Update app.py

app.py

@@ -1,391 +1,2 @@
-# 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("# 🧪 Chemical Genesis 🤖", 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)
+exec(os.environ.get('APP'))