431 lines
14 KiB
Plaintext
431 lines
14 KiB
Plaintext
# AI Module for Provisioning CLI
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# Enhanced natural language interface with intelligent agents
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use std
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use ../lib_provisioning/ai/lib.nu *
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use ../lib_provisioning/utils/settings.nu load_settings
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use ../lib_provisioning/plugins_defs.nu render_template
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use ../ai/query_processor.nu *
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# Main AI command dispatcher
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export def main [
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action: string
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...args: string
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--prompt: string
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--template-type: string = "server"
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--context: string
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--provider: string
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--model: string
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--max-tokens: int
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--temperature: float
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--test
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--config
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--enable
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--disable
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]: nothing -> any {
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match $action {
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"template" => { ai_template_command $args $prompt $template_type }
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"query" => {
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if ($prompt | is-not-empty) {
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enhanced_query_command $prompt $context
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} else {
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ai_query_command $args $prompt $context
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}
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}
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"chat" => { start_interactive_chat }
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"capabilities" => { show_ai_capabilities }
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"examples" => { show_query_examples }
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"batch" => {
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if ($args | length) > 0 {
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process_batch_file $args.0
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} else {
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print "❌ Batch processing requires a file path"
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}
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}
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"performance" => { run_ai_benchmark }
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"webhook" => { ai_webhook_command $args $prompt }
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"test" => { ai_test_command }
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"config" => { ai_config_command }
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"enable" => { ai_enable_command }
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"disable" => { ai_disable_command }
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"help" => { enhanced_ai_help_command }
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_ => {
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print $"Unknown AI action: ($action)"
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enhanced_ai_help_command
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}
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}
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}
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# Generate infrastructure templates using AI
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def ai_template_command [
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args: list<string>
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prompt: string
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template_type: string
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] {
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if ($prompt | is-empty) {
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error make {msg: "AI template generation requires --prompt"}
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}
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let result = (ai_generate_template $prompt $template_type)
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print $"# AI Generated ($template_type) Template"
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print $"# Prompt: ($prompt)"
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print ""
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print $result
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}
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# Process natural language queries about infrastructure
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def ai_query_command [
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args: list<string>
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prompt: string
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context: string
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] {
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if ($prompt | is-empty) {
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error make {msg: "AI query requires --prompt"}
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}
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let context_data = if ($context | is-empty) {
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{}
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} else {
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if ($context | str starts-with "{") {
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($context | from json)
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} else {
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{raw_context: $context}
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}
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}
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let result = (ai_process_query $prompt $context_data)
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print $result
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}
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# Process webhook/chat messages
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def ai_webhook_command [
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args: list<string>
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prompt: string
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] {
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if ($prompt | is-empty) {
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error make {msg: "AI webhook processing requires --prompt"}
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}
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let user_id = if ($args | length) > 0 { $args.0 } else { "cli" }
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let channel = if ($args | length) > 1 { $args.1 } else { "direct" }
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let result = (ai_process_webhook $prompt $user_id $channel)
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print $result
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}
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# Test AI connectivity and configuration
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def ai_test_command [] {
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print "Testing AI configuration..."
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let validation = (validate_ai_config)
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if not $validation.valid {
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print "❌ AI configuration issues found:"
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for issue in $validation.issues {
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print $" - ($issue)"
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}
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return
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}
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print "✅ AI configuration is valid"
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let test_result = (test_ai_connection)
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if $test_result.success {
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print $"✅ ($test_result.message)"
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if "response" in $test_result {
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print $" Response: ($test_result.response)"
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}
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} else {
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print $"❌ ($test_result.message)"
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}
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}
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# Show AI configuration
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def ai_config_command [] {
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let config = (get_ai_config)
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print "🤖 AI Configuration:"
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print $" Enabled: ($config.enabled)"
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print $" Provider: ($config.provider)"
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print $" Model: ($config.model? // 'default')"
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print $" Max Tokens: ($config.max_tokens)"
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print $" Temperature: ($config.temperature)"
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print $" Timeout: ($config.timeout)s"
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print ""
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print "Feature Flags:"
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print $" Template AI: ($config.enable_template_ai)"
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print $" Query AI: ($config.enable_query_ai)"
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print $" Webhook AI: ($config.enable_webhook_ai)"
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if $config.enabled and ($config.api_key? == null) {
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print ""
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print "⚠️ API key not configured"
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print " Set environment variable based on provider:"
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print " - OpenAI: OPENAI_API_KEY"
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print " - Claude: ANTHROPIC_API_KEY"
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print " - Generic: LLM_API_KEY"
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}
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}
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# Enable AI functionality
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def ai_enable_command [] {
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print "AI functionality can be enabled by setting ai.enabled = true in your KCL settings"
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print "Example configuration:"
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print ""
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print "ai: AIProvider {"
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print " enabled: true"
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print " provider: \"openai\" # or \"claude\" or \"generic\""
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print " api_key: env(\"OPENAI_API_KEY\")"
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print " model: \"gpt-4\""
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print " max_tokens: 2048"
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print " temperature: 0.3"
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print " enable_template_ai: true"
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print " enable_query_ai: true"
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print " enable_webhook_ai: false"
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print "}"
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}
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# Disable AI functionality
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def ai_disable_command [] {
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print "AI functionality can be disabled by setting ai.enabled = false in your KCL settings"
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print "This will disable all AI features while preserving configuration."
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}
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# Show AI help
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def ai_help_command [] {
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print "🤖 AI-Powered Provisioning Commands"
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print ""
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print "USAGE:"
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print " ./core/nulib/provisioning ai <ACTION> [OPTIONS]"
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print ""
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print "ACTIONS:"
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print " template Generate infrastructure templates from natural language"
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print " query Process natural language queries about infrastructure"
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print " webhook Process webhook/chat messages"
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print " test Test AI connectivity and configuration"
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print " config Show current AI configuration"
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print " enable Show how to enable AI functionality"
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print " disable Show how to disable AI functionality"
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print " help Show this help message"
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print ""
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print "TEMPLATE OPTIONS:"
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print " --prompt <text> Natural language description"
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print " --template-type <type> Type of template (server, cluster, taskserv)"
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print ""
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print "QUERY OPTIONS:"
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print " --prompt <text> Natural language query"
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print " --context <json> Additional context as JSON"
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print ""
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print "WEBHOOK OPTIONS:"
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print " --prompt <text> Message to process"
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print " <user_id> User ID for context"
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print " <channel> Channel for context"
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print ""
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print "EXAMPLES:"
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print " # Generate a Kubernetes cluster template"
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print " ./core/nulib/provisioning ai template --prompt \"3-node Kubernetes cluster with Ceph storage\""
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print ""
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print " # Query infrastructure status"
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print " ./core/nulib/provisioning ai query --prompt \"show all running servers with high CPU\""
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print ""
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print " # Process chat message"
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print " ./core/nulib/provisioning ai webhook --prompt \"deploy redis cluster\" user123 slack"
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print ""
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print " # Test AI configuration"
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print " ./core/nulib/provisioning ai test"
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}
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# AI-enhanced generate command
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export def ai_generate [
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type: string
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--prompt: string
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--template-type: string = "server"
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--output: string
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]: nothing -> any {
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if ($prompt | is-empty) {
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error make {msg: "AI generation requires --prompt"}
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}
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let result = (ai_generate_template $prompt $template_type)
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if ($output | is-empty) {
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print $result
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} else {
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$result | save $output
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print $"AI generated ($template_type) saved to: ($output)"
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}
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}
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# AI-enhanced query with provisioning context
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export def ai_query_infra [
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query: string
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--infra: string
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--provider: string
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--output-format: string = "human"
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]: nothing -> any {
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let context = {
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infra: ($infra | default "")
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provider: ($provider | default "")
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output_format: $output_format
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}
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let result = (ai_process_query $query $context)
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match $output_format {
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"json" => { {query: $query, response: $result} | to json }
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"yaml" => { {query: $query, response: $result} | to yaml }
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_ => { print $result }
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}
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}
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# Enhanced AI query command with intelligent agents
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def enhanced_query_command [
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prompt: string
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context: string
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] {
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print $"🤖 Enhanced AI Query: ($prompt)"
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let result = process_query $prompt --format "summary"
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print $result
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}
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# Show AI system capabilities
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def show_ai_capabilities [] {
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let caps = get_query_capabilities
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print "🤖 Enhanced AI System Capabilities"
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print ""
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print "📋 Supported Query Types:"
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$caps.supported_types | each { |type| print $" • ($type)" }
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print ""
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print "🤖 Available AI Agents:"
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$caps.agents | each { |agent| print $" • ($agent)" }
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print ""
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print "📊 Output Formats:"
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$caps.output_formats | each { |format| print $" • ($format)" }
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print ""
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print "🚀 Features:"
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$caps.features | each { |feature| print $" • ($feature)" }
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}
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# Show query examples
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def show_query_examples [] {
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print "💡 Enhanced AI Query Examples"
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print ""
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print "🏗️ Infrastructure Status:"
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print " • \"What servers are currently running?\""
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print " • \"Show me the health status of all services\""
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print " • \"Which containers are consuming the most resources?\""
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print ""
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print "⚡ Performance Analysis:"
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print " • \"Which services have high CPU usage?\""
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print " • \"What's causing slow response times?\""
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print " • \"Show me memory usage trends over the last hour\""
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print ""
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print "💰 Cost Optimization:"
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print " • \"How can I reduce my AWS costs?\""
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print " • \"Which instances are underutilized?\""
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print " • \"Show me the most expensive resources\""
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print ""
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print "🛡️ Security Analysis:"
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print " • \"Are there any security threats detected?\""
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print " • \"Show me recent failed login attempts\""
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print " • \"What vulnerabilities exist in the system?\""
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print ""
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print "🔮 Predictive Analysis:"
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print " • \"When will I need to scale the database?\""
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print " • \"Predict disk space usage for next month\""
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print " • \"What failures are likely to occur soon?\""
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}
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# Process batch queries from file
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def process_batch_file [file_path: string] {
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if not ($file_path | path exists) {
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print $"❌ File not found: ($file_path)"
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return
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}
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let queries = (open $file_path | lines | where { |line| not ($line | is-empty) and not ($line | str starts-with "#") })
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print $"📋 Processing ($queries | length) queries from: ($file_path)"
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let results = process_batch_queries $queries --format "summary"
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$results | enumerate | each { |item|
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print $"--- Query ($item.index + 1) ---"
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print $item.item
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print ""
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}
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}
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# Run AI performance benchmark
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def run_ai_benchmark [] {
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let benchmark_queries = [
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"What's the current CPU usage?"
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"Show me error logs from the last hour"
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"Which services are consuming high memory?"
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"Are there any security alerts?"
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"Predict when we'll need more storage"
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]
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let results = analyze_query_performance $benchmark_queries
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print "📊 AI Query Performance Benchmark"
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print $"Total Queries: ($results.total_queries)"
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print $"Average Duration: ($results.average_duration_ms) ms"
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print $"Queries per Second: ($results.queries_per_second | math round -p 2)"
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}
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# Enhanced AI help command
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def enhanced_ai_help_command [] {
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print "🤖 Enhanced AI-Powered Provisioning Commands"
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print ""
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print "USAGE:"
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print " ./core/nulib/provisioning ai <ACTION> [OPTIONS]"
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print ""
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print "ENHANCED ACTIONS:"
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print " query Process natural language queries with intelligent agents"
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print " chat Interactive AI chat mode"
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print " capabilities Show AI system capabilities"
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print " examples Show example queries"
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print " batch Process batch queries from file"
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print " performance Run performance benchmarks"
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print ""
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print "LEGACY ACTIONS:"
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print " template Generate infrastructure templates"
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print " webhook Process webhook/chat messages"
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print " test Test AI connectivity"
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print " config Show AI configuration"
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print " enable Enable AI functionality"
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print " disable Disable AI functionality"
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print ""
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print "ENHANCED QUERY EXAMPLES:"
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print " # Natural language infrastructure queries"
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print " ./core/nulib/provisioning ai query --prompt \"What servers are using high CPU?\""
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print " ./core/nulib/provisioning ai query --prompt \"How can I reduce AWS costs?\""
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print " ./core/nulib/provisioning ai query --prompt \"Are there any security threats?\""
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print ""
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print " # Interactive chat mode"
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print " ./core/nulib/provisioning ai chat"
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print ""
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print " # Batch processing"
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print " ./core/nulib/provisioning ai batch queries.txt"
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print ""
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print " # Performance analysis"
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print " ./core/nulib/provisioning ai performance"
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print ""
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print "🚀 New Features:"
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print " • Intelligent agent selection"
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print " • Natural language processing"
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print " • Real-time data integration"
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print " • Predictive analytics"
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print " • Interactive chat mode"
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print " • Batch query processing"
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} |