app.py

import gradio as gr
import requests
import io
import random
import os
import time
from PIL import Image, UnidentifiedImageError # Added UnidentifiedImageError
from deep_translator import GoogleTranslator
import json
import uuid
from urllib.parse import quote
import traceback # For detailed error logging
from openai import OpenAI, RateLimitError, APIConnectionError, AuthenticationError # Added OpenAI errors

# Project by Nymbo

# --- Constants ---
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-3.5-large-turbo"
API_TOKEN = os.getenv("HF_READ_TOKEN")
if not API_TOKEN:
    print("WARNING: HF_READ_TOKEN environment variable not set. API calls may fail.")
    # Optionally, raise an error or exit if the token is essential
    # raise ValueError("Missing required environment variable: HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"} if API_TOKEN else {}
timeout = 100 # seconds for API call timeout

IMAGE_DIR = "temp_generated_images" # Directory to store temporary images
ARINTELI_REDIRECT_BASE = "https://arinteli.com/app/" # Your redirector URL

# --- Ensure temporary directory exists ---
try:
    os.makedirs(IMAGE_DIR, exist_ok=True)
    print(f"Confirmed temporary image directory exists: {IMAGE_DIR}")
except OSError as e:
    print(f"ERROR: Could not create directory {IMAGE_DIR}: {e}")
    # This is critical, so raise an error to prevent app start if dir fails
    raise gr.Error(f"Fatal Error: Cannot create temporary image directory: {e}")

# --- Get Absolute Path for allowed_paths ---
# This needs to be done *before* calling launch()
absolute_image_dir = os.path.abspath(IMAGE_DIR)
print(f"Absolute path for allowed_paths: {absolute_image_dir}")

# --- OpenAI Client ---
# Initialize OpenAI client (it will automatically look for the OPENAI_API_KEY env var)
try:
    # Check if the environment variable exists and is not empty
    openai_api_key = os.getenv("OPENAI_API_KEY")
    if not openai_api_key:
        print("WARNING: OPENAI_API_KEY environment variable not set or empty. Moderation will be skipped.")
        openai_client = None
    else:
        openai_client = OpenAI() # Key is implicitly used by the library
        print("OpenAI client initialized successfully.")
except Exception as e:
    print(f"ERROR: Failed to initialize OpenAI client: {e}. Moderation will be skipped.")
    openai_client = None # Set to None so we can check later

# --- Function to query the API and return the generated image and download link ---
def query(prompt, negative_prompt, steps=4, cfg_scale=0, seed=-1, width=1024, height=1024):
    # Basic Input Validation
    if not prompt or not prompt.strip():
        print("WARNING: Empty prompt received.\n") # Add newline for separation
        return None, "<p style='color: orange; text-align: center;'>Please enter a prompt.</p>"

    # Store original prompt for logging
    original_prompt = prompt

    # Translation
    translated_prompt = prompt # Start with original
    try:
        translated_prompt = GoogleTranslator(source='auto', target='en').translate(prompt)
    except Exception as e:
        print(f"WARNING: Translation failed. Using original prompt.")
        print(f"  Error: {e}")
        print(f"  Prompt: '{original_prompt}'\n") # Add newline
        translated_prompt = prompt # Ensure it's the original if translation fails

    # --- OpenAI Moderation Check ---
    if openai_client:
        try:
            mod_response = openai_client.moderations.create(
                model="omni-moderation-latest",
                input=translated_prompt
            )
            result = mod_response.results[0]

            if result.categories.sexual_minors:
                print("BLOCKED:")
                print(f"  Reason: sexual/minors")
                print(f"  Prompt: '{original_prompt}'")
                if translated_prompt != original_prompt:
                    print(f"  Translated: '{translated_prompt}'")
                print("") # Add newline
                return None, "<p style='color: red; text-align: center;'>Prompt violates safety guidelines. Generation blocked.</p>"

        except AuthenticationError:
             print("BLOCKED:")
             print(f"  Reason: OpenAI Auth Error")
             print(f"  Prompt: '{original_prompt}'\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>Safety check failed. Generation blocked.</p>"
        except RateLimitError:
             print("BLOCKED:")
             print(f"  Reason: OpenAI Rate Limit")
             print(f"  Prompt: '{original_prompt}'\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>Safety check failed. Please try again later.</p>"
        except APIConnectionError as e:
             print("BLOCKED:")
             print(f"  Reason: OpenAI Connection Error")
             print(f"  Prompt: '{original_prompt}'")
             if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
             print(f"  Error: {e}\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>Safety check failed. Please try again later.</p>"
        except Exception as e:
            print("BLOCKED:")
            print(f"  Reason: OpenAI Unexpected Error")
            print(f"  Prompt: '{original_prompt}'")
            if translated_prompt != original_prompt:
                print(f"  Translated: '{translated_prompt}'")
            print(f"  Error: {e}\n") # Add newline
            traceback.print_exc() # Keep traceback for unexpected errors
            return None, "<p style='color: red; text-align: center;'>An unexpected error occurred during safety check. Generation blocked.</p>"
    else:
        print(f"WARNING: OpenAI client not available. Skipping moderation.")
        print(f"  Prompt: '{original_prompt}'") # Log original prompt even if skipping
        if translated_prompt != original_prompt:
             print(f"  (Would use translated: '{translated_prompt}')")
        print("") # Add newline

    # --- Proceed with Generation ---
    # Define a threshold for modifying prompts based on sexual content score
    SEXUAL_SCORE_THRESHOLD = 0.6
    prompt_suffix = " | ultra detail, ultra elaboration, ultra quality, perfect" # Base quality enhancers
    negative_prompt_addition = "" # Start with no additions

    # Check moderation scores if available and adjust prompts
    if openai_client and 'mod_response' in locals(): # Check if moderation ran and response exists
        result = mod_response.results[0]
        if hasattr(result, 'category_scores') and result.category_scores.sexual > SEXUAL_SCORE_THRESHOLD:
            print(f"INFO: High 'sexual' score detected ({result.category_scores.sexual:.4f}). Modifying prompts.")
            prompt_suffix += "adult face, mature face, grown-up, of age, " 
            negative_prompt_addition = "child, minor, underage, teenager, "

    final_prompt = f"{prompt_suffix}{translated_prompt}"
    final_negative_prompt = f"{negative_prompt_addition}{negative_prompt}".strip(', ') # Combine and clean up potential leading comma

    payload = {
        "inputs": final_prompt,
        "parameters": {
            "width": width, "height": height, "num_inference_steps": steps,
            "negative_prompt": final_negative_prompt, # Use the potentially modified negative prompt
            "guidance_scale": cfg_scale,
            "seed": seed if seed != -1 else random.randint(1, 1000000000),
        }
    }

    # API Call Section
    try:
        if not headers:
             print("FAILED:")
             print(f"  Reason: HF Token Missing")
             print(f"  Prompt: '{original_prompt}'\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>Configuration Error: API Token missing.</p>"

        response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
        response.raise_for_status()

        image_bytes = response.content
        if not image_bytes or len(image_bytes) < 100:
             print("FAILED:")
             print(f"  Reason: Invalid Image Data (Empty/Small)")
             print(f"  Prompt: '{original_prompt}'")
             if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
             print(f"  Length: {len(image_bytes)}\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>API returned invalid image data.</p>"

        try:
            image = Image.open(io.BytesIO(image_bytes))
        except UnidentifiedImageError as img_err:
             print("FAILED:")
             print(f"  Reason: Image Processing Error")
             print(f"  Prompt: '{original_prompt}'")
             if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
             print(f"  Error: {img_err}\n") # Add newline
             return None, "<p style='color: red; text-align: center;'>Failed to process image data from API.</p>"

        # --- Save image and create download link ---
        filename = f"{int(time.time())}_{uuid.uuid4().hex[:8]}.png"
        save_path = os.path.join(IMAGE_DIR, filename)
        absolute_save_path = os.path.abspath(save_path)

        try:
            image.save(save_path, "PNG")

            if not os.path.exists(save_path) or os.path.getsize(save_path) < 100:
                 print("FAILED:")
                 print(f"  Reason: Image Save Verification Error")
                 print(f"  Prompt: '{original_prompt}'")
                 if translated_prompt != original_prompt:
                      print(f"  Translated: '{translated_prompt}'")
                 print(f"  Path: '{save_path}'\n") # Add newline
                 return image, "<p style='color: red; text-align: center;'>Internal Error: Failed to confirm image file save.</p>"

            space_name = "greendra-stable-diffusion-3-5-large-serverless"
            relative_file_url = f"gradio_api/file={save_path}"
            encoded_file_url = quote(relative_file_url)
            arinteli_url = f"{ARINTELI_REDIRECT_BASE}?download_url={encoded_file_url}&space_name={space_name}"

            download_html = (
                f'<div style="text-align: right; margin-right: -8px;">'
                f'<a href="{arinteli_url}" target="_blank" style="background: #3dd49f; color: white; padding: 7px 25px; border-radius: 6px; text-decoration: none;">'
                f'Download Image'
                f'</a>'
                f'</div>'
            )

            # *** SUCCESS LOG ***
            print("SUCCESS:")
            print(f"  Prompt: '{original_prompt}'")
            if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
            print(f"  {arinteli_url}\n") # Add newline
            return image, download_html

        except (OSError, IOError) as save_err:
            print("FAILED:")
            print(f"  Reason: Image Save IO Error")
            print(f"  Prompt: '{original_prompt}'")
            if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
            print(f"  Path: '{save_path}'")
            print(f"  Error: {save_err}\n") # Add newline
            traceback.print_exc()
            return image, f"<p style='color: red; text-align: center;'>Internal Error: Failed to save image file.</p>"
        except Exception as e:
            print("FAILED:")
            print(f"  Reason: Link Creation/Save Unexpected Error")
            print(f"  Prompt: '{original_prompt}'")
            if translated_prompt != original_prompt:
                 print(f"  Translated: '{translated_prompt}'")
            print(f"  Error: {e}\n") # Add newline
            traceback.print_exc()
            return image, "<p style='color: red; text-align: center;'>Internal Error creating download link.</p>"

    # --- Exception Handling for API Call ---
    except requests.exceptions.Timeout:
        print("FAILED:")
        print(f"  Reason: HF API Timeout")
        print(f"  Prompt: '{original_prompt}'\n") # Add newline
        return None, "<p style='color: red; text-align: center;'>Request timed out. The model is taking too long.</p>"
    except requests.exceptions.HTTPError as e:
        status_code = e.response.status_code
        error_text = e.response.text
        error_data = {}
        try:
            error_data = e.response.json()
            parsed_error = error_data.get('error', error_text)
            if isinstance(parsed_error, dict) and 'message' in parsed_error: error_text = parsed_error['message']
            elif isinstance(parsed_error, list): error_text = "; ".join(map(str, parsed_error))
            else: error_text = str(parsed_error)
        except json.JSONDecodeError:
            pass

        print("FAILED:")
        print(f"  Reason: HF API HTTP Error {status_code}")
        print(f"  Prompt: '{original_prompt}'")
        if translated_prompt != original_prompt:
             print(f"  Translated: '{translated_prompt}'")
        print(f"  Details: '{error_text[:200]}'\n") # Add newline

        # User-facing messages remain the same
        if status_code == 503:
             estimated_time = error_data.get("estimated_time") if isinstance(error_data, dict) else None
             error_message = f"Model is loading (503), please wait." + (f" Est. time: {estimated_time:.1f}s." if estimated_time else "") + " Try again."
        elif status_code == 400: error_message = f"Bad Request (400): Check parameters."
        elif status_code == 422: error_message = f"Validation Error (422): Input invalid."
        elif status_code == 401 or status_code == 403: error_message = f"Authorization Error ({status_code}): Check API Token."
        elif status_code == 429: error_message = f"Rate Limit Error (429): Too many requests. Try again later."
        else: error_message = f"API Error ({status_code}). Please try again."

        return None, f"<p style='color: red; text-align: center;'>{error_message}</p>"
    except Exception as e:
        print("FAILED:")
        print(f"  Reason: Unexpected Error During Generation")
        print(f"  Prompt: '{original_prompt}'")
        if translated_prompt != original_prompt:
             print(f"  Translated: '{translated_prompt}'")
        print(f"  Error: {e}\n") # Add newline
        traceback.print_exc()
        return None, f"<p style='color: red; text-align: center;'>An unexpected error occurred. Please check logs.</p>"


# --- CSS Styling ---
css = """
#app-container {
    max-width: 800px;
    margin-left: auto;
    margin-right: auto;
}
textarea:focus {
    background: #0d1117 !important;
}
#download-link-container p { /* Style the link container */
    margin-top: 10px; /* Add some space above the link */
    font-size: 0.9em; /* Slightly smaller text for the link message */
}
"""

# --- Build the Gradio UI with Blocks ---
with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
    with gr.Column(elem_id="app-container"):
        # --- Input Components ---
        with gr.Row():
            with gr.Column(elem_id="prompt-container"):
                with gr.Row():
                    text_prompt = gr.Textbox(
                        label="Prompt",
                        placeholder="Enter a prompt here",
                        lines=2,
                        elem_id="prompt-text-input"
                    )
                with gr.Row():
                    with gr.Accordion("Advanced Settings", open=False):
                        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"
                        )
                        with gr.Row():
                            width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
                            height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
                        steps = gr.Slider(label="Sampling steps", value=4, minimum=1, maximum=8, step=1)
                        cfg = gr.Slider(label="CFG Scale (guidance_scale)", value=0, minimum=0, maximum=10, step=1)
                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1, info="Set to -1 for random seed")

        # --- Action Button ---
        with gr.Row():
            text_button = gr.Button("Run", variant='primary', elem_id="gen-button")

        # --- Output Components ---
        with gr.Row():
            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)
        with gr.Row():
             download_link_display = gr.HTML(elem_id="download-link-container")

        # --- Event Listener ---
        text_button.click(
            query,
            inputs=[text_prompt, negative_prompt, steps, cfg, seed, width, height],
            outputs=[image_output, download_link_display]
        )

# --- Launch the Gradio app ---
print("Starting Gradio app...")
app.launch(
    show_api=False,
    share=False,
    allowed_paths=[absolute_image_dir],
    # server_name="0.0.0.0"
)