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| import gradio as gr | |
| import requests | |
| import io | |
| import os | |
| import json | |
| from PIL import Image | |
| # Load Hugging Face API Key from Space Secrets | |
| HF_API_KEY = os.getenv("HF_TOKEN") | |
| API_URL = "https://api-inference.huggingface.co/models/sameedhayat/corgy_dog_LoRA" | |
| headers = {"Authorization": f"Bearer {HF_API_KEY}"} | |
| def query(payload): | |
| try: | |
| response = requests.post(API_URL, headers=headers, json=payload, timeout=30) | |
| response.raise_for_status() | |
| # Check if the response is an image | |
| content_type = response.headers.get("Content-Type", "") | |
| if "image" in content_type: | |
| return response.content | |
| else: | |
| return f"API Error: Unexpected response format - {response.text}" | |
| except requests.exceptions.RequestException as e: | |
| return f"API Error: {str(e)}" | |
| def generate_image(user_text): | |
| prompt = f"{user_text} in the style of TOK" | |
| try: | |
| image_bytes = query({"inputs": prompt}) | |
| if isinstance(image_bytes, str) and "API Error" in image_bytes: | |
| return image_bytes # Return error message | |
| image = Image.open(io.BytesIO(image_bytes)) | |
| return image | |
| except Exception as e: | |
| return f"Error generating image: {str(e)}" | |
| def fetch_showcase_images(): | |
| """Fetch images from the local 'images' directory and use prompts from a JSON file.""" | |
| images_dir = "images" | |
| json_file = os.path.join(images_dir, "prompts.json") | |
| showcase_images = [] | |
| if os.path.exists(json_file): | |
| with open(json_file, "r") as f: | |
| image_prompts = json.load(f) | |
| for filename, prompt in image_prompts.items(): | |
| image_path = os.path.join(images_dir, filename) | |
| if os.path.exists(image_path): | |
| showcase_images.append((image_path, prompt)) | |
| return showcase_images | |
| def create_interface(): | |
| showcase_images = fetch_showcase_images() | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## 🧵 EmbroideryAI - AI-Powered Embroidery Design") | |
| with gr.Row(): | |
| user_input = gr.Textbox(label="Describe your embroidery design") | |
| btn = gr.Button("Generate") | |
| output_image = gr.Image(label="Generated Image") | |
| btn.click(generate_image, inputs=user_input, outputs=output_image) | |
| gr.Markdown("### 🎨 Showcase of AI-Generated Designs") | |
| for img_path, prompt in showcase_images: | |
| gr.Markdown(f"**Prompt:** {prompt}") | |
| gr.Image(value=img_path, show_label=False) | |
| demo.launch() | |
| if __name__ == "__main__": | |
| create_interface() | |