Bump version: 0.3.11 → 0.3.12

fix(openrouter): handle rate limit errors with OpenWebUI fallback

When OpenRouter returns a 429 error due to rate limiting, the application now attempts to fall back to using an OpenWebUI model instead of returning a default prompt. This provides better resilience when external API limits are exceeded while maintaining functionality through local models.

The changes include:
- Adding RateLimitError import from openai
- Implementing fallback logic in create_prompt_on_openrouter function
- Using OpenWebUI as secondary source for prompts when rate limiting occurs
- Proper error handling and logging for both primary and fallback scenarios

This change improves the robustness of prompt generation by ensuring that users receive generated content even when external services are temporarily unavailable due to rate limits. The fallback mechanism prioritizes configured local models if available, with a final default prompt as backup.

The implementation follows the existing pattern of using random selection from configured OpenWebUI models and includes comprehensive error handling for both primary and fallback operations. This ensures that all failure modes are gracefully handled while maintaining backward compatibility.

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.2.15"
+current_version = "0.3.12"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 replace = "{new_version}"

.gitignore

@@ -11,3 +11,5 @@ publish.sh
 test.py
 .vscode/launch.json
 favourites.json
+.vscode/launch.json
+venv/*

.vscode/launch.json

@@ -8,7 +8,7 @@
             "name": "Python Debugger: Current File",
             "type": "debugpy",
             "request": "launch",
-            "program": "${file}",
+            "program": "ai_frame_image_server.py",
             "console": "integratedTerminal",
             "justMyCode": false,
             "env": {"SECRET_KEY":"dkdkdk"}

Dockerfile

@@ -4,7 +4,7 @@ FROM python:3.11-slim
 # Set the working directory in the container
 WORKDIR /app
 # Set version label
-ARG VERSION="0.2.15"
+ARG VERSION="0.3.12"
 LABEL version=$VERSION
 
 # Copy project files into the container

ai_frame_image_server.py

@@ -4,6 +4,7 @@ import os
 
 from routes import (
     auth_routes,
+    favourites_routes,
     gallery_routes,
     image_routes,
     index_routes,
@@ -17,6 +18,13 @@ user_config = load_config()
 app = Flask(__name__)
 app.secret_key = os.environ.get("SECRET_KEY")
 
+# Make version available to all templates
+from libs.generic import get_current_version
+@app.context_processor
+def inject_version():
+    version = get_current_version()
+    return dict(version=version)
+
 # Inject config into routes that need it
 create_routes.init_app(user_config)
 auth_routes.init_app(user_config)
@@ -24,6 +32,7 @@ auth_routes.init_app(user_config)
 # Register blueprints
 app.register_blueprint(index_routes.bp)
 app.register_blueprint(auth_routes.bp)
+app.register_blueprint(favourites_routes.bp)
 app.register_blueprint(gallery_routes.bp)
 app.register_blueprint(image_routes.bp)
 app.register_blueprint(job_routes.bp)
@@ -37,7 +46,16 @@ from libs.comfyui import create_image
 
 def scheduled_task():
     print(f"Executing scheduled task at {time.strftime('%Y-%m-%d %H:%M:%S')}")
-    create_image(None)
+    # Generate a random prompt using either OpenWebUI or OpenRouter
+    from libs.generic import create_prompt_with_random_model
+    prompt = create_prompt_with_random_model("Generate a random detailed prompt for stable diffusion.")
+    if prompt:
+        # Select a random model
+        import random
+        model = "Random Image Model"
+        create_image(prompt, model)
+    else:
+        print("Failed to generate a prompt for the scheduled task.")
 
 if user_config["frame"]["auto_regen"] == "True":
     if os.environ.get("WERKZEUG_RUN_MAIN") == "true":

libs/comfyui.py

@@ -15,7 +15,7 @@ from tenacity import (
 import nest_asyncio
 from libs.generic import rename_image, load_config, save_prompt
 from libs.create_thumbnail import generate_thumbnail
-from libs.ollama import create_prompt_on_openwebui
+from libs.openwebui import create_prompt_on_openwebui
 nest_asyncio.apply()
 
 logging.basicConfig(level=logging.INFO)
@@ -32,9 +32,17 @@ def get_available_models() -> list:
     response = requests.get(url)
     if response.status_code == 200:
         data = response.json()
-        general = data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {}).get("ckpt_name", [])[0]
-        flux = data.get("UnetLoaderGGUF", {}).get("input", {}).get("required", {}).get("unet_name", [])[0]
-        return general + flux
+        # Get SDXL models from CheckpointLoaderSimple
+        general = data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {}).get("ckpt_name", [[]])[0]
+        # Get FLUX models from UnetLoaderGGUF
+        flux = data.get("UnetLoaderGGUF", {}).get("input", {}).get("required", {}).get("unet_name", [[]])[0]
+        # Combine both lists, handling cases where one might be missing
+        all_models = []
+        if isinstance(general, list):
+            all_models.extend(general)
+        if isinstance(flux, list):
+            all_models.extend(flux)
+        return all_models
     else:
         print(f"Failed to fetch models: {response.status_code}")
         return []
@@ -122,30 +130,61 @@ def generate_image(
 def select_model(model: str) -> tuple[str, str]:
     use_flux = json.loads(user_config["comfyui"].get("FLUX", "false").lower())
     only_flux = json.loads(user_config["comfyui"].get("ONLY_FLUX", "false").lower())
+    use_qwen = json.loads(user_config["comfyui"].get("Qwen", "false").lower())
 
-    if model == "Random":
-        selected_workflow = "FLUX" if (use_flux and (only_flux or random.choice([True, False]))) else "SDXL"
+    if model == "Random Image Model":
+        # Create a list of available workflows based on configuration
+        available_workflows = []
+        if not only_flux:
+            available_workflows.append("SDXL")
+        if use_flux:
+            available_workflows.append("FLUX")
+        if use_qwen:
+            available_workflows.append("Qwen")
+        
+        # If no workflows are available, default to SDXL
+        if not available_workflows:
+            available_workflows.append("SDXL")
+        
+        # Randomly select a workflow
+        selected_workflow = random.choice(available_workflows)
     elif "flux" in model.lower():
         selected_workflow = "FLUX"
+    elif "qwen" in model.lower():
+        selected_workflow = "Qwen"
     else:
         selected_workflow = "SDXL"
 
-    if model == "Random":
+    if model == "Random Image Model":
         if selected_workflow == "FLUX":
             valid_models = user_config["comfyui:flux"]["models"].split(",")
+        elif selected_workflow == "Qwen":
+            valid_models = user_config["comfyui:qwen"]["models"].split(",")
         else:  # SDXL
             available_model_list = user_config["comfyui"]["models"].split(",")
             valid_models = list(set(get_available_models()) & set(available_model_list))
+            # If no valid models found, fall back to configured models
+            if not valid_models:
+                valid_models = available_model_list
+        # Ensure we have at least one model to choose from
+        if not valid_models:
+            # Fallback to a default model
+            valid_models = ["zavychromaxl_v100.safetensors"]
         model = random.choice(valid_models)
 
     return selected_workflow, model
 
 
-def create_image(prompt: str | None = None, model: str = "Random") -> None:
+def create_image(prompt: str | None = None, model: str = "Random Image Model") -> None:
     """Generate an image with a chosen workflow (Random, FLUX*, or SDXL*)."""
 
     if prompt is None:
-        prompt = create_prompt_on_openwebui(user_config["comfyui"]["prompt"])
+        # Generate a random prompt using either OpenWebUI or OpenRouter
+        from libs.generic import create_prompt_with_random_model
+        prompt = create_prompt_with_random_model("Generate a random detailed prompt for stable diffusion.")
+        if not prompt:
+            logging.error("Failed to generate a prompt.")
+            return
 
     if not prompt:
         logging.error("No prompt generated.")
@@ -153,22 +192,101 @@ def create_image(prompt: str | None = None, model: str = "Random") -> None:
 
     save_prompt(prompt)
     selected_workflow, model = select_model(model)
-
+    
     if selected_workflow == "FLUX":
         generate_image(
             file_name="image",
             comfy_prompt=prompt,
             workflow_path="./workflow_flux.json",
-            prompt_node="Positive Prompt T5",
-            seed_node="Seed",
-            seed_param="seed",
-            save_node="CivitAI Image Saver",
-            save_param="filename",
-            model_node="UnetLoaderGGUFAdvancedDisTorchMultiGPU",
+            prompt_node="CLIP Text Encode (Positive Prompt)",
+            seed_node="RandomNoise",
+            seed_param="noise_seed",
+            save_node="Save Image",
+            save_param="filename_prefix",
+            model_node="UnetLoaderGGUFDisTorchMultiGPU",
             model_param="unet_name",
             model=model
         )
+    elif selected_workflow == "Qwen":
+        generate_image(
+            file_name="image",
+            comfy_prompt=prompt,
+            workflow_path="./workflow_qwen.json",
+            prompt_node="Positive",
+            seed_node="KSampler",
+            seed_param="seed",
+            save_node="Save Image",
+            save_param="filename_prefix",
+            model_node="Load Checkpoint",
+            model_param="ckpt_name",
+            model=model
+        )
     else:  # SDXL
         generate_image("image", comfy_prompt=prompt, model=model)
 
     logging.info(f"{selected_workflow} generation started with prompt: {prompt}")
+
+def get_queue_count() -> int:
+    """Fetches the current queue count from ComfyUI (pending + running jobs)."""
+    url = user_config["comfyui"]["comfyui_url"] + "/queue"
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        pending = len(data.get("queue_pending", []))
+        running = len(data.get("queue_running", []))
+        return pending + running
+    except Exception as e:
+        logging.error(f"Error fetching queue count: {e}")
+        return 0
+
+def get_queue_details() -> list:
+    """Fetches detailed queue information including model names and prompts."""
+    url = user_config["comfyui"]["comfyui_url"] + "/queue"
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        jobs = []
+        for job_list in [data.get("queue_running", []), data.get("queue_pending", [])]:
+            for job in job_list:
+                # Extract prompt data (format: [priority, time, prompt])
+                prompt_data = job[2]
+                model = "Unknown"
+                prompt = "No prompt"
+                
+                # Find model loader node (works for SDXL/FLUX/Qwen workflows)
+                for node in prompt_data.values():
+                    if node.get("class_type") in ["CheckpointLoaderSimple", "UnetLoaderGGUFAdvancedDisTorchMultiGPU"]:
+                        model = node["inputs"].get("ckpt_name", "Unknown")
+                        break
+                
+                # Find prompt node using class_type pattern and title matching
+                for node in prompt_data.values():
+                    class_type = node.get("class_type", "")
+                    if "CLIPTextEncode" in class_type and "text" in node["inputs"]:
+                        meta = node.get('_meta', {})
+                        title = meta.get('title', '').lower()
+                        if 'positive' in title or 'prompt' in title:
+                            prompt = node["inputs"]["text"]
+                            break
+                
+                jobs.append({
+                    "id": job[0],
+                    "model": model.split(".")[0] if model != "Unknown" else model,
+                    "prompt": prompt
+                })
+        return jobs
+    except Exception as e:
+        logging.error(f"Error fetching queue details: {e}")
+        return []
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        pending = len(data.get("queue_pending", []))
+        running = len(data.get("queue_running", []))
+        return pending + running
+    except Exception as e:
+        logging.error(f"Error fetching queue count: {e}")
+        return 0

libs/generic.py

@@ -4,6 +4,7 @@ import logging
 import sys
 import time
 import os
+import random
 from PIL import Image
 import nest_asyncio
 import json
@@ -83,8 +84,8 @@ def get_details_from_png(path):
             try:
                 # Flux workflow
                 data = json.loads(img.info["prompt"])
-                prompt = data['44']['inputs']['text']
-                model = data['35']['inputs']['unet_name'].split(".")[0]
+                prompt = data['6']['inputs']['text']
+                model = data['38']['inputs']['unet_name'].split(".")[0]
             except KeyError:
                 # SDXL workflow
                 data = json.loads(img.info["prompt"])
@@ -109,14 +110,31 @@ def get_current_version():
         return version
     except subprocess.CalledProcessError as e:
         print("Error running bump-my-version:", e)
-        return None
+        return "unknown"
 
 def load_models_from_config():
-    flux_models = load_config()["comfyui:flux"]["models"].split(",")
-    sdxl_models = load_config()["comfyui"]["models"].split(",")
+    config = load_config()
+    
+    # Only load FLUX models if FLUX feature is enabled
+    use_flux = config["comfyui"].get("flux", "False").lower() == "true"
+    if use_flux and "comfyui:flux" in config and "models" in config["comfyui:flux"]:
+        flux_models = config["comfyui:flux"]["models"].split(",")
+    else:
+        flux_models = []
+    
+    sdxl_models = config["comfyui"]["models"].split(",")
+    
+    # Only load Qwen models if Qwen feature is enabled
+    use_qwen = config["comfyui"].get("qwen", "False").lower() == "true"
+    if use_qwen and "comfyui:qwen" in config and "models" in config["comfyui:qwen"]:
+        qwen_models = config["comfyui:qwen"]["models"].split(",")
+    else:
+        qwen_models = []
+    
     sorted_flux_models = sorted(flux_models, key=str.lower)
     sorted_sdxl_models = sorted(sdxl_models, key=str.lower)
-    return sorted_sdxl_models, sorted_flux_models
+    sorted_qwen_models = sorted(qwen_models, key=str.lower)
+    return sorted_sdxl_models, sorted_flux_models, sorted_qwen_models
 
 
 def load_topics_from_config():
@@ -124,5 +142,104 @@ def load_topics_from_config():
     sorted_topics = sorted(topics, key=str.lower)
     return sorted_topics
 
+def load_openrouter_models_from_config():
+    config = load_config()
+    if config["openrouter"].get("enabled", "False").lower() == "true":
+        models = config["openrouter"]["models"].split(",")
+        return sorted([model.strip() for model in models if model.strip()], key=str.lower)
+    return []
+
+def load_openwebui_models_from_config():
+    config = load_config()
+    if "openwebui" in config and "models" in config["openwebui"]:
+        models = config["openwebui"]["models"].split(",")
+        return sorted([model.strip() for model in models if model.strip()], key=str.lower)
+    return []
+
+def load_prompt_models_from_config():
+    """Load and return a list of available prompt generation models (both OpenWebUI and OpenRouter)."""
+    config = load_config()
+    prompt_models = []
+    
+    # Add OpenWebUI models if configured
+    if "openwebui" in config and "models" in config["openwebui"]:
+        openwebui_models = config["openwebui"]["models"].split(",")
+        prompt_models.extend([("openwebui", model.strip()) for model in openwebui_models if model.strip()])
+    
+    # Add OpenRouter models if enabled and configured
+    if config["openrouter"].get("enabled", "False").lower() == "true" and "models" in config["openrouter"]:
+        openrouter_models = config["openrouter"]["models"].split(",")
+        prompt_models.extend([("openrouter", model.strip()) for model in openrouter_models if model.strip()])
+    
+    return prompt_models
+
+
+def create_prompt_with_random_model(base_prompt: str, topic: str = "random"):
+    """Create a prompt using a randomly selected model from OpenWebUI or OpenRouter.
+    
+    If OpenWebUI fails, it will retry once. If it fails again, it will fallback to OpenRouter.
+    """
+    prompt_models = load_prompt_models_from_config()
+    
+    if not prompt_models:
+        logging.warning("No prompt generation models configured.")
+        return None
+    
+    # Randomly select a model
+    service, model = random.choice(prompt_models)
+    
+    # Import here to avoid circular imports
+    from libs.openwebui import create_prompt_on_openwebui
+    from libs.openrouter import create_prompt_on_openrouter
+    
+    if service == "openwebui":
+        try:
+            # First attempt with OpenWebUI
+            logging.info(f"Attempting to generate prompt with OpenWebUI using model: {model}")
+            result = create_prompt_on_openwebui(base_prompt, topic, model)
+            if result:
+                return result
+            
+            # If first attempt returns None, try again
+            logging.warning("First OpenWebUI attempt failed. Retrying...")
+            result = create_prompt_on_openwebui(base_prompt, topic, model)
+            if result:
+                return result
+            
+            # If second attempt fails, fallback to OpenRouter
+            logging.warning("Second OpenWebUI attempt failed. Falling back to OpenRouter...")
+            openrouter_models = [m for m in prompt_models if m[0] == "openrouter"]
+            if openrouter_models:
+                _, openrouter_model = random.choice(openrouter_models)
+                return create_prompt_on_openrouter(base_prompt, topic, openrouter_model)
+            else:
+                logging.error("No OpenRouter models configured for fallback.")
+                return "A colorful abstract composition"  # Default fallback prompt
+                
+        except Exception as e:
+            logging.error(f"Error with OpenWebUI: {e}")
+            # Fallback to OpenRouter on exception
+            logging.warning("OpenWebUI exception. Falling back to OpenRouter...")
+            openrouter_models = [m for m in prompt_models if m[0] == "openrouter"]
+            if openrouter_models:
+                _, openrouter_model = random.choice(openrouter_models)
+                try:
+                    return create_prompt_on_openrouter(base_prompt, topic, openrouter_model)
+                except Exception as e2:
+                    logging.error(f"Error with OpenRouter fallback: {e2}")
+                    return "A colorful abstract composition"  # Default fallback prompt
+            else:
+                logging.error("No OpenRouter models configured for fallback.")
+                return "A colorful abstract composition"  # Default fallback prompt
+    
+    elif service == "openrouter":
+        try:
+            # Use OpenRouter
+            return create_prompt_on_openrouter(base_prompt, topic, model)
+        except Exception as e:
+            logging.error(f"Error with OpenRouter: {e}")
+            return "A colorful abstract composition"  # Default fallback prompt
+    
+
 user_config = load_config()
 output_folder = user_config["comfyui"]["output_dir"]

libs/ollama.py

@@ -1,84 +0,0 @@
-import random
-import logging
-import litellm
-import nest_asyncio
-from libs.generic import load_recent_prompts, load_config
-import re
-nest_asyncio.apply()
-
-logging.basicConfig(level=logging.INFO)
-
-LOG_FILE = "./prompts_log.jsonl"
-
-user_config = load_config()
-output_folder = user_config["comfyui"]["output_dir"]
-
-def create_prompt_on_openwebui(prompt: str, topic: str = "random") -> str:
-    """Sends prompt to OpenWebui and returns the generated response."""
-    topic_instruction = ""
-    selected_topic = ""
-    # Unique list of recent prompts
-    recent_prompts = list(set(load_recent_prompts()))
-    if topic == "random":
-        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
-        selected_topic = random.choice(topics)
-    elif topic != "":
-        selected_topic = topic
-    else:
-        # Decide on whether to include a topic (e.g., 30% chance to include)
-        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
-        if random.random() < 0.3 and topics:
-            selected_topic = random.choice(topics)
-    if selected_topic != "":
-        topic_instruction = f" Incorporate the theme of '{selected_topic}' into the new prompt."
-
-    user_content = (
-        "Can you generate me a really random image idea, Do not exceed 10 words. Use clear language, not poetic metaphors.”"
-        + topic_instruction
-        + "Avoid prompts similar to the following:"
-        + "\n".join(f"{i+1}. {p}" for i, p in enumerate(recent_prompts))
-    )
-
-
-    model = random.choice(user_config["openwebui"]["models"].split(","))
-    response = litellm.completion(
-        api_base=user_config["openwebui"]["base_url"],
-        model="openai/" + model,
-        messages=[
-            {
-                "role": "system",
-                "content": (
-                    "You are a prompt generator for Stable Diffusion. "
-                    "Generate a detailed and imaginative prompt with a strong visual theme. "
-                    "Focus on lighting, atmosphere, and artistic style. "
-                    "Keep the prompt concise, no extra commentary or formatting."
-                ),
-            },
-            {
-                "role": "user",
-                "content": user_content,
-            },
-        ],
-        api_key=user_config["openwebui"]["api_key"],
-    )
-
-    prompt = response["choices"][0]["message"]["content"].strip('"')
-    # response = litellm.completion(
-    #     api_base=user_config["openwebui"]["base_url"],
-    #     model="openai/brxce/stable-diffusion-prompt-generator:latest",
-    #     messages=[
-    #         {
-    #             "role": "user",
-    #             "content": prompt,
-    #         },
-    #     ],
-    #     api_key=user_config["openwebui"]["api_key"],
-    # )
-    # prompt = response["choices"][0]["message"]["content"].strip('"')
-    match = re.search(r'"([^"]+)"', prompt)
-    if not match:
-        match = re.search(r":\s*\n*\s*(.+)", prompt) 
-    if match:
-        prompt = match.group(1)
-    logging.debug(prompt)
-    return prompt

libs/openrouter.py

@@ -0,0 +1,110 @@
+import random
+import logging
+from openai import OpenAI, RateLimitError
+import nest_asyncio
+from libs.generic import load_recent_prompts, load_config
+from libs.openwebui import create_prompt_on_openwebui
+import re
+nest_asyncio.apply()
+
+logging.basicConfig(level=logging.INFO)
+
+LOG_FILE = "./prompts_log.jsonl"
+
+user_config = load_config()
+output_folder = user_config["comfyui"]["output_dir"]
+
+def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str = None) -> str:
+    """Sends prompt to OpenRouter and returns the generated response."""
+    # Check if OpenRouter is enabled
+    if user_config["openrouter"].get("enabled", "False").lower() != "true":
+        logging.warning("OpenRouter is not enabled in the configuration.")
+        return ""
+    
+    topic_instruction = ""
+    selected_topic = ""
+    # Unique list of recent prompts
+    recent_prompts = list(set(load_recent_prompts()))
+    if topic == "random":
+        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
+        selected_topic = random.choice(topics) if topics else ""
+    elif topic != "":
+        selected_topic = topic
+    else:
+        # Decide on whether to include a topic (e.g., 30% chance to include)
+        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
+        if random.random() < 0.3 and topics:
+            selected_topic = random.choice(topics)
+    if selected_topic != "":
+        topic_instruction = f" Incorporate the theme of '{selected_topic}' into the new prompt."
+
+    user_content = (
+        "Can you generate me a really random image idea, Do not exceed 10 words. Use clear language, not poetic metaphors."
+        + topic_instruction
+        + "Avoid prompts similar to the following:"
+        + "\n".join(f"{i+1}. {p}" for i, p in enumerate(recent_prompts))
+    )
+
+    # Use the specified model or select a random model from the configured OpenRouter models
+    if model:
+        # Use the specified model
+        model = model
+    else:
+        # Select a random model from the configured OpenRouter models
+        models = [m.strip() for m in user_config["openrouter"]["models"].split(",") if m.strip()]
+        if not models:
+            logging.error("No OpenRouter models configured.")
+            return ""
+        
+        model = random.choice(models)
+    
+    try:
+        client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=user_config["openrouter"]["api_key"],
+        )
+
+        completion = client.chat.completions.create(
+            model=model,
+            messages=[
+                {
+                    "role": "system",
+                    "content": (
+                        "You are a prompt generator for Stable Diffusion. "
+                        "Generate a detailed and imaginative prompt with a strong visual theme. "
+                        "Focus on lighting, atmosphere, and artistic style. "
+                        "Keep the prompt concise, no extra commentary or formatting."
+                    ),
+                },
+                {
+                    "role": "user",
+                    "content": user_content,
+                },
+            ]
+        )
+
+        prompt = completion.choices[0].message.content.strip('"')
+        match = re.search(r'"([^"]+)"', prompt)
+        if not match:
+            match = re.search(r":\s*\n*\s*(.+)", prompt)
+        if match:
+            prompt = match.group(1)
+        logging.debug(prompt)
+        return prompt
+    except RateLimitError as e:
+        logging.warning(f"OpenRouter rate limit exceeded (429): {e}. Falling back to local OpenWebUI model.")
+        # Try to use OpenWebUI as fallback
+        openwebui_models = [m.strip() for m in user_config["openwebui"]["models"].split(",") if m.strip()] if "openwebui" in user_config and "models" in user_config["openwebui"] else []
+        if openwebui_models:
+            selected_model = random.choice(openwebui_models)
+            try:
+                return create_prompt_on_openwebui(user_content, topic, selected_model)
+            except Exception as e2:
+                logging.error(f"OpenWebUI fallback also failed: {e2}")
+                return "A colorful abstract composition"  # Final fallback
+        else:
+            logging.error("No OpenWebUI models configured for fallback.")
+            return "A colorful abstract composition"  # Final fallback
+    except Exception as e:
+        logging.error(f"Error generating prompt with OpenRouter: {e}")
+        return ""

libs/openwebui.py

@@ -0,0 +1,99 @@
+import random
+import logging
+import nest_asyncio
+from libs.generic import load_recent_prompts, load_config
+import re
+from openwebui_chat_client import OpenWebUIClient
+from datetime import datetime
+
+nest_asyncio.apply()
+
+logging.basicConfig(level=logging.INFO)
+
+LOG_FILE = "./prompts_log.jsonl"
+
+user_config = load_config()
+output_folder = user_config["comfyui"]["output_dir"]
+
+def create_prompt_on_openwebui(prompt: str, topic: str = "random", model: str = None) -> str:
+    """Sends prompt to OpenWebui and returns the generated response."""
+    topic_instruction = ""
+    selected_topic = ""
+    # Unique list of recent prompts
+    recent_prompts = list(set(load_recent_prompts()))
+    if topic == "random":
+        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
+        selected_topic = random.choice(topics)
+    elif topic != "":
+        selected_topic = topic
+    else:
+        # Decide on whether to include a topic (e.g., 30% chance to include)
+        topics = [t.strip() for t in user_config["comfyui"]["topics"].split(",") if t.strip()]
+        if random.random() < 0.3 and topics:
+            selected_topic = random.choice(topics)
+    if selected_topic != "":
+        topic_instruction = f" Incorporate the theme of '{selected_topic}' into the new prompt."
+
+    user_content = (
+        "Can you generate me a really random image idea, Do not exceed 10 words. Use clear language, not poetic metaphors."
+        + topic_instruction
+        + "Avoid prompts similar to the following:"
+        + "\n".join(f"{i+1}. {p}" for i, p in enumerate(recent_prompts))
+    )
+
+    if model:
+        # Use the specified model
+        model = model
+    else:
+        # Select a random model
+        model = random.choice(user_config["openwebui"]["models"].split(",")).strip()
+
+    # Create OpenWebUI client
+    client = OpenWebUIClient(
+        base_url=user_config["openwebui"]["base_url"],
+        token=user_config["openwebui"]["api_key"],
+        default_model_id=model
+    )
+
+    # Prepare messages for the chat
+    messages = [
+        {
+            "role": "system",
+            "content": (
+                "You are a prompt generator for Stable Diffusion. "
+                "Generate a detailed and imaginative prompt with a strong visual theme. "
+                "Focus on lighting, atmosphere, and artistic style. "
+                "Keep the prompt concise, no extra commentary or formatting."
+            ),
+        },
+        {
+            "role": "user",
+            "content": user_content,
+        },
+    ]
+
+    # Send the chat request
+    try:
+        result = client.chat(
+            question=user_content,
+            chat_title=datetime.now().strftime("%Y-%m-%d %H:%M"),
+            folder_name="ai-frame-image-server"
+        )
+
+        if result:
+            prompt = result["response"].strip('"')
+        else:
+            # Return None if the request fails
+            logging.warning(f"OpenWebUI request failed with model: {model}")
+            return None
+    except Exception as e:
+        logging.error(f"Error in OpenWebUI request with model {model}: {e}")
+        return None
+
+    match = re.search(r'"([^"]+)"', prompt)
+    if not match:
+        match = re.search(r":\s*\n*\s*(.+)", prompt) 
+    if match:
+        prompt = match.group(1)
+    logging.debug(prompt)
+    return prompt

routes/__init__.py

@@ -1,8 +1,9 @@
-from . import auth_routes, create_routes, gallery_routes, image_routes, index_routes, job_routes, settings_routes
+from . import auth_routes, create_routes, favourites_routes, gallery_routes, image_routes, index_routes, job_routes, settings_routes
 
 __all__ = [
     "auth_routes",
     "create_routes",
+    "favourites_routes",
     "gallery_routes",
     "image_routes",
     "index_routes",

routes/create_routes.py

@@ -1,8 +1,8 @@
 from flask import Blueprint, request, render_template, redirect, url_for, session
 import threading
-from libs.comfyui import create_image, select_model, get_available_models
-from libs.ollama import create_prompt_on_openwebui
-from libs.generic import load_models_from_config, load_topics_from_config
+from libs.comfyui import create_image, select_model, get_available_models, get_queue_count
+from libs.openwebui import create_prompt_on_openwebui
+from libs.generic import load_models_from_config, load_topics_from_config, load_openrouter_models_from_config, load_openwebui_models_from_config, create_prompt_with_random_model
 import os
 
 bp = Blueprint("create_routes", __name__)
@@ -12,28 +12,73 @@ user_config = None  # will be set in init_app
 def create():
     if request.method == "POST":
         prompt = request.form.get("prompt")
-        selected_workflow, model = select_model(request.form.get("model") or "Random")
+        image_model = request.form.get("model") or "Random Image Model"
+        selected_workflow, model = select_model(image_model)
         topic = request.form.get("topic")
 
         if not prompt:
-            prompt = create_prompt_on_openwebui(user_config["comfyui"]["prompt"], topic)
+            # Get the prompt model from the form data
+            prompt_model = request.form.get("prompt_model") or ""
+            if prompt_model and prompt_model != "Random Prompt Model":
+                # Use the specified prompt model
+                service, service_model = prompt_model.split(":", 1) if ":" in prompt_model else (prompt_model, "")
+                if service == "openwebui":
+                    from libs.openwebui import create_prompt_on_openwebui
+                    prompt = create_prompt_on_openwebui(user_config["comfyui"]["prompt"], topic, service_model)
+                elif service == "openrouter":
+                    from libs.openrouter import create_prompt_on_openrouter
+                    prompt = create_prompt_on_openrouter(user_config["comfyui"]["prompt"], topic, service_model)
+            else:
+                # Use a random prompt model
+                prompt = create_prompt_with_random_model(user_config["comfyui"]["prompt"], topic)
 
         threading.Thread(target=lambda: create_image(prompt, model)).start()
         return redirect(url_for("create_routes.image_queued", prompt=prompt, model=model.split(".")[0]))
 
-    return render_template("create_image.html", models=load_models_from_config()[0]+load_models_from_config()[1], topics=load_topics_from_config())
+    # Load all models (SDXL, FLUX, and Qwen)
+    sdxl_models, flux_models, qwen_models = load_models_from_config()
+    openwebui_models = load_openwebui_models_from_config()
+    openrouter_models = load_openrouter_models_from_config()
+    
+    queue_count = get_queue_count()
+    return render_template("create_image.html",
+                         sdxx_models=sdxl_models,
+                         flux_models=flux_models,
+                         qwen_models=qwen_models,
+                         openwebui_models=openwebui_models,
+                         openrouter_models=openrouter_models,
+                         topics=load_topics_from_config(),
+                         queue_count=queue_count)
 
 @bp.route("/image_queued")
 def image_queued():
     prompt = request.args.get("prompt", "No prompt provided.")
-    model = request.args.get("model", "No model selected.").split(".")[0]
+    model = request.args.get("model", "No model selected.")
+    if model == "Random Image Model":
+        model = "Random"
+    else:
+        model = model.split(".")[0]
     return render_template("image_queued.html", prompt=prompt, model=model)
 
 @bp.route("/create_image", methods=["GET"])
 def create_image_page():
     if user_config["frame"]["create_requires_auth"] == "True" and not session.get("authenticated"):
         return redirect(url_for("auth_routes.login", next=request.path))
-    return render_template("create_image.html", models=load_models_from_config()[0]+load_models_from_config()[1], topics=load_topics_from_config())
+    
+    # Load all models (SDXL, FLUX, and Qwen)
+    sdxl_models, flux_models, qwen_models = load_models_from_config()
+    openwebui_models = load_openwebui_models_from_config()
+    openrouter_models = load_openrouter_models_from_config()
+    
+    queue_count = get_queue_count()
+    return render_template("create_image.html",
+                         sdxl_models=sdxl_models,
+                         flux_models=flux_models,
+                         qwen_models=qwen_models,
+                         openwebui_models=openwebui_models,
+                         openrouter_models=openrouter_models,
+                         topics=load_topics_from_config(),
+                         queue_count=queue_count)
 
 
 def init_app(config):

routes/favourites_routes.py

@@ -0,0 +1,23 @@
+from flask import Blueprint, jsonify, send_file
+import os
+import json
+
+bp = Blueprint("favourites_routes", __name__)
+favourites_file = "./favourites.json"
+
+def get_favourites():
+    if not os.path.exists(favourites_file):
+        return []
+    with open(favourites_file, 'r') as f:
+        return json.load(f)
+
+@bp.route("/favourites", methods=["GET"])
+def favourites():
+    """
+    Route to return the favourites.json file
+    """
+    if os.path.exists(favourites_file):
+        return send_file(favourites_file, mimetype='application/json')
+    else:
+        # If the file doesn't exist, return an empty array as JSON
+        return jsonify([])

routes/index_routes.py

@@ -11,12 +11,10 @@ def index():
     image_filename = "./image.png"
     image_path = os.path.join(image_folder, image_filename)
     prompt = get_details_from_png(image_path)["p"]
-    version = get_current_version()
 
     return render_template(
         "index.html",
         image=image_filename,
         prompt=prompt,
         reload_interval=user_config["frame"]["reload_interval"],
-        version=version,
     )

routes/job_routes.py

@@ -1,8 +1,12 @@
-from flask import Blueprint
-from libs.comfyui import cancel_current_job
+from flask import Blueprint, jsonify
+from libs.comfyui import cancel_current_job, get_queue_details
 
 bp = Blueprint("job_routes", __name__)
 
 @bp.route("/cancel", methods=["GET"])
 def cancel_job():
     return cancel_current_job()
+
+@bp.route("/api/queue", methods=["GET"])
+def api_queue():
+    return jsonify(get_queue_details())

templates/base.html

@@ -12,7 +12,7 @@
 
     <!-- Version number at bottom right -->
     <div class="version">
-        <a href="{{ url_for('settings_route.config_editor') }}">v{{ version }}</a>
+        <a href="{{ url_for('settings_route.config_editor') }}">{% if version and version != 'unknown' %}v{{ version }}{% else %}v?.?.?{% endif %}</a>
     </div>
 
     {% block scripts %}{% endblock %}

templates/create_image.html

@@ -33,6 +33,28 @@
         align-items: center;
     }
 
+    .model-selection {
+        display: flex;
+        flex-wrap: wrap;
+        gap: 20px;
+        justify-content: center;
+        margin: 20px 0;
+        width: 100%;
+        max-width: 800px;
+    }
+
+    .model-group {
+        display: flex;
+        flex-direction: column;
+        align-items: flex-start;
+        gap: 5px;
+    }
+
+    .model-group label {
+        font-weight: bold;
+        color: #ddd;
+    }
+
     button,
     select {
         background: #333;
@@ -43,6 +65,7 @@
         font-size: 16px;
         cursor: pointer;
         transition: background 0.3s;
+        min-width: 150px;
     }
 
     button:hover,
@@ -50,6 +73,7 @@
         background: #555;
     }
 
+
     #spinner-overlay {
         position: fixed;
         inset: 0;
@@ -90,6 +114,15 @@
             width: 100%;
         }
 
+        .model-selection {
+            flex-direction: column;
+            align-items: stretch;
+        }
+
+        .model-group {
+            align-items: stretch;
+        }
+
         button,
         select {
             width: 100%;
@@ -99,44 +132,138 @@
             height: 150px;
         }
     }
+    .queue-dropdown {
+        position: absolute;
+        top: 100%;
+        right: 0;
+        background: #222;
+        border: 1px solid #444;
+        border-radius: 5px;
+        padding: 10px;
+        z-index: 1001;
+        display: none;
+        max-height: 300px;
+        overflow-y: auto;
+        width: 400px;
+    }
+
+    .queue-item {
+        margin-bottom: 5px;
+        padding: 5px;
+        border-bottom: 1px solid #333;
+    }
+
+    .queue-item:last-child {
+        border-bottom: none;
+    }
+
+    .queue-item .prompt {
+        font-size: 0.9em;
+        color: #aaa;
+        white-space: normal;
+        word-wrap: break-word;
+        position: relative;
+        cursor: pointer;
+    }
+    
+    .queue-item .prompt:hover::after {
+        content: "Model: " attr(data-model);
+        position: absolute;
+        bottom: 100%;
+        left: 0;
+        background: #333;
+        color: #00aaff;
+        padding: 4px 8px;
+        border-radius: 4px;
+        font-size: 0.8em;
+        white-space: nowrap;
+        z-index: 1002;
+        box-shadow: 0 2px 4px rgba(0,0,0,0.3);
+    }
 </style>
 {% endblock %}
 
 {% block content %}
+<div class="queue-container" style="position: fixed; top: 20px; right: 20px; z-index: 1000;">
+    <button id="queue-btn" style="background: #333; color: white; border: none; padding: 5px 10px; border-radius: 5px; cursor: pointer;">
+        Queue: <span id="queue-count">{{ queue_count | default(0) }}</span>
+    </button>
+    <div id="queue-dropdown" class="queue-dropdown">
+        <!-- Queue items will be populated here -->
+    </div>
+</div>
 <h1 style="margin-bottom: 20px;">Create An Image</h1>
 
 <textarea id="prompt-box" placeholder="Enter your custom prompt here..."></textarea>
 
 <div class="button-group">
     <button onclick="showSpinner(); location.href='/'">Back</button>
-
     <button onclick="sendPrompt()">Send Prompt</button>
-
     <button onclick="randomPrompt()">Random Prompt</button>
+</div>
 
-    <select id="model-select">
-        <option value="" selected>Random</option>
-        <optgroup label="FLUX">
-            {% for m in models if 'flux' in m|lower %}
-            <option value="{{ m }}">{{ m.rsplit('.', 1)[0] }}</option>
-            {% endfor %}
-        </optgroup>
-        <optgroup label="SDXL">
-            {% for m in models if 'flux' not in m|lower %}
-            <option value="{{ m }}">{{ m.rsplit('.', 1)[0] }}</option>
-            {% endfor %}
-        </optgroup>
-    </select>
-
-    <select id="topic-select">
-        <option value="">No Topic</option>
-        <option value="random">Random</option>
-        <optgroup label="Topics">
-            {% for t in topics %}
-            <option value="{{ t }}">{{ t }}</option>
-            {% endfor %}
-        </optgroup>
-    </select>
+<div class="model-selection">
+    <div class="model-group">
+        <label for="model-select">Image Model:</label>
+        <select id="model-select">
+            <option value="" selected>Random Image Model</option>
+            {% if flux_models %}
+            <optgroup label="FLUX">
+                {% for m in flux_models %}
+                <option value="{{ m }}">{{ m.rsplit('.', 1)[0] if '.' in m else m }}</option>
+                {% endfor %}
+            </optgroup>
+            {% endif %}
+            {% if qwen_models %}
+            <optgroup label="Qwen">
+                {% for m in qwen_models %}
+                <option value="{{ m }}">{{ m.rsplit('.', 1)[0] if '.' in m else m }}</option>
+                {% endfor %}
+            </optgroup>
+            {% endif %}
+            {% if sdxl_models %}
+            <optgroup label="SDXL">
+                {% for m in sdxl_models %}
+                <option value="{{ m }}">{{ m.rsplit('.', 1)[0] if '.' in m else m }}</option>
+                {% endfor %}
+            </optgroup>
+            {% endif %}
+        </select>
+    </div>
+    
+    <div class="model-group">
+        <label for="prompt-model-select">Prompt Model:</label>
+        <select id="prompt-model-select">
+            <option value="" selected>Random Prompt Model</option>
+            {% if openwebui_models %}
+            <optgroup label="OpenWebUI">
+                {% for m in openwebui_models %}
+                <option value="openwebui:{{ m }}">{{ m }}</option>
+                {% endfor %}
+            </optgroup>
+            {% endif %}
+            {% if openrouter_models %}
+            <optgroup label="OpenRouter">
+                {% for m in openrouter_models %}
+                <option value="openrouter:{{ m }}">{{ m }}</option>
+                {% endfor %}
+            </optgroup>
+            {% endif %}
+        </select>
+    </div>
+    
+    <div class="model-group">
+        <label for="topic-select">Topic:</label>
+        <select id="topic-select">
+            <option value="">No Topic</option>
+            <option value="random">Random</option>
+            <optgroup label="Topics">
+                {% for t in topics %}
+                <option value="{{ t }}">{{ t }}</option>
+                {% endfor %}
+            </optgroup>
+        </select>
+    </div>
 </div>
 
 <div id="spinner-overlay">
@@ -154,10 +281,12 @@
         showSpinner();
         const prompt = document.getElementById('prompt-box').value;
         const model = document.getElementById('model-select').value;
+        const promptModel = document.getElementById('prompt-model-select').value;
 
         const formData = new URLSearchParams();
         formData.append('prompt', prompt);
         formData.append('model', model);
+        formData.append('prompt_model', promptModel);
 
         fetch('/create', {
             method: 'POST',
@@ -176,10 +305,12 @@
     function randomPrompt() {
         showSpinner();
         const model = document.getElementById('model-select').value;
+        const promptModel = document.getElementById('prompt-model-select').value;
         const topic = document.getElementById('topic-select').value;
 
         const formData = new URLSearchParams();
         formData.append('model', model);
+        formData.append('prompt_model', promptModel);
         formData.append('topic', topic);
 
         fetch('/create', {
@@ -195,5 +326,59 @@
                 alert("Error requesting random prompt: " + error);
             });
     }
+    document.addEventListener('DOMContentLoaded', function() {
+        const queueBtn = document.getElementById('queue-btn');
+        const queueDropdown = document.getElementById('queue-dropdown');
+        const queueCountSpan = document.getElementById('queue-count');
+
+        // Toggle dropdown visibility
+        queueBtn.addEventListener('click', function(e) {
+            e.stopPropagation();
+            if (queueDropdown.style.display === 'block') {
+                queueDropdown.style.display = 'none';
+            } else {
+                fetchQueueDetails();
+                queueDropdown.style.display = 'block';
+            }
+        });
+
+        // Close dropdown when clicking outside
+        document.addEventListener('click', function() {
+            queueDropdown.style.display = 'none';
+        });
+
+        // Prevent dropdown from closing when clicking inside it
+        queueDropdown.addEventListener('click', function(e) {
+            e.stopPropagation();
+        });
+
+        function fetchQueueDetails() {
+            fetch('/api/queue')
+                .then(response => response.json())
+                .then(jobs => {
+                    queueCountSpan.textContent = jobs.length;
+                    const container = queueDropdown;
+                    container.innerHTML = '';
+
+                    if (jobs.length === 0) {
+                        container.innerHTML = '<div class="queue-item">No jobs in queue</div>';
+                        return;
+                    }
+
+                    jobs.forEach(job => {
+                        const item = document.createElement('div');
+                        item.className = 'queue-item';
+                        item.innerHTML = `
+                            <div class="prompt" data-model="${job.model}">${job.prompt}</div>
+                        `;
+                        container.appendChild(item);
+                    });
+                })
+                .catch(error => {
+                    console.error('Error fetching queue:', error);
+                    queueDropdown.innerHTML = '<div class="queue-item">Error loading queue</div>';
+                });
+        }
+    });
 </script>
 {% endblock %}

user_config.cfg.sample

@@ -24,4 +24,9 @@ models = flux1-dev-Q4_0.gguf,flux1-schnell-Q4_0.gguf
 [openwebui]
 base_url = https://openwebui
 api_key = sk-
-models = llama3:latest,cogito:14b,gemma3:12b
+models = llama3:latest,cogito:14b,gemma3:12b
+
+[openrouter]
+enabled = False
+api_key =
+models = mistralai/mistral-7b-instruct:free,google/gemma-7b-it:free,meta-llama/llama-3.1-8b-instruct:free

workflow_flux.json

@@ -1,12 +1,31 @@
 {
+  "6": {
+    "inputs": {
+      "text": "Terminator endoskeleton riding a bmx bike",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
+      "clip": [
+        "39",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Positive Prompt)"
+    }
+  },
   "8": {
     "inputs": {
       "samples": [
-        "62",
-        1
+        "13",
+        0
       ],
       "vae": [
-        "73",
+        "41",
         0
       ]
     },
@@ -15,298 +34,157 @@
       "title": "VAE Decode"
     }
   },
-  "40": {
+  "9": {
     "inputs": {
-      "int": 20
-    },
-    "class_type": "Int Literal (Image Saver)",
-    "_meta": {
-      "title": "Generation Steps"
-    }
-  },
-  "41": {
-    "inputs": {
-      "width": 720,
-      "height": 1080,
-      "aspect_ratio": "custom",
-      "swap_dimensions": "Off",
-      "upscale_factor": 2,
-      "prescale_factor": 1,
-      "batch_size": 1
-    },
-    "class_type": "CR Aspect Ratio",
-    "_meta": {
-      "title": "CR Aspect Ratio"
-    }
-  },
-  "42": {
-    "inputs": {
-      "filename": "THISFILE",
-      "path": "",
-      "extension": "png",
-      "steps": [
-        "40",
-        0
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-      "cfg": [
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-        0
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-      "modelname": "flux1-dev-Q4_0.gguf",
-      "sampler_name": [
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-      "scheduler_name": "normal",
-      "positive": [
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-      "negative": [
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-      "seed_value": [
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-      "width": [
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-      "height": [
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-      "lossless_webp": true,
-      "quality_jpeg_or_webp": 100,
-      "optimize_png": false,
-      "counter": 0,
-      "denoise": [
-        "53",
-        0
-      ],
-      "clip_skip": 0,
-      "time_format": "%Y-%m-%d-%H%M%S",
-      "save_workflow_as_json": true,
-      "embed_workflow": true,
-      "additional_hashes": "",
-      "download_civitai_data": true,
-      "easy_remix": true,
-      "speak_and_recognation": {
-        "__value__": [
-          false,
-          true
-        ]
-      },
+      "filename_prefix": "ComfyUI",
       "images": [
-        "8",
+        "42",
         0
       ]
     },
-    "class_type": "Image Saver",
+    "class_type": "SaveImage",
     "_meta": {
-      "title": "CivitAI Image Saver"
+      "title": "Save Image"
     }
   },
-  "44": {
-    "inputs": {
-      "text": "Yautja Predator wielding flamethrower in smoky, cyberpunk alleyway darkness",
-      "speak_and_recognation": {
-        "__value__": [
-          false,
-          true
-        ]
-      }
-    },
-    "class_type": "ttN text",
-    "_meta": {
-      "title": "Positive Prompt T5"
-    }
-  },
-  "45": {
-    "inputs": {
-      "text": "text, watermark, deformed Avoid flat colors, poor lighting, and artificial elements. No unrealistic elements, low resolution, or flat colors. Avoid generic objects, poor lighting, and inconsistent styles, blurry, low-quality, distorted faces, overexposed lighting, extra limbs, bad anatomy, low contrast",
-      "speak_and_recognation": {
-        "__value__": [
-          false,
-          true
-        ]
-      }
-    },
-    "class_type": "ttN text",
-    "_meta": {
-      "title": "Negative Prompt"
-    }
-  },
-  "47": {
-    "inputs": {
-      "text": [
-        "44",
-        0
-      ],
-      "speak_and_recognation": {
-        "__value__": [
-          false,
-          true
-        ]
-      },
-      "clip": [
-        "72",
-        0
-      ]
-    },
-    "class_type": "CLIPTextEncode",
-    "_meta": {
-      "title": "Prompt Encoder"
-    }
-  },
-  "48": {
-    "inputs": {
-      "seed": 47371998700984,
-      "increment": 1
-    },
-    "class_type": "Seed Generator (Image Saver)",
-    "_meta": {
-      "title": "Seed"
-    }
-  },
-  "49": {
-    "inputs": {
-      "scheduler": "beta"
-    },
-    "class_type": "Scheduler Selector (Comfy) (Image Saver)",
-    "_meta": {
-      "title": "Scheduler"
-    }
-  },
-  "50": {
-    "inputs": {
-      "sampler_name": "euler"
-    },
-    "class_type": "Sampler Selector (Image Saver)",
-    "_meta": {
-      "title": "Sampler"
-    }
-  },
-  "52": {
-    "inputs": {
-      "float": 3.500000000000001
-    },
-    "class_type": "Float Literal (Image Saver)",
-    "_meta": {
-      "title": "CFG Scale"
-    }
-  },
-  "53": {
-    "inputs": {
-      "float": 1.0000000000000002
-    },
-    "class_type": "Float Literal (Image Saver)",
-    "_meta": {
-      "title": "Denoise"
-    }
-  },
-  "62": {
+  "13": {
     "inputs": {
       "noise": [
-        "65",
+        "25",
         0
       ],
       "guider": [
-        "67",
+        "22",
         0
       ],
       "sampler": [
-        "63",
+        "16",
         0
       ],
       "sigmas": [
-        "64",
+        "17",
         0
       ],
       "latent_image": [
-        "41",
-        5
+        "27",
+        0
       ]
     },
     "class_type": "SamplerCustomAdvanced",
     "_meta": {
-      "title": "Custom Sampler"
+      "title": "SamplerCustomAdvanced"
     }
   },
-  "63": {
+  "16": {
     "inputs": {
-      "sampler_name": [
-        "50",
-        0
-      ]
+      "sampler_name": "euler"
     },
     "class_type": "KSamplerSelect",
     "_meta": {
-      "title": "KSampler Select"
+      "title": "KSamplerSelect"
     }
   },
-  "64": {
+  "17": {
     "inputs": {
-      "scheduler": [
-        "49",
-        0
-      ],
-      "steps": [
-        "40",
-        0
-      ],
-      "denoise": [
-        "53",
-        0
-      ],
+      "scheduler": "simple",
+      "steps": 20,
+      "denoise": 1,
       "model": [
-        "35",
+        "30",
         0
       ]
     },
     "class_type": "BasicScheduler",
     "_meta": {
-      "title": "Sigma Generator"
+      "title": "BasicScheduler"
     }
   },
-  "65": {
-    "inputs": {
-      "noise_seed": [
-        "48",
-        0
-      ]
-    },
-    "class_type": "RandomNoise",
-    "_meta": {
-      "title": "Noise Generator"
-    }
-  },
-  "67": {
+  "22": {
     "inputs": {
       "model": [
-        "35",
+        "30",
         0
       ],
       "conditioning": [
-        "47",
+        "26",
         0
       ]
     },
     "class_type": "BasicGuider",
     "_meta": {
-      "title": "Prompt Guider"
+      "title": "BasicGuider"
     }
   },
-  "72": {
+  "25": {
+    "inputs": {
+      "noise_seed": 707623342760804
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "RandomNoise"
+    }
+  },
+  "26": {
+    "inputs": {
+      "guidance": 3.5,
+      "conditioning": [
+        "6",
+        0
+      ]
+    },
+    "class_type": "FluxGuidance",
+    "_meta": {
+      "title": "FluxGuidance"
+    }
+  },
+  "27": {
+    "inputs": {
+      "width": 720,
+      "height": 1088,
+      "batch_size": 1
+    },
+    "class_type": "EmptySD3LatentImage",
+    "_meta": {
+      "title": "CR Aspect Ratio"
+    }
+  },
+  "30": {
+    "inputs": {
+      "max_shift": 1.15,
+      "base_shift": 0.5,
+      "width": 720,
+      "height": 1088,
+      "model": [
+        "38",
+        0
+      ]
+    },
+    "class_type": "ModelSamplingFlux",
+    "_meta": {
+      "title": "ModelSamplingFlux"
+    }
+  },
+  "38": {
+    "inputs": {
+      "unet_name": "flux1-dev-Q4_0.gguf",
+      "device": "cuda:1",
+      "virtual_vram_gb": 0,
+      "use_other_vram": true,
+      "expert_mode_allocations": ""
+    },
+    "class_type": "UnetLoaderGGUFDisTorchMultiGPU",
+    "_meta": {
+      "title": "UnetLoaderGGUFDisTorchMultiGPU"
+    }
+  },
+  "39": {
     "inputs": {
       "clip_name1": "t5-v1_1-xxl-encoder-Q4_K_M.gguf",
       "clip_name2": "clip_l.safetensors",
       "type": "flux",
       "device": "cuda:0",
       "virtual_vram_gb": 0,
-      "use_other_vram": false,
+      "use_other_vram": true,
       "expert_mode_allocations": ""
     },
     "class_type": "DualCLIPLoaderGGUFDisTorchMultiGPU",
@@ -314,7 +192,7 @@
       "title": "DualCLIPLoaderGGUFDisTorchMultiGPU"
     }
   },
-  "73": {
+  "41": {
     "inputs": {
       "vae_name": "FLUX1/ae.safetensors",
       "device": "cuda:0"
@@ -324,20 +202,18 @@
       "title": "VAELoaderMultiGPU"
     }
   },
-  "35": {
+  "42": {
     "inputs": {
-      "unet_name": "flux1-dev-Q4_0.gguf",
-      "dequant_dtype": "default",
-      "patch_dtype": "default",
-      "patch_on_device": false,
-      "device": "cuda:1",
-      "virtual_vram_gb": 0,
-      "use_other_vram": false,
-      "expert_mode_allocations": ""
+      "offload_model": true,
+      "offload_cache": true,
+      "anything": [
+        "8",
+        0
+      ]
     },
-    "class_type": "UnetLoaderGGUFAdvancedDisTorchMultiGPU",
+    "class_type": "VRAMCleanup",
     "_meta": {
-      "title": "UnetLoaderGGUFAdvancedDisTorchMultiGPU"
+      "title": "🎈VRAM-Cleanup"
     }
   }
 }

workflow_qwen.json

@@ -0,0 +1,161 @@
+{
+  "93": {
+    "inputs": {
+      "text": "jpeg compression",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
+      "clip": [
+        "126",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "95": {
+    "inputs": {
+      "seed": 22,
+      "steps": 10,
+      "cfg": 4.5,
+      "sampler_name": "euler",
+      "scheduler": "normal",
+      "denoise": 1,
+      "model": [
+        "127",
+        0
+      ],
+      "positive": [
+        "100",
+        0
+      ],
+      "negative": [
+        "93",
+        0
+      ],
+      "latent_image": [
+        "97",
+        0
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "KSampler"
+    }
+  },
+  "97": {
+    "inputs": {
+      "width": 1280,
+      "height": 768,
+      "length": 1,
+      "batch_size": 1
+    },
+    "class_type": "EmptyHunyuanLatentVideo",
+    "_meta": {
+      "title": "EmptyHunyuanLatentVideo"
+    }
+  },
+  "98": {
+    "inputs": {
+      "samples": [
+        "95",
+        0
+      ],
+      "vae": [
+        "128",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "100": {
+    "inputs": {
+      "text": "Terminator riding a push bike",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
+      "clip": [
+        "126",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "102": {
+    "inputs": {
+      "images": [
+        "129",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "126": {
+    "inputs": {
+      "clip_name": "Qwen2.5-VL-7B-Instruct-Q3_K_M.gguf",
+      "type": "qwen_image",
+      "device": "cuda:1",
+      "virtual_vram_gb": 6,
+      "use_other_vram": true,
+      "expert_mode_allocations": ""
+    },
+    "class_type": "CLIPLoaderGGUFDisTorchMultiGPU",
+    "_meta": {
+      "title": "CLIPLoaderGGUFDisTorchMultiGPU"
+    }
+  },
+  "127": {
+    "inputs": {
+      "unet_name": "qwen-image-Q2_K.gguf",
+      "device": "cuda:0",
+      "virtual_vram_gb": 6,
+      "use_other_vram": true,
+      "expert_mode_allocations": ""
+    },
+    "class_type": "UnetLoaderGGUFDisTorchMultiGPU",
+    "_meta": {
+      "title": "UnetLoaderGGUFDisTorchMultiGPU"
+    }
+  },
+  "128": {
+    "inputs": {
+      "vae_name": "qwen_image_vae.safetensors",
+      "device": "cuda:1"
+    },
+    "class_type": "VAELoaderMultiGPU",
+    "_meta": {
+      "title": "VAELoaderMultiGPU"
+    }
+  },
+  "129": {
+    "inputs": {
+      "offload_model": true,
+      "offload_cache": true,
+      "anything": [
+        "98",
+        0
+      ]
+    },
+    "class_type": "VRAMCleanup",
+    "_meta": {
+      "title": "🎈VRAM-Cleanup"
+    }
+  }
+}

workflow_sdxl.json

@@ -52,6 +52,12 @@
   "6": {
     "inputs": {
       "text": "A bustling cyberpunk street at night, filled with neon signs, rain-soaked pavement, and futuristic street vendors. High detail, vivid neon colors, and realistic reflections.",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
       "clip": [
         "4",
         1
@@ -65,6 +71,12 @@
   "7": {
     "inputs": {
       "text": "text, watermark, deformed Avoid flat colors, poor lighting, and artificial elements. No unrealistic elements, low resolution, or flat colors. Avoid generic objects, poor lighting, and inconsistent styles, blurry, low-quality, distorted faces, overexposed lighting, extra limbs, bad anatomy, low contrast",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
       "clip": [
         "4",
         1
@@ -95,7 +107,7 @@
     "inputs": {
       "filename_prefix": "ComfyUI",
       "images": [
-        "8",
+        "10",
         0
       ]
     },
@@ -103,5 +115,19 @@
     "_meta": {
       "title": "Save Image"
     }
+  },
+  "10": {
+    "inputs": {
+      "offload_model": true,
+      "offload_cache": true,
+      "anything": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "VRAMCleanup",
+    "_meta": {
+      "title": "🎈VRAM-Cleanup"
+    }
   }
 }