🤖 RTILA Assistant

Full-powered fine-tuned AI model for generating automation configurations for the RTILA Automation Engine

💡 Don't have 16GB? Try RTILA Assistant Lite (8GB) or Mini (6GB)

🚀 Quick Start

Option 1: Ollama (Easiest)

ollama run hf.co/rtila-corporation/rtila-assistant:Q4KM

Option 2: LM Studio

1. Download LM Studio
2. Search for rtila-corporation/rtila-assistant
3. Download Q4K_M
4. Set parameters: Temperature=0.7, Top-P=0.8, Top-K=20
5. Start chatting!

Option 3: llama.cpp

# Download model
huggingface-cli download rtila-corporation/rtila-assistant \
  rtila-assistant.Q4KM.gguf --local-dir ./models

Run interactive chat
./llama-cli -m ./models/rtila-assistant.Q4KM.gguf \
  -p "Scrape product prices from an e-commerce site" \
  --temp 0.7 --top-p 0.8 --top-k 20

Option 4: Python (llama-cpp-python)

from llama_cpp import Llama

llm = Llama(
    modelpath="./models/rtila-assistant.Q4K_M.gguf",
    n_ctx=1536,
    ngpulayers=-1,  # Use GPU if available
)

response = llm.createchatcompletion(
    messages=[
        {"role": "system", "content": "You are RTILA Assistant..."},
        {"role": "user", "content": "Create a config for scraping product data"}
    ],
    temperature=0.7,
    top_p=0.8,
    top_k=20,
)
print(response['choices'][0]['message']['content'])

⚙️ Recommended Generation Settings

💬 Example Prompts & Outputs

Example 1: Basic Extraction

Prompt:

Extract all product names and prices from the current page

Output:

{
  "settings": {
    "name": "Product Extraction"
  },
  "datasets": {
    "products": {
      "selector": ".product-item",
      "type": "list",
      "fields": {
        "name": {
          "selector": ".product-title",
          "type": "text"
        },
        "price": {
          "selector": ".product-price",
          "type": "text",
          "transform": "extractNumber"
        }
      }
    }
  },
  "commands": [
    {"action": "extract", "dataset": "products"}
  ]
}

Example 2: Pagination Loop

Prompt:

Scrape reviews from multiple pages, clicking "Next" until no more pages

Output:

{
  "settings": {
    "name": "Review Scraper with Pagination"
  },
  "datasets": {
    "reviews": {
      "selector": ".review-card",
      "type": "list",
      "fields": {
        "author": {"selector": ".reviewer-name", "type": "text"},
        "rating": {"selector": ".star-rating", "type": "attribute", "attribute": "data-rating"},
        "text": {"selector": ".review-body", "type": "text"},
        "date": {"selector": ".review-date", "type": "text"}
      }
    }
  },
  "commands": [
    {
      "action": "loop",
      "while": {"exists": ".next-page:not(.disabled)"},
      "maxIterations": 50,
      "commands": [
        {"action": "extract", "dataset": "reviews", "append": true},
        {"action": "click", "selector": ".next-page"},
        {"action": "wait", "duration": 2000}
      ]
    }
  ]
}

Example 3: Database Integration

Prompt:

After extraction, save data to PostgreSQL and send Slack notification

Output:

{
  "triggers": {
    "onComplete": [
      {
        "type": "database",
        "config": {
          "driver": "postgresql",
          "connection": "{{env.DATABASE_URL}}",
          "table": "scraped_data",
          "mode": "upsert",
          "uniqueKey": "id"
        }
      },
      {
        "type": "webhook",
        "config": {
          "url": "{{env.SLACK_WEBHOOK}}",
          "method": "POST",
          "body": {
            "text": "✅ Extraction complete: {{datasets.products.length}} items saved"
          }
        }
      }
    ]
  }
}

Example 4: Knowledge Question

Prompt:

What is the difference between executescript and runscript?

Output:

executescript and runscript serve different purposes in RTILA:


execute_script: Runs JavaScript synchronously in the page context. Returns immediately 
with the result. Best for quick DOM queries, getting values, or simple manipulations.

run_script: Executes JavaScript asynchronously with full control flow. Supports 
await, can make fetch requests, and handles complex async operations. Returns a Promise.

Use execute_script for: Reading values, checking conditions, simple DOM changes
Use run_script for: API calls, complex async workflows, operations that need to wait

🏋️ Training Details

Training Data

• Navigation & Interaction patterns
• Data extraction configurations
• Logic & flow control
• Triggers & integrations
• Variables & substitution
• Advanced scripting
• Error handling
• Knowledge base Q&A

📝 System Prompt

For best results, use this system prompt:

You are RTILA Assistant, an expert AI for generating automation configurations for the RTILA Automation Engine.

Your capabilities:
Generate complete JSON configurations for web automation tasks
Define datasets with selectors, properties, and transformations
Configure navigation, extraction, loops, and conditionals
Set up triggers for webhooks, databases, and integrations
Explain RTILA concepts and best practices


When generating configurations:
Always output valid JSON with proper structure
Include 'settings', 'datasets', and 'commands' sections as needed
Use appropriate selectors (CSS, XPath) for the target elements
Apply transformations when data cleaning is required


When answering questions:
Be concise and accurate
Provide examples when helpful
Reference specific RTILA features and commands

🔗 Model Family

📄 License

Apache 2.0

🙏 Acknowledgments

• Built on Qwen3-14B by Alibaba
• Fine-tuned with Unsloth
• Quantized with llama.cpp