM: 4 * GB,
	},
	"embedding": {
		ID:          "embedding",
		Name:        "Embeddings (Semantic search)",
		Description: "Text embeddings for semantic search and similarity",
		Category:    "ai",
		Services:    []string{"ai"},
		Models: []Model{
			{Name: "nomic-embed-text", Size: "274MB", RAM: 768 * MB, Dimensions: 768, Default: true},
			{Name: "mxbai-embed-large", Size: "670MB", RAM: 1 * GB, Dimensions: 1024},
			{Name: "all-minilm", Size: "46MB", RAM: 256 * MB, Dimensions: 384},
			{Name: "bge-small", Size: "134MB", RAM: 512 * MB, Dimensions: 384},
		},
		MinRAM: 2 * GB,
	},
	"database": {
		ID:          "database",
		Name:        "Database (PostgreSQL)",
		Description: "Standard relational database for data storage",
		Category:    "database",
		Services:    []string{"postgres"},
		MinRAM:      512 * MB,
	},
	"vector": {
		ID:          "vector",
		Name:        "Vector Search (pgvector)",
		Description: "Add vector similarity search to PostgreSQL",
		Category:    "database",
		Services:    []string{"postgres"},
		MinRAM:      512 * MB,
		Config: map[string]interface{}{
			"extension":  "pgvector",
			"depends_on": "database",
		},
	},
	"mongodb": {
		ID:          "mongodb",
		Name:        "NoSQL Database (MongoDB)",
		Description: "Document-oriented database for flexible data storage",
		Category:    "database",
		Services:    []string{"mongodb"},
		MinRAM:      1 * GB,
	},
	"cache": {
		ID:          "cache",
		Name:        "Cache (Redis)",
		Description: "In-memory cache for temporary data and sessions",
		Category:    "infrastructure",
		Services:    []string{"cache"},
		MinRAM:      512 * MB,
	},
	"queue": {
		ID:          "queue",
		Name:        "Queue (Redis)",
		Description: "Reliable job queue for background processing",
		Category:    "infrastructure",
		Services:    []string{"queue"},
		MinRAM:      512 * MB,
	},
	"storage": {
		ID:          "storage",
		Name:        "Object Storage (MinIO)",
		Description: "S3-compatible object storage for files and media",
		Category:    "infrastructure",
		Services:    []string{"minio"},
		MinRAM:      1 * GB,
	},
}