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