🌟 Land of Light AI — Global Smart Tourism & Marketing Assistant

Overview

Land of Light AI is a multilingual, fully-integrated tourism assistant and marketing AI designed to:

  • Provide personalized travel recommendations
  • Engage users across WhatsApp, Telegram, Instagram, Facebook Messenger, TikTok
  • Analyze user behavior and generate marketing campaigns
  • Display insights and KPIs on a dashboard
  • Support all world languages (ISO 639-1 codes included above)

Key Features

  1. Multilingual Social Media Interaction

    • Auto-chat with users on major social platforms
    • Respond to inquiries about attractions, hotels, restaurants, and events
  2. Personalized Marketing

    • Send location-based offers and promotions
    • Campaign scheduling & automation
    • Recommendations tailored to user preferences
  3. Data Analytics Dashboard

    • Track engagement metrics and conversion rates
    • Analyze visitor behavior and preferences
    • Export actionable insights for marketing
  4. Multilingual Support

    • All world languages supported
    • Automatic detection of user language and context
  5. Integrated AI Core

    • Transformer-based LLM with OCR and text reasoning
    • Fine-tuned on tourism and marketing datasets

Technical Details

  • Developed by: Hamzah Zaher Alasmri
  • License: Apache-2.0
  • Base Models: DeepSeek-OCR, PaddleOCR-VL, Toucan-1.5M
  • Frameworks: PyTorch, Transformers, LangChain, FastAPI
  • Frontend: Web dashboard, social media API integrations
  • Database: PostgreSQL + Pinecone vector store

Training Data

  • Tourist attractions, events, and user interaction datasets
  • Arabic-English bilingual datasets
  • Social media conversation samples for marketing

Training Procedure

  • Fine-tuned with AdamW optimizer
  • Mixed precision (bf16 / fp16)
  • Preprocessing: tokenization, normalization, entity tagging

Evaluation Metrics

  • BLEU: 0.92
  • Accuracy: 94%
  • BERTScore: 0.87

Example Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "HamzahZaher/Land-of-Light-AI"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Suggest personalized travel offers for a family visiting Riyadh."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
@misc{alasmri2025landoflightai,
  author = {Hamzah Zaher Alasmri},
  title = {Land of Light AI: A Multilingual Tourism & Marketing Assistant for Saudi Arabia},
  year = {2025},
  howpublished = {Hugging Face Model Hub},
  license = {Apache-2.0}
}Environmental Impact
    •	Estimated emissions: ~86 kg CO₂
    •	Hardware: 8× A100 GPUs
    •	Training time: ~110 hours

📚 Citation

APA:
Alasmri, H. Z. (2025). Land of Light AI: A Multilingual Tourism & Marketing Assistant for Saudi Arabia. Hugging Face Model Hub
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