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import gradio as gr |
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import requests |
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import io |
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import random |
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import os |
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import time |
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from PIL import Image, UnidentifiedImageError |
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from deep_translator import GoogleTranslator |
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import json |
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import uuid |
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from urllib.parse import quote |
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import traceback |
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from openai import OpenAI, RateLimitError, APIConnectionError, AuthenticationError |
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API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell" |
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API_TOKEN = os.getenv("HF_READ_TOKEN") |
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if not API_TOKEN: |
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print("WARNING: HF_READ_TOKEN environment variable not set. API calls may fail.") |
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headers = {"Authorization": f"Bearer {API_TOKEN}"} if API_TOKEN else {} |
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timeout = 100 |
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IMAGE_DIR = "temp_generated_images" |
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ARINTELI_REDIRECT_BASE = "https://arinteli.com/app/" |
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try: |
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os.makedirs(IMAGE_DIR, exist_ok=True) |
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print(f"Confirmed temporary image directory exists: {IMAGE_DIR}") |
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except OSError as e: |
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print(f"ERROR: Could not create directory {IMAGE_DIR}: {e}") |
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raise gr.Error(f"Fatal Error: Cannot create temporary image directory: {e}") |
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absolute_image_dir = os.path.abspath(IMAGE_DIR) |
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print(f"Absolute path for allowed_paths: {absolute_image_dir}") |
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try: |
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openai_api_key = os.getenv("OPENAI_API_KEY") |
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if not openai_api_key: |
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print("WARNING: OPENAI_API_KEY environment variable not set or empty. Moderation will be skipped.") |
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openai_client = None |
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else: |
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openai_client = OpenAI() |
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print("OpenAI client initialized successfully.") |
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except Exception as e: |
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print(f"ERROR: Failed to initialize OpenAI client: {e}. Moderation will be skipped.") |
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openai_client = None |
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def query(prompt, negative_prompt="", steps=4, cfg_scale=0, seed=-1, width=1024, height=1024): |
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if not prompt or not prompt.strip(): |
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print("WARNING: Empty prompt received.\n") |
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return None, "<p style='color: orange; text-align: center;'>Please enter a prompt.</p>" |
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original_prompt = prompt |
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translated_prompt = prompt |
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try: |
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translated_prompt = GoogleTranslator(source='auto', target='en').translate(prompt) |
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except Exception as e: |
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print(f"WARNING: Translation failed. Using original prompt.") |
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print(f" Error: {e}") |
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print(f" Prompt: '{original_prompt}'\n") |
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translated_prompt = prompt |
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if openai_client: |
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try: |
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mod_response = openai_client.moderations.create( |
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model="omni-moderation-latest", |
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input=translated_prompt |
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) |
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result = mod_response.results[0] |
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if result.categories.sexual_minors: |
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print("BLOCKED:") |
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print(f" Reason: sexual/minors") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print("") |
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return None, "<p style='color: red; text-align: center;'>Prompt violates safety guidelines. Generation blocked.</p>" |
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except AuthenticationError: |
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print("BLOCKED:") |
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print(f" Reason: OpenAI Auth Error") |
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print(f" Prompt: '{original_prompt}'\n") |
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return None, "<p style='color: red; text-align: center;'>Safety check failed. Generation blocked.</p>" |
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except RateLimitError: |
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print("BLOCKED:") |
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print(f" Reason: OpenAI Rate Limit") |
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print(f" Prompt: '{original_prompt}'\n") |
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return None, "<p style='color: red; text-align: center;'>Safety check failed. Please try again later.</p>" |
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except APIConnectionError as e: |
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print("BLOCKED:") |
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print(f" Reason: OpenAI Connection Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Error: {e}\n") |
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return None, "<p style='color: red; text-align: center;'>Safety check failed. Please try again later.</p>" |
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except Exception as e: |
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print("BLOCKED:") |
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print(f" Reason: OpenAI Unexpected Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Error: {e}\n") |
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traceback.print_exc() |
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return None, "<p style='color: red; text-align: center;'>An unexpected error occurred during safety check. Generation blocked.</p>" |
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else: |
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print(f"WARNING: OpenAI client not available. Skipping moderation.") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" (Would use translated: '{translated_prompt}')") |
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print("") |
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final_prompt = f"{translated_prompt} | ultra detail, ultra elaboration, ultra quality, perfect." |
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payload = { |
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"inputs": final_prompt, |
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"parameters": { |
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"negative_prompt": negative_prompt, |
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"num_inference_steps": steps, |
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"guidance_scale": cfg_scale, |
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"seed": seed if seed != -1 else random.randint(1, 1000000000), |
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"width": width, |
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"height": height, |
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} |
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} |
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try: |
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if not headers: |
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print("FAILED:") |
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print(f" Reason: HF Token Missing") |
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print(f" Prompt: '{original_prompt}'\n") |
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return None, "<p style='color: red; text-align: center;'>Configuration Error: API Token missing.</p>" |
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response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout) |
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response.raise_for_status() |
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image_bytes = response.content |
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if not image_bytes or len(image_bytes) < 100: |
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print("FAILED:") |
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print(f" Reason: Invalid Image Data (Empty/Small)") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Length: {len(image_bytes)}\n") |
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return None, "<p style='color: red; text-align: center;'>API returned invalid image data.</p>" |
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try: |
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image = Image.open(io.BytesIO(image_bytes)) |
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except UnidentifiedImageError as img_err: |
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print("FAILED:") |
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print(f" Reason: Image Processing Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Error: {img_err}\n") |
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return None, "<p style='color: red; text-align: center;'>Failed to process image data from API.</p>" |
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filename = f"{int(time.time())}_{uuid.uuid4().hex[:8]}.png" |
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save_path = os.path.join(IMAGE_DIR, filename) |
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absolute_save_path = os.path.abspath(save_path) |
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try: |
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image.save(save_path, "PNG") |
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if not os.path.exists(save_path) or os.path.getsize(save_path) < 100: |
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print("FAILED:") |
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print(f" Reason: Image Save Verification Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Path: '{save_path}'\n") |
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return image, "<p style='color: red; text-align: center;'>Internal Error: Failed to confirm image file save.</p>" |
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space_name = "greendra-flux-1-schnell-serverless" |
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relative_file_url = f"gradio_api/file={save_path}" |
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encoded_file_url = quote(relative_file_url) |
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arinteli_url = f"{ARINTELI_REDIRECT_BASE}?download_url={encoded_file_url}&space_name={space_name}" |
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download_html = ( |
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f'<div style="text-align: right; margin-right: -8px;">' |
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f'<a href="{arinteli_url}" target="_blank" style="background: #3dd49f; color: white; padding: 7px 25px; border-radius: 6px; text-decoration: none;">' |
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f'Download Image' |
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f'</a>' |
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f'</div>' |
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) |
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print("SUCCESS:") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" {arinteli_url}\n") |
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return image, download_html |
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except (OSError, IOError) as save_err: |
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print("FAILED:") |
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print(f" Reason: Image Save IO Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Path: '{save_path}'") |
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print(f" Error: {save_err}\n") |
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traceback.print_exc() |
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return image, f"<p style='color: red; text-align: center;'>Internal Error: Failed to save image file. Details: {save_err}</p>" |
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except Exception as e: |
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print("FAILED:") |
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print(f" Reason: Link Creation/Save Unexpected Error") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Error: {e}\n") |
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traceback.print_exc() |
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return image, "<p style='color: red; text-align: center;'>Internal Error creating download link.</p>" |
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except requests.exceptions.Timeout: |
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print("FAILED:") |
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print(f" Reason: HF API Timeout") |
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print(f" Prompt: '{original_prompt}'\n") |
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return None, "<p style='color: red; text-align: center;'>Request timed out. The model is taking too long.</p>" |
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except requests.exceptions.HTTPError as e: |
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status_code = e.response.status_code |
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error_text = e.response.text |
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error_data = {} |
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try: |
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error_data = e.response.json() |
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parsed_error = error_data.get('error', error_text) |
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if isinstance(parsed_error, dict) and 'message' in parsed_error: error_text = parsed_error['message'] |
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elif isinstance(parsed_error, list): error_text = "; ".join(map(str, parsed_error)) |
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else: error_text = str(parsed_error) |
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except json.JSONDecodeError: |
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pass |
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print("FAILED:") |
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print(f" Reason: HF API HTTP Error {status_code}") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Details: '{error_text[:200]}'\n") |
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if status_code == 503: |
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estimated_time = error_data.get("estimated_time") if isinstance(error_data, dict) else None |
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error_message = f"Model is loading (503), please wait." + (f" Est. time: {estimated_time:.1f}s." if estimated_time else "") + " Try again." |
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elif status_code == 400: error_message = f"Bad Request (400): Check parameters. API Error: {error_text}" |
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elif status_code == 422: error_message = f"Validation Error (422): Input invalid. API Error: {error_text}" |
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elif status_code == 401 or status_code == 403: error_message = f"Authorization Error ({status_code}): Check your API Token (HF_READ_TOKEN)." |
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else: error_message = f"API Error: {status_code}. Details: {error_text}" |
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return None, f"<p style='color: red; text-align: center;'>{error_message}</p>" |
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except Exception as e: |
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print("FAILED:") |
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print(f" Reason: Unexpected Error During Generation") |
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print(f" Prompt: '{original_prompt}'") |
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if translated_prompt != original_prompt: |
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print(f" Translated: '{translated_prompt}'") |
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print(f" Error: {e}\n") |
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traceback.print_exc() |
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return None, f"<p style='color: red; text-align: center;'>An unexpected error occurred: {e}</p>" |
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css = """ |
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#app-container { |
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max-width: 800px; |
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margin-left: auto; |
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margin-right: auto; |
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} |
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textarea:focus { |
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background: #0d1117 !important; |
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} |
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#download-link-container p { |
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margin-top: 10px; |
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font-size: 0.9em; |
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} |
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""" |
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with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app: |
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with gr.Column(elem_id="app-container"): |
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with gr.Row(): |
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with gr.Column(elem_id="prompt-container"): |
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with gr.Row(): |
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text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input") |
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with gr.Row(): |
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with gr.Accordion("Advanced Settings", open=False): |
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negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input") |
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with gr.Row(): |
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width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32) |
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height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32) |
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steps = gr.Slider(label="Sampling steps", value=4, minimum=1, maximum=8, step=1) |
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cfg = gr.Slider(label="CFG Scale (guidance_scale)", value=0, minimum=0, maximum=10, step=1) |
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seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1, info="Set to -1 for random seed") |
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with gr.Row(): |
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text_button = gr.Button("Run", variant='primary', elem_id="gen-button") |
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with gr.Row(): |
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image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery", show_label=False, show_download_button=False, show_share_button=False, show_fullscreen_button=False) |
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with gr.Row(): |
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download_link_display = gr.HTML(elem_id="download-link-container") |
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text_button.click( |
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query, |
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inputs=[text_prompt, negative_prompt, steps, cfg, seed, width, height], |
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outputs=[image_output, download_link_display] |
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) |
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print("Starting Gradio app...") |
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app.launch( |
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show_api=False, |
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share=False, |
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allowed_paths=[absolute_image_dir] |
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) |