Hugging Face's logo

OktoSeek
/
oktoscript

English
ai
training
dsl
oktoscript
oktoseek
okto
automation
ai-pipelines
ai-governance
Model card Files
xet
Community
oktoscript / examples /README.md
OktoSeek's picture
OktoSeek
Update
5df2c77 verified
preview code
|
raw
history blame contribute delete
6.71 kB

OktoScript Examples

This folder contains official example scripts written in OktoScript (.okt).

These examples are used by:

  • Developers learning OktoScript
  • Students and researchers
  • OktoSeek IDE
  • VS Code Extension
  • Automatic tests and validation

Available Examples

Basic Examples

File Description Use Case
basic.okt Minimal example Getting started
chatbot.okt Conversational AI Customer service, assistants
computer_vision.okt Image classification Vision models, object detection
recommender.okt Recommendation system E-commerce, content suggestions

Advanced Examples

File Description Use Case
finetuning-llm.okt Fine-tuning LLM with checkpoints Advanced language models, resume training
vision-pipeline.okt Complete vision pipeline Production vision systems, ONNX export
qa-embeddings.okt QA with embeddings Semantic search, retrieval systems

v1.1 Examples (New Features)

File Description Use Case
lora-finetuning.okt LoRA fine-tuning with dataset mixing Efficient fine-tuning, memory-efficient training
dataset-mixing.okt Training with multiple weighted datasets Combining datasets, weighted sampling

🧪 Test Scripts (Recommended for Testing)

These scripts are specifically designed for testing different features of OktoScript v1.2:

File Description Features Tested
test-t5-basic.okt Basic training PROJECT, ENV, DATASET, MODEL, TRAIN, EXPORT
test-t5-monitor.okt Training with MONITOR Full metrics tracking, notifications
test-t5-control.okt Training with CONTROL Automatic decisions, IF/WHEN/EVERY
test-flan-t5-complete.okt All advanced blocks MONITOR, CONTROL, STABILITY together
test-flan-t5-inference.okt Inference with governance BEHAVIOR, GUARD, INFERENCE blocks
test-t5-explorer.okt AutoML with EXPLORER Hyperparameter search, best model selection

📖 See TESTING_GUIDE.md for detailed testing instructions.

v1.2 Examples (Advanced Features)

File Description Use Case
control-nested.okt Nested CONTROL blocks with advanced decision-making Dynamic training control, conditional logic
behavior-chat.okt BEHAVIOR block with mode and prompt_style Chatbot personality, response style
guard-safety.okt GUARD block with multiple detection methods Content safety, ethical AI
deploy-api.okt DEPLOY block for API deployment Production API deployment
security-full.okt Complete SECURITY block configuration Input/output validation, rate limiting
model-adapter.okt MODEL block with ADAPTER (LoRA/PEFT) Parameter-efficient fine-tuning
inference-advanced.okt Advanced INFERENCE with nested CONTROL Smart inference with retry logic
monitor-full.okt Complete MONITOR block with all metrics Full system and training telemetry
explorer-automl.okt EXPLORER block for hyperparameter search AutoML-style optimization
stability-training.okt STABILITY block for safe training Training stability and safety
complete-v1.2.okt Complete example with all v1.2 features Full feature demonstration

Complete Projects

File Description Use Case
pizzabot/ Complete project example Full workflow demonstration

Quick Start

To run these examples with OktoEngine (when available):

# Validate syntax
okto validate examples/basic.okt

# Train a model
okto train examples/chatbot.okt

# Evaluate performance
okto eval examples/recommender.okt

# Export model
okto export examples/computer_vision.okt --format=okm

Export Formats

OktoScript supports multiple export formats for different use cases:

Standard Formats

  • ONNX - Universal inference, production-ready
  • GGUF - Local inference, Ollama, Llama.cpp
  • SafeTensors - HuggingFace, research, standard training

OktoSeek Optimized Formats

  • OktoModel (.okm) - Optimized for OktoSeek SDK & Flutter plugins
  • OktoBundle (.okx) - Mobile + Edge package (iOS, Android, Edge AI)

💡 Tip: While standard formats work everywhere, .okm and .okx formats are optimized for the OktoSeek ecosystem, providing better integration with Flutter apps, mobile SDKs, and OktoSeek tools.

Example: Using OktoModel Format 

EXPORT {
  format: ["onnx", "okm"]
  path: "export/"
}

Why use .okm?

  • ✅ Optimized for OktoSeek Flutter SDK
  • ✅ Better performance on mobile devices
  • ✅ Access to exclusive OktoSeek tools and plugins
  • ✅ Seamless integration with OktoSeek ecosystem
  • ✅ Support for iOS and Android apps

Note: .okm is optional. You can always export to standard formats (ONNX, GGUF, SafeTensors) for universal compatibility.

Training Workflow

During training, OktoScript uses standard formats (this is industry-standard):

runs/my-model/
├── checkpoint-100/
│   └── model.safetensors
├── checkpoint-200/
│   └── model.safetensors
├── tokenizer.json
└── training_logs.json

After training, you choose your export format based on your deployment needs.

Complete Project Example

See pizzabot/ for a complete project example with:

  • Full project structure
  • Multiple dataset files
  • Training configuration
  • Export settings
  • Example outputs

Contributing

Want to add your own example?

  1. Create a new .okt file in this directory
  2. Follow the OktoScript grammar specification
  3. Include clear comments and descriptions
  4. Submit a pull request!

Powered by OktoSeek AI