#!/usr/bin/env python3
"""
Dwrko-M1.0 Usage Examples
How others can use your Claude-like AI assistant
"""

import requests
import json

# Method 1: Using HuggingFace Spaces API
def use_dwrko_via_api(prompt):
    """Use Dwrko-M1.0 via HuggingFace Spaces API"""
    
    api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
    
    payload = {
        "data": [prompt]
    }
    
    response = requests.post(api_url, json=payload)
    return response.json()

# Method 2: Direct Integration
def use_dwrko_direct():
    """Direct integration example"""
    
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    # Load your trained Dwrko-M1.0
    tokenizer = AutoTokenizer.from_pretrained("dwrkotech/Dwrko-M1.0")
    model = AutoModelForCausalLM.from_pretrained("dwrkotech/Dwrko-M1.0")
    
    # Generate response
    prompt = "Write a Python function to calculate factorial"
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=200)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    return response

# Method 3: Gradio Interface Integration
def create_custom_interface():
    """Create custom interface using Dwrko-M1.0"""
    
    import gradio as gr
    
    def dwrko_chat(message):
        # Call your Dwrko-M1.0 API
        response = use_dwrko_via_api(message)
        return response
    
    # Create custom interface
    interface = gr.Interface(
        fn=dwrko_chat,
        inputs="text",
        outputs="text",
        title="My Custom Dwrko-M1.0 Assistant",
        description="Powered by Dwrko-M1.0"
    )
    
    return interface

# Example usage
if __name__ == "__main__":
    # Test API method
    result = use_dwrko_via_api("Explain what is machine learning")
    print("API Response:", result)
    
    # Test direct method (requires model download)
    # result = use_dwrko_direct()
    # print("Direct Response:", result)
    
    # Launch custom interface
    # interface = create_custom_interface()
    # interface.launch()