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| import gradio as gr | |
| import google.generativeai as genai | |
| from docx import Document | |
| from PIL import Image | |
| import os | |
| # 1. API Configuration using Hugging Face Secret | |
| # In 2026, 'gemini-3-flash-preview' is the most stable high-speed model | |
| MODEL_ID = 'gemini-3-flash-preview' | |
| api_key = os.getenv("GEMINI_API_KEY") | |
| if api_key: | |
| genai.configure(api_key=api_key) | |
| else: | |
| print("Warning: GEMINI_API_KEY not found in environment secrets.") | |
| def process_document(input_img): | |
| if input_img is None: | |
| return None, "Error: No image uploaded.", "" | |
| if not api_key: | |
| return None, "Error: API Key missing in Space Secrets (GEMINI_API_KEY).", "" | |
| try: | |
| # Load the 2026 stable Flash model | |
| model = genai.GenerativeModel(MODEL_ID) | |
| # Convert Gradio numpy image to PIL for Gemini | |
| pil_img = Image.fromarray(input_img) | |
| # Expert prompt for high-fidelity document extraction | |
| prompt = """ | |
| Extract all text from this document accurately. | |
| - Identify titles and align them correctly. | |
| - Preserve Bold and Italic formatting. | |
| - Group lines into logical paragraphs. | |
| - If there are handwritten notes, transcribe them faithfully. | |
| """ | |
| # Generate Content | |
| response = model.generate_content([prompt, pil_img]) | |
| if not response or not response.text: | |
| return None, "Error: Model returned an empty response.", "" | |
| extracted_text = response.text | |
| # 2. Create Formatted Word Document | |
| doc = Document() | |
| for line in extracted_text.split('\n'): | |
| clean_line = line.strip() | |
| if clean_line: | |
| p = doc.add_paragraph() | |
| # Basic cleaning of markdown tags if Gemini adds them | |
| text_to_write = clean_line.replace('**', '').replace('*', '') | |
| run = p.add_run(text_to_write) | |
| if '**' in line: run.bold = True | |
| if '*' in line and '**' not in line: run.italic = True | |
| output_path = "Converted_Document.docx" | |
| doc.save(output_path) | |
| return output_path, "✅ Conversion Successful!", extracted_text | |
| except Exception as e: | |
| return None, f"❌ System Error: {str(e)}", "" | |
| # --- Gradio UI Setup --- | |
| with gr.Blocks(theme=gr.themes.Soft(), title="Gemini 3 Smart OCR") as demo: | |
| gr.Markdown("# 🖋️ AI Document Architect (Gemini 3)") | |
| gr.Markdown("Convert messy handwriting or document scans into formatted Word files instantly.") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| input_image = gr.Image(label="Source Image", type="numpy") | |
| submit_btn = gr.Button("🚀 Convert to Word", variant="primary") | |
| # --- Added Example Images --- | |
| gr.Examples( | |
| examples=["image1.jpg", "image2.jpg"], | |
| inputs=input_image, | |
| label="Sample Notes" | |
| ) | |
| with gr.Column(scale=1): | |
| status_msg = gr.Textbox(label="Status", interactive=False) | |
| download_link = gr.File(label="📄 Download Word File") | |
| with gr.Accordion("Review Extracted Text", open=False): | |
| extracted_text = gr.TextArea(label="Text Preview", lines=12) | |
| submit_btn.click( | |
| fn=process_document, | |
| inputs=input_image, | |
| outputs=[download_link, status_msg, extracted_text] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |