440 lines
13 KiB
Text
440 lines
13 KiB
Text
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#!/usr/bin/env nu
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# AI-Enhanced CLI Commands for AuroraFrame
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#
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# Integrates with the Nushell MCP server to provide AI-powered development commands:
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# - Content generation and enhancement
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# - Schema design and validation
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# - Error resolution and debugging
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# - Asset optimization and generation
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# Configuration for MCP server
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let MCP_SERVER_PATH = "./auroraframe-mcp-server/mcp-server.nu"
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let MCP_CONFIG = {
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timeout: 30000 # 30 seconds
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max_retries: 3
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}
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# Main AI command dispatcher
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export def "ai" [
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command: string # AI command to execute
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...args: string # Command arguments
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--debug(-d) # Enable debug output
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] {
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match $command {
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"generate" => (ai_generate ...$args --debug=$debug)
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"enhance" => (ai_enhance ...$args --debug=$debug)
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"schema" => (ai_schema ...$args --debug=$debug)
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"fix" => (ai_fix ...$args --debug=$debug)
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"analyze" => (ai_analyze ...$args --debug=$debug)
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"help" => (ai_help)
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_ => {
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print $"❌ Unknown AI command: ($command)"
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ai_help
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}
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}
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}
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# AI Content Generation
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export def "ai generate" [
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type: string = "content" # Type: content, page, schema, docs
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...args: string # Additional arguments
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--prompt(-p): string # Generation prompt
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--schema(-s): string # Schema file to use
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--format(-f): string = "markdown" # Output format
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--output(-o): string # Output file
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--debug(-d) # Debug mode
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] {
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if $debug { print "🧠 AI Generate: Starting content generation..." }
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match $type {
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"content" => (generate_content $prompt $schema $format $output $debug)
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"page" => (generate_page $args $prompt $debug)
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"schema" => (generate_schema_from_prompt $prompt $debug)
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"docs" => (generate_documentation $args $debug)
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_ => {
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print $"❌ Unknown generation type: ($type)"
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print "Available types: content, page, schema, docs"
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}
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}
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}
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# AI Content Enhancement
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export def "ai enhance" [
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target: string # File or content to enhance
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--type(-t): string = "seo" # Enhancement type: seo, readability, structure, metadata
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--output(-o): string # Output file
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--debug(-d) # Debug mode
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] {
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if $debug { print $"🚀 AI Enhance: Enhancing ($target) for ($type)" }
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if not ($target | path exists) {
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print $"❌ File not found: ($target)"
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return
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}
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let content = (open $target)
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let enhancement_types = [$type]
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let mcp_request = {
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method: "tools/call"
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params: {
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name: "enhance_content"
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arguments: {
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content: $content
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enhancements: $enhancement_types
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}
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}
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}
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let result = (call_mcp_server $mcp_request $debug)
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if "error" in $result {
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print $"❌ Enhancement failed: ($result.error)"
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return
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}
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let enhanced_content = $result.content.0.text
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if ($output | is-not-empty) {
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$enhanced_content | save $output
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print $"✅ Enhanced content saved to: ($output)"
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} else {
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print $enhanced_content
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}
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}
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# AI Schema Operations
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export def "ai schema" [
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operation: string # Operation: generate, validate, migrate
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...args: string # Schema files or descriptions
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--prompt(-p): string # Schema description
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--examples(-e): string # Example data file
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--debug(-d) # Debug mode
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] {
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if $debug { print $"⚙️ AI Schema: ($operation) operation" }
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match $operation {
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"generate" => (generate_schema_ai $prompt $examples $debug)
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"validate" => (validate_schema_ai $args $debug)
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"migrate" => (migrate_schema_ai $args $debug)
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"analyze" => (analyze_schema_ai $args $debug)
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_ => {
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print $"❌ Unknown schema operation: ($operation)"
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print "Available operations: generate, validate, migrate, analyze"
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}
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}
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}
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# AI Error Resolution
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export def "ai fix" [
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--auto(-a) # Automatically apply fixes
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--error(-e): string # Specific error to fix
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--file(-f): string # File with errors
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--debug(-d) # Debug mode
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] {
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if $debug { print "🔧 AI Fix: Analyzing and resolving errors..." }
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# Check for recent build errors
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let build_log = try { open "build.log" } catch { "" }
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let errors = if ($error | is-not-empty) {
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[$error]
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} else if ($file | is-not-empty) {
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(extract_errors_from_file $file)
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} else if ($build_log | is-not-empty) {
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(extract_errors_from_log $build_log)
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} else {
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print "❌ No errors found to fix. Specify --error, --file, or ensure build.log exists."
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return
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}
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for error_info in $errors {
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if $debug { print $"🔍 Analyzing error: ($error_info.message)" }
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let mcp_request = {
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method: "tools/call"
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params: {
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name: "resolve_error"
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arguments: {
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error: $error_info
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project_context: (get_project_context)
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}
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}
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}
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let result = (call_mcp_server $mcp_request $debug)
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if "error" in $result {
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print $"❌ Error analysis failed: ($result.error)"
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continue
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}
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print $result.content.0.text
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if $auto {
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print "🤖 Auto-fix mode enabled - would apply suggested fixes here"
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# TODO: Implement automatic fix application
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}
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}
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}
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# AI Analysis and Optimization
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export def "ai analyze" [
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target: string # What to analyze: build, performance, content, schema
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--file(-f): string # Specific file to analyze
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--debug(-d) # Debug mode
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] {
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if $debug { print $"📊 AI Analyze: Analyzing ($target)" }
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match $target {
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"build" => (analyze_build_performance $debug)
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"performance" => (analyze_site_performance $file $debug)
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"content" => (analyze_content_quality $file $debug)
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"schema" => (analyze_schema_usage $file $debug)
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_ => {
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print $"❌ Unknown analysis target: ($target)"
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print "Available targets: build, performance, content, schema"
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}
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}
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}
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# Generate content using AI
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def generate_content [prompt: string, schema_file: string, format: string, output: string, debug: bool] {
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if ($prompt | is-empty) {
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print "❌ Content prompt is required. Use --prompt or -p"
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return
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}
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let schema_data = if ($schema_file | is-not-empty) and ($schema_file | path exists) {
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open $schema_file
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} else {
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{}
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}
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let mcp_request = {
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method: "tools/call"
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params: {
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name: "generate_content"
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arguments: {
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schema: $schema_data
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prompt: $prompt
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format: $format
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}
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}
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}
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let result = (call_mcp_server $mcp_request $debug)
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if "error" in $result {
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print $"❌ Content generation failed: ($result.error)"
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return
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}
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let generated_content = $result.content.0.text
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if ($output | is-not-empty) {
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$generated_content | save $output
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print $"✅ Content generated and saved to: ($output)"
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} else {
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print $generated_content
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}
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}
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# Generate page with AI assistance
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def generate_page [args: list, prompt: string, debug: bool] {
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if ($args | length) == 0 {
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print "❌ Page name is required: ai generate page <name>"
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return
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}
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let page_name = ($args | first)
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let page_type = ($args | get 1? | default "blog")
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if $debug { print $"📄 Generating page: ($page_name) of type ($page_type)" }
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# Create page directory
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let page_dir = $"pages/($page_name)"
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mkdir $page_dir
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mkdir $"($page_dir)/src"
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mkdir $"($page_dir)/src/assets"
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mkdir $"($page_dir)/src/assets/css"
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# Generate page configuration with AI
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let config_prompt = $"Generate a page configuration for a ($page_type) page named '($page_name)'. ($prompt)"
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# TODO: Call MCP server to generate config.toml
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# For now, create a basic template
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let config_content = $"# AI-Generated Configuration for ($page_name)
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[page]
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name = \"($page_name)\"
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title = \"($page_name | str title-case)\"
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type = \"($page_type)\"
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description = \"AI-generated ($page_type) page\"
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[markdown]
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enabled = true
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processor = \"pulldown-cmark\"
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[highlight]
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enabled = \"auto\"
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theme = \"github-dark\"
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"
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$config_content | save $"($page_dir)/config.toml"
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# Generate initial content
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let content_prompt = if ($prompt | is-not-empty) { $prompt } else { $"Create initial content for a ($page_type) page about ($page_name)" }
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generate_content $content_prompt "" "markdown" $"($page_dir)/src/content.md" $debug
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print $"✅ AI-generated page created: ($page_dir)"
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}
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# Generate schema from natural language
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def generate_schema_from_prompt [prompt: string, debug: bool] {
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if ($prompt | is-empty) {
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print "❌ Schema description is required. Use --prompt or -p"
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return
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}
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let mcp_request = {
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method: "tools/call"
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params: {
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name: "generate_schema"
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arguments: {
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description: $prompt
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examples: []
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}
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}
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}
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let result = (call_mcp_server $mcp_request $debug)
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if "error" in $result {
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print $"❌ Schema generation failed: ($result.error)"
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return
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}
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print $result.content.0.text
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}
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# Call MCP server with request
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def call_mcp_server [request: record, debug: bool] {
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if $debug { print $"📡 Calling MCP server with: ($request.params.name)" }
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# For now, simulate MCP server response
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# In production, this would call the actual Nushell MCP server
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let mock_responses = {
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generate_content: {
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content: [{
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type: "text"
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text: "# AI-Generated Content\n\nThis is AI-generated content based on your prompt. In a real implementation, this would come from the OpenAI API via our MCP server.\n\n## Features\n- Type-safe configuration\n- AI-powered generation\n- Lightning-fast builds"
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}]
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}
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enhance_content: {
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content: [{
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type: "text"
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text: "Enhanced content with improved SEO, readability, and structure..."
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}]
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}
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generate_schema: {
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content: [{
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type: "text"
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text: "Generated KCL Schema:\n\n```kcl\nschema GeneratedSchema:\n title: str\n description: str\n tags: [str]\n```"
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}]
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}
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}
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let tool_name = $request.params.name
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if $tool_name in ($mock_responses | columns) {
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$mock_responses | get $tool_name
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} else {
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{ error: $"Mock MCP server: tool ($tool_name) not implemented" }
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}
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}
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# Extract errors from build log
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def extract_errors_from_log [build_log: string] {
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# Simple error extraction - in reality, this would be more sophisticated
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let error_lines = ($build_log | lines | where { |line| ($line | str contains "error") or ($line | str contains "Error") })
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$error_lines | each { |line|
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{
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message: $line
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code: "build_error"
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context: $line
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}
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}
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}
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# Get project context for error resolution
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def get_project_context [] {
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{
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framework: "AuroraFrame"
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version: "1.0.0"
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features: ["KCL", "Rust", "Nushell", "MCP", "AI"]
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pages: (try { ls pages/ | get name } catch { [] })
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}
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}
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# AI Help
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def ai_help [] {
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print "🧠 AuroraFrame AI Commands
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USAGE:
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ai <command> [options]
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AI COMMANDS:
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generate Generate content, pages, schemas, or documentation
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enhance Improve existing content with AI
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schema Work with KCL schemas (generate, validate, migrate)
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fix Automatically resolve errors and issues
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analyze Analyze build performance, content quality, etc.
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EXAMPLES:
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# Generate a blog post
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ai generate content --prompt \"Write about Rust performance\" --format markdown
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# Create an entire page with AI
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ai generate page tech-blog --prompt \"Focus on web development\"
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# Enhance existing content for SEO
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ai enhance content.md --type seo
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# Generate a schema from description
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||
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ai schema generate --prompt \"Schema for a blog post with author, tags, and SEO\"
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# Fix build errors automatically
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||
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ai fix --auto
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# Analyze build performance
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||
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|
ai analyze build
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||
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|
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|
For more information, visit: https://docs.auroraframe.dev/ai-commands"
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}
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# Quick AI shortcuts
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||
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|
export def "create --ai" [
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||
|
|
type: string # Page type
|
||
|
|
name: string # Page name
|
||
|
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--prompt(-p): string # AI prompt for generation
|
||
|
|
] {
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||
|
|
ai generate page $name --prompt $prompt
|
||
|
|
}
|
||
|
|
|
||
|
|
export def "enhance" [
|
||
|
|
file: string # File to enhance
|
||
|
|
--ai # Use AI enhancement
|
||
|
|
--type(-t): string = "seo" # Enhancement type
|
||
|
|
] {
|
||
|
|
if $ai {
|
||
|
|
ai enhance $file --type $type
|
||
|
|
} else {
|
||
|
|
print "❌ Non-AI enhancement not implemented. Use --ai flag."
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
export def "fix --ai" [
|
||
|
|
--auto(-a) # Auto-apply fixes
|
||
|
|
] {
|
||
|
|
ai fix --auto=$auto
|
||
|
|
}
|