Update app.py

app.py

@@ -8,131 +8,77 @@ from deep_translator import GoogleTranslator
 
 # os.makedirs('assets', exist_ok=True)
 if not os.path.exists('icon.jpg'):
-    print("Downloading icon.jpg...")
-    try:
-        # Use a more robust way to download, requests is already imported
-        response = requests.get("https://i.pinimg.com/564x/64/49/88/644988c59447eb00286834c2e70fdd6b.jpg", stream=True)
-        response.raise_for_status() # Raise an exception for HTTP errors
-        with open('icon.jpg', 'wb') as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                f.write(chunk)
-        print("Icon downloaded successfully.")
-    except requests.exceptions.RequestException as e:
-        print(f"Error downloading icon.jpg: {e}. Please ensure you have internet access or place icon.jpg manually.")
-        # As a fallback, you might want to skip using the icon or use a placeholder
-        # For now, the app will proceed and might show a broken image if icon.jpg is missing.
-
+    os.system("wget -O icon.jpg https://i.pinimg.com/564x/64/49/88/644988c59447eb00286834c2e70fdd6b.jpg")
 API_URL_DEV = "https://lol-v2.mxflower.eu.org/api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
 API_URL = "https://lol-v2.mxflower.eu.org/api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
 timeout = 100
 
-def query(prompt, negative_prompt_text, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key_ui=None, use_dev=False):
+def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None, use_dev=False):
     # Determine which API URL to use
     api_url = API_URL_DEV if use_dev else API_URL
 
-    # Determine the API Token to use
-    # Priority: 1. UI input, 2. Environment variable HF_READ_TOKEN
-    auth_token = None
-    if huggingface_api_key_ui and huggingface_api_key_ui.strip(): # Check if UI key is provided and not just whitespace
-        auth_token = huggingface_api_key_ui.strip()
-        print("Using API key provided in the UI.")
-    else:
-        auth_token = os.getenv("HF_READ_TOKEN")
-        if auth_token:
-            print("Using API key from HF_READ_TOKEN environment variable.")
-        else:
-            # If neither is available, raise an error.
-            raise gr.Error("Hugging Face API Key is required. Please provide it in the 'Hugging Face API Key' field or set the HF_READ_TOKEN environment variable.")
+    # Check if the request is an API call by checking for the presence of the huggingface_api_key
+    is_api_call = huggingface_api_key is not None
 
-    headers = {"Authorization": f"Bearer {auth_token}"}
+    if is_api_call:
+        # Use the environment variable for the API key in GUI mode
+        API_TOKEN = os.getenv("HF_READ_TOKEN")
+        headers = {"Authorization": f"Bearer {API_TOKEN}"}
+    else:
+        # Validate the API key if it's an API call
+        if huggingface_api_key == "":
+            raise gr.Error("API key is required for API calls.")
+        headers = {"Authorization": f"Bearer {huggingface_api_key}"}
 
-    if not prompt or not prompt.strip(): # Check if prompt is None, empty, or just whitespace
-        # Optionally, return a placeholder or a message instead of None
-        # For now, returning None as per original logic for empty prompt
-        gr.Warning("Prompt cannot be empty.")
-        return None, seed # Return seed as well to match output structure
+    if prompt == "" or prompt is None:
+        return None
 
     key = random.randint(0, 999)
 
-    # Translate prompt if it seems to be in Russian (simple check, can be improved)
-    # For simplicity, let's assume Russian if it contains Cyrillic characters
-    try:
-        # A more robust check might be needed, but this is a common heuristic
-        if any('\u0400' <= char <= '\u04FF' for char in prompt):
-            translated_prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
-            print(f'\033[1mGeneration {key} RU->EN translation:\033[0m {translated_prompt}')
-            prompt = translated_prompt
-        else:
-            print(f'\033[1mGeneration {key} using EN prompt (no translation needed).\033[0m')
-    except Exception as e:
-        print(f"Error during translation: {e}. Using original prompt.")
-        # Fallback to original prompt if translation fails
+    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
+    print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
 
-    # Augment the prompt
-    augmented_prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-    print(f'\033[1mGeneration {key} final prompt:\033[0m {augmented_prompt}')
+    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
+    print(f'\033[1mGeneration {key}:\033[0m {prompt}')
 
     # If seed is -1, generate a random seed and use it
-    current_seed = seed
-    if current_seed == -1:
-        current_seed = random.randint(1, 1000000000)
-    
-    # Note: The 'sampler' variable is passed to this function but not used in the payload.
-    # The custom API might handle sampler selection server-side or not support it.
-    # The 'is_negative' key in payload might be expecting the negative_prompt_text.
-    # Assuming the custom API expects negative prompt text under the 'is_negative' key.
-    # If it expects a boolean, this part needs adjustment.
+    if seed == -1:
+        seed = random.randint(1, 1000000000)
+
     payload = {
-        "inputs": augmented_prompt,
-        "is_negative": negative_prompt_text, # This sends the text of negative_prompt
+        "inputs": prompt,
+        "is_negative": is_negative,
         "steps": steps,
         "cfg_scale": cfg_scale,
-        "seed": current_seed,
+        "seed": seed,
         "strength": strength
     }
 
-    print(f"Sending payload to {api_url}: {payload}") # For debugging
-
-    try:
-        response = requests.post(api_url, headers=headers, json=payload, timeout=timeout)
-        response.raise_for_status() # This will raise an HTTPError for bad responses (4xx or 5xx)
-    except requests.exceptions.Timeout:
-        raise gr.Error(f"Request timed out after {timeout} seconds. The model might be too busy or the server is slow.")
-    except requests.exceptions.HTTPError as e:
-        print(f"Error: Failed to get image. Response status: {e.response.status_code}")
-        print(f"Response content: {e.response.text}")
-        if e.response.status_code == 503:
-            raise gr.Error(f"{e.response.status_code}: Service Unavailable. The model might be loading or overloaded. Please try again later.")
-        elif e.response.status_code == 401:
-             raise gr.Error(f"{e.response.status_code}: Unauthorized. Please check your API Key.")
-        elif e.response.status_code == 400:
-             raise gr.Error(f"{e.response.status_code}: Bad Request. Please check your prompt and parameters. Details: {e.response.text[:200]}") # Show first 200 chars of error
-        else:
-            raise gr.Error(f"API Error: {e.response.status_code}. Details: {e.response.text[:200]}")
-    except requests.exceptions.RequestException as e: # Catch other network errors
-        raise gr.Error(f"A network error occurred: {e}")
-
-
+    response = requests.post(api_url, headers=headers, json=payload, timeout=timeout)
+    if response.status_code != 200:
+        print(f"Error: Failed to get image. Response status: {response.status_code}")
+        print(f"Response content: {response.text}")
+        if response.status_code == 503:
+            raise gr.Error(f"{response.status_code} : The model is being loaded")
+        raise gr.Error(f"{response.status_code}")
+    
     try:
         image_bytes = response.content
         image = Image.open(io.BytesIO(image_bytes))
-        print(f'\033[1mGeneration {key} completed!\033[0m ({augmented_prompt})')
+        print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
 
         # Save the image to a file and return the file path and seed
-        os.makedirs("outputs", exist_ok=True) # Ensure output directory exists
-        output_path = f"./outputs/output_{key}_{current_seed}.png" # Include seed in filename for uniqueness
+        output_path = f"./output_{key}.png"
         image.save(output_path)
         
-        return output_path, current_seed
+        return output_path, seed
     except Exception as e:
-        print(f"Error processing image response: {e}")
-        print(f"Response content that caused error: {response.content[:500]}") # Log first 500 bytes
-        raise gr.Error(f"Failed to process the image from API. The API might have returned an unexpected response. Details: {str(e)}")
-
+        print(f"Error when trying to open the image: {e}")
+        return None, None
 
 css = """
 #app-container {
-    max-width: 700px; /* Slightly wider for better layout */
+    max-width: 600px;
     margin-left: auto;
     margin-right: auto;
 }
@@ -140,110 +86,51 @@ css = """
     display: flex;
     align-items: center;
     justify-content: center;
-    margin-bottom: 10px; /* Add some space below title */
 }
 #title-icon {
-    width: 32px; 
+    width: 32px; /* Adjust the width of the icon as needed */
     height: auto;
-    margin-right: 10px; 
+    margin-right: 10px; /* Space between icon and title */
 }
 #title-text {
-    font-size: 24px; 
+    font-size: 24px; /* Adjust font size as needed */
     font-weight: bold;
 }
-.gr-box { /* Ensure accordion and other boxes have some padding */
-    padding: 10px;
-}
 """
 
 with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
     gr.HTML("""
-        <div style="text-align: center; margin-bottom: 20px;">
+        <center>
             <div id="title-container">
-                <img id="title-icon" src="file/icon.jpg" alt="Icon"> <!-- Use file/ prefix for local files in Gradio -->
+                <img id="title-icon" src="icon.jpg" alt="Icon">
                 <h1 id="title-text">FLUX Capacitor</h1>
             </div>
-            <p>Generate images using FLUX models. Provide your API key or ensure HF_READ_TOKEN is set.</p>
-        </div>
+        </center>
     """)
 
     with gr.Column(elem_id="app-container"):
         with gr.Row():
-            with gr.Column(scale=3): # Give more space to prompt
-                text_prompt = gr.Textbox(
-                    label="Prompt",
-                    placeholder="Enter your prompt here (Russian will be auto-translated)",
-                    lines=3, # Increased lines for prompt
-                    elem_id="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=2, # Increased lines for negative prompt
-                    elem_id="negative-prompt-text-input"
-                )
-            with gr.Column(scale=2): # Settings column
-                 huggingface_api_key = gr.Textbox(
-                    label="Hugging Face API Key (optional)",
-                    placeholder="Uses HF_READ_TOKEN env var if empty",
-                    type="password",
-                    elem_id="api-key"
-                )
-                 use_dev = gr.Checkbox(label="Use Dev API (FLUX.1-dev)", value=False, elem_id="use-dev-checkbox")
-
-
-        with gr.Accordion("Advanced Generation Settings", open=False):
-            with gr.Row():
-                steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
-                cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=0.5) # Allow 0.5 steps
-            with gr.Row():
-                # Sampler is not currently used in the payload. If your API supports it, add it to the payload.
-                sampler_method = gr.Radio(
-                    label="Sampling method (Note: Not sent to API)",
-                    value="DPM++ 2M Karras",
-                    choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"],
-                    # info="This setting is currently for UI only and not passed to the backend API."
-                )
-                strength = gr.Slider(label="Strength (e.g., for img2img)", value=0.7, minimum=0, maximum=1, step=0.01) # Finer steps
-            seed = gr.Slider(label="Seed (-1 for random)", value=-1, minimum=-1, maximum=2147483647, step=1) # Max 32-bit signed int
+            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")
+                        steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
+                        cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
+                        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
+                        strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
+                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
+                        huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key")
+                        use_dev = gr.Checkbox(label="Use Dev API", value=False, elem_id="use-dev-checkbox")
 
         with gr.Row():
-            text_button = gr.Button("Generate Image", variant='primary', elem_id="gen-button", scale=1)
-        
-        gr.Markdown("### Output")
+            text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
         with gr.Row():
-            image_output = gr.Image(type="filepath", label="Generated Image", elem_id="gallery") # Use filepath for saved images
-            seed_output = gr.Textbox(label="Seed Used", interactive=False, elem_id="seed-output") # interactive=False as it's an output
+            image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
+            seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
         
-        # Ensure the order of inputs matches the function signature of query
-        text_button.click(
-            query,
-            inputs=[
-                text_prompt,
-                negative_prompt, # This is passed as `negative_prompt_text`
-                steps,
-                cfg,
-                sampler_method, # Passed as `sampler`
-                seed,
-                strength,
-                huggingface_api_key, # Passed as `huggingface_api_key_ui`
-                use_dev
-            ],
-            outputs=[image_output, seed_output]
-        )
-
-# To run this:
-# 1. Make sure 'gradio', 'requests', 'Pillow', 'deep_translator' are installed:
-#    pip install gradio requests Pillow deep_translator
-# 2. Optionally, set the HF_READ_TOKEN environment variable:
-#    export HF_READ_TOKEN="your_hf_api_token_here" (Linux/macOS)
-#    set HF_READ_TOKEN="your_hf_api_token_here" (Windows CMD)
-#    $env:HF_READ_TOKEN="your_hf_api_token_here" (Windows PowerShell)
-# 3. Run the script: python your_script_name.py
-
-if __name__ == "__main__":
-    # For local Gradio image serving, Gradio needs to know where the 'icon.jpg' is.
-    # If it's in the same directory, 'file/icon.jpg' should work.
-    # If you have an 'assets' folder, it would be 'file/assets/icon.jpg'.
-    app.launch(show_api=True, share=False)
+        # Adjust the click function to include the API key and use_dev as inputs
+        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev], outputs=[image_output, seed_output])
+
+app.launch(show_api=True, share=False)