{ "report_info": { "version": "9.0.1", "generated_at": "2026-04-11T17:16:14Z", "binary_name": "ai-trainer" }, "binary": { "name": "ai-trainer", "path": "/home/kodachi/k900/dashboard/hooks/ai-trainer", "timestamp": "2026-04-11T17:16:14Z", "file_info": { "size": 3001296, "sha256": "09645b66922f6e03ac1ba575907d6c132f455a1b382ab420334bb3ea903a7edb" }, "flag_n": { "status": "success", "timestamp": "2026-04-11T17:16:14.291997229Z", "command": "info", "version": "9.0.1", "data": { "name": "ai-trainer", "version": "9.0.1", "author": "Warith Al Maawali ", "description": "AI model training and validation for Kodachi OS command intelligence", "copyright": "© 2026 Linux Kodachi", "website": "https://www.digi77.com", "license": "LicenseRef-Kodachi-SAN-1.0", "features": [ "TF-IDF based command embeddings", "Incremental model updates", "Model validation and accuracy testing" ], "securityFeatures": { "inputValidation": "All inputs are validated and sanitized", "rateLimiting": "Built-in rate limiting for network operations", "authentication": "Secure authentication with certificate pinning", "encryption": "TLS 1.3 for all network communications" }, "systemRequirements": { "os": "Linux (Debian-based)", "privileges": "root/sudo for system operations", "dependencies": [ "OpenSSL", "libcurl" ] } }, "errors": [], "warnings": [], "metadata": { "executionTime": 1, "hostname": "Boardroom-System", "user": "kodachi" } }, "flag_v": { "status": "success", "timestamp": "2026-04-11T17:16:14.373407520Z", "command": "version", "version": "9.0.1", "data": { "name": "ai-trainer", "version": "9.0.1", "buildDate": "2026-04-11T17:16:14.372850105Z", "gitCommit": "unknown", "rustVersion": "1.82.0" }, "errors": [], "warnings": [], "metadata": { "executionTime": 0, "hostname": "Boardroom-System", "user": "kodachi" } }, "flag_h": { "status": "success", "timestamp": "2026-04-11T17:16:14.450148956Z", "command": "help", "version": "9.0.1", "data": { "name": "ai-trainer", "description": "AI model training and validation for Kodachi OS command intelligence", "usage": "ai-trainer [OPTIONS] [COMMAND] [ARGS]", "commandCategories": [ { "category": "Model Management", "commands": [ { "name": "export", "description": "Export model embeddings and metadata to JSON file", "usage": "ai-trainer export --output [--format ]", "options": [], "requires_sudo": false, "examples": [ "ai-trainer export --output model_export.json" ] }, { "name": "snapshot", "description": "Save current model as versioned snapshot", "usage": "ai-trainer snapshot --snapshot-version ", "options": [], "requires_sudo": false, "examples": [ "ai-trainer snapshot --snapshot-version 1.0.0", "ai-trainer snapshot -s 1.1.0-beta" ] }, { "name": "list-snapshots", "description": "List all saved model snapshots", "usage": "ai-trainer list-snapshots", "options": [], "requires_sudo": false, "examples": [ "ai-trainer list-snapshots" ] }, { "name": "status", "description": "Display current model status and statistics", "usage": "ai-trainer status", "options": [], "requires_sudo": false, "examples": [ "ai-trainer status" ] }, { "name": "download-model", "description": "Download ONNX model, tokenizer, or GGUF model for AI engine tiers", "usage": "ai-trainer download-model [--llm [default|small|large]] [--show-models] [--all] [--output-dir ] [--force]", "options": [], "requires_sudo": false, "examples": [ "ai-trainer download-model", "ai-trainer download-model --llm", "ai-trainer download-model --llm small", "ai-trainer download-model --all", "ai-trainer download-model --show-models", "ai-trainer download-model --force" ] } ] }, { "category": "Model Training", "commands": [ { "name": "train", "description": "Train AI model from command metadata (full retraining)", "usage": "ai-trainer train --data [--database ]", "options": [], "requires_sudo": false, "examples": [ "ai-trainer train --data commands.json", "ai-trainer train --data commands.json --json" ] }, { "name": "incremental", "description": "Update model incrementally with new command data", "usage": "ai-trainer incremental --new-data [--database ]", "options": [], "requires_sudo": false, "examples": [ "ai-trainer incremental --new-data new_commands.json" ] } ] }, { "category": "Validation & Testing", "commands": [ { "name": "validate", "description": "Validate model accuracy against test dataset", "usage": "ai-trainer validate --test-data [--threshold ]", "options": [], "requires_sudo": false, "examples": [ "ai-trainer validate --test-data test_cases.json" ] } ] } ], "globalOptions": [ { "flag": "-h, --help", "description": "Print help information" }, { "flag": "-v, --version", "description": "Print version information" }, { "flag": "-n, --info", "description": "Display detailed information" }, { "flag": "-e, --examples", "description": "Show usage examples" }, { "flag": "--json", "description": "Output in JSON format" }, { "flag": "--json-pretty", "description": "Pretty-print JSON output with indentation" }, { "flag": "--json-human", 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"executionTime": 0, "hostname": "Boardroom-System", "user": "kodachi" } }, "flag_e": { "status": "success", "timestamp": "2026-04-11T17:16:14.616422099Z", "command": "examples", "version": "9.0.1", "data": { "name": "ai-trainer", "description": "Usage examples for ai-trainer", "categories": [ { "id": "1_model_training", "title": "Model Training", "description": "Full model training operations", "examples": [ { "command": "sudo ai-trainer train --data commands.json", "description": "Train model with command data", "expectedOutput": "Training statistics and embeddings metrics", "notes": "Creates new model from scratch" }, { "command": "sudo ai-trainer train --data commands.json --database custom.db", "description": "Train with custom database", "expectedOutput": "Training results with custom DB location", "notes": "Allows custom database path specification" }, { "command": "sudo ai-trainer train --data commands.json --json", "description": "Train and output results as JSON", "expectedOutput": "JSON-formatted training metrics", "notes": "Structured output for automation" } ] }, { "id": "2_incremental_training", "title": "Incremental Training", "description": "Update existing models with new data", "examples": [ { "command": "sudo ai-trainer incremental --new-data updates.json", "description": "Incrementally train with new data", "expectedOutput": "New embeddings added to existing model", "notes": "Requires existing trained model" }, { "command": "sudo ai-trainer incremental --new-data updates.json --database custom.db --json", "description": "Incremental training with custom DB and JSON output", "expectedOutput": "JSON-formatted incremental training results", "notes": "Combines custom DB path with structured output" } ] }, { "id": "3_validation", "title": "Validation", "description": "Model accuracy testing and validation", "examples": [ { "command": "sudo ai-trainer validate --test-data test_commands.json", "description": "Validate model with test data", "expectedOutput": "Validation results with accuracy metrics", "notes": "Tests model against known test cases" }, { "command": "sudo ai-trainer validate --test-data test_commands.json --threshold 0.90", "description": "Validate with custom accuracy threshold", "expectedOutput": "Pass/fail validation with 90% threshold", "notes": "Default threshold is 0.85" }, { "command": "sudo ai-trainer validate --test-data test_commands.json --database custom.db --json", "description": "Validate with custom DB and JSON output", "expectedOutput": "JSON-formatted validation metrics", "notes": "Structured validation results" }, { "command": "sudo ai-trainer validate --test-data tests.json --threshold 0.90 --database custom.db --json", "description": "Validate with all parameters combined", "expectedOutput": "JSON validation with custom test data, 90% threshold, and custom DB", "notes": "Full parameter example for CI/CD pipelines" } ] }, { "id": "4_model_export", "title": "Model Export", "description": "Export trained models and statistics", "examples": [ { "command": "sudo ai-trainer export --output model_export.json", "description": "Export trained model", "expectedOutput": "Complete model export with embeddings", "notes": "Default format includes all embeddings" }, { "command": "sudo ai-trainer export --output model_compact.json --format compact", "description": "Export in compact format", "expectedOutput": "Compact model export without full embeddings", "notes": "Reduces export file size" }, { "command": "sudo ai-trainer export --output model_stats.json --format stats --json", "description": "Export statistics as JSON", "expectedOutput": "Model statistics without embeddings", "notes": "Lightweight statistics export" }, { "command": "sudo ai-trainer export --output model.json --format full --json", "description": "Full export with JSON envelope output", "expectedOutput": "Complete model export with JSON status envelope", "notes": "Combines full embeddings export with structured output" } ] }, { "id": "5_snapshots", "title": "Snapshots", "description": "Model versioning and snapshot management", "examples": [ { "command": "sudo ai-trainer snapshot --snapshot-version 1.0.0", "description": "Create model snapshot with version", "expectedOutput": "Versioned snapshot created successfully", "notes": "Preserves model state at specific version" }, { "command": "sudo ai-trainer list-snapshots", "description": "List all model snapshots", "expectedOutput": "List of saved model versions", "notes": "Shows snapshot metadata and versions" }, { "command": "sudo ai-trainer list-snapshots --json", "description": "List snapshots as JSON", "expectedOutput": "JSON-formatted snapshot listing", "notes": "Structured snapshot information" }, { "command": "sudo ai-trainer snapshot --snapshot-version 1.0.0 --json", "description": "Create snapshot with JSON output", "expectedOutput": "JSON with snapshot name, version, and embedding count", "notes": "Structured output for automation" } ] }, { "id": "6_download", "title": "Model Download", "description": "Download ONNX and GGUF model files for AI engine tiers", "examples": [ { "command": "sudo ai-trainer download-model", "description": "Download ONNX embeddings model to default models/ directory", "expectedOutput": "Model files downloaded successfully", "notes": "Downloads all-MiniLM-L6-v2 ONNX model and tokenizer" }, { "command": "sudo ai-trainer download-model --llm", "description": "Download default GGUF model (Qwen2.5-3B-Instruct Q4_K_M, ~1.8GB)", "expectedOutput": "GGUF model downloaded to models/ directory", "notes": "Best balance of quality, speed, and size for CPU inference" }, { "command": "sudo ai-trainer download-model --llm small", "description": "Download small GGUF model (Qwen2.5-1.5B, ~0.9GB)", "expectedOutput": "Small GGUF model downloaded", "notes": "For systems with <4GB available RAM" }, { "command": "sudo ai-trainer download-model --llm large", "description": "Download large GGUF model (Phi-3.5-mini, ~2.3GB)", "expectedOutput": "Large GGUF model downloaded", "notes": "Better reasoning, 128K trained context" }, { "command": "sudo ai-trainer download-model --all", "description": "Download both ONNX embeddings and default GGUF model", "expectedOutput": "All model files downloaded", "notes": "Complete setup for all AI tiers" }, { "command": "sudo ai-trainer download-model --show-models", "description": "List downloaded and available models", "expectedOutput": "Model inventory with sizes and status", "notes": "Shows what's installed and what can be downloaded" }, { "command": "sudo ai-trainer download-model --show-models --json", "description": "Model inventory as JSON", "expectedOutput": "JSON with downloaded and available model details" }, { "command": "sudo ai-trainer download-model --force", "description": "Force re-download of ONNX model", "expectedOutput": "Model files re-downloaded", "notes": "Overwrites existing files" } ] }, { "id": "7_status", "title": "Status", "description": "Model status and health checks", "examples": [ { "command": "sudo ai-trainer status", "description": "Show training status", "expectedOutput": "Current model status and statistics", "notes": "Displays model readiness and metrics" }, { "command": "sudo ai-trainer status --json", "description": "Show training status as JSON", "expectedOutput": "JSON-formatted status information", "notes": "Structured status output for automation" } ] }, { "id": "8_ai_tiers", "title": "AI Tier Integration", "description": "Training operations related to the 6-tier AI engine (TF-IDF, ONNX, Mistral.rs, GenAI/Ollama, Legacy LLM, Claude)", "examples": [ { "command": "sudo ai-trainer validate --test-data tests.json --json", "description": "Validate model against all tier responses", "expectedOutput": "Validation results covering all active AI tiers", "notes": "Tests model accuracy across available tiers" }, { "command": "sudo ai-trainer train --data commands.json --json", "description": "Train model with feedback from all tiers", "expectedOutput": "Training metrics including multi-tier feedback data", "notes": "Includes feedback from mistral.rs and GenAI tier executions" } ] }, { "id": "9_intent_classifier", "title": "ONNX Intent Classifier", "description": "Evaluate the ONNX intent classifier used for fast-path routing (12 categories, <5ms inference)", "examples": [ { "command": "sudo ai-trainer validate --test-data intent_tests.json --json", "description": "Evaluate ONNX intent classifier accuracy", "expectedOutput": "JSON with per-intent precision, recall, and F1-score", "notes": "Target: 95%+ accuracy on held-out test set" }, { "command": "sudo ai-trainer download-model --show-models --json", "description": "Check if intent classifier model is downloaded", "expectedOutput": "JSON showing classifier model status", "notes": "Model: kodachi-intent-classifier.onnx (~65MB)" } ] } ], "quickReference": [ "sudo ai-trainer --help", "sudo ai-trainer --version", "sudo ai-trainer --info --json", "sudo ai-trainer --examples --json" ] }, "errors": [], "warnings": [], "metadata": { "executionTime": 0, "hostname": "Boardroom-System", "user": "kodachi" } } } }