.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.5.5"
+current_version = "0.3.14"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 replace = "{new_version}"

Dockerfile

@@ -4,7 +4,7 @@ FROM python:3.11-slim
 # Set the working directory in the container
 WORKDIR /app
 # Set version label
-ARG VERSION="0.5.5"
+ARG VERSION="0.3.14"
 LABEL version=$VERSION
 
 # Copy project files into the container

README.md

@@ -4,19 +4,12 @@ This project is a Flask-based web server designed to generate and display images
 
 ## Features
 
-*   **Web Interface:** A simple web interface to view generated images, manage favourites, and monitor job queues.
-*   **Image Generation:** Integrates with ComfyUI to generate images using SDXL, FLUX, and Qwen models based on given prompts.
-*   **Prompt Generation:** Automatic prompt generation using OpenWebUI or OpenRouter APIs with topic-based theming.
+*   **Web Interface:** A simple web interface to view generated images.
+*   **Image Generation:** Integrates with ComfyUI to generate images based on given prompts and models.
 *   **Scheduled Generation:** Automatically generates new images at a configurable time.
-*   **Favourites System:** Mark and manage favourite images.
-*   **Job Queue Management:** View and cancel running/pending image generation jobs.
-*   **Thumbnail Generation:** Automatic thumbnail creation for generated images.
-*   **Prompt Logging:** Maintains a log of recent prompts to avoid repetition.
-*   **Settings Management:** Web-based configuration editor for all settings.
 *   **Docker Support:** Comes with a `Dockerfile` and `docker-compose.yml` for easy setup and deployment.
-*   **Configurable:** Most options can be configured through a `user_config.cfg` file or web interface.
+*   **Configurable:** Most options can be configured through a `user_config.cfg` file.
 *   **Authentication:** Optional password protection for image creation.
-*   **Version Management:** Uses bump-my-version for version tracking.
 
 ## Prerequisites
 
@@ -40,8 +33,8 @@ This project is a Flask-based web server designed to generate and display images
     ```
 
 3.  **Configure the application:**
-    *   The `user_config.cfg` file will be automatically created from `user_config.cfg.sample` on first run if it doesn't exist.
-    *   Edit `user_config.cfg` with your settings, or use the web-based settings page accessible by clicking the version number in the bottom right corner of the home page. See the [Configuration](#configuration) section for more details.
+    *   Copy the `user_config.cfg.sample` to `user_config.cfg`.
+    *   Edit `user_config.cfg` with your settings. See the [Configuration](#configuration) section for more details.
 
 4.  **Run the application:**
     ```bash
@@ -58,8 +51,8 @@ This project is a Flask-based web server designed to generate and display images
     ```
 
 2.  **Configure the application:**
-    *   The `user_config.cfg` file will be automatically created from `user_config.cfg.sample` on first run if it doesn't exist.
-    *   Edit `user_config.cfg` with your settings, or use the web-based settings page accessible by clicking the version number in the bottom right corner of any page. The `comfyui_url` should be the address of your ComfyUI instance, accessible from within the Docker network (e.g., `http://host.docker.internal:8188` or your server's IP).
+    *   Copy the `user_config.cfg.sample` to `user_config.cfg`.
+    *   Edit `user_config.cfg` with your settings. The `comfyui_url` should be the address of your ComfyUI instance, accessible from within the Docker network (e.g., `http://host.docker.internal:8188` or your server's IP).
 
 3.  **Build and run with Docker Compose:**
     ```bash
@@ -86,27 +79,17 @@ The application is configured via the `user_config.cfg` file.
 | `[comfyui]` | `width`              | The width of the generated image.                                           | `1568`                |
 | `[comfyui]` | `height`             | The height of the generated image.                                          | `672`                 |
 | `[comfyui]` | `topics`             | A comma-separated list of topics to generate prompts from.                  |                       |
-| `[comfyui]` | `secondary_topic`    | A secondary topic for prompt generation.                                    |                       |
-| `[comfyui]` | `flux`               | Enable FLUX models (`True`/`False`).                                        | `False`               |
-| `[comfyui]` | `qwen`               | Enable Qwen models (`True`/`False`).                                        | `False`               |
+| `[comfyui]` | `FLUX`               | Enable FLUX models (`True`/`False`).                                        | `False`               |
+| `[comfyui]` | `ONLY_FLUX`          | Only use FLUX models (`True`/`False`).                                      | `False`               |
 | `[comfyui:flux]` | `models`       | A comma-separated list of FLUX models.                                      | `flux1-dev-Q4_0.gguf,flux1-schnell-Q4_0.gguf` |
-| `[comfyui:qwen]` | `models`       | A comma-separated list of Qwen models.                                      | `qwen-image-Q4_K_S.gguf, qwen-image-Q2_K.gguf` |
 | `[openwebui]` | `base_url`         | The base URL for OpenWebUI.                                                 | `https://openwebui`   |
 | `[openwebui]` | `api_key`          | The API key for OpenWebUI.                                                  | `sk-`                 |
 | `[openwebui]` | `models`           | A comma-separated list of models for OpenWebUI.                             | `llama3:latest,cogito:14b,gemma3:12b` |
-| `[openrouter]` | `enabled`          | Enable OpenRouter integration (`True`/`False`).                             | `False`               |
-| `[openrouter]` | `api_key`          | The API key for OpenRouter.                                                 |                       |
-| `[openrouter]` | `models`           | A comma-separated list of models for OpenRouter.                            | `mistralai/mistral-7b-instruct:free,google/gemma-7b-it:free,meta-llama/llama-3.1-8b-instruct:free` |
-| `[openrouter]` | `list_all_free_models` | List all free models (`True`/`False`).                                      | `False`               |
 
 ## Usage
 
 *   **Gallery:** Open your browser to `http://<server_ip>:<port>` to see the gallery of generated images.
-*   **Create Image:** Navigate to `/create` or `/create_image` to manually trigger image generation with various model options.
-*   **Job Queue:** Monitor and cancel running/pending jobs via the gallery interface.
-*   **API Endpoints:**
-    *   `/api/queue` - Get current job queue details (JSON)
-    *   `/cancel` - Cancel the current running job
+*   **Create Image:** Navigate to `/create` to manually trigger image generation.
 
 ## Dependencies
 
@@ -114,12 +97,6 @@ The application is configured via the `user_config.cfg` file.
 *   comfy_api_simplified
 *   APScheduler
 *   Pillow
-*   tenacity
-*   nest_asyncio
-*   openai
-*   websockets
-*   bump-my-version
-*   openwebui-chat-client
 *   And others, see `requirements.txt`.
 
 ## Contributing

libs/generic.py

@@ -5,7 +5,6 @@ import sys
 import time
 import os
 import random
-import shutil
 from PIL import Image
 import nest_asyncio
 import json
@@ -39,21 +38,10 @@ def save_prompt(prompt):
 
 
 def load_config() -> configparser.ConfigParser:
-    """Loads user configuration from ./user_config.cfg. If it doesn't exist, copies from user_config.cfg.sample."""
+    """Loads user configuration from ./user_config.cfg."""
     user_config = configparser.ConfigParser()
-    config_path = "./user_config.cfg"
-    sample_path = "./user_config.cfg.sample"
-
-    if not os.path.exists(config_path):
-        if os.path.exists(sample_path):
-            shutil.copy(sample_path, config_path)
-            logging.info("Configuration file copied from sample.")
-        else:
-            logging.error("Neither user_config.cfg nor user_config.cfg.sample found.")
-            sys.exit(1)
-
     try:
-        user_config.read(config_path)
+        user_config.read("./user_config.cfg")
         logging.debug("Configuration loaded successfully.")
         return user_config
     except KeyError as e:
@@ -93,20 +81,17 @@ def get_details_from_png(path):
     try:
         date = datetime.fromtimestamp(os.path.getctime(path)).strftime("%d-%m-%Y")
         with Image.open(path) as img:
+            try:
+                # Flux workflow
                 data = json.loads(img.info["prompt"])
                 prompt = data['6']['inputs']['text']
-            if '38' in data and 'unet_name' in data['38']['inputs']:
-                # Flux workflow
                 model = data['38']['inputs']['unet_name'].split(".")[0]
-            elif '4' in data and 'ckpt_name' in data['4']['inputs']:
+            except KeyError:
                 # SDXL workflow
+                data = json.loads(img.info["prompt"])
+                prompt = data['6']['inputs']['text']
                 model = data['4']['inputs']['ckpt_name']
-            elif '80' in data and 'unet_name' in data['80']['inputs']:
-                # Qwen workflow
-                model = data['80']['inputs']['unet_name'].split(".")[0]
-            else:
-                model = "unknown"
-            return {"p":prompt,"m":model,"d":date}
+            return {"p":prompt,"m":model,"d":date} or {"p":"","m":"","c":""}
     except Exception as e:
         print(f"Error reading metadata from {path}: {e}")
         return ""
@@ -161,13 +146,8 @@ def load_openrouter_models_from_config():
     config = load_config()
     if config["openrouter"].get("enabled", "False").lower() == "true":
         models = config["openrouter"]["models"].split(",")
-        configured_models = sorted([model.strip() for model in models if model.strip()], key=str.lower)
-        free_models = []
-        if config["openrouter"].get("list_all_free_models", "False").lower() == "true":
-            from libs.openrouter import get_free_models
-            free_models = get_free_models()
-        return configured_models, free_models
-    return [], []
+        return sorted([model.strip() for model in models if model.strip()], key=str.lower)
+    return []
 
 def load_openwebui_models_from_config():
     config = load_config()
@@ -190,54 +170,10 @@ def load_prompt_models_from_config():
     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()])
-        # Add free models if flag is set
-        if config["openrouter"].get("list_all_free_models", "False").lower() == "true":
-            from libs.openrouter import get_free_models
-            free_models = get_free_models()
-            prompt_models.extend([("openrouter", model) for model in free_models])
     
     return prompt_models
 
 
-def build_user_content(topic: str = "random") -> str:
-    """Build the user content string for prompt generation, including topic instructions and recent prompts avoidance."""
-    config = load_config()
-    topic_instruction = ""
-    selected_topic = ""
-    secondary_topic_instruction = ""
-    # Unique list of recent prompts
-    recent_prompts = list(set(load_recent_prompts()))
-
-    if topic == "random":
-        topics = [t.strip() for t in 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 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."
-
-    # Add secondary topic if configured and not empty
-    secondary_topic = config["comfyui"].get("secondary_topic", "").strip()
-    if secondary_topic:
-        secondary_topic_instruction = f" Additionally incorporate the theme of '{secondary_topic}' into the new prompt."
-
-    user_content = (
-        "Can you generate me a really random image idea, Do not exceed 20 words. Use clear language, not poetic metaphors."
-        + topic_instruction
-        + secondary_topic_instruction
-        + "Avoid prompts similar to the following:"
-        + "\n".join(f"{i+1}. {p}" for i, p in enumerate(recent_prompts))
-    )
-
-    return user_content
-
-
 def create_prompt_with_random_model(base_prompt: str, topic: str = "random"):
     """Create a prompt using a randomly selected model from OpenWebUI or OpenRouter.
     

libs/openrouter.py

@@ -2,7 +2,7 @@ import random
 import logging
 from openai import OpenAI, RateLimitError
 import nest_asyncio
-from libs.generic import load_recent_prompts, load_config, build_user_content
+from libs.generic import load_recent_prompts, load_config
 from libs.openwebui import create_prompt_on_openwebui
 import re
 nest_asyncio.apply()
@@ -14,78 +14,49 @@ LOG_FILE = "./prompts_log.jsonl"
 user_config = load_config()
 output_folder = user_config["comfyui"]["output_dir"]
 
-def get_free_models():
-    """Fetch all free models from OpenRouter."""
-    if user_config["openrouter"].get("enabled", "False").lower() != "true":
-        return []
-    try:
-        client = OpenAI(
-            base_url="https://openrouter.ai/api/v1",
-            api_key=user_config["openrouter"]["api_key"],
-        )
-        all_models_response = client.models.list()
-        all_models = [m.id for m in all_models_response.data]
-        free_models = [m for m in all_models if "free" in m.lower()]
-        return sorted(free_models, key=str.lower)
-    except Exception as e:
-        logging.warning(f"Failed to fetch free models from OpenRouter: {e}")
-        return []
-
 def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str = None) -> str:
     """Sends prompt to OpenRouter and returns the generated response."""
-    # Reload config to get latest values
-    config = load_config()
     # Check if OpenRouter is enabled
-    if config["openrouter"].get("enabled", "False").lower() != "true":
+    if user_config["openrouter"].get("enabled", "False").lower() != "true":
         logging.warning("OpenRouter is not enabled in the configuration.")
         return ""
     
-    user_content = build_user_content(topic)
+    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."
 
-    # Load configured models
-    configured_models = [m.strip() for m in user_config["openrouter"]["models"].split(",") if m.strip()]
-    if not configured_models:
+    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 ""
         
-    # Create client early for model checking
-    client = OpenAI(
-        base_url="https://openrouter.ai/api/v1",
-        api_key=user_config["openrouter"]["api_key"],
-    )
-
-    # Select model
-    if model:
-        original_model = model
-        # Always check if model exists on OpenRouter
-        try:
-            all_models_response = client.models.list()
-            all_models = [m.id for m in all_models_response.data]
-            if model not in all_models:
-                # Fallback to random free model from all OpenRouter models
-                free_models = [m for m in all_models if "free" in m.lower()]
-                if free_models:
-                    model = random.choice(free_models)
-                    logging.info(f"Specified model '{original_model}' not found on OpenRouter, falling back to free model: {model}")
-                else:
-                    # No free models, fallback to random configured model
-                    model = random.choice(configured_models)
-                    logging.warning(f"Specified model '{original_model}' not found, no free models available on OpenRouter, using random configured model: {model}")
-            # else model exists, use it
-        except Exception as e:
-            logging.warning(f"Failed to fetch OpenRouter models for validation: {e}. Falling back to configured models.")
-            if model not in configured_models:
-                # Fallback to random free from configured
-                free_models = [m for m in configured_models if "free" in m.lower()]
-                if free_models:
-                    model = random.choice(free_models)
-                    logging.info(f"Specified model '{original_model}' not found, falling back to free configured model: {model}")
-                else:
-                    model = random.choice(configured_models)
-                    logging.warning(f"Specified model '{original_model}' not found, no free configured models available, using random configured model: {model}")
-            # else use the specified model
-    else:
-        model = random.choice(configured_models)
+        model = random.choice(models)
     
     try:
         client = OpenAI(
@@ -93,21 +64,17 @@ def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str =
             api_key=user_config["openrouter"]["api_key"],
         )
 
-        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."
-        )
-
-        # Try the specified model first
-        try:
         completion = client.chat.completions.create(
             model=model,
             messages=[
                 {
                     "role": "system",
-                        "content": system_content,
+                    "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",
@@ -115,27 +82,6 @@ def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str =
                 },
             ]
         )
-        except Exception as e:
-            # If system message fails (e.g., model doesn't support developer instructions),
-            # retry with instructions included in user message
-            if "developer instruction" in str(e).lower() or "system message" in str(e).lower():
-                logging.info(f"Model {model} doesn't support system messages, retrying with instructions in user message")
-                combined_content = f"{system_content}\n\n{user_content}"
-                completion = client.chat.completions.create(
-                    model=model,
-                    messages=[
-                        {
-                            "role": "user",
-                            "content": combined_content,
-                        },
-                    ]
-                )
-            else:
-                # If it's another error, try fallback models
-                logging.warning(f"Error with model {model}: {e}. Trying fallback models.")
-                raise e
-
-        # If we get here, the completion was successful
 
         prompt = completion.choices[0].message.content.strip('"')
         match = re.search(r'"([^"]+)"', prompt)
@@ -160,45 +106,5 @@ def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str =
             logging.error("No OpenWebUI models configured for fallback.")
             return "A colorful abstract composition"  # Final fallback
     except Exception as e:
-        # If the specified model fails, try fallback models
-        logging.warning(f"Primary model {model} failed: {e}. Trying fallback models.")
-
-        # Get all available models for fallback
-        configured_models = [m.strip() for m in user_config["openrouter"]["models"].split(",") if m.strip()]
-        free_models = get_free_models()
-
-        # Combine configured and free models, excluding the failed one
-        all_models = configured_models + free_models
-        fallback_models = [m for m in all_models if m != model]
-
-        if not fallback_models:
-            logging.error("No fallback models available.")
-            return ""
-
-        # Try up to 3 fallback models
-        for fallback_model in fallback_models[:3]:
-            try:
-                logging.info(f"Trying fallback model: {fallback_model}")
-                completion = client.chat.completions.create(
-                    model=fallback_model,
-                    messages=[
-                        {
-                            "role": "user",
-                            "content": f"{system_content}\n\n{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.info(f"Successfully generated prompt with fallback model: {fallback_model}")
-                return prompt
-            except Exception as fallback_e:
-                logging.warning(f"Fallback model {fallback_model} also failed: {fallback_e}")
-                continue
-
-        logging.error("All models failed, including fallbacks.")
+        logging.error(f"Error generating prompt with OpenRouter: {e}")
         return ""

libs/openwebui.py

@@ -1,7 +1,7 @@
 import random
 import logging
 import nest_asyncio
-from libs.generic import load_recent_prompts, load_config, build_user_content
+from libs.generic import load_recent_prompts, load_config
 import re
 from openwebui_chat_client import OpenWebUIClient
 from datetime import datetime
@@ -17,9 +17,29 @@ 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."""
-    # Reload config to get latest values
-    config = load_config()
-    user_content = build_user_content(topic)
+    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

routes/create_routes.py

@@ -38,7 +38,7 @@ def create():
     # 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, openrouter_free_models = load_openrouter_models_from_config()
+    openrouter_models = load_openrouter_models_from_config()
     
     queue_count = get_queue_count()
     return render_template("create_image.html",
@@ -47,7 +47,6 @@ def create():
                          qwen_models=qwen_models,
                          openwebui_models=openwebui_models,
                          openrouter_models=openrouter_models,
-                         openrouter_free_models=openrouter_free_models,
                          topics=load_topics_from_config(),
                          queue_count=queue_count)
 
@@ -69,7 +68,7 @@ def create_image_page():
     # 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, openrouter_free_models = load_openrouter_models_from_config()
+    openrouter_models = load_openrouter_models_from_config()
     
     queue_count = get_queue_count()
     return render_template("create_image.html",
@@ -78,7 +77,6 @@ def create_image_page():
                          qwen_models=qwen_models,
                          openwebui_models=openwebui_models,
                          openrouter_models=openrouter_models,
-                         openrouter_free_models=openrouter_free_models,
                          topics=load_topics_from_config(),
                          queue_count=queue_count)
 

templates/create_image.html

@@ -249,13 +249,6 @@
                 {% endfor %}
             </optgroup>
             {% endif %}
-            {% if openrouter_free_models %}
-            <optgroup label="OpenRouter Free">
-                {% for m in openrouter_free_models %}
-                <option value="openrouter:{{ m }}">{{ m }}</option>
-                {% endfor %}
-            </optgroup>
-            {% endif %}
         </select>
     </div>
     

user_config.cfg.sample

@@ -14,14 +14,10 @@ prompt = "Generate a random detailed prompt for stable diffusion."
 width = 1568
 height = 672
 topics = 
-secondary_topic =
 
-flux = False
-qwen = False
-only_flux = False
+FLUX = False
+ONLY_FLUX = False
 
-[comfyui:qwen]
-models = qwen-image-Q4_K_S.gguf, qwen-image-Q2_K.gguf
 [comfyui:flux]
 models = flux1-dev-Q4_0.gguf,flux1-schnell-Q4_0.gguf
 
@@ -34,4 +30,3 @@ models = llama3:latest,cogito:14b,gemma3:12b
 enabled = False
 api_key =
 models = mistralai/mistral-7b-instruct:free,google/gemma-7b-it:free,meta-llama/llama-3.1-8b-instruct:free
-list_all_free_models = False

workflow_flux_original.json

@@ -0,0 +1,433 @@
+{
+  "8": {
+    "inputs": {
+      "samples": [
+        "62",
+        1
+      ],
+      "vae": [
+        "27",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "22": {
+    "inputs": {
+      "clip_name1": "t5/t5xxl_fp8_e4m3fn.safetensors",
+      "clip_name2": "clip_l.safetensors",
+      "type": "flux",
+      "device": "default"
+    },
+    "class_type": "DualCLIPLoader",
+    "_meta": {
+      "title": "DualCLIPLoader"
+    }
+  },
+  "27": {
+    "inputs": {
+      "vae_name": "FLUX1/ae.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "32": {
+    "inputs": {
+      "upscale_model": [
+        "33",
+        0
+      ],
+      "image": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "ImageUpscaleWithModel",
+    "_meta": {
+      "title": "Upscale Image (using Model)"
+    }
+  },
+  "33": {
+    "inputs": {
+      "model_name": "4x-UltraSharp.pth"
+    },
+    "class_type": "UpscaleModelLoader",
+    "_meta": {
+      "title": "Load Upscale Model"
+    }
+  },
+  "34": {
+    "inputs": {
+      "upscale_method": "lanczos",
+      "scale_by": 0.5,
+      "image": [
+        "32",
+        0
+      ]
+    },
+    "class_type": "ImageScaleBy",
+    "_meta": {
+      "title": "Half size"
+    }
+  },
+  "35": {
+    "inputs": {
+      "unet_name": "flux1-dev-Q4_0.gguf"
+    },
+    "class_type": "UnetLoaderGGUF",
+    "_meta": {
+      "title": "Unet Loader (GGUF)"
+    }
+  },
+  "40": {
+    "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
+      ],
+      "cfg": [
+        "52",
+        0
+      ],
+      "modelname": "flux1-dev-Q4_0.gguf",
+      "sampler_name": [
+        "50",
+        1
+      ],
+      "positive": [
+        "44",
+        0
+      ],
+      "negative": [
+        "45",
+        0
+      ],
+      "seed_value": [
+        "48",
+        0
+      ],
+      "width": [
+        "41",
+        0
+      ],
+      "height": [
+        "41",
+        1
+      ],
+      "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
+        ]
+      },
+      "images": [
+        "34",
+        0
+      ]
+    },
+    "class_type": "Image Saver",
+    "_meta": {
+      "title": "CivitAI Image Saver"
+    }
+  },
+  "44": {
+    "inputs": {
+      "text": "",
+      "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": [
+        "68",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "48": {
+    "inputs": {
+      "seed": 903006749445372,
+      "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 Selector"
+    }
+  },
+  "50": {
+    "inputs": {
+      "sampler_name": "euler"
+    },
+    "class_type": "Sampler Selector (Image Saver)",
+    "_meta": {
+      "title": "Sampler Selector (Image Saver)"
+    }
+  },
+  "51": {
+    "inputs": {
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "52": {
+    "inputs": {
+      "float": 3.5
+    },
+    "class_type": "Float Literal (Image Saver)",
+    "_meta": {
+      "title": "CFG"
+    }
+  },
+  "53": {
+    "inputs": {
+      "float": 1
+    },
+    "class_type": "Float Literal (Image Saver)",
+    "_meta": {
+      "title": "Denoise"
+    }
+  },
+  "60": {
+    "inputs": {
+      "clip_l": "",
+      "t5xxl": [
+        "44",
+        0
+      ],
+      "guidance": [
+        "52",
+        0
+      ],
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
+      },
+      "clip": [
+        "68",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncodeFlux",
+    "_meta": {
+      "title": "CLIPTextEncodeFlux"
+    }
+  },
+  "62": {
+    "inputs": {
+      "noise": [
+        "65",
+        0
+      ],
+      "guider": [
+        "67",
+        0
+      ],
+      "sampler": [
+        "63",
+        0
+      ],
+      "sigmas": [
+        "64",
+        0
+      ],
+      "latent_image": [
+        "41",
+        5
+      ]
+    },
+    "class_type": "SamplerCustomAdvanced",
+    "_meta": {
+      "title": "SamplerCustomAdvanced"
+    }
+  },
+  "63": {
+    "inputs": {
+      "sampler_name": [
+        "50",
+        0
+      ]
+    },
+    "class_type": "KSamplerSelect",
+    "_meta": {
+      "title": "KSamplerSelect"
+    }
+  },
+  "64": {
+    "inputs": {
+      "scheduler": [
+        "49",
+        0
+      ],
+      "steps": [
+        "40",
+        0
+      ],
+      "denoise": [
+        "53",
+        0
+      ],
+      "model": [
+        "68",
+        0
+      ]
+    },
+    "class_type": "BasicScheduler",
+    "_meta": {
+      "title": "BasicScheduler"
+    }
+  },
+  "65": {
+    "inputs": {
+      "noise_seed": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "RandomNoise"
+    }
+  },
+  "67": {
+    "inputs": {
+      "model": [
+        "68",
+        0
+      ],
+      "conditioning": [
+        "47",
+        0
+      ]
+    },
+    "class_type": "BasicGuider",
+    "_meta": {
+      "title": "BasicGuider"
+    }
+  },
+  "68": {
+    "inputs": {
+      "lora_01": "None",
+      "strength_01": 1,
+      "lora_02": "None",
+      "strength_02": 1,
+      "lora_03": "None",
+      "strength_03": 1,
+      "lora_04": "None",
+      "strength_04": 1,
+      "model": [
+        "35",
+        0
+      ],
+      "clip": [
+        "22",
+        0
+      ]
+    },
+    "class_type": "Lora Loader Stack (rgthree)",
+    "_meta": {
+      "title": "Lora Loader Stack (rgthree)"
+    }
+  }
+}

workflow_qwen.json

@@ -1,26 +1,45 @@
 {
-  "3": {
+  "93": {
     "inputs": {
-      "seed": 367723847870487,
-      "steps": 8,
-      "cfg": 2.5,
+      "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": "simple",
+      "scheduler": "normal",
       "denoise": 1,
       "model": [
-        "66",
+        "127",
         0
       ],
       "positive": [
-        "6",
+        "100",
         0
       ],
       "negative": [
-        "7",
+        "93",
         0
       ],
       "latent_image": [
-        "58",
+        "97",
         0
       ]
     },
@@ -29,40 +48,26 @@
       "title": "KSampler"
     }
   },
-  "6": {
+  "97": {
     "inputs": {
-      "text": "Cat sitting at desk, surrounded by taxidermied dinosaurs",
-      "clip": [
-        "38",
-        0
-      ]
+      "width": 1280,
+      "height": 768,
+      "length": 1,
+      "batch_size": 1
     },
-    "class_type": "CLIPTextEncode",
+    "class_type": "EmptyHunyuanLatentVideo",
     "_meta": {
-      "title": "Positive"
+      "title": "EmptyHunyuanLatentVideo"
     }
   },
-  "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",
-      "clip": [
-        "38",
-        0
-      ]
-    },
-    "class_type": "CLIPTextEncode",
-    "_meta": {
-      "title": "Negative"
-    }
-  },
-  "8": {
+  "98": {
     "inputs": {
       "samples": [
-        "3",
+        "95",
         0
       ],
       "vae": [
-        "39",
+        "128",
         0
       ]
     },
@@ -71,84 +76,86 @@
       "title": "VAE Decode"
     }
   },
-  "38": {
+  "100": {
     "inputs": {
-      "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors",
-      "type": "qwen_image",
-      "device": "default"
+      "text": "Terminator riding a push bike",
+      "speak_and_recognation": {
+        "__value__": [
+          false,
+          true
+        ]
       },
-    "class_type": "CLIPLoader",
+      "clip": [
+        "126",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
     "_meta": {
-      "title": "Load CLIP"
+      "title": "CLIP Text Encode (Prompt)"
     }
   },
-  "39": {
+  "102": {
     "inputs": {
-      "vae_name": "qwen_image_vae.safetensors"
-    },
-    "class_type": "VAELoader",
-    "_meta": {
-      "title": "Load VAE"
-    }
-  },
-  "58": {
-    "inputs": {
-      "width": 720,
-      "height": 1088,
-      "batch_size": 1
-    },
-    "class_type": "EmptySD3LatentImage",
-    "_meta": {
-      "title": "CR Aspect Ratio"
-    }
-  },
-  "60": {
-    "inputs": {
-      "filename_prefix": "ComfyUI",
       "images": [
-        "8",
+        "129",
         0
       ]
     },
-    "class_type": "SaveImage",
+    "class_type": "PreviewImage",
     "_meta": {
-      "title": "Save Image"
+      "title": "Preview Image"
     }
   },
-  "66": {
+  "126": {
     "inputs": {
-      "shift": 3.1000000000000005,
-      "model": [
-        "73",
+      "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": "ModelSamplingAuraFlow",
+    "class_type": "VRAMCleanup",
     "_meta": {
-      "title": "ModelSamplingAuraFlow"
-    }
-  },
-  "73": {
-    "inputs": {
-      "lora_name": "Qwen-Image-Lightning-8steps-V1.0.safetensors",
-      "strength_model": 1,
-      "model": [
-        "80",
-        0
-      ]
-    },
-    "class_type": "LoraLoaderModelOnly",
-    "_meta": {
-      "title": "LoraLoaderModelOnly"
-    }
-  },
-  "80": {
-    "inputs": {
-      "unet_name": "qwen-image-Q4_K_S.gguf"
-    },
-    "class_type": "UnetLoaderGGUF",
-    "_meta": {
-      "title": "Load Checkpoint"
+      "title": "🎈VRAM-Cleanup"
     }
   }
 }