fix mistake

app.py

@@ -4,22 +4,20 @@ import io
 import random
 import os
 import time
-from PIL import Image, UnidentifiedImageError # Added UnidentifiedImageError
+from PIL import Image, UnidentifiedImageError
 from deep_translator import GoogleTranslator
 import json
 import uuid
 from urllib.parse import quote
-import traceback # For detailed error logging
+import traceback
 
 # Project by Nymbo
 
 # --- Constants ---
-API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-3.5-large"
+API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
 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
 
@@ -40,13 +38,10 @@ except OSError as e:
 absolute_image_dir = os.path.abspath(IMAGE_DIR)
 print(f"Absolute path for allowed_paths: {absolute_image_dir}")
 
-
-# --- Function to query the API and return the generated image and download link ---
-def query(prompt, negative_prompt, steps=35, cfg_scale=7, seed=-1, width=1024, height=1024):
-    # Renamed `strength` input as it wasn't used in the payload for txt2img
-    # Removed `sampler` input as it wasn't used in payload
-
-    # Basic Input Validation
+# Function to query the API and return the generated image and download link
+def query(prompt, negative_prompt="", steps=30, cfg_scale=7, seed=-1, width=1024, height=1024):
+    # Removed sampler and strength as they are not explicitly used in the payload below
+    # Note: If the API endpoint *does* support sampler/strength, add them back to the payload
     if not prompt or not prompt.strip():
         print("Empty prompt received.")
         # Return None for image and an informative message for the HTML component
@@ -57,120 +52,99 @@ def query(prompt, negative_prompt, steps=35, cfg_scale=7, seed=-1, width=1024, h
 
     # Translation
     try:
-        # Using 'auto' source detection
         translated_prompt = GoogleTranslator(source='auto', target='en').translate(prompt)
-        print(f'Generation {key} translation: {translated_prompt}')
     except Exception as e:
-        print(f"Translation failed: {e}. Using original prompt.")
         translated_prompt = prompt # Fallback to original if translation fails
 
     # Add suffix to prompt
     final_prompt = f"{translated_prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-    print(f'Generation {key} final prompt: {final_prompt}')
+    print(f'Generation {key} prompt: {final_prompt}')
 
-    # Prepare payload for API call
+    # Prepare the payload for the API call
     payload = {
         "inputs": final_prompt,
-        "negative_prompt": negative_prompt,
+        "negative_prompt": negative_prompt, # Assuming API accepts negative_prompt
         "steps": steps,
         "guidance_scale": cfg_scale, # API often uses guidance_scale
         "seed": seed if seed != -1 else random.randint(1, 1000000000),
-        "parameters": { # Nested parameters as per original structure
+        "parameters": {
             "width": width,
             "height": height,
+            # If the API supports other params like 'steps', 'guidance_scale', they might belong here or top-level
         }
-        # Add other parameters here if needed (e.g., sampler if supported)
+        # Removed 'is_negative' as negative_prompt is usually passed directly
+        # Removed 'strength' and 'sampler' as they weren't in the target API structure
     }
 
     # API Call Section
     try:
-        print(f"Sending request to API: {API_URL}")
         if not headers:
              print("WARNING: Authorization header is missing (HF_READ_TOKEN not set?)")
-             # Handle error appropriately - maybe return an error message
              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() # Raises HTTPError for 4xx/5xx responses
+        response.raise_for_status()
 
         image_bytes = response.content
-        # Check for valid image data before proceeding
-        if not image_bytes or len(image_bytes) < 100: # Basic check for empty/tiny response
+        if not image_bytes or len(image_bytes) < 100:
              print(f"Error: Received empty or very small response content (length: {len(image_bytes)}). Potential API issue.")
              return None, "<p style='color: red; text-align: center;'>API returned invalid image data.</p>"
 
         try:
             image = Image.open(io.BytesIO(image_bytes))
-            print(f"Image received and opened successfully. Format: {image.format}, Size: {image.size}")
         except UnidentifiedImageError as img_err:
              print(f"Error: Could not identify or open image from API response bytes: {img_err}")
-             # Optionally save the invalid bytes for debugging
-             # error_bytes_path = os.path.join(IMAGE_DIR, f"error_{key}_bytes.bin")
-             # with open(error_bytes_path, "wb") as f: f.write(image_bytes)
-             # print(f"Saved problematic bytes to {error_bytes_path}")
              return None, "<p style='color: red; text-align: center;'>Failed to process image data from API.</p>"
 
-        print(f'Generation {key} API call successful!')
-
         # --- Save image and create download link ---
         filename = f"{int(time.time())}_{uuid.uuid4().hex[:8]}.png"
-        # save_path is relative to the script's execution directory
         save_path = os.path.join(IMAGE_DIR, filename)
-        absolute_save_path = os.path.abspath(save_path) # Get absolute path for logging
+        absolute_save_path = os.path.abspath(save_path)
 
         try:
-            print(f"Attempting to save image to: {absolute_save_path}")
-            # Save image explicitly as PNG
             image.save(save_path, "PNG")
 
-            # *** Verify file exists after saving ***
             if os.path.exists(save_path):
                 file_size = os.path.getsize(save_path)
-                print(f"SUCCESS: Image confirmed saved to: {save_path} (Absolute: {absolute_save_path})")
-                print(f"Saved file size: {file_size} bytes")
-                if file_size < 100: # Warn if the saved file is suspiciously small
+                if file_size < 100:
                      print(f"WARNING: Saved file {save_path} is very small ({file_size} bytes). May indicate an issue.")
-                     # Optionally return a warning message in the UI
-                     # return image, "<p style='color: orange; text-align: center;'>Warning: Saved image file is unexpectedly small.</p>"
             else:
-                # This indicates a serious problem if save() didn't raise an error but the file isn't there
                 print(f"CRITICAL ERROR: File NOT found at {save_path} (Absolute: {absolute_save_path}) immediately after saving!")
                 return image, "<p style='color: red; text-align: center;'>Internal Error: Failed to confirm image file save.</p>"
 
-            # Get current space name from the API URL
-            space_name = "greendra-stable-diffusion-3-5-large-serverless"
-            print(f"Current space name: {space_name}")
-            
+            # Determine space name (adjust logic if API_URL format differs)
+            try:
+                space_name = "greendra-flux-1-schnell-serverless"
+                # A more robust way might involve getting the space ID from env vars if available
+            except IndexError:
+                 print("WARNING: Could not reliably determine space name from API_URL. Using a default.")
+                 space_name = "unknown-flux-space" # Provide a fallback
+
             relative_file_url = f"/gradio_api/file={save_path}"
-            print(f"Generated relative file URL for Gradio API: {relative_file_url}")
 
             encoded_file_url = quote(relative_file_url)
-            # Add space_name parameter to the URL
             arintelli_url = f"{ARINTELLI_REDIRECT_BASE}?download_url={encoded_file_url}&space_name={space_name}"
-            print(f"Generated redirect link: {arintelli_url}")
+            print(f"{arintelli_url}")
 
-            # Use simpler button style like the Run button
+            # Use Gradio's primary button style for the link
             download_html = (
-                f'<div style="text-align: center;">'
+                f'<div style="text-align: center; margin-top: 15px;">' # Added margin-top
                 f'<a href="{arintelli_url}" target="_blank" class="gr-button gr-button-lg gr-button-primary">'
                 f'Download Image'
                 f'</a>'
                 f'</div>'
             )
 
-            print(f"--- Generation {key} Completed Successfully ---")
+            print(f"--- Generation {key} Done ---")
             return image, download_html
 
         except (OSError, IOError) as save_err:
-            # Handle errors during the file save operation
             print(f"CRITICAL ERROR: Failed to save image to {save_path} (Absolute: {absolute_save_path}): {save_err}")
-            traceback.print_exc() # Log detailed traceback
+            traceback.print_exc()
             return image, f"<p style='color: red; text-align: center;'>Internal Error: Failed to save image file. Details: {save_err}</p>"
         except Exception as e:
-            # Catch any other unexpected errors during link creation/saving
             print(f"Error during link creation or unexpected save issue: {e}")
             traceback.print_exc()
-            # Return the generated image (if available) but indicate link error
             return image, "<p style='color: red; text-align: center;'>Internal Error creating download link.</p>"
 
     # --- Exception Handling for API Call ---
@@ -178,46 +152,41 @@ def query(prompt, negative_prompt, steps=35, cfg_scale=7, seed=-1, width=1024, h
         print(f"Error: Request timed out after {timeout} seconds.")
         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:
-        # Handle HTTP errors from the API (4xx, 5xx)
         status_code = e.response.status_code
-        error_text = e.response.text # Default error text
+        error_text = e.response.text
         try:
-            # Try to parse more specific error message from JSON response
             error_data = e.response.json()
             error_text = error_data.get('error', error_text)
             if isinstance(error_text, dict) and 'message' in error_text:
-                 error_text = error_text['message'] # Handle nested messages
+                 error_text = error_text['message']
         except json.JSONDecodeError:
-            pass # Keep raw text if not JSON
+            pass
 
         print(f"Error: Failed API call. Status: {status_code}, Response: {error_text}")
 
-        # Generate user-friendly messages based on status code
-        if status_code == 503: # Service Unavailable (often model loading)
+        if status_code == 503:
              estimated_time = error_data.get("estimated_time") if 'error_data' in locals() and isinstance(error_data, dict) else None
              if estimated_time:
                   error_message = f"Model is loading (503), please wait. Est. time: {estimated_time:.1f}s. Try again."
              else:
                   error_message = f"Service unavailable (503). Model might be loading or down. Try again later."
-        elif status_code == 400: # Bad Request (invalid parameters)
+        elif status_code == 400:
              error_message = f"Bad Request (400): Check parameters. API Error: {error_text}"
-        elif status_code == 422: # Unprocessable Entity (validation error)
+        elif status_code == 422:
              error_message = f"Validation Error (422): Input invalid. API Error: {error_text}"
-        elif status_code == 401 or status_code == 403: # Unauthorized / Forbidden
+        elif status_code == 401 or status_code == 403:
              error_message = f"Authorization Error ({status_code}): Check your API Token (HF_READ_TOKEN)."
-        else: # Generic API error
+        else:
             error_message = f"API Error: {status_code}. Details: {error_text}"
 
-        # Return None for image, and the error message string for the HTML component
         return None, f"<p style='color: red; text-align: center;'>{error_message}</p>"
     except Exception as e:
-        # Catch any other unexpected errors during the process
         print(f"An unexpected error occurred: {e}")
-        traceback.print_exc() # Log detailed traceback
+        traceback.print_exc()
         return None, f"<p style='color: red; text-align: center;'>An unexpected error occurred: {e}</p>"
 
 
-# --- CSS Styling ---
+# CSS to style the app
 css = """
 #app-container {
     max-width: 800px;
@@ -227,48 +196,33 @@ css = """
 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 */
+#download-link-container p {
+    margin-top: 10px;
+    font-size: 0.9em;
 }
 """
 
-# --- Build the Gradio UI with Blocks ---
+# Build the Gradio UI with Blocks
 with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
-    gr.HTML("<center><h1>Stable Diffusion 3.5 Large</h1></center>")
+    gr.HTML("<center><h1>FLUX.1-Schnell</h1></center>")
 
     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"
-                    )
+                    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"
-                        )
+                        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=35, minimum=1, maximum=100, step=1)
-                        cfg = gr.Slider(label="CFG Scale (guidance_scale)", value=7, minimum=1, maximum=20, step=1)
-                        # Removed 'strength' slider as it wasn't used in query payload
-                        # strength = gr.Slider(label="Strength (Primarily for Img2Img)", value=0.7, minimum=0, maximum=1, step=0.001, info="Note: Strength is mainly used in Image-to-Image generation.")
+                        steps = gr.Slider(label="Sampling steps", value=30, minimum=1, maximum=100, step=1) # Default updated based on query function default
+                        cfg = gr.Slider(label="CFG Scale (guidance_scale)", value=7, minimum=1, maximum=20, step=1) # Label updated
+                        # Removed strength and sampler sliders as they are not passed to query
                         seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1, info="Set to -1 for random seed")
-                        # Removed 'method' radio as it wasn't used in query payload
-                        # method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"], info="Note: Sampler choice might not be supported by this API.")
 
-        # --- Action Button ---
         with gr.Row():
             text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
 
@@ -279,21 +233,19 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
              # HTML component to display status messages or the download link
              download_link_display = gr.HTML(elem_id="download-link-container")
 
-        # --- Event Listener ---
-        # Bind the button click to the query function
+        # Bind the button to the query function
         text_button.click(
             query,
-            # Ensure the inputs list matches the parameters of the `query` function definition
+            # Ensure inputs match the query function definition
             inputs=[text_prompt, negative_prompt, steps, cfg, seed, width, height],
-            # Outputs go to the image component and the HTML component
+            # Outputs go to the image and HTML components
             outputs=[image_output, download_link_display]
         )
 
-# --- Launch the Gradio app ---
+# Launch the Gradio app with allowed_paths
 print("Starting Gradio app...")
-# Use allowed_paths with the pre-calculated absolute path to the image directory
 app.launch(
     show_api=False,
-    share=False, # Set to True only if you need a public link for direct testing
-    allowed_paths=[absolute_image_dir]
+    share=False,
+    allowed_paths=[absolute_image_dir] # Added allowed_paths
 )