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| from base64 import b64decode | |
| from PIL import Image | |
| from reportlab.lib.pagesizes import A4 | |
| from reportlab.pdfgen import canvas | |
| import deepl | |
| import gradio as gr | |
| import io | |
| import os | |
| import requests | |
| # Global Stuff | |
| durations = ["5 min", "10 min", "more than 10 min"] | |
| amount_children = ["1", "2", "3", "more than 3"] | |
| ages = ["3 years and older", "5 years and older", "7 years and older"] | |
| languages = ["English", "French", "German", "Italian", "Spanish"] | |
| targets = ["Girls", "Boys", "Girls and Boys"] | |
| themes = ["Dinosaurs", "Fairies", "Firebrigade", "Friendship", "Magic", "Pirates", "Ponys", "Princesses", "Police", "Space", "Superheroes"] | |
| IONOS_API_TOKEN = os.getenv('IONOS_API_TOKEN') | |
| deepl_auth_key = os.getenv('deepl_auth_key') | |
| def create_story(number_of_children, target, theme, target_age, duration): | |
| # Generate story | |
| MODEL_NAME = "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8" | |
| endpoint = "https://openai.inference.de-txl.ionos.com/v1/chat/completions" | |
| PROMPT = [ | |
| {"role": "system", "content": "You are an author who creates beautiful bedtime stories for kids."}, | |
| {"role": "user", "content": f"Generate a beautiful bedtime story for {target} about {theme}. The audience contains {number_of_children} kids in the age of {target_age}. The story should take about {duration} to read assuming an average speed of 183 words per minute. Avoid any additional comments besides the actual story. Do not use too long sentences, the story shall be easy to read and understandable for children."} | |
| ] | |
| header = { | |
| "Authorization": f"Bearer {IONOS_API_TOKEN}", | |
| "Content-Type": "application/json" | |
| } | |
| body = { | |
| "model": MODEL_NAME, | |
| "messages": PROMPT, | |
| } | |
| response = requests.post(endpoint, json=body, headers=header).json() | |
| return response['choices'][0]['message']['content'] | |
| def translate(story_english, to_language): | |
| MODEL_NAME = "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8" | |
| endpoint = "https://openai.inference.de-txl.ionos.com/v1/chat/completions" | |
| PROMPT = [ | |
| {"role": "system", "content": f"You are an assistant who translates text from English into different languages."}, | |
| {"role": "user", "content": f"Carefully translate the following story into {to_language}. Take care about grammar and correct spelling. Create only the translated story without any additional comments:\n\n{story_english}"} | |
| ] | |
| header = { | |
| "Authorization": f"Bearer {IONOS_API_TOKEN}", | |
| "Content-Type": "application/json" | |
| } | |
| body = { | |
| "model": MODEL_NAME, | |
| "messages": PROMPT, | |
| } | |
| response = requests.post(endpoint, json=body, headers=header).json() | |
| return response['choices'][0]['message']['content'] | |
| def create_image(story:str): | |
| MODEL_NAME = "black-forest-labs/FLUX.1-schnell" | |
| endpoint = "https://openai.inference.de-txl.ionos.com/v1/images/generations" | |
| PROMPT = f"A beautiful book cover without any titles for the following story:\n\n{story}." | |
| header = { | |
| "Authorization": f"Bearer {IONOS_API_TOKEN}", | |
| "Content-Type": "application/json" | |
| } | |
| body = { | |
| "model": MODEL_NAME, | |
| "prompt": PROMPT, | |
| "size": "1024x1024" | |
| } | |
| response = requests.post(endpoint, json=body, headers=header) | |
| return response.json()['data'][0]['b64_json'] # Return only the base64 encoded string | |
| def create_book(language, target, theme, number_of_children, target_age, duration): | |
| story = create_story(number_of_children, target, theme, target_age, duration) | |
| if not "English" in language: | |
| deepl_client = deepl.DeepLClient(deepl_auth_key) | |
| usage = deepl_client.get_usage() | |
| if usage.any_limit_reached: | |
| story_output = translate(story, language) | |
| else: | |
| match language: | |
| case "French": | |
| target_lang = "FR" | |
| case "German": | |
| target_lang = "DE" | |
| case "Italian": | |
| target_lang = "IT" | |
| case "Spanish": | |
| target_lang = "ES" | |
| story_output = deepl_client.translate_text(story, target_lang=target_lang) | |
| else: | |
| story_output = story | |
| image_response = create_image(story) | |
| # Decode the base64 image data | |
| img_data = b64decode(image_response) | |
| # Create a PIL image | |
| image_data_pil = Image.open(io.BytesIO(img_data)) | |
| return story_output, image_data_pil | |
| def download_as_pdf(story, image): | |
| # Create a PDF file | |
| pdf_path = "story.pdf" | |
| c = canvas.Canvas(pdf_path, pagesize=A4) | |
| # A4 dimensions in points (595.2, 841.8) | |
| page_width = A4[0] | |
| page_height = A4[1] | |
| # Set image width to 80% of page width and maintain aspect ratio | |
| image_width = page_width * 0.8 | |
| image_height = image_width # Since it's a square image | |
| # Add disclaimer at the top | |
| disclaimer = "AI Generated Story from https://stories.brose-engineering.de" | |
| c.setFont("Helvetica", 10) # Smaller font for disclaimer | |
| disclaimer_width = c.stringWidth(disclaimer, "Helvetica", 10) | |
| disclaimer_x = (page_width - disclaimer_width) / 2 | |
| disclaimer_y = page_height - 30 # Position at top with margin | |
| c.drawString(disclaimer_x, disclaimer_y, disclaimer) | |
| # Position image at top of page with some margin | |
| margin_top = 50 | |
| image_x = (page_width - image_width) / 2 | |
| image_y = page_height - margin_top - image_height | |
| # Add the image to the PDF (only on first page) | |
| c.drawInlineImage(image, image_x, image_y, width=image_width, height=image_height) | |
| # Text parameters | |
| text_margin_top = 30 | |
| text_width = page_width * 0.9 # 90% of page width | |
| text_x = (page_width - text_width) / 2 | |
| text_y = image_y - text_margin_top | |
| line_height = 20 | |
| margin_bottom = 50 | |
| # Split story into words | |
| words = story.split() | |
| current_line = [] | |
| c.setFont("Helvetica", 12) | |
| # Process words and create lines | |
| for word in words: | |
| current_line.append(word) | |
| line_width = c.stringWidth(' '.join(current_line), "Helvetica", 12) | |
| if line_width > text_width: | |
| current_line.pop() | |
| # Draw the line | |
| if text_y < margin_bottom: # Need new page | |
| c.showPage() # Start new page | |
| text_y = page_height - margin_top # Reset Y position for new page | |
| c.setFont("Helvetica", 12) # Need to reset font after new page | |
| c.drawString(text_x, text_y, ' '.join(current_line)) | |
| text_y -= line_height | |
| current_line = [word] | |
| # Draw remaining text | |
| if current_line: | |
| if text_y < margin_bottom: # Need new page | |
| c.showPage() # Start new page | |
| text_y = page_height - margin_top | |
| c.setFont("Helvetica", 12) | |
| c.drawString(text_x, text_y, ' '.join(current_line)) | |
| # Save the PDF | |
| c.save() | |
| return pdf_path | |
| # Define Gradio interface | |
| with gr.Blocks(theme=gr.themes.Glass(), title="BedTimeStories", css="footer{display:none !important}") as demo: | |
| gr.Markdown("# 🥱 BedTime Stories") | |
| gr.Markdown("### Daily a new bedtime story for kids. It just takes a minute.") | |
| gr.Markdown("### Available for many languages spoken in the EU. 🇪🇺") | |
| with gr.Row(): | |
| number_of_children = gr.Dropdown(label="Number of children: 🥱😌😴", choices=amount_children) | |
| language = gr.Dropdown(label="Select your language: 🇬🇧 🇫🇷 🇩🇪 🇮🇹 🇪🇦", choices=languages) | |
| target_age = gr.Dropdown(label="Childrens age: 3️⃣4️⃣5️⃣", choices=ages) | |
| with gr.Row(): | |
| duration = gr.Dropdown(label="Story length: ⏳", choices=durations) | |
| target = gr.Dropdown(label="Story for: ♀️♂️", choices=targets) | |
| theme = gr.Dropdown(label="Story about: 📖", choices=themes) | |
| create_button = gr.Button("Create Story") | |
| with gr.Row(): | |
| image_output = gr.Image(type="pil", interactive=False, show_label=False) | |
| with gr.Row(): | |
| story_output = gr.Textbox(label="Story:", interactive=False, lines=25) | |
| download_story_button = gr.Button("Download Story", interactive=True) | |
| create_button.click(fn=create_book, inputs=[language, target, theme, number_of_children, target_age, duration], outputs=[story_output, image_output], concurrency_limit=3) | |
| download_story_button.click(fn=download_as_pdf, inputs=[story_output, image_output], outputs=gr.File(label="Your story as PDF", interactive=False)) | |
| gr.Markdown("Made with ❤️ in 🇩🇪 | [brose-engineering.de](https://brose-engineering.de/) | [GitHub](https://github.com/brose-engineering/bedtime_stories)") | |
| gr.Markdown("Translations by DeepL | [deepl.com](https://www.deepl.com) | [Why DeepL?](https://www.deepl.com/en/quality)") | |
| gr.Markdown("This Gradio-App is hosted on Huggingface | [Huggingface Terms of Service](https://huggingface.co/terms-of-service) | [Gradio.app](https://www.gradio.app/)") | |
| demo.launch() | |