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Create app.py
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app.py
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import os
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import base64
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from io import BytesIO
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import gradio as gr
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from mistralai import Mistral
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from PIL import Image
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from pathlib import Path
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api_key = os.environ.get("MISTRAL")
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client = Mistral(api_key=api_key)
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#config
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VALID_DOCUMENT_EXTENSIONS = {".pdf"}
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VALID_IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png",}
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def upload_pdf(content, filename):
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uploaded_file = client.files.upload(
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file={"file_name": filename, "content": content},
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purpose="ocr",
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)
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signed_url = client.files.get_signed_url(file_id=uploaded_file.id)
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return signed_url.url
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def process_ocr(document_source):
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return client.ocr.process(
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model="mistral-ocr-latest",
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document=document_source,
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include_image_base64=True
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)
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def do_ocr(input_type, url=None, file=None):
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document_source = None
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if input_type == "URL":
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if not url or url.strip() == "":
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return "Please provide a valid URL.", "", []
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url_lower = url.lower()
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if any(url_lower.endswith(ext) for ext in VALID_IMAGE_EXTENSIONS):
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document_source = {"type": "image_url", "image_url": url.strip()}
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else:
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document_source = {"type": "document_url", "document_url": url.strip()}
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elif input_type == "Upload file":
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if not file:
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return "Please upload a file.", "", []
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file_name = file.name.lower()
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file_extension = os.path.splitext(file_name)[1]
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if file_extension in VALID_DOCUMENT_EXTENSIONS:
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with open(file.name, "rb") as f:
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content = f.read()
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signed_url = upload_pdf(content, os.path.basename(file_name))
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document_source = {"type": "document_url", "document_url": signed_url}
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elif file_extension in VALID_IMAGE_EXTENSIONS:
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img = Image.open(file)
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buffered = BytesIO()
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img.save(buffered, format="PNG")
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img_str = base64.b64encode(buffered.getvalue()).decode()
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document_source = {"type": "image_url", "image_url": f"data:image/png;base64,{img_str}"}
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else:
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return f"Error: Unsupported file type. Supported types: {', '.join(VALID_DOCUMENT_EXTENSIONS | VALID_IMAGE_EXTENSIONS)}", "", []
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else:
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return "Invalid input type ", "", []
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ocr_response = process_ocr(document_source)
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markdown_text = "\n\n".join(page.markdown for page in ocr_response.pages)
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extracted_text = markdown_text
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rendered_markdown = markdown_text
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images = []
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for page in ocr_response.pages:
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for img in page.images:
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if img.image_base64:
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base64_str = img.image_base64
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if "," in base64_str:
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base64_str = base64_str.split(",")[1]
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img_bytes = base64.b64decode(base64_str)
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img_pil = Image.open(BytesIO(img_bytes))
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images.append(img_pil)
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img_buffer = BytesIO()
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img_pil.save(img_buffer, format="PNG")
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img_base64 = base64.b64encode(img_buffer.getvalue()).decode()
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data_url = f"data:image/png;base64,{img_base64}"
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rendered_markdown = rendered_markdown.replace(
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f"", f""
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)
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else:
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rendered_markdown += f"\n\n[Image Warning: No base64 data for {img.id}]"
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return extracted_text.strip(), rendered_markdown.strip(), images
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custom_css = """
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body {font-family: body {font-family: 'Helvetica Neue', Helvetica;}
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.gr-button {background-color: #4CAF50; color: white; border: none; padding: 10px 20px; border-radius: 5px;}
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.gr-button:hover {background-color: #45a049;}
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.gr-textbox {margin-bottom: 15px;}
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.example-button {background-color: #1E90FF; color: white; border: none; padding: 8px 15px; border-radius: 5px; margin: 5px;}
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.example-button:hover {background-color: #FF4500;}
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.tall-radio .gr-radio-item {padding: 15px 0; min-height: 50px; display: flex; align-items: center;}
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.tall-radio label {font-size: 16px;}
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"""
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with gr.Blocks(
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title="Mistral OCR Demo",
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css=custom_css,
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theme=gr.themes.Soft()
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) as demo:
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gr.Markdown("<h1 style='text-align: center; color: #333;'>Mistral OCR Demo</h1>")
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gr.Markdown("<p style='text-align: center; color: #666;'>Extract text and images from PDFs or images using Mistral's latest OCR model. You can also see markdown live.</p>")
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with gr.Row():
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with gr.Column(scale=1):
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input_type = gr.Radio(
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choices=["URL", "Upload file"],
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label="Input Type",
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value="URL",
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elem_classes="tall-radio"
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)
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url_input = gr.Textbox(
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label="Document or Image URL",
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placeholder="e.g., https://arxiv.org/pdf/2501.12948",
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visible=True,
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lines=1
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)
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file_input = gr.File(
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label="Upload PDF or Image",
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file_types=[".pdf", ".jpg", ".jpeg", ".png"],
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visible=False
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)
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submit_btn = gr.Button("Extract Text and Images")
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gr.Markdown("### Try These Examples")
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pdf_example = gr.Button("PDF", elem_classes="example-button")
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img_example = gr.Button("Image", elem_classes="example-button")
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with gr.Column(scale=2):
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cleaned_output = gr.Textbox(label="Extracted Plain Text", lines=10, show_copy_button=True)
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markdown_output = gr.Markdown(label="Rendered Markdown Text")
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image_output = gr.Gallery(label="OCR Extracted Images", columns=2, height="auto")
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def update_visibility(choice):
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return gr.update(visible=(choice == "URL")), gr.update(visible=(choice == "Upload file"))
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input_type.change(fn=update_visibility, inputs=input_type, outputs=[url_input, file_input])
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def set_url_and_type(url):
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return url, "URL"
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pdf_example.click(
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fn=lambda: set_url_and_type("https://arxiv.org/pdf/2501.12948"),
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outputs=[url_input, input_type]
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)
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img_example.click(
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fn=lambda: set_url_and_type("https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/unit0/recommended-pace.jpg"),
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outputs=[url_input, input_type]
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)
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submit_btn.click(
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fn=do_ocr,
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inputs=[input_type, url_input, file_input],
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outputs=[cleaned_output, markdown_output, image_output]
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)
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if __name__ == "__main__":
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demo.launch()
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