82 lines
2.7 KiB
Plaintext
82 lines
2.7 KiB
Plaintext
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# VAPORA Composed Configuration - Enterprise Mode
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#
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# Production high-availability configuration
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# Uses: schema → common defaults → enterprise mode defaults → user customizations
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#
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# Features:
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# - Network accessible with clustering (0.0.0.0)
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# - SurrealDB cluster with replication
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# - NATS JetStream cluster
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# - All LLM providers enabled (Claude, OpenAI, Gemini, Ollama)
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# - Aggressive cost optimization with multi-provider fallback
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# - Enterprise-grade security (TLS enforced, MFA required)
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# - Full observability (Prometheus, OpenTelemetry, distributed tracing)
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# - 90-day knowledge graph retention for learning
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# - 6-hour automated backup interval
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#
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# Prerequisites:
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# - Kubernetes cluster (production-grade)
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# - SurrealDB cluster with replication
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# - NATS JetStream cluster
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# - Prometheus/Grafana stack
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# - TLS certificates for all services
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# - Multi-provider LLM setup
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#
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# Generated: January 12, 2026
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let helpers = import "../common/helpers.ncl" in
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let schema = import "../../vapora/main.ncl" in
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let defaults_mode = import "../defaults/deployment/enterprise.ncl" in
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# Composition: Schema → Mode Defaults → User Config
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helpers.compose_config schema defaults_mode {
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# Production domain configuration
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frontend.api_url = "https://api.vapora.production.com",
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# All providers enabled for cost optimization
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providers = {
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claude_enabled = true,
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openai_enabled = true,
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gemini_enabled = true,
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ollama_enabled = true,
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ollama_url = "http://ollama-cluster.production:11434",
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},
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# Optional: Customize cost control strategy
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# llm_router.budget_enforcement = {
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# enabled = true,
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# window = "monthly",
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# near_threshold_percent = 70, # Alert at 70%
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# auto_fallback = true, # Always fallback to cheaper
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# detailed_tracking = true, # Track every token for billing
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# role_limits = {
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# architect_cents = 2000000, # $20,000/month
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# developer_cents = 1500000, # $15,000/month
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# reviewer_cents = 800000, # $8,000/month
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# testing_cents = 500000, # $5,000/month
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# },
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# },
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# Optional: Customize agent learning
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# agents.learning = {
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# enabled = true,
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# recency_window_days = 30, # 30-day learning window
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# recency_multiplier = 4.0, # Stronger recency weighting
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# },
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# Optional: Customize knowledge graph
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# agents.knowledge_graph = {
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# enabled = true,
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# retention_days = 365, # Full year of history
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# causal_reasoning = true,
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# similarity_search = true,
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# },
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# Optional: Custom backup strategy
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# storage = {
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# base_path = "/var/lib/vapora",
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# backup_enabled = true,
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# backup_interval = 6, # Backup every 6 hours
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# },
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}
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