.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.3.12"
+current_version = "0.3.5"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 replace = "{new_version}"

.gitignore

@@ -12,4 +12,3 @@ test.py
 .vscode/launch.json
 favourites.json
 .vscode/launch.json
-venv/*

Dockerfile

@@ -4,7 +4,7 @@ FROM python:3.11-slim
 # Set the working directory in the container
 WORKDIR /app
 # Set version label
-ARG VERSION="0.3.12"
+ARG VERSION="0.3.5"
 LABEL version=$VERSION
 
 # Copy project files into the container

libs/comfyui.py

@@ -32,17 +32,9 @@ def get_available_models() -> list:
     response = requests.get(url)
     if response.status_code == 200:
         data = response.json()
-        # Get SDXL models from CheckpointLoaderSimple
+        general = data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {}).get("ckpt_name", [])[0]
-        general = data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {}).get("ckpt_name", [[]])[0]
+        flux = data.get("UnetLoaderGGUF", {}).get("input", {}).get("required", {}).get("unet_name", [])[0]
-        # Get FLUX models from UnetLoaderGGUF
+        return general + flux
-        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 []
@@ -133,25 +125,9 @@ def select_model(model: str) -> tuple[str, str]:
     use_qwen = json.loads(user_config["comfyui"].get("Qwen", "false").lower())
 
     if model == "Random Image Model":
-        # Create a list of available workflows based on configuration
+        selected_workflow = "FLUX" if (use_flux and (only_flux or random.choice([True, False]))) else "SDXL"
-        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"
 
@@ -163,13 +139,6 @@ def select_model(model: str) -> tuple[str, str]:
         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
@@ -198,12 +167,12 @@ def create_image(prompt: str | None = None, model: str = "Random Image Model") -
             file_name="image",
             comfy_prompt=prompt,
             workflow_path="./workflow_flux.json",
-            prompt_node="CLIP Text Encode (Positive Prompt)",
+            prompt_node="Positive Prompt T5",
-            seed_node="RandomNoise",
+            seed_node="Seed",
-            seed_param="noise_seed",
+            seed_param="seed",
-            save_node="Save Image",
+            save_node="CivitAI Image Saver",
-            save_param="filename_prefix",
+            save_param="filename",
-            model_node="UnetLoaderGGUFDisTorchMultiGPU",
+            model_node="UnetLoaderGGUFAdvancedDisTorchMultiGPU",
             model_param="unet_name",
             model=model
         )

libs/generic.py

@@ -84,8 +84,8 @@ def get_details_from_png(path):
             try:
                 # Flux workflow
                 data = json.loads(img.info["prompt"])
-                prompt = data['6']['inputs']['text']
+                prompt = data['44']['inputs']['text']
-                model = data['38']['inputs']['unet_name'].split(".")[0]
+                model = data['35']['inputs']['unet_name'].split(".")[0]
             except KeyError:
                 # SDXL workflow
                 data = json.loads(img.info["prompt"])
@@ -113,24 +113,9 @@ def get_current_version():
         return "unknown"
 
 def load_models_from_config():
-    config = load_config()
+    flux_models = load_config()["comfyui:flux"]["models"].split(",")
-    
+    sdxl_models = load_config()["comfyui"]["models"].split(",")
-    # Only load FLUX models if FLUX feature is enabled
+    qwen_models = load_config()["comfyui:qwen"]["models"].split(",")
-    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)
     sorted_qwen_models = sorted(qwen_models, key=str.lower)
@@ -240,6 +225,7 @@ def create_prompt_with_random_model(base_prompt: str, topic: str = "random"):
             logging.error(f"Error with OpenRouter: {e}")
             return "A colorful abstract composition"  # Default fallback prompt
     
+    return "A colorful abstract composition"  # Default fallback prompt
 
 user_config = load_config()
 output_folder = user_config["comfyui"]["output_dir"]

libs/openrouter.py

@@ -1,9 +1,8 @@
 import random
 import logging
-from openai import OpenAI, RateLimitError
+from openai import OpenAI
 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()
 
@@ -91,20 +90,6 @@ def create_prompt_on_openrouter(prompt: str, topic: str = "random", model: str =
             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 ""

templates/create_image.html

@@ -73,7 +73,6 @@
         background: #555;
     }
 
-
     #spinner-overlay {
         position: fixed;
         inset: 0;
@@ -144,7 +143,7 @@
         display: none;
         max-height: 300px;
         overflow-y: auto;
-        width: 400px;
+        width: 300px;
     }
 
     .queue-item {
@@ -157,28 +156,17 @@
         border-bottom: none;
     }
 
+    .queue-item .model {
+        font-weight: bold;
+        color: #00aaff;
+    }
+
     .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;
+        overflow: hidden;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.3);
+        text-overflow: ellipsis;
     }
 </style>
 {% endblock %}
@@ -369,7 +357,8 @@
                         const item = document.createElement('div');
                         item.className = 'queue-item';
                         item.innerHTML = `
-                            <div class="prompt" data-model="${job.model}">${job.prompt}</div>
+                            <div class="model">${job.model}</div>
+                            <div class="prompt" title="${job.prompt}">${job.prompt}</div>
                         `;
                         container.appendChild(item);
                     });

workflow_flux.json

@@ -1,31 +1,12 @@
 {
-  "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": [
-        "13",
+        "62",
-        0
+        1
       ],
       "vae": [
-        "41",
+        "73",
         0
       ]
     },
@@ -34,157 +15,298 @@
       "title": "VAE Decode"
     }
   },
-  "9": {
+  "40": {
     "inputs": {
-      "filename_prefix": "ComfyUI",
+      "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
+      ],
+      "scheduler_name": "normal",
+      "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": [
-        "42",
+        "8",
         0
       ]
     },
-    "class_type": "SaveImage",
+    "class_type": "Image Saver",
     "_meta": {
-      "title": "Save Image"
+      "title": "CivitAI Image Saver"
     }
   },
-  "13": {
+  "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": {
     "inputs": {
       "noise": [
-        "25",
+        "65",
         0
       ],
       "guider": [
-        "22",
+        "67",
         0
       ],
       "sampler": [
-        "16",
+        "63",
         0
       ],
       "sigmas": [
-        "17",
+        "64",
         0
       ],
       "latent_image": [
-        "27",
+        "41",
-        0
+        5
       ]
     },
     "class_type": "SamplerCustomAdvanced",
     "_meta": {
-      "title": "SamplerCustomAdvanced"
+      "title": "Custom Sampler"
     }
   },
-  "16": {
+  "63": {
     "inputs": {
-      "sampler_name": "euler"
+      "sampler_name": [
+        "50",
+        0
+      ]
     },
     "class_type": "KSamplerSelect",
     "_meta": {
       "title": "KSampler Select"
     }
   },
-  "17": {
+  "64": {
     "inputs": {
-      "scheduler": "simple",
+      "scheduler": [
-      "steps": 20,
+        "49",
-      "denoise": 1,
+        0
+      ],
+      "steps": [
+        "40",
+        0
+      ],
+      "denoise": [
+        "53",
+        0
+      ],
       "model": [
-        "30",
+        "35",
         0
       ]
     },
     "class_type": "BasicScheduler",
     "_meta": {
-      "title": "BasicScheduler"
+      "title": "Sigma Generator"
     }
   },
-  "22": {
+  "65": {
+    "inputs": {
+      "noise_seed": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "Noise Generator"
+    }
+  },
+  "67": {
     "inputs": {
       "model": [
-        "30",
+        "35",
         0
       ],
       "conditioning": [
-        "26",
+        "47",
         0
       ]
     },
     "class_type": "BasicGuider",
     "_meta": {
-      "title": "BasicGuider"
+      "title": "Prompt Guider"
     }
   },
-  "25": {
+  "72": {
-    "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": true,
+      "use_other_vram": false,
       "expert_mode_allocations": ""
     },
     "class_type": "DualCLIPLoaderGGUFDisTorchMultiGPU",
@@ -192,7 +314,7 @@
       "title": "DualCLIPLoaderGGUFDisTorchMultiGPU"
     }
   },
-  "41": {
+  "73": {
     "inputs": {
       "vae_name": "FLUX1/ae.safetensors",
       "device": "cuda:0"
@@ -202,18 +324,20 @@
       "title": "VAELoaderMultiGPU"
     }
   },
-  "42": {
+  "35": {
     "inputs": {
-      "offload_model": true,
+      "unet_name": "flux1-dev-Q4_0.gguf",
-      "offload_cache": true,
+      "dequant_dtype": "default",
-      "anything": [
+      "patch_dtype": "default",
-        "8",
+      "patch_on_device": false,
-        0
+      "device": "cuda:1",
-      ]
+      "virtual_vram_gb": 0,
+      "use_other_vram": false,
+      "expert_mode_allocations": ""
     },
-    "class_type": "VRAMCleanup",
+    "class_type": "UnetLoaderGGUFAdvancedDisTorchMultiGPU",
     "_meta": {
-      "title": "🎈VRAM-Cleanup"
+      "title": "UnetLoaderGGUFAdvancedDisTorchMultiGPU"
     }
   }
 }

workflow_qwen.json

@@ -98,7 +98,7 @@
   "102": {
     "inputs": {
       "images": [
-        "129",
+        "98",
         0
       ]
     },
@@ -143,19 +143,5 @@
     "_meta": {
       "title": "VAELoaderMultiGPU"
     }
-  },
-  "129": {
-    "inputs": {
-      "offload_model": true,
-      "offload_cache": true,
-      "anything": [
-        "98",
-        0
-      ]
-    },
-    "class_type": "VRAMCleanup",
-    "_meta": {
-      "title": "🎈VRAM-Cleanup"
-    }
   }
 }

workflow_sdxl.json

@@ -52,12 +52,6 @@
   "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
@@ -71,12 +65,6 @@
   "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
@@ -107,7 +95,7 @@
     "inputs": {
       "filename_prefix": "ComfyUI",
       "images": [
-        "10",
+        "8",
         0
       ]
     },
@@ -115,19 +103,5 @@
     "_meta": {
       "title": "Save Image"
     }
-  },
-  "10": {
-    "inputs": {
-      "offload_model": true,
-      "offload_cache": true,
-      "anything": [
-        "8",
-        0
-      ]
-    },
-    "class_type": "VRAMCleanup",
-    "_meta": {
-      "title": "🎈VRAM-Cleanup"
-    }
   }
 }