import gradio as gr
import spaces
import torch
import difflib
from threading import Thread
from transformers import AutoModel, AutoTokenizer, AutoModelForCausalLM, AutoModelForSeq2SeqLM, TextIteratorStreamer

model_id = "textcleanlm/textcleanlm-1-8b"
model = None
tokenizer = None

def load_model():
    global model, tokenizer
    if model is None:
        tokenizer = AutoTokenizer.from_pretrained(model_id)
        
        # Add padding token if needed
        if tokenizer.pad_token is None:
            tokenizer.pad_token = tokenizer.eos_token
        
        # Try different model classes
        for model_class in [AutoModelForSeq2SeqLM, AutoModelForCausalLM, AutoModel]:
            try:
                model = model_class.from_pretrained(
                    model_id,
                    torch_dtype=torch.bfloat16,
                    device_map="auto"
                )
                break
            except:
                continue
                
        if model is None:
            raise ValueError(f"Could not load model {model_id}")
            
    return model, tokenizer

def create_diff_html(original, cleaned):
    """Create HTML diff visualization"""
    original_lines = original.splitlines(keepends=True)
    cleaned_lines = cleaned.splitlines(keepends=True)
    
    differ = difflib.unified_diff(original_lines, cleaned_lines, fromfile='Original', tofile='Cleaned', lineterm='')
    
    html_diff = '<div style="font-family: monospace; font-size: 12px; white-space: pre-wrap;">'
    
    for line in differ:
        if line.startswith('+++') or line.startswith('---'):
            html_diff += f'<div style="color: #666;">{line}</div>'
        elif line.startswith('@@'):
            html_diff += f'<div style="color: #0066cc; font-weight: bold;">{line}</div>'
        elif line.startswith('+'):
            html_diff += f'<div style="background-color: #e6ffed; color: #24292e;">{line}</div>'
        elif line.startswith('-'):
            html_diff += f'<div style="background-color: #ffeef0; color: #24292e;">{line}</div>'
        else:
            html_diff += f'<div>{line}</div>'
    
    html_diff += '</div>'
    return html_diff

@spaces.GPU(duration=60)
def clean_text(text):
    model, tokenizer = load_model()
    
    # Apply chat template
    messages = [
        {"role": "user", "content": text}
    ]
    
    # Apply the chat template
    formatted_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
    
    inputs = tokenizer(formatted_text, return_tensors="pt", max_length=4096, truncation=True)
    inputs = {k: v.cuda() for k, v in inputs.items()}
    
    # Enable streaming
    streamer = TextIteratorStreamer(tokenizer, skip_special_tokens=True)
    
    generation_kwargs = dict(
        **inputs,
        max_length=4096,
        num_beams=1,  # Set to 1 for streaming
        do_sample=True,
        temperature=1.0,
        streamer=streamer,
    )
    
    # Run generation in a separate thread
    thread = Thread(target=model.generate, kwargs=generation_kwargs)
    thread.start()
    
    # Collect generated text, skipping the input
    generated_text = ""
    input_length = len(formatted_text)
    full_output = ""
    
    for new_text in streamer:
        full_output += new_text
        # Only yield the part after the input
        if len(full_output) > input_length:
            generated_text = full_output[input_length:].strip()
            yield generated_text, ""
    
    thread.join()
    
    # After generation is complete, create diff
    diff_html = create_diff_html(text, generated_text)
    yield generated_text, diff_html

# Create the interface with blocks for better control
with gr.Blocks(title="TextClean-4B Demo") as demo:
    gr.Markdown("# TextClean-4B Demo")
    gr.Markdown("Simple demo for text cleaning using textcleanlm/textclean-4B model")
    
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(
                lines=5,
                placeholder="Enter text to clean...",
                label="Input Text"
            )
            submit_btn = gr.Button("Clean Text", variant="primary")
    
    with gr.Row():
        output_text = gr.Textbox(
            lines=5,
            label="Cleaned Text",
            interactive=False
        )
    
    with gr.Row():
        diff_display = gr.HTML(label="Diff View")
    
    submit_btn.click(
        fn=clean_text,
        inputs=input_text,
        outputs=[output_text, diff_display]
    )

if __name__ == "__main__":
    demo.launch()