# Authenticate with Hugging Face
from huggingface_hub import login
import os
# Log in to Hugging Face using the provided token
hf_token = os.getenv("HF_TOKEN")
login(hf_token)

# Required imports
import gradio as gr
import spaces
from transformers import Qwen2VLForConditionalGeneration, AutoProcessor, TextIteratorStreamer
from qwen_vl_utils import process_vision_info
import torch
from PIL import Image
import os
import uuid
import io
from threading import Thread
from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.lib import colors
from reportlab.platypus import SimpleDocTemplate, Image as RLImage, Paragraph, Spacer
from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.ttfonts import TTFont
import docx
from docx.enum.text import WD_ALIGN_PARAGRAPH
from reportlab.lib.units import inch

# Define model options
MODEL_OPTIONS = {
    "ChemQwen-1": "prithivMLmods/ChemQwen-vL",
    "ChemQwen-2": "prithivMLmods/ChemQwen2-vL",    
}

# Preload models and processors into CUDA
models = {}
processors = {}
for name, model_id in MODEL_OPTIONS.items():
    print(f"Loading {name}...")
    models[name] = Qwen2VLForConditionalGeneration.from_pretrained(
        model_id,
        trust_remote_code=True,
        torch_dtype=torch.float16
    ).to("cuda").eval()
    processors[name] = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)

image_extensions = Image.registered_extensions()

def identify_and_save_blob(blob_path):
    """Identifies if the blob is an image and saves it."""
    try:
        with open(blob_path, 'rb') as file:
            blob_content = file.read()
            try:
                Image.open(io.BytesIO(blob_content)).verify()
                extension = ".png"
                media_type = "image"
            except (IOError, SyntaxError):
                raise ValueError("Unsupported media type. Please upload a valid image.")

            filename = f"temp_{uuid.uuid4()}_media{extension}"
            with open(filename, "wb") as f:
                f.write(blob_content)

            return filename, media_type

    except FileNotFoundError:
        raise ValueError(f"The file {blob_path} was not found.")
    except Exception as e:
        raise ValueError(f"An error occurred while processing the file: {e}")


@spaces.GPU
def qwen_inference(model_name, media_input, text_input=None):
    """Handles inference for the selected model."""
    model = models[model_name]
    processor = processors[model_name]

    if isinstance(media_input, str):
        media_path = media_input
        if media_path.endswith(tuple([i for i in image_extensions.keys()])):
            media_type = "image"
        else:
            try:
                media_path, media_type = identify_and_save_blob(media_input)
            except Exception as e:
                raise ValueError("Unsupported media type. Please upload a valid image.")

    messages = [
        {
            "role": "user",
            "content": [
                {
                    "type": media_type,
                    media_type: media_path
                },
                {"type": "text", "text": text_input},
            ],
        }
    ]

    text = processor.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )
    image_inputs, _ = process_vision_info(messages)
    inputs = processor(
        text=[text],
        images=image_inputs,
        padding=True,
        return_tensors="pt",
    ).to("cuda")

    streamer = TextIteratorStreamer(
        processor.tokenizer, skip_prompt=True, skip_special_tokens=True
    )
    generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024)

    thread = Thread(target=model.generate, kwargs=generation_kwargs)
    thread.start()

    buffer = ""
    for new_text in streamer:
        buffer += new_text
        # Remove <|im_end|> or similar tokens from the output
        buffer = buffer.replace("<|im_end|>", "")
        yield buffer


def format_plain_text(output_text):
    """Formats the output text as plain text without LaTeX delimiters."""
    plain_text = output_text.replace("\\(", "").replace("\\)", "").replace("\\[", "").replace("\\]", "")
    return plain_text

def generate_document(media_path, output_text, file_format, font_size, line_spacing, alignment, image_size):
    """Generates a document with the input image and plain text output."""
    plain_text = format_plain_text(output_text)
    if file_format == "pdf":
        return generate_pdf(media_path, plain_text, font_size, line_spacing, alignment, image_size)
    elif file_format == "docx":
        return generate_docx(media_path, plain_text, font_size, line_spacing, alignment, image_size)

def generate_pdf(media_path, plain_text, font_size, line_spacing, alignment, image_size):
    """Generates a PDF document."""
    filename = f"output_{uuid.uuid4()}.pdf"
    doc = SimpleDocTemplate(
        filename,
        pagesize=A4,
        rightMargin=inch,
        leftMargin=inch,
        topMargin=inch,
        bottomMargin=inch
    )
    styles = getSampleStyleSheet()
    styles["Normal"].fontSize = int(font_size)
    styles["Normal"].leading = int(font_size) * line_spacing
    styles["Normal"].alignment = {
        "Left": 0,
        "Center": 1,
        "Right": 2,
        "Justified": 4
    }[alignment]

    story = []

    image_sizes = {
        "Small": (200, 200),
        "Medium": (400, 400),
        "Large": (600, 600)
    }
    img = RLImage(media_path, width=image_sizes[image_size][0], height=image_sizes[image_size][1])
    story.append(img)
    story.append(Spacer(1, 12))

    text = Paragraph(plain_text, styles["Normal"])
    story.append(text)

    doc.build(story)
    return filename

def generate_docx(media_path, plain_text, font_size, line_spacing, alignment, image_size):
    """Generates a DOCX document."""
    filename = f"output_{uuid.uuid4()}.docx"
    doc = docx.Document()

    # Convert image to PNG format before adding to document
    try:
        img = Image.open(media_path)
        temp_image_path = f"temp_{uuid.uuid4()}.png"
        img.save(temp_image_path, "PNG")
        
        image_sizes = {
            "Small": docx.shared.Inches(2),
            "Medium": docx.shared.Inches(4),
            "Large": docx.shared.Inches(6)
        }
        
        doc.add_picture(temp_image_path, width=image_sizes[image_size])
        
        # Clean up temporary image file
        os.remove(temp_image_path)
        
    except Exception as e:
        print(f"Error processing image: {e}")
        # Continue without image if there's an error

    doc.add_paragraph()

    paragraph = doc.add_paragraph()
    paragraph.paragraph_format.line_spacing = line_spacing
    paragraph.paragraph_format.alignment = {
        "Left": WD_ALIGN_PARAGRAPH.LEFT,
        "Center": WD_ALIGN_PARAGRAPH.CENTER,
        "Right": WD_ALIGN_PARAGRAPH.RIGHT,
        "Justified": WD_ALIGN_PARAGRAPH.JUSTIFY
    }[alignment]
    run = paragraph.add_run(plain_text)
    run.font.size = docx.shared.Pt(int(font_size))

    doc.save(filename)
    return filename

# CSS styling
css = """
  #output {
    height: 500px;
    overflow: auto;
    border: 1px solid #ccc;
  }
  .container {
    background: linear-gradient(145deg, #f0f0f0, #ffffff);
    border-radius: 20px;
    box-shadow: 20px 20px 60px #bebebe, -20px -20px 60px #ffffff;
    padding: 2rem;
    margin: 1rem;
  }
  .title {
    text-align: center;
    font-size: 2.5rem;
    color: #2d3436;
    text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
    margin-bottom: 2rem;
  }
  .submit-btn {
    background: linear-gradient(145deg, #ff4757, #ff6b81) !important;
    color: white !important;
    border: none !important;
    border-radius: 10px !important;
    padding: 0.8rem 1.5rem !important;
    font-weight: bold !important;
    transform: translateY(0);
    transition: all 0.3s ease !important;
    box-shadow: 0 4px 15px rgba(255, 71, 87, 0.3) !important;
  }
  .submit-btn:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 6px 20px rgba(255, 71, 87, 0.4) !important;
  }
  .download-btn {
    background: linear-gradient(145deg, #00b894, #00cec9) !important;
    color: white !important;
    border: none !important;
    border-radius: 10px !important;
    padding: 0.8rem 1.5rem !important;
    font-weight: bold !important;
    transform: translateY(0);
    transition: all 0.3s ease !important;
    box-shadow: 0 4px 15px rgba(0, 184, 148, 0.3) !important;
  }
  .download-btn:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 6px 20px rgba(0, 184, 148, 0.4) !important;
  }
  .input-box {
    border-radius: 10px !important;
    border: 2px solid #dfe6e9 !important;
    transition: all 0.3s ease !important;
  }
  .input-box:focus {
    border-color: #00b894 !important;
    box-shadow: 0 0 10px rgba(0, 184, 148, 0.2) !important;
  }
"""

# Gradio app setup
with gr.Blocks(css=css) as demo:
    gr.Markdown("# 🧪 ChemQwen Chemical Identifier AI 🤖", elem_classes="title")

    with gr.Tab(label="🖼️ Image Analysis"):
        with gr.Row(elem_classes="container"):
            with gr.Column():
                model_choice = gr.Dropdown(
                    label="🔍 Select Model",
                    choices=list(MODEL_OPTIONS.keys()),
                    value="ChemQwen-1",
                    elem_classes="input-box"
                )
                input_media = gr.File(
                    label="📤 Upload Image",
                    type="filepath",
                    elem_classes="input-box"
                )
                text_input = gr.Textbox(
                    label="❓ Your Question",
                    placeholder="Ask anything about the image...",
                    elem_classes="input-box"
                )
                submit_btn = gr.Button(value="🚀 Analyze", elem_classes="submit-btn")

            with gr.Column():
                output_text = gr.Textbox(
                    label="📝 AI Response",
                    lines=10,
                    elem_classes="input-box"
                )
                plain_text_output = gr.Textbox(
                    label="📋 Standardized Text",
                    lines=10,
                    elem_classes="input-box"
                )

        with gr.Row(elem_classes="container"):
            with gr.Column():
                gr.Markdown("### 📄 Document Settings")
                line_spacing = gr.Dropdown(
                    choices=[0.5, 1.0, 1.15, 1.5, 2.0, 2.5, 3.0],
                    value=1.5,
                    label="↕️ Line Spacing",
                    elem_classes="input-box"
                )
                font_size = gr.Dropdown(
                    choices=["8", "10", "12", "14", "16", "18", "20", "22", "24"],
                    value="18",
                    label="📏 Font Size",
                    elem_classes="input-box"
                )
                alignment = gr.Dropdown(
                    choices=["Left", "Center", "Right", "Justified"],
                    value="Justified",
                    label="⚡ Text Alignment",
                    elem_classes="input-box"
                )
                image_size = gr.Dropdown(
                    choices=["Small", "Medium", "Large"],
                    value="Medium",
                    label="🖼️ Image Size",
                    elem_classes="input-box"
                )
                file_format = gr.Radio(
                    ["pdf", "docx"],
                    label="📁 File Format",
                    value="pdf",
                    elem_classes="input-box"
                )
                get_document_btn = gr.Button(
                    value="💾 Generate Document",
                    elem_classes="download-btn"
                )


    
        submit_btn.click(
            qwen_inference,
            [model_choice, input_media, text_input],
            output_text,
        ).then(
            format_plain_text,
            output_text,
            plain_text_output
        )


        get_document_btn.click(
            generate_document,
            [input_media, output_text, file_format, font_size, line_spacing, alignment, image_size],
            gr.File(label="📥 Download Document")
        )

    gr.Markdown("""
    ### 🌟 Features
    - 🔬 Advanced Chemical Structure Analysis
    - 📊 Multiple Model Support
    - 💫 Real-time Processing
    - 📑 Custom Document Generation
    
    ### 💡 Tips
    - 📸 Upload clear images for better results
    - ✍️ Be specific with your questions
    - 📝 Use the document generator for professional reports
    """)

demo.launch(debug=True)