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| import os | |
| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| class HaikuGenerator: | |
| def __init__(self): | |
| HUGGINGFACE_API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN") | |
| self.text_client = InferenceClient(token=HUGGINGFACE_API_TOKEN, model="HuggingFaceH4/zephyr-7b-beta") | |
| self.image_client = InferenceClient(token=HUGGINGFACE_API_TOKEN, model="stabilityai/stable-diffusion-xl-base-1.0") | |
| def generate_haiku(self, prompt): | |
| system_message = "You are a Haiku generator." | |
| response = "" | |
| messages = [{"role": "system", "content": system_message}, | |
| {"role": "user", "content": prompt}] | |
| # Get the chat completion response | |
| message = self.text_client.chat_completion( | |
| messages, | |
| max_tokens=30, | |
| stream=False, | |
| temperature=0.7, | |
| top_p=0.95, | |
| ) | |
| # Extract the generated content | |
| response = message['choices'][0]['message']['content'] | |
| return response.strip() | |
| def text_to_image(self, prompt, style): | |
| # Modify the prompt based on the selected style | |
| if style == "Japanese": | |
| prompt += ", in Japanese art style" | |
| elif style == "oil painting": | |
| prompt += ", in the style of an oil painting" | |
| image = self.image_client.text_to_image(prompt) | |
| return image | |
| def gradio_interface(self): | |
| # Custom CSS to apply a Japanese-style font | |
| custom_css = """ | |
| body { | |
| font-family: 'Sawarabi Mincho', serif !important; | |
| } | |
| h1, h6 { | |
| font-family: 'Sawarabi Mincho', serif !important; | |
| } | |
| .button { | |
| font-family: 'Sawarabi Mincho', serif !important; | |
| } | |
| """ | |
| with gr.Blocks(theme='earneleh/paris', css=custom_css) as demo: | |
| gr.HTML(""" | |
| <center><h1 style="color:#C73E3A">HaiKool - Haiku Poem and Image Generator</h1></center>""") | |
| gr.HTML(""" | |
| <center><h6 style="color:#C73E3A">Generate a Haiku poem and an image based on it - Please note that loading time can be up to 1 minute.</h6></center>""") | |
| with gr.Column(elem_id="col-container"): | |
| haiku_output = gr.Textbox(label="Generated Haiku", interactive=False) | |
| image_output = gr.Image() | |
| with gr.Row(elem_id="col-container"): | |
| with gr.Column(): | |
| prompt = gr.Textbox(show_label=False, placeholder="Enter a prompt for the Haiku") | |
| with gr.Column(): | |
| style = gr.Dropdown(label="Select Image Style", choices=["default", "Japanese", "oil painting"], value="default") | |
| with gr.Column(): | |
| generate_button = gr.Button("Generate Haiku and Image", elem_classes="button") | |
| # Define the function that integrates both steps: Haiku generation and image creation | |
| def generate_haiku_and_image(prompt, style): | |
| haiku = self.generate_haiku(prompt) | |
| image = self.text_to_image(haiku, style) | |
| return haiku, image | |
| generate_button.click(generate_haiku_and_image, inputs=[prompt, style], outputs=[haiku_output, image_output]) | |
| prompt.submit(generate_haiku_and_image, inputs=[prompt, style], outputs=[haiku_output, image_output]) | |
| demo.launch(debug=True) | |
| if __name__ == "__main__": | |
| haiku_generator = HaikuGenerator() | |
| haiku_generator.gradio_interface() | |