diff --git a/ComfyUI/comfy_api_nodes/apis/request_logger.py b/ComfyUI/comfy_api_nodes/apis/request_logger.py
index 93517ede..cf9cc798 100644
--- a/ComfyUI/comfy_api_nodes/apis/request_logger.py
+++ b/ComfyUI/comfy_api_nodes/apis/request_logger.py
@@ -3,7 +3,7 @@
 import json
 import logging
 import folder_paths
-
+from typing import Optional, Any
 # Get the logger instance
 logger = logging.getLogger(__name__)
 
@@ -40,13 +40,13 @@ def log_request_response(
     operation_id: str,
     request_method: str,
     request_url: str,
-    request_headers: dict | None = None,
-    request_params: dict | None = None,
-    request_data: any = None,
-    response_status_code: int | None = None,
-    response_headers: dict | None = None,
-    response_content: any = None,
-    error_message: str | None = None
+    request_headers: Optional[dict] = None,
+    request_params: Optional[dict] = None,
+    request_data: Any = None,
+    response_status_code: Optional[int] = None,
+    response_headers: Optional[dict] = None,
+    response_content: Any = None,
+    error_message: Optional[str] = None
 ):
     """
     Logs API request and response details to a file in the temp/api_logs directory.
diff --git a/ComfyUI/comfy_api_nodes/nodes_gemini.py b/ComfyUI/comfy_api_nodes/nodes_gemini.py
index 2690b51b..ae7b0484 100644
--- a/ComfyUI/comfy_api_nodes/nodes_gemini.py
+++ b/ComfyUI/comfy_api_nodes/nodes_gemini.py
@@ -312,51 +312,41 @@ def api_call(
         unique_id: Optional[str] = None,
         **kwargs,
     ) -> tuple[str]:
-        try:
-            # Validate inputs
-            validate_string(prompt, strip_whitespace=False)
-
-            # Create parts list with text prompt as the first part
-            parts: list[GeminiPart] = [self.create_text_part(prompt)]
-
-            # Add other modal parts
-            if images is not None:
-                image_parts = self.create_image_parts(images)
-                parts.extend(image_parts)
-            if audio is not None:
-                parts.extend(self.create_audio_parts(audio))
-            if video is not None:
-                parts.extend(self.create_video_parts(video))
-            if files is not None:
-                parts.extend(files)
-
-            # Create response
-            response = SynchronousOperation(
-                endpoint=get_gemini_endpoint(model),
-                request=GeminiGenerateContentRequest(
-                    contents=[
-                        GeminiContent(
-                            role="user",
-                            parts=parts,
-                        )
-                    ]
-                ),
-                auth_kwargs=kwargs,
-            ).execute()
-
-            # Get result output
-            output_text = self.get_text_from_response(response)
-            if unique_id and output_text:
-                PromptServer.instance.send_progress_text(output_text, node_id=unique_id)
-        
-        except Exception as e:
-            # Handle API errors, network issues, and validation failures gracefully
-            error_message = f"Gemini API Error: {str(e)}"
-            print(f"[GeminiNode] {error_message}")  # Log full error for debugging
-            sanitized_message = "An error occurred while processing your request. Please try again later."
-            if unique_id:
-                PromptServer.instance.send_progress_text(sanitized_message, node_id=unique_id)
-            output_text = sanitized_message
+        # Validate inputs
+        validate_string(prompt, strip_whitespace=False)
+
+        # Create parts list with text prompt as the first part
+        parts: list[GeminiPart] = [self.create_text_part(prompt)]
+
+        # Add other modal parts
+        if images is not None:
+            image_parts = self.create_image_parts(images)
+            parts.extend(image_parts)
+        if audio is not None:
+            parts.extend(self.create_audio_parts(audio))
+        if video is not None:
+            parts.extend(self.create_video_parts(video))
+        if files is not None:
+            parts.extend(files)
+
+        # Create response
+        response = SynchronousOperation(
+            endpoint=get_gemini_endpoint(model),
+            request=GeminiGenerateContentRequest(
+                contents=[
+                    GeminiContent(
+                        role="user",
+                        parts=parts,
+                    )
+                ]
+            ),
+            auth_kwargs=kwargs,
+        ).execute()
+
+        # Get result output
+        output_text = self.get_text_from_response(response)
+        if unique_id and output_text:
+            PromptServer.instance.send_progress_text(output_text, node_id=unique_id)
 
         return (output_text or "Empty response from Gemini model...",)
 
@@ -439,17 +429,10 @@ def prepare_files(
         """
         Loads and formats input files for Gemini API.
         """
-        try:
-            file_path = folder_paths.get_annotated_filepath(file)
-            input_file_content = self.create_file_part(file_path)
-            files = [input_file_content] + GEMINI_INPUT_FILES
-            return (files,)
-        except Exception as e:
-            # Handle file processing errors gracefully
-            error_message = f"File processing error: {str(e)}"
-            print(f"[GeminiInputFiles] {error_message}")
-            # Return empty list on error
-            return ([],)
+        file_path = folder_paths.get_annotated_filepath(file)
+        input_file_content = self.create_file_part(file_path)
+        files = [input_file_content] + GEMINI_INPUT_FILES
+        return (files,)
 
 
 NODE_CLASS_MAPPINGS = {
diff --git a/ComfyUI/comfy_api_nodes/nodes_stability.py b/ComfyUI/comfy_api_nodes/nodes_stability.py
index 447c4df7..02e42167 100644
--- a/ComfyUI/comfy_api_nodes/nodes_stability.py
+++ b/ComfyUI/comfy_api_nodes/nodes_stability.py
@@ -30,8 +30,6 @@
 import base64
 from io import BytesIO
 from enum import Enum
-import requests
-import os
 
 
 class StabilityPollStatus(str, Enum):
@@ -69,24 +67,24 @@ def INPUT_TYPES(s):
                         "multiline": True,
                         "default": "",
                         "tooltip": "What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
-                        "What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
-                        "elements, colors, and subjects will lead to better results. " +
-                        "To control the weight of a given word use the format `(word:weight)`," +
-                        "where `word` is the word you'd like to control the weight of and `weight`" +
-                        "is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)`" +
-                        "would convey a sky that was blue and green, but more green than blue."
+                                    "What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
+                                    "elements, colors, and subjects will lead to better results. " +
+                                    "To control the weight of a given word use the format `(word:weight)`," +
+                                    "where `word` is the word you'd like to control the weight of and `weight`" +
+                                    "is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)`" +
+                                    "would convey a sky that was blue and green, but more green than blue."
                     },
                 ),
                 "aspect_ratio": ([x.value for x in StabilityAspectRatio],
-                                 {
-                    "default": StabilityAspectRatio.ratio_1_1,
-                    "tooltip": "Aspect ratio of generated image.",
-                },
+                    {
+                        "default": StabilityAspectRatio.ratio_1_1,
+                        "tooltip": "Aspect ratio of generated image.",
+                    },
                 ),
                 "style_preset": (get_stability_style_presets(),
-                                 {
-                    "tooltip": "Optional desired style of generated image.",
-                },
+                    {
+                        "tooltip": "Optional desired style of generated image.",
+                    },
                 ),
                 "seed": (
                     IO.INT,
@@ -121,30 +119,19 @@ def INPUT_TYPES(s):
                 ),
             },
             "hidden": {
-                # Changed from auth_token/comfy_api_key
-                "stability_api_key": "STABILITY_API_KEY",
+                "auth_token": "AUTH_TOKEN_COMFY_ORG",
+                "comfy_api_key": "API_KEY_COMFY_ORG",
             },
         }
 
     def api_call(self, prompt: str, aspect_ratio: str, style_preset: str, seed: int,
-                 negative_prompt: str = None, image: torch.Tensor = None, image_denoise: float = None,
+                 negative_prompt: str=None, image: torch.Tensor = None, image_denoise: float=None,
                  **kwargs):
         validate_string(prompt, strip_whitespace=False)
-
-        # Get Stability API key from kwargs or environment
-        stability_api_key = kwargs.get(
-            'stability_api_key') or os.environ.get('STABILITY_API_KEY')
-        if not stability_api_key:
-            raise Exception(
-                "STABILITY_API_KEY not found. Please set it in your environment or .env file.")
-
-        # Prepare image binary if image present
+        # prepare image binary if image present
         image_binary = None
         if image is not None:
-            image_binary = tensor_to_bytesio(
-                image, total_pixels=1504*1504).read()
-            # Convert image to base64 for JSON payload
-            image_base64 = base64.b64encode(image_binary).decode('utf-8')
+            image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
         else:
             image_denoise = None
 
@@ -153,72 +140,38 @@ def api_call(self, prompt: str, aspect_ratio: str, style_preset: str, seed: int,
         if style_preset == "None":
             style_preset = None
 
-        # Prepare the request data for direct Stability AI API (JSON format)
-        request_data = {
-            "text_prompts": [
-                {
-                    "text": prompt,
-                    "weight": 1.0
-                }
-            ],
-            "aspect_ratio": aspect_ratio,
-            "seed": seed,
-        }
-
-        if negative_prompt:
-            request_data["text_prompts"].append({
-                "text": negative_prompt,
-                "weight": -1.0
-            })
-
-        if style_preset:
-            request_data["style_preset"] = style_preset
-
-        if image_denoise:
-            request_data["image_strength"] = image_denoise
-
-        # Add init_image if present (for image-to-image)
-        if image_binary:
-            request_data["init_image"] = image_base64
-
-        # Make direct API call to Stability AI
-        headers = {
-            "Authorization": f"Bearer {stability_api_key}",
-            "Accept": "application/json",
-            "Content-Type": "application/json"
+        files = {
+            "image": image_binary
         }
 
-        try:
-            print(
-                f"[DEBUG] Making request to Stability AI API with data: {request_data}")
-            response = requests.post(
-                "https://api.stability.ai/v1/generation/stable-diffusion-xl-1024-v1-0/text-to-image",
-                headers=headers,
-                json=request_data,
-                timeout=300
-            )
-
-            if response.status_code != 200:
-                raise Exception(
-                    f"Stability AI API error: {response.status_code} - {response.text}")
-
-            response_data = response.json()
-
-            if "artifacts" not in response_data or not response_data["artifacts"]:
-                raise Exception("No image generated in response")
+        operation = SynchronousOperation(
+            endpoint=ApiEndpoint(
+                path="/proxy/stability/v2beta/stable-image/generate/ultra",
+                method=HttpMethod.POST,
+                request_model=StabilityStableUltraRequest,
+                response_model=StabilityStableUltraResponse,
+            ),
+            request=StabilityStableUltraRequest(
+                prompt=prompt,
+                negative_prompt=negative_prompt,
+                aspect_ratio=aspect_ratio,
+                seed=seed,
+                strength=image_denoise,
+                style_preset=style_preset,
+            ),
+            files=files,
+            content_type="multipart/form-data",
+            auth_kwargs=kwargs,
+        )
+        response_api = operation.execute()
 
-            # Get the first image from the response
-            image_data = base64.b64decode(
-                response_data["artifacts"][0]["base64"])
-            returned_image = bytesio_to_image_tensor(BytesIO(image_data))
+        if response_api.finish_reason != "SUCCESS":
+            raise Exception(f"Stable Image Ultra generation failed: {response_api.finish_reason}.")
 
-            return (returned_image,)
+        image_data = base64.b64decode(response_api.image)
+        returned_image = bytesio_to_image_tensor(BytesIO(image_data))
 
-        except requests.exceptions.RequestException as e:
-            raise Exception(
-                f"Network error calling Stability AI API: {str(e)}")
-        except Exception as e:
-            raise Exception(f"Error generating image: {str(e)}")
+        return (returned_image,)
 
 
 class StabilityStableImageSD_3_5Node:
@@ -246,15 +199,15 @@ def INPUT_TYPES(s):
                 ),
                 "model": ([x.value for x in Stability_SD3_5_Model],),
                 "aspect_ratio": ([x.value for x in StabilityAspectRatio],
-                                 {
-                    "default": StabilityAspectRatio.ratio_1_1,
-                    "tooltip": "Aspect ratio of generated image.",
-                },
+                    {
+                        "default": StabilityAspectRatio.ratio_1_1,
+                        "tooltip": "Aspect ratio of generated image.",
+                    },
                 ),
                 "style_preset": (get_stability_style_presets(),
-                                 {
-                    "tooltip": "Optional desired style of generated image.",
-                },
+                    {
+                        "tooltip": "Optional desired style of generated image.",
+                    },
                 ),
                 "cfg_scale": (
                     IO.FLOAT,
@@ -305,15 +258,14 @@ def INPUT_TYPES(s):
         }
 
     def api_call(self, model: str, prompt: str, aspect_ratio: str, style_preset: str, seed: int, cfg_scale: float,
-                 negative_prompt: str = None, image: torch.Tensor = None, image_denoise: float = None,
+                 negative_prompt: str=None, image: torch.Tensor = None, image_denoise: float=None,
                  **kwargs):
         validate_string(prompt, strip_whitespace=False)
         # prepare image binary if image present
         image_binary = None
         mode = Stability_SD3_5_GenerationMode.text_to_image
         if image is not None:
-            image_binary = tensor_to_bytesio(
-                image, total_pixels=1504*1504).read()
+            image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
             mode = Stability_SD3_5_GenerationMode.image_to_image
             aspect_ratio = None
         else:
@@ -353,8 +305,7 @@ def api_call(self, model: str, prompt: str, aspect_ratio: str, style_preset: str
         response_api = operation.execute()
 
         if response_api.finish_reason != "SUCCESS":
-            raise Exception(
-                f"Stable Diffusion 3.5 Image generation failed: {response_api.finish_reason}.")
+            raise Exception(f"Stable Diffusion 3.5 Image generation failed: {response_api.finish_reason}.")
 
         image_data = base64.b64decode(response_api.image)
         returned_image = bytesio_to_image_tensor(BytesIO(image_data))
@@ -423,7 +374,7 @@ def INPUT_TYPES(s):
             },
         }
 
-    def api_call(self, image: torch.Tensor, prompt: str, creativity: float, seed: int, negative_prompt: str = None,
+    def api_call(self, image: torch.Tensor, prompt: str, creativity: float, seed: int, negative_prompt: str=None,
                  **kwargs):
         validate_string(prompt, strip_whitespace=False)
         image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
@@ -445,7 +396,7 @@ def api_call(self, image: torch.Tensor, prompt: str, creativity: float, seed: in
             request=StabilityUpscaleConservativeRequest(
                 prompt=prompt,
                 negative_prompt=negative_prompt,
-                creativity=round(creativity, 2),
+                creativity=round(creativity,2),
                 seed=seed,
             ),
             files=files,
@@ -455,8 +406,7 @@ def api_call(self, image: torch.Tensor, prompt: str, creativity: float, seed: in
         response_api = operation.execute()
 
         if response_api.finish_reason != "SUCCESS":
-            raise Exception(
-                f"Stability Upscale Conservative generation failed: {response_api.finish_reason}.")
+            raise Exception(f"Stability Upscale Conservative generation failed: {response_api.finish_reason}.")
 
         image_data = base64.b64decode(response_api.image)
         returned_image = bytesio_to_image_tensor(BytesIO(image_data))
@@ -499,9 +449,9 @@ def INPUT_TYPES(s):
                     },
                 ),
                 "style_preset": (get_stability_style_presets(),
-                                 {
-                    "tooltip": "Optional desired style of generated image.",
-                },
+                    {
+                        "tooltip": "Optional desired style of generated image.",
+                    },
                 ),
                 "seed": (
                     IO.INT,
@@ -530,7 +480,7 @@ def INPUT_TYPES(s):
             },
         }
 
-    def api_call(self, image: torch.Tensor, prompt: str, creativity: float, style_preset: str, seed: int, negative_prompt: str = None,
+    def api_call(self, image: torch.Tensor, prompt: str, creativity: float, style_preset: str, seed: int, negative_prompt: str=None,
                  **kwargs):
         validate_string(prompt, strip_whitespace=False)
         image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
@@ -554,7 +504,7 @@ def api_call(self, image: torch.Tensor, prompt: str, creativity: float, style_pr
             request=StabilityUpscaleCreativeRequest(
                 prompt=prompt,
                 negative_prompt=negative_prompt,
-                creativity=round(creativity, 2),
+                creativity=round(creativity,2),
                 style_preset=style_preset,
                 seed=seed,
             ),
@@ -580,8 +530,7 @@ def api_call(self, image: torch.Tensor, prompt: str, creativity: float, style_pr
         response_poll: StabilityResultsGetResponse = operation.execute()
 
         if response_poll.finish_reason != "SUCCESS":
-            raise Exception(
-                f"Stability Upscale Creative generation failed: {response_poll.finish_reason}.")
+            raise Exception(f"Stability Upscale Creative generation failed: {response_poll.finish_reason}.")
 
         image_data = base64.b64decode(response_poll.result)
         returned_image = bytesio_to_image_tensor(BytesIO(image_data))
@@ -637,8 +586,7 @@ def api_call(self, image: torch.Tensor,
         response_api = operation.execute()
 
         if response_api.finish_reason != "SUCCESS":
-            raise Exception(
-                f"Stability Upscale Fast failed: {response_api.finish_reason}.")
+            raise Exception(f"Stability Upscale Fast failed: {response_api.finish_reason}.")
 
         image_data = base64.b64decode(response_api.image)
         returned_image = bytesio_to_image_tensor(BytesIO(image_data))
diff --git a/ComfyUI/user/default/comfy.settings.json b/ComfyUI/user/default/comfy.settings.json
index 512a22bd..438b3dad 100644
--- a/ComfyUI/user/default/comfy.settings.json
+++ b/ComfyUI/user/default/comfy.settings.json
@@ -1,6 +1,3 @@
 {
-    "Comfy.TutorialCompleted": true,
-    "Comfy.Queue.ImageFit": "cover",
-    "Comfy.Release.Version": "0.3.48",
-    "Comfy.Release.Timestamp": 1754374644423
+    "Comfy.TutorialCompleted": true
 }
\ No newline at end of file
diff --git a/GEMINI_INTEGRATION_DEMO.md b/GEMINI_INTEGRATION_DEMO.md
deleted file mode 100644
index b1633c5d..00000000
--- a/GEMINI_INTEGRATION_DEMO.md
+++ /dev/null
@@ -1,188 +0,0 @@
-# 🔮 **Gemini Integration for DreamLayer AI**
-
-## 🎯 **Overview**
-
-This PR completes the Gemini integration for DreamLayer AI, adding Google's powerful multimodal AI capabilities to the platform. Users can now leverage Gemini Pro Vision for text generation, image analysis, document processing, and creative workflows.
-
-## ✨ **What's New**
-
-### 🔧 **Backend Integration**
-- ✅ **API Key Support**: Added `GEMINI_API_KEY` to environment configuration
-- ✅ **Model Mapping**: Gemini Pro and Gemini Pro Vision available in model dropdown
-- ✅ **Workflow Templates**: Created both simple and advanced workflow examples
-
-### 🎨 **Frontend Integration** 
-- ✅ **API Key Configuration**: Added Gemini to the API key management UI
-- ✅ **Model Selection**: Gemini models appear in the model dropdown when API key is configured
-- ✅ **User Experience**: Seamless integration with existing DreamLayer interface
-
-### 🚀 **ComfyUI Node**
-- ✅ **Multimodal Support**: Text + Image + Audio + Video + Files input
-- ✅ **Node Chaining**: Text output can be consumed by downstream nodes
-- ✅ **Advanced Features**: Deterministic seeding, multiple model options
-
-## 🔗 **Node Chaining Demonstration**
-
-### **Simple Text Workflow**
-```json
-LoadImage → GeminiNode → (Text Output)
-```
-
-### **Advanced Multimodal Chain**
-```json
-LoadImage → GeminiNode(analysis) → GeminiNode(prompt_generation) → CLIPTextEncode → KSampler → SaveImage
-```
-
-**Real-world example:**
-1. **Load Image** - User uploads photo
-2. **Gemini Analysis** - "Analyze this image's artistic elements"  
-3. **Prompt Generation** - "Create an enhanced AI art prompt based on this analysis"
-4. **CLIP Encoding** - Convert Gemini-generated prompt to tokens
-5. **Image Generation** - Generate enhanced version using Stable Diffusion
-6. **Save Result** - Output the improved image
-
-## 🧪 **Test Case: Prompt → Gemini → Downstream Node**
-
-### **Test Workflow**
-```json
-{
-  "1": {
-    "class_type": "GeminiNode",
-    "inputs": {
-      "prompt": "Create a detailed prompt for generating a cyberpunk cityscape artwork",
-      "model": "gemini-2.5-pro-preview-05-06"
-    }
-  },
-  "2": {
-    "class_type": "CLIPTextEncode", 
-    "inputs": {
-      "clip": ["3", 1],
-      "text": ["1", 0]  // <-- Gemini text output feeds into CLIP
-    }
-  }
-}
-```
-
-### **Expected Behavior**
-1. User provides high-level request: "Create a detailed prompt for cyberpunk cityscape"
-2. Gemini generates: "A futuristic cyberpunk cityscape at night, neon-lit skyscrapers, flying cars, rain-soaked streets, purple and blue color palette, highly detailed, digital art, masterpiece"
-3. CLIP encodes this Gemini-generated prompt
-4. Stable Diffusion uses the encoding for image generation
-
-## 🎯 **Key Features Demonstrated**
-
-### **✅ Multimodal AI Integration**
-- Text generation and analysis
-- Image understanding and description  
-- Creative prompt optimization
-- Professional workflow automation
-
-### **✅ Seamless Node Chaining**
-- Gemini output directly feeds downstream nodes
-- No manual copy/paste required
-- Automated creative pipelines
-- AI-assisted content creation
-
-### **✅ Production-Ready Implementation**
-- Error handling and validation
-- Comprehensive API key management
-- User-friendly interface integration
-- Professional documentation
-
-## 🛠 **Setup Instructions**
-
-### **1. Get Gemini API Key**
-```bash
-# Visit: https://ai.google.dev/gemini-api/docs/api-key
-# Create account and generate API key
-```
-
-### **2. Configure DreamLayer**
-1. Start DreamLayer application
-2. Go to Model Selector → "Add API KEY"
-3. Enter your Gemini API key in the "Gemini - Google AI" field
-4. Click Submit
-
-### **3. Test the Integration**
-1. Go to txt2img tab
-2. Select "Gemini Pro Vision" from model dropdown
-3. Enter prompt: "Analyze this image and suggest improvements"
-4. Upload an image (if using multimodal workflow)
-5. Generate and see Gemini's analysis
-
-## 🎨 **Usage Examples**
-
-### **Creative Writing**
-```
-Prompt: "Write a short story about AI and humans collaborating"
-→ Gemini generates creative, engaging narrative
-```
-
-### **Image Analysis**
-```
-Input: [User uploads artwork]
-Prompt: "Analyze this image's composition, style, and suggest improvements"
-→ Gemini provides detailed artistic critique
-```
-
-### **Code Generation**
-```
-Prompt: "Create a Python function that processes image metadata"
-→ Gemini generates functional, well-documented code
-```
-
-### **Prompt Engineering**
-```
-Prompt: "Transform this basic idea into a detailed AI art prompt: 'sunset landscape'"
-→ Gemini: "A breathtaking sunset landscape with golden hour lighting, rolling hills, dramatic clouds, warm color palette, highly detailed, digital painting, cinematic composition"
-```
-
-## 🔄 **Integration Quality**
-
-### **✅ Follows Existing Patterns**
-- Uses same API key injection system as OpenAI/FLUX
-- Matches workflow template structure
-- Consistent with DreamLayer's design patterns
-
-### **✅ Professional Implementation**
-- Comprehensive error handling
-- Type-safe API integration
-- Scalable architecture
-- Production-ready code quality
-
-### **✅ Enhanced User Experience**
-- Intuitive API key configuration
-- Seamless model selection
-- Powerful multimodal capabilities
-- Professional workflow automation
-
-## 🚀 **Impact & Value**
-
-### **For AI Artists**
-- Intelligent image analysis and critique
-- Automated prompt optimization
-- Creative workflow enhancement
-- Professional artistic guidance
-
-### **For Developers**
-- Multimodal AI integration example
-- Advanced node chaining patterns
-- API integration best practices
-- Extensible architecture foundation
-
-### **For Content Creators**
-- Text generation and refinement
-- Image understanding and enhancement
-- Automated content workflows
-- AI-assisted creative processes
-
-## 🔮 **Future Enhancements**
-
-- **File Processing**: Document analysis and summarization
-- **Video Analysis**: Frame-by-frame content understanding  
-- **Audio Processing**: Speech recognition and analysis
-- **Advanced Chaining**: Multi-step AI reasoning workflows
-
----
-
-**🎉 This integration demonstrates DreamLayer's commitment to cutting-edge AI technology and user-centric design, making advanced AI capabilities accessible through an intuitive, professional interface.** 
\ No newline at end of file
diff --git a/README.md b/README.md
index 79295e0b..fa9ec09e 100644
--- a/README.md
+++ b/README.md
@@ -15,6 +15,8 @@
 <p align="center">
   <b>Product Vision:</b>
   <a href="https://huggingface.co/blog/ytmack7/benchmarking-diffusion-models">AI Research</a>
+  &nbsp;|&nbsp;
+  <a href="https://huggingface.co/blog/ytmack7/stable-diffusion-ui-for-creatives">AI Art</a>
 </p>
 
 
@@ -27,9 +29,9 @@
 DreamLayer AI is an open-source Stable Diffusion WebUI that keeps the familiar Automatic1111 ⁄ Forge layout you know, replaces the clutter with a modern design system, and runs every generation step on ComfyUI in the background.  
 No node graph on screen, no server rental, just a lightning-fast local interface for:
 
-- **AI artists** producing portfolio-ready images
-- **Developers and prompt engineers** iterating on prompts and LoRAs
-- **Researchers** benchmarking new models and samplers
+* **AI artists** producing portfolio-ready images  
+* **Developers and prompt engineers** iterating on prompts and LoRAs  
+* **Researchers** benchmarking new models and samplers  
 
 > **Status:** ✨ **Now live:** Open Alpha • **Beta V1 ships:** **Mid-July 2025**
 
@@ -48,7 +50,6 @@ Easiest way to run DreamLayer 😃 Best for non-technical users
 3. Type `run it` or press the **"Run"** button — then follow the guided steps
 
 Cursor will:
-
 - Walk you through each setup step
 - Install Python and Node dependencies
 - Create a virtual environment
@@ -62,19 +63,16 @@ Cursor will:
 ### Installation
 
 **linux:**
-
 ```bash
 ./install_linux_dependencies.sh
 ```
 
 **macOS:**
-
 ```bash
 ./install_mac_dependencies.sh
 ```
 
 **Windows:**
-
 ```bash
 install_windows_dependencies.ps1
 ```
@@ -82,43 +80,39 @@ install_windows_dependencies.ps1
 ### Start Application
 
 **linux:**
-
 ```bash
 ./start_dream_layer.sh
 ```
 
 **macOS:**
-
 ```bash
 ./start_dream_layer.sh
 ```
 
 **Windows:**
-
 ```bash
 start_dream_layer.bat
 ```
-
 ### Env Variables
-
 **install_dependencies_linux**
 DLVENV_PATH // preferred path to python virtual env. default is /tmp/dlvenv
 
 **start_dream_layer**
-DREAMLAYER_COMFYUI_CPU_MODE // if no nvidia drivers available run using CPU only. default is false
+DREAMLAYER_COMFYUI_CPU_MODE // if no nvidia drivers available run using CPU only.  default is false
 
 ### Access
 
 - **Frontend:** http://localhost:8080
 - **ComfyUI:** http://localhost:8188
 
+
 ### Installing Models ⭐️
 
 DreamLayer ships without weights to keep the download small. You have two ways to add models:
 
 ### a) Closed-source API models
 
-DreamLayer can also call external APIs (OpenAI DALL·E, Flux, Ideogram).
+DreamLayer can also call external APIs (OpenAI DALL·E, Flux, Ideogram). 
 
 To enable them:
 
@@ -128,7 +122,6 @@ Edit your `.env` file at `dream_layer/.env`:
 OPENAI_API_KEY=sk-...
 BFL_API_KEY=flux-...
 IDEOGRAM_API_KEY=id-...
-STABILITY_API_KEY=sk-...
 ```
 
 Once a key is present, the model becomes visible in the dropdown.
@@ -137,13 +130,11 @@ No key = feature stays hidden.
 ### b) Open-source checkpoints (offline)
 
 **Step 1:** Download .safetensors or .ckpt files from:
-
 - Hugging Face
 - Civitai
 - Your own training runs
 
 **Step 2:** Place the models in the appropriate folders (auto-created on first run):
-
 - Checkpoints/ → # full checkpoints (.safetensors)
 - Lora/ → # LoRA & LoCon files
 - ControlNet/ → # ControlNet models
@@ -153,19 +144,22 @@ No key = feature stays hidden.
 
 > Tip: Use symbolic links if your checkpoints live on another drive.
 
-_The installation scripts will automatically install all dependencies and set up the environment._
+*The installation scripts will automatically install all dependencies and set up the environment.* 
+
 
 ---
 
 ## Why DreamLayer AI?
 
-| 🔍 Feature                      | 🚀 How it’s better                                                                                          |
-| ------------------------------- | ----------------------------------------------------------------------------------------------------------- |
-| **Familiar Layout**             | If you’ve used A1111 or Forge, you’ll feel at home in sec. Zero learning curve                              |
-| **Modern UX**                   | Responsive design with light & dark themes and a clutter-free interface that lets you work faster           |
-| **ComfyUI Engine Inside**       | All generation runs on a proven, modular, stable ComfyUI backend. Ready for custom nodes and advanced hacks |
-| **Closed-Source Model Support** | One-click swap to GPT-4o Image, Ideogram V3, Runway Gen-4, Recraft V3, and more                             |
-| **Local first**                 | Runs entirely on your GPU with no hosting fees, full privacy, and instant acceleration out of the box       |
+| 🔍 Feature | 🚀 How it’s better |
+|------------|-----------|
+| **Familiar Layout** | If you’ve used A1111 or Forge, you’ll feel at home in sec. Zero learning curve |
+| **Modern UX** | Responsive design with light & dark themes and a clutter-free interface that lets you work faster |
+| **ComfyUI Engine Inside** | All generation runs on a proven, modular, stable ComfyUI backend. Ready for custom nodes and advanced hacks |
+| **Closed-Source Model Support** | One-click swap to GPT-4o Image, Ideogram V3, Runway Gen-4, Recraft V3, and more |
+| **Local first** | Runs entirely on your GPU with no hosting fees, full privacy, and instant acceleration out of the box |
+
+
 
 ---
 
@@ -182,11 +176,11 @@ _The installation scripts will automatically install all dependencies and set up
 Starring helps us trend on GitHub which brings more contributors and faster features.  
 Early stargazers get perks:
 
-- **GitHub Hall of Fame**: Your handle listed forever in the README under Founding Supporter
-- **Early Builds**: Download private binaries before everyone else
-- **Community first hiring**: We prioritize contributors and stargazers for all freelance, full-time, and AI artist or engineering roles.
-- **Closed Beta Invites**: Give feedback that shapes 1.0
-- **Discord badge**: Exclusive Founding Supporter role
+* **GitHub Hall of Fame**: Your handle listed forever in the README under Founding Supporter  
+* **Early Builds**: Download private binaries before everyone else
+* **Community first hiring**: We prioritize contributors and stargazers for all freelance, full-time, and AI artist or engineering roles.    
+* **Closed Beta Invites**: Give feedback that shapes 1.0  
+* **Discord badge**: Exclusive Founding Supporter role
 
 > ⭐ **Hit the star button right now** and join us at the ground floor ☺️
 
@@ -194,8 +188,8 @@ Early stargazers get perks:
 
 ## Get Involved Today
 
-1. **Star** this repository.
-2. **Watch** releases for the July code drop.
+1. **Star** this repository.  
+2. **Watch** releases for the July code drop.  
 3. **Join** the Discord (link coming soon) and say hi.
 4. **Open issues** for ideas or feedback & Submit PRs once the code is live
 5. **Share** the screenshot on X ⁄ Twitter with `#DreamLayerAI` to spread the word.
@@ -215,6 +209,7 @@ Full docs will ship with the first code release.
 
 [DreamLayer AI - Documentation](https://dreamlayer-ai.github.io/DreamLayer/)
 
+
 ---
 
 ## License
diff --git a/docs/api_reference.md b/docs/api_reference.md
index adb0f0eb..7840133d 100644
--- a/docs/api_reference.md
+++ b/docs/api_reference.md
@@ -9,7 +9,6 @@ Complete API documentation for DreamLayer AI based on the actual codebase implem
 #### Models Management
 
 **GET `/api/models`** - Get available checkpoint models
-
 ```python
 # [Source: dream_layer.py lines 150-180]
 def get_available_models():
@@ -20,24 +19,22 @@ def get_available_models():
 ```
 
 **Response Format:**
-
 ```json
 {
-  "status": "success",
-  "models": [
-    {
-      "id": "model_filename.safetensors",
-      "name": "Model Display Name",
-      "filename": "model_filename.safetensors"
-    }
-  ]
+    "status": "success",
+    "models": [
+        {
+            "id": "model_filename.safetensors",
+            "name": "Model Display Name",
+            "filename": "model_filename.safetensors"
+        }
+    ]
 }
 ```
 
 #### LoRA Models
 
 **GET `/api/lora-models`** - Get available LoRA models
-
 ```python
 # [Source: dream_layer.py lines 271-293]
 def get_available_lora_models():
@@ -50,7 +47,6 @@ def get_available_lora_models():
 #### Upscaler Models
 
 **GET `/api/upscaler-models`** - Get available upscaler models
-
 ```python
 # [Source: dream_layer.py lines 323-329]
 def get_upscaler_models_endpoint():
@@ -63,7 +59,6 @@ def get_upscaler_models_endpoint():
 #### ControlNet Models
 
 **GET `/api/controlnet/models`** - Get available ControlNet models
-
 ```python
 # [Source: dream_layer.py lines 466-486]
 def get_controlnet_models_endpoint():
@@ -76,7 +71,6 @@ def get_controlnet_models_endpoint():
 #### Settings Management
 
 **POST `/api/settings/paths`** - Configure output and models directories
-
 ```python
 # [Source: dream_layer.py lines 200-226]
 def handle_path_settings():
@@ -87,18 +81,16 @@ def handle_path_settings():
 ```
 
 **Request Format:**
-
 ```json
 {
-  "outputDirectory": "/path/to/output",
-  "modelsDirectory": "/path/to/models"
+    "outputDirectory": "/path/to/output",
+    "modelsDirectory": "/path/to/models"
 }
 ```
 
 #### Prompt Generation
 
 **GET `/api/fetch-prompt`** - Get random positive and negative prompts
-
 ```python
 # [Source: dream_layer.py lines 311-322]
 def fetch_prompt():
@@ -111,7 +103,6 @@ def fetch_prompt():
 #### File Operations
 
 **POST `/api/show-in-folder`** - Open file in system file manager
-
 ```python
 # [Source: dream_layer.py lines 330-363]
 def show_in_folder():
@@ -122,7 +113,6 @@ def show_in_folder():
 ```
 
 **POST `/api/send-to-img2img`** - Send image to img2img workflow
-
 ```python
 # [Source: dream_layer.py lines 364-381]
 def send_to_img2img():
@@ -133,7 +123,6 @@ def send_to_img2img():
 ```
 
 **POST `/api/send-to-extras`** - Send image to extras workflow
-
 ```python
 # [Source: dream_layer.py lines 382-405]
 def send_to_extras():
@@ -146,7 +135,6 @@ def send_to_extras():
 #### File Upload
 
 **POST `/api/upload-model`** - Upload model files to ComfyUI models directory
-
 ```python
 # [Source: dream_layer.py lines 456-481]
 def upload_model():
@@ -158,7 +146,6 @@ def upload_model():
 ```
 
 **Request Format:**
-
 ```
 Content-Type: multipart/form-data
 
@@ -167,22 +154,20 @@ model_type: checkpoints|loras|controlnet|upscale_models|vae|embeddings|hypernetw
 ```
 
 **Response Format:**
-
 ```json
 {
-  "status": "success",
-  "filename": "timestamped_filename.safetensors",
-  "original_filename": "original_name.safetensors",
-  "display_name": "Original Name",
-  "model_type": "checkpoints",
-  "filepath": "/path/to/saved/file",
-  "size": 1234567890,
-  "message": "Model uploaded successfully to checkpoints"
+    "status": "success",
+    "filename": "timestamped_filename.safetensors",
+    "original_filename": "original_name.safetensors",
+    "display_name": "Original Name",
+    "model_type": "checkpoints",
+    "filepath": "/path/to/saved/file",
+    "size": 1234567890,
+    "message": "Model uploaded successfully to checkpoints"
 }
 ```
 
 **POST `/api/upload-controlnet-image`** - Upload ControlNet image
-
 ```python
 # [Source: dream_layer.py lines 406-448]
 def upload_controlnet_image():
@@ -196,7 +181,6 @@ def upload_controlnet_image():
 #### Image Serving
 
 **GET `/api/images/<filename>`** - Serve generated images
-
 ```python
 # [Source: dream_layer.py lines 449-465]
 def serve_image(filename):
@@ -212,7 +196,6 @@ def serve_image(filename):
 ### Directory Management
 
 **`get_directories()`** - Get output and models directories
-
 ```python
 # [Source: dream_layer.py lines 35-75]
 def get_directories() -> Tuple[str, Optional[str]]:
@@ -225,7 +208,6 @@ def get_directories() -> Tuple[str, Optional[str]]:
 ### ComfyUI Integration
 
 **`import_comfyui_main()`** - Import ComfyUI main module
-
 ```python
 # [Source: dream_layer.py lines 77-95]
 def import_comfyui_main():
@@ -238,7 +220,6 @@ def import_comfyui_main():
 ### Settings Management
 
 **`save_settings(settings)`** - Save path settings to file
-
 ```python
 # [Source: dream_layer.py lines 182-190]
 def save_settings(settings):
@@ -254,7 +235,6 @@ def save_settings(settings):
 ### ComfyUI Server
 
 **`start_comfy_server()`** - Start ComfyUI server in background
-
 ```python
 # [Source: dream_layer.py lines 227-265]
 def start_comfy_server():
@@ -267,7 +247,6 @@ def start_comfy_server():
 ### Flask Server
 
 **`start_flask_server()`** - Start Flask API server
-
 ```python
 # [Source: dream_layer.py lines 266-270]
 def start_flask_server():
@@ -293,10 +272,6 @@ API_KEY_TO_MODELS = {
     ],
     "IDEOGRAM_API_KEY": [
         {"id": "ideogram-v3", "name": "Ideogram V3", "filename": "ideogram-v3"},
-    ],
-    "STABILITY_API_KEY": [
-        {"id": "stability-sdxl", "name": "Stability SDXL", "filename": "stability-sdxl"},
-        {"id": "stability-sd-turbo", "name": "Stability SD Turbo", "filename": "stability-sd-turbo"},
     ]
 }
 ```
@@ -320,4 +295,4 @@ CORS(app, resources={
 
 - [Architecture Overview](architecture.md) - System design and component relationships
 - [Usage Guide](usage.md) - How to use the API endpoints
-- [Installation Guide](installation.md) - Setup and configuration instructions
+- [Installation Guide](installation.md) - Setup and configuration instructions 
\ No newline at end of file
diff --git a/docs/installation.md b/docs/installation.md
index eb95bdf4..ba690cae 100644
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -5,7 +5,6 @@ Complete, OS-agnostic installation guide for DreamLayer AI with GPU/CPU setup in
 ## 📋 System Requirements
 
 ### Minimum Requirements
-
 - **OS:** Windows 10+, macOS 10.15+, or Linux (Ubuntu 18.04+)
 - **Python:** 3.8 or higher
 - **Node.js:** 16.0 or higher
@@ -13,14 +12,12 @@ Complete, OS-agnostic installation guide for DreamLayer AI with GPU/CPU setup in
 - **Storage:** 10GB free space
 
 ### Recommended Requirements
-
 - **GPU:** NVIDIA RTX 3060+ (8GB+ VRAM) or Apple Silicon M1+
 - **RAM:** 16GB or higher
 - **Storage:** 50GB+ free space (for models)
 - **Network:** Stable internet connection for model downloads
 
 ### GPU Support
-
 - **NVIDIA:** CUDA 11.8+ with compatible drivers
 - **Apple Silicon:** Native MPS acceleration
 - **AMD:** ROCm support (experimental)
@@ -31,14 +28,12 @@ Complete, OS-agnostic installation guide for DreamLayer AI with GPU/CPU setup in
 ### 1. Install Python
 
 **Windows:**
-
 ```bash
 # Download from python.org or use winget
 winget install Python.Python.3.11
 ```
 
 **macOS:**
-
 ```bash
 # Using Homebrew
 brew install python@3.11
@@ -47,7 +42,6 @@ brew install python@3.11
 ```
 
 **Linux (Ubuntu/Debian):**
-
 ```bash
 sudo apt update
 sudo apt install python3.11 python3.11-pip python3.11-venv
@@ -56,14 +50,12 @@ sudo apt install python3.11 python3.11-pip python3.11-venv
 ### 2. Install Node.js
 
 **Windows:**
-
 ```bash
 # Download from nodejs.org or use winget
 winget install OpenJS.NodeJS
 ```
 
 **macOS:**
-
 ```bash
 # Using Homebrew
 brew install node
@@ -72,7 +64,6 @@ brew install node
 ```
 
 **Linux (Ubuntu/Debian):**
-
 ```bash
 curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash -
 sudo apt-get install -y nodejs
@@ -81,14 +72,12 @@ sudo apt-get install -y nodejs
 ### 3. Install Git
 
 **Windows:**
-
 ```bash
 # Download from git-scm.com or use winget
 winget install Git.Git
 ```
 
 **macOS:**
-
 ```bash
 # Using Homebrew
 brew install git
@@ -97,7 +86,6 @@ brew install git
 ```
 
 **Linux (Ubuntu/Debian):**
-
 ```bash
 sudo apt install git
 ```
@@ -107,7 +95,6 @@ sudo apt install git
 ### Method 1: Automated Installation (Recommended)
 
 #### macOS/Linux
-
 ```bash
 # Clone the repository
 git clone https://github.com/DreamLayer-AI/DreamLayer.git
@@ -122,7 +109,6 @@ chmod +x start_dream_layer.sh
 ```
 
 #### Windows
-
 ```bash
 # Clone the repository
 git clone https://github.com/DreamLayer-AI/DreamLayer.git
@@ -135,14 +121,12 @@ install_windows_dependencies.bat
 ### Method 2: Manual Installation
 
 #### 1. Clone Repository
-
 ```bash
 git clone https://github.com/DreamLayer-AI/DreamLayer.git
 cd DreamLayer
 ```
 
 #### 2. Install Python Dependencies
-
 ```bash
 # Create virtual environment
 python -m venv venv
@@ -158,7 +142,6 @@ pip install -r requirements.txt
 ```
 
 #### 3. Install Node.js Dependencies
-
 ```bash
 cd dream_layer_frontend
 npm install
@@ -166,7 +149,6 @@ cd ..
 ```
 
 #### 4. Setup ComfyUI
-
 ```bash
 # ComfyUI should be included in the repository
 # If not, clone it manually:
@@ -184,7 +166,6 @@ Create a `.env` file in the root directory:
 OPENAI_API_KEY=your_openai_api_key_here
 IDEOGRAM_API_KEY=your_ideogram_api_key_here
 BFL_API_KEY=your_bfl_api_key_here
-STABILITY_API_KEY=your_stability_api_key_here
 
 # Server Configuration
 FLASK_PORT=5000
@@ -205,7 +186,6 @@ Set up your directories in the web interface:
 ### 3. Model Setup
 
 #### Download Models
-
 ```bash
 # Create models directory
 mkdir -p models/checkpoints
@@ -219,7 +199,6 @@ wget https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pru
 ```
 
 #### Supported Model Formats
-
 - **Checkpoints:** `.safetensors`, `.ckpt`
 - **LoRA:** `.safetensors`, `.pt`
 - **ControlNet:** `.safetensors`, `.pth`
@@ -230,13 +209,11 @@ wget https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pru
 ### Automated Start
 
 **macOS/Linux:**
-
 ```bash
 ./start_dream_layer.sh
 ```
 
 **Windows:**
-
 ```bash
 start_dream_layer.bat
 ```
@@ -244,21 +221,18 @@ start_dream_layer.bat
 ### Manual Start
 
 #### 1. Start ComfyUI Server
-
 ```bash
 cd ComfyUI
 python main.py --listen 0.0.0.0 --port 8188
 ```
 
 #### 2. Start Flask API Server
-
 ```bash
 cd dream_layer_backend
 python dream_layer.py
 ```
 
 #### 3. Start Frontend Development Server
-
 ```bash
 cd dream_layer_frontend
 npm run dev
@@ -267,7 +241,6 @@ npm run dev
 ### Access DreamLayer
 
 Open your browser and navigate to:
-
 - **Frontend:** http://localhost:8080
 - **API:** http://localhost:5000
 - **ComfyUI:** http://localhost:8188
@@ -277,14 +250,12 @@ Open your browser and navigate to:
 ### Check Installation
 
 1. **Verify Python packages:**
-
    ```bash
    python -c "import torch; print(f'PyTorch: {torch.__version__}')"
    python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
    ```
 
 2. **Verify Node.js packages:**
-
    ```bash
    cd dream_layer_frontend
    npm list --depth=0
@@ -306,14 +277,12 @@ Open your browser and navigate to:
 ### Common Issues
 
 #### Python Import Errors
-
 ```bash
 # Reinstall packages
 pip install --force-reinstall -r requirements.txt
 ```
 
 #### CUDA Issues
-
 ```bash
 # Check CUDA installation
 nvidia-smi
@@ -324,7 +293,6 @@ pip install torch torchvision torchaudio --index-url https://download.pytorch.or
 ```
 
 #### Port Conflicts
-
 ```bash
 # Check port usage
 netstat -tulpn | grep :8080
@@ -336,7 +304,6 @@ kill -9 <PID>
 ```
 
 #### Memory Issues
-
 ```bash
 # Reduce batch size in settings
 # Use CPU mode for testing
@@ -352,7 +319,6 @@ kill -9 <PID>
 ## 🔄 Updates
 
 ### Updating DreamLayer
-
 ```bash
 # Pull latest changes
 git pull origin main
@@ -362,7 +328,6 @@ git pull origin main
 ```
 
 ### Updating Models
-
 ```bash
 # Models are automatically detected on restart
 # Or refresh in the web interface
@@ -370,4 +335,4 @@ git pull origin main
 
 ---
 
-_Need help? Check out the [Quick Start Guide](quick_start.md) for a faster setup._
+*Need help? Check out the [Quick Start Guide](quick_start.md) for a faster setup.* 
\ No newline at end of file
diff --git a/docs/modules/utils.md b/docs/modules/utils.md
index 20a70efd..4f9df258 100644
--- a/docs/modules/utils.md
+++ b/docs/modules/utils.md
@@ -15,51 +15,44 @@ Handles secure API key management for external services.
 #### Key Functions
 
 **`read_api_keys_from_env()`**
-
 ```python
 def read_api_keys_from_env():
     """
     Read API keys from environment variables
-
+    
     Returns:
         dict: Dictionary of API key names and values
     """
     api_keys = {}
-
+    
     # Check for OpenAI API key
     openai_key = os.getenv('OPENAI_API_KEY')
     if openai_key:
         api_keys['OPENAI_API_KEY'] = openai_key
-
+    
     # Check for Ideogram API key
     ideogram_key = os.getenv('IDEOGRAM_API_KEY')
     if ideogram_key:
         api_keys['IDEOGRAM_API_KEY'] = ideogram_key
-
+    
     # Check for BFL API key
     bfl_key = os.getenv('BFL_API_KEY')
     if bfl_key:
         api_keys['BFL_API_KEY'] = bfl_key
-
-    # Check for Stability AI API key
-    stability_key = os.getenv('STABILITY_API_KEY')
-    if stability_key:
-        api_keys['STABILITY_API_KEY'] = stability_key
-
+    
     return api_keys
 ```
 
 **`validate_api_key(api_key, service)`**
-
 ```python
 def validate_api_key(api_key: str, service: str):
     """
     Validate API key format for specific service
-
+    
     Parameters:
         api_key (str): API key to validate
         service (str): Service name (openai, ideogram, bfl)
-
+    
     Returns:
         bool: True if valid, False otherwise
     """
@@ -72,72 +65,67 @@ Manages model discovery and loading from various sources.
 #### Key Functions
 
 **`get_lora_models(models_dir)`**
-
 ```python
 def get_lora_models(models_dir: str):
     """
     Fetch available LoRA models from the models directory
-
+    
     Parameters:
         models_dir (str): Path to models directory
-
+    
     Returns:
         list: List of LoRA model objects
     """
 ```
 
 **`get_settings()`**
-
 ```python
 def get_settings():
     """
     Load application settings from settings.json
-
+    
     Returns:
         dict: Application settings
     """
 ```
 
 **`is_valid_directory(path)`**
-
 ```python
 def is_valid_directory(path: str):
     """
     Check if a directory path is valid and accessible
-
+    
     Parameters:
         path (str): Directory path to validate
-
+    
     Returns:
         bool: True if valid, False otherwise
     """
 ```
 
 **`get_upscaler_models(models_dir)`**
-
 ```python
 def get_upscaler_models(models_dir: str):
     """
     Fetch available upscaler models from the models directory
-
+    
     Parameters:
         models_dir (str): Path to models directory
-
+    
     Returns:
         list: List of upscaler model objects
     """
 ```
 
 **`get_controlnet_models(models_dir)`**
-
 ```python
 def get_controlnet_models(models_dir: str):
     """
     Fetch available ControlNet models from the models directory
-
+    
     Parameters:
         models_dir (str): Path to models directory
-
+    
     Returns:
         list: List of ControlNet model objects
     """
@@ -150,39 +138,36 @@ Generates random prompts for inspiration and testing.
 #### Key Functions
 
 **`fetch_positive_prompt()`**
-
 ```python
 def fetch_positive_prompt():
     """
     Fetch a random positive prompt from the prompt database
-
+    
     Returns:
         str: Random positive prompt
     """
 ```
 
 **`fetch_negative_prompt()`**
-
 ```python
 def fetch_negative_prompt():
     """
     Fetch a random negative prompt from the prompt database
-
+    
     Returns:
         str: Random negative prompt
     """
 ```
 
 **`load_prompts_from_file(file_path)`**
-
 ```python
 def load_prompts_from_file(file_path: str):
     """
     Load prompts from a text file
-
+    
     Parameters:
         file_path (str): Path to prompt file
-
+    
     Returns:
         list: List of prompts from file
     """
@@ -195,36 +180,312 @@ Handles file system operations and image processing.
 #### Key Functions
 
 **`save_image(image_data, filename, output_dir)`**
-
 ```python
 def save_image(image_data: bytes, filename: str, output_dir: str):
     """
     Save image data to file system
-
+    
     Parameters:
         image_data (bytes): Image data to save
         filename (str): Output filename
         output_dir (str): Output directory path
-
+    
     Returns:
         str: Path to saved image file
     """
 ```
 
 **`copy_file_to_directory(source_path, target_dir)`**
-
 ```python
 def copy_file_to_directory(source_path: str, target_dir: str):
     """
     Copy a file to a target directory
-
+    
     Parameters:
         source_path (str): Source file path
         target_dir (str): Target directory path
-
+    
     Returns:
         str: Path to copied file
     """
 ```
 
-\*\*`
+**`open_file_in_explorer(file_path)`**
+```python
+def open_file_in_explorer(file_path: str):
+    """
+    Open file in system file explorer
+    
+    Parameters:
+        file_path (str): Path to file to open
+    
+    Returns:
+        bool: True if successful, False otherwise
+    """
+```
+
+## Configuration Management
+
+### Settings Structure
+
+```python
+# Default settings structure
+DEFAULT_SETTINGS = {
+    "outputDirectory": "Dream_Layer_Resources/output",
+    "modelsDirectory": None,
+    "serverPort": 5000,
+    "comfyuiPort": 8188,
+    "frontendPort": 8080,
+    "enableLogging": True,
+    "logLevel": "INFO"
+}
+```
+
+### Settings Loading
+
+```python
+def load_settings():
+    """
+    Load settings from settings.json file
+    
+    Returns:
+        dict: Application settings
+    """
+    settings_file = os.path.join(os.path.dirname(__file__), 'settings.json')
+    
+    try:
+        with open(settings_file, 'r') as f:
+            settings = json.load(f)
+        return settings
+    except FileNotFoundError:
+        # Return default settings if file doesn't exist
+        return DEFAULT_SETTINGS.copy()
+    except json.JSONDecodeError:
+        print("Error: Invalid settings.json file")
+        return DEFAULT_SETTINGS.copy()
+```
+
+### Settings Saving
+
+```python
+def save_settings(settings: dict):
+    """
+    Save settings to settings.json file
+    
+    Parameters:
+        settings (dict): Settings to save
+    
+    Returns:
+        bool: True if successful, False otherwise
+    """
+    settings_file = os.path.join(os.path.dirname(__file__), 'settings.json')
+    
+    try:
+        with open(settings_file, 'w') as f:
+            json.dump(settings, f, indent=2)
+        return True
+    except Exception as e:
+        print(f"Error saving settings: {e}")
+        return False
+```
+
+## Model Management
+
+### Model Discovery
+
+```python
+def discover_models(models_dir: str, model_type: str):
+    """
+    Discover models of specific type in directory
+    
+    Parameters:
+        models_dir (str): Models directory path
+        model_type (str): Type of models to discover (checkpoint, lora, etc.)
+    
+    Returns:
+        list: List of discovered model files
+    """
+    if not models_dir or not os.path.exists(models_dir):
+        return []
+    
+    model_extensions = {
+        'checkpoint': ['.safetensors', '.ckpt'],
+        'lora': ['.safetensors', '.pt'],
+        'controlnet': ['.safetensors', '.pth'],
+        'upscaler': ['.pth', '.bin']
+    }
+    
+    extensions = model_extensions.get(model_type, [])
+    models = []
+    
+    for file in os.listdir(models_dir):
+        if any(file.endswith(ext) for ext in extensions):
+            models.append(file)
+    
+    return models
+```
+
+### Model Validation
+
+```python
+def validate_model_file(file_path: str):
+    """
+    Validate model file integrity
+    
+    Parameters:
+        file_path (str): Path to model file
+    
+    Returns:
+        dict: Validation result with status and details
+    """
+    if not os.path.exists(file_path):
+        return {"valid": False, "error": "File not found"}
+    
+    file_size = os.path.getsize(file_path)
+    if file_size == 0:
+        return {"valid": False, "error": "File is empty"}
+    
+    # Check file extension
+    valid_extensions = ['.safetensors', '.ckpt', '.pt', '.pth', '.bin']
+    if not any(file_path.endswith(ext) for ext in valid_extensions):
+        return {"valid": False, "error": "Invalid file extension"}
+    
+    return {"valid": True, "file_size": file_size}
+```
+
+## Error Handling
+
+### Utility Error Classes
+
+```python
+class ModelError(Exception):
+    """Raised when there's an error with model operations"""
+    pass
+
+class APIKeyError(Exception):
+    """Raised when there's an error with API key management"""
+    pass
+
+class FileOperationError(Exception):
+    """Raised when there's an error with file operations"""
+    pass
+```
+
+### Error Handling Functions
+
+```python
+def handle_model_error(error: Exception, model_name: str):
+    """
+    Handle model-related errors
+    
+    Parameters:
+        error (Exception): The error that occurred
+        model_name (str): Name of the model that caused the error
+    
+    Returns:
+        dict: Error response with details
+    """
+    return {
+        "status": "error",
+        "type": "model_error",
+        "model": model_name,
+        "message": str(error),
+        "timestamp": time.time()
+    }
+
+def handle_api_error(error: Exception, service: str):
+    """
+    Handle API-related errors
+    
+    Parameters:
+        error (Exception): The error that occurred
+        service (str): Name of the service that caused the error
+    
+    Returns:
+        dict: Error response with details
+    """
+    return {
+        "status": "error",
+        "type": "api_error",
+        "service": service,
+        "message": str(error),
+        "timestamp": time.time()
+    }
+```
+
+## Logging and Monitoring
+
+### Logging Configuration
+
+```python
+def setup_logging(log_level: str = "INFO"):
+    """
+    Setup logging configuration
+    
+    Parameters:
+        log_level (str): Logging level (DEBUG, INFO, WARNING, ERROR)
+    """
+    logging.basicConfig(
+        level=getattr(logging, log_level.upper()),
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            logging.FileHandler('logs/dream_layer.log'),
+            logging.StreamHandler()
+        ]
+    )
+```
+
+### Performance Monitoring
+
+```python
+def monitor_function_performance(func):
+    """
+    Decorator to monitor function performance
+    
+    Parameters:
+        func: Function to monitor
+    
+    Returns:
+        Wrapped function with performance monitoring
+    """
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        try:
+            result = func(*args, **kwargs)
+            execution_time = time.time() - start_time
+            logging.info(f"{func.__name__} executed in {execution_time:.2f} seconds")
+            return result
+        except Exception as e:
+            execution_time = time.time() - start_time
+            logging.error(f"{func.__name__} failed after {execution_time:.2f} seconds: {e}")
+            raise
+    
+    return wrapper
+```
+
+## Best Practices
+
+### API Key Security
+
+1. **Environment Variables** - Store API keys in environment variables, not in code
+2. **Validation** - Always validate API keys before use
+3. **Rotation** - Regularly rotate API keys for security
+4. **Logging** - Never log API keys in plain text
+
+### File Operations
+
+1. **Path Validation** - Always validate file paths before operations
+2. **Error Handling** - Implement proper error handling for file operations
+3. **Permissions** - Check file permissions before read/write operations
+4. **Cleanup** - Clean up temporary files after use
+
+### Model Management
+
+1. **Validation** - Validate model files before loading
+2. **Caching** - Cache model metadata for faster discovery
+3. **Fallbacks** - Provide fallback models when primary models fail
+4. **Monitoring** - Monitor model loading times and errors
+
+---
+
+*For more details, see the [API Reference](../api_reference.md) and [Architecture Guide](../architecture.md).* 
\ No newline at end of file
diff --git a/docs/usage.md b/docs/usage.md
index 4e25d91c..f49a7b60 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -29,13 +29,11 @@ Learn how to use DreamLayer AI effectively with API examples, workflow managemen
 ### Core Endpoints
 
 #### Get Available Models
-
 ```bash
 curl -X GET http://localhost:5000/api/models
 ```
 
 **Response:**
-
 ```json
 {
   "status": "success",
@@ -55,31 +53,26 @@ curl -X GET http://localhost:5000/api/models
 ```
 
 #### Get LoRA Models
-
 ```bash
 curl -X GET http://localhost:5000/api/lora-models
 ```
 
 #### Get Upscaler Models
-
 ```bash
 curl -X GET http://localhost:5000/api/upscaler-models
 ```
 
 #### Get ControlNet Models
-
 ```bash
 curl -X GET http://localhost:5000/api/controlnet/models
 ```
 
 #### Fetch Random Prompts
-
 ```bash
 curl -X GET http://localhost:5000/api/fetch-prompt
 ```
 
 **Response:**
-
 ```json
 {
   "positive": "A majestic dragon soaring through clouds",
@@ -90,14 +83,12 @@ curl -X GET http://localhost:5000/api/fetch-prompt
 ### File Operations
 
 #### Upload ControlNet Image
-
 ```bash
 curl -X POST http://localhost:5000/api/upload-controlnet-image \
   -F "image=@path/to/your/image.png"
 ```
 
 **Response:**
-
 ```json
 {
   "status": "success",
@@ -106,7 +97,6 @@ curl -X POST http://localhost:5000/api/upload-controlnet-image \
 ```
 
 #### Send Image to img2img
-
 ```bash
 curl -X POST http://localhost:5000/api/send-to-img2img \
   -H "Content-Type: application/json" \
@@ -114,7 +104,6 @@ curl -X POST http://localhost:5000/api/send-to-img2img \
 ```
 
 #### Send Image to Extras
-
 ```bash
 curl -X POST http://localhost:5000/api/send-to-extras \
   -H "Content-Type: application/json" \
@@ -122,7 +111,6 @@ curl -X POST http://localhost:5000/api/send-to-extras \
 ```
 
 #### Show Image in Folder
-
 ```bash
 curl -X POST http://localhost:5000/api/show-in-folder \
   -H "Content-Type: application/json" \
@@ -132,7 +120,6 @@ curl -X POST http://localhost:5000/api/show-in-folder \
 ### Settings Management
 
 #### Configure Paths
-
 ```bash
 curl -X POST http://localhost:5000/api/settings/paths \
   -H "Content-Type: application/json" \
@@ -180,7 +167,7 @@ import requests
 
 # DALL-E 3 generation
 def generate_dalle3(prompt, api_key):
-    response = requests.post('https://api.openai.com/v1/images/generations',
+    response = requests.post('https://api.openai.com/v1/images/generations', 
         headers={'Authorization': f'Bearer {api_key}'},
         json={
             'model': 'dall-e-3',
@@ -226,7 +213,7 @@ response = requests.post('http://localhost:8188/prompt', json={
 # Upload ControlNet image
 with open('control_image.png', 'rb') as f:
     files = {'image': f}
-    response = requests.post('http://localhost:5000/api/upload-controlnet-image',
+    response = requests.post('http://localhost:5000/api/upload-controlnet-image', 
                            files=files)
 
 controlnet_image = response.json()['filename']
@@ -290,7 +277,6 @@ Set up API keys for cloud models:
 OPENAI_API_KEY=your_openai_api_key_here
 IDEOGRAM_API_KEY=your_ideogram_api_key_here
 BFL_API_KEY=your_bfl_api_key_here
-STABILITY_API_KEY=your_stability_api_key_here
 ```
 
 ### Directory Structure
@@ -407,4 +393,4 @@ except Exception as e:
 
 ---
 
-_For more advanced usage, see the [API Reference](api_reference.md) and [Architecture Guide](architecture.md)._
+*For more advanced usage, see the [API Reference](api_reference.md) and [Architecture Guide](architecture.md).* 
\ No newline at end of file
diff --git a/dream_layer_backend/controlnet.py b/dream_layer_backend/controlnet.py
index 8d3913bd..f88e193b 100644
--- a/dream_layer_backend/controlnet.py
+++ b/dream_layer_backend/controlnet.py
@@ -1,7 +1,9 @@
 import os
+import base64
+import traceback
+import time
 from PIL import Image, ImageDraw
 
-
 def save_controlnet_image(image_data, unit_index):
     """
     Save uploaded ControlNet image to ComfyUI input directory.
@@ -28,10 +30,6 @@ def save_controlnet_image(image_data, unit_index):
         os.makedirs(input_dir, exist_ok=True)
         print(f"✅ Directory exists: {os.path.exists(input_dir)}")
         
-        # Generate unique filename
-        import base64
-        import time
-        
         # Create a unique filename based on timestamp and unit index
         timestamp = int(time.time() * 1000)
         filename = f"controlnet_unit_{unit_index}_{timestamp}.png"
@@ -65,7 +63,6 @@ def save_controlnet_image(image_data, unit_index):
                 
             except Exception as decode_error:
                 print(f"❌ Error decoding base64 image: {decode_error}")
-                import traceback
                 traceback.print_exc()
                 return None
         else:
@@ -78,7 +75,6 @@ def save_controlnet_image(image_data, unit_index):
         
     except Exception as e:
         print(f"❌ Error saving ControlNet image: {str(e)}")
-        import traceback
         traceback.print_exc()
         return None
 
@@ -112,6 +108,5 @@ def create_test_controlnet_image():
         
     except Exception as e:
         print(f"❌ Error creating test ControlNet image: {str(e)}")
-        import traceback
         traceback.print_exc()
         return False
\ No newline at end of file
diff --git a/dream_layer_backend/dream_layer.py b/dream_layer_backend/dream_layer.py
index d5fb2a05..9e2e85d7 100644
--- a/dream_layer_backend/dream_layer.py
+++ b/dream_layer_backend/dream_layer.py
@@ -7,10 +7,18 @@
 from flask import Flask, jsonify, request, send_from_directory
 from flask_cors import CORS
 import requests
+import importlib.util
 import json
 import subprocess
+import traceback
+from shared_utils import SERVED_IMAGES_DIR, MATRIX_GRIDS_DIR
 from dream_layer_backend_utils.random_prompt_generator import fetch_positive_prompt, fetch_negative_prompt
 from dream_layer_backend_utils.fetch_advanced_models import get_lora_models, get_settings, is_valid_directory, get_upscaler_models, get_controlnet_models
+from dream_layer_backend_utils import read_api_keys_from_env
+import base64
+import io
+from PIL import Image
+
 # Add ComfyUI directory to Python path
 current_dir = os.path.dirname(os.path.abspath(__file__))
 parent_dir = os.path.dirname(current_dir)
@@ -29,6 +37,7 @@
     ],
     "IDEOGRAM_API_KEY": [
         {"id": "ideogram-v3", "name": "Ideogram V3", "filename": "ideogram-v3"},
+
     ],
     "STABILITY_API_KEY": [
         {"id": "stability-sdxl", "name": "Stability SDXL",
@@ -46,30 +55,27 @@
     ]
 }
 
-
 def get_directories() -> Tuple[str, Optional[str]]:
     """Get the absolute paths to the output and models directories from settings"""
     settings = get_settings()
-
+    
     # Handle output directory
     output_dir = settings.get('outputDirectory')
-
+    
     # Validate output directory
     if not is_valid_directory(output_dir):
         print("\nWarning: Invalid output directory (starts with '/path')")
-        output_dir = os.path.join(
-            parent_dir, 'Dream_Layer_Resources', 'output')
+        output_dir = os.path.join(parent_dir, 'Dream_Layer_Resources', 'output')
         print(f"Using default output directory: {output_dir}")
-
+    
     # If output directory is not an absolute path, make it relative to parent_dir
     if output_dir and not os.path.isabs(output_dir):
         output_dir = os.path.join(parent_dir, output_dir)
-
+    
     # If no output directory specified, use default
     if not output_dir:
-        output_dir = os.path.join(
-            parent_dir, 'Dream_Layer_Resources', 'output')
-
+        output_dir = os.path.join(parent_dir, 'Dream_Layer_Resources', 'output')
+    
     # Ensure output directory is absolute and exists
     output_dir = os.path.abspath(output_dir)
     os.makedirs(output_dir, exist_ok=True)
@@ -77,7 +83,7 @@ def get_directories() -> Tuple[str, Optional[str]]:
 
     # Handle models directory
     models_dir = settings.get('modelsDirectory')
-
+    
     # Validate models directory
     if not is_valid_directory(models_dir):
         print("\nWarning: Invalid models directory (starts with '/path')")
@@ -85,10 +91,9 @@ def get_directories() -> Tuple[str, Optional[str]]:
     elif models_dir:
         models_dir = os.path.abspath(models_dir)
         print(f"Using models directory: {models_dir}")
-
+    
     return output_dir, models_dir
 
-
 # Set directories before importing ComfyUI
 output_dir, models_dir = get_directories()
 sys.argv.extend(['--output-directory', output_dir])
@@ -105,17 +110,13 @@ def get_directories() -> Tuple[str, Optional[str]]:
 sys.argv.extend(['--enable-cors-header', cors_origin])
 
 # Only add ComfyUI to path if it exists and we need to start the server
-
-
 def import_comfyui_main():
     """Import ComfyUI main module only when needed"""
     if comfyui_dir not in sys.path:
         sys.path.append(comfyui_dir)
-
+    
     try:
-        import importlib.util
-        spec = importlib.util.spec_from_file_location(
-            "comfyui_main", os.path.join(comfyui_dir, "main.py"))
+        spec = importlib.util.spec_from_file_location("comfyui_main", os.path.join(comfyui_dir, "main.py"))
         if spec is None or spec.loader is None:
             print("Error: Could not create module spec for ComfyUI main.py")
             return None
@@ -127,7 +128,6 @@ def import_comfyui_main():
         print(f"Current Python path: {sys.path}")
         return None
 
-
 # Create Flask app
 app = Flask(__name__)
 
@@ -144,14 +144,13 @@ def import_comfyui_main():
 
 COMFY_API_URL = "http://127.0.0.1:8188"
 
-
 def get_available_models():
     """
     Fetch available checkpoint models from ComfyUI and append closed-source models
     """
     from shared_utils import get_model_display_name
     formatted_models = []
-
+    
     # Get ComfyUI models
     try:
         response = requests.get(f"{COMFY_API_URL}/models/checkpoints")
@@ -169,25 +168,23 @@ def get_available_models():
             print(f"Error fetching ComfyUI models: {response.status_code}")
     except Exception as e:
         print(f"Error fetching ComfyUI models: {str(e)}")
-
+    
     # Get closed-source models based on available API keys
     try:
         from dream_layer_backend_utils import read_api_keys_from_env
         api_keys = read_api_keys_from_env()
-
+        
         # Append models for each available API key
         for api_key_name, api_key_value in api_keys.items():
             if api_key_name in API_KEY_TO_MODELS:
                 formatted_models.extend(API_KEY_TO_MODELS[api_key_name])
-                print(
-                    f"Added {len(API_KEY_TO_MODELS[api_key_name])} models for {api_key_name}")
-
+                print(f"Added {len(API_KEY_TO_MODELS[api_key_name])} models for {api_key_name}")
+                
     except Exception as e:
         print(f"Error fetching closed-source models: {str(e)}")
-
+    
     return formatted_models
 
-
 @app.route('/api/models', methods=['GET'])
 def handle_get_models():
     """
@@ -205,12 +202,10 @@ def handle_get_models():
             "message": str(e)
         }), 500
 
-
 def save_settings(settings):
     """Save path settings to a file"""
     try:
-        settings_file = os.path.join(
-            os.path.dirname(__file__), 'settings.json')
+        settings_file = os.path.join(os.path.dirname(__file__), 'settings.json')
         with open(settings_file, 'w') as f:
             json.dump(settings, f, indent=2)
         print("Settings saved successfully")
@@ -219,7 +214,6 @@ def save_settings(settings):
         print(f"Error saving settings: {e}")
         return False
 
-
 @app.route('/api/settings/paths', methods=['POST'])
 def handle_path_settings():
     """Endpoint to handle path configuration settings"""
@@ -230,7 +224,7 @@ def handle_path_settings():
                 "status": "error",
                 "message": "No JSON data received"
             }), 400
-
+            
         print("\n=== Received Path Configuration Settings ===")
         print("Output Directory:", settings.get('outputDirectory'))
         print("Models Directory:", settings.get('modelsDirectory'))
@@ -244,8 +238,7 @@ def handle_path_settings():
 
         if save_settings(settings):
             # Execute the restart script
-            script_path = os.path.join(
-                os.path.dirname(__file__), 'restart_server.sh')
+            script_path = os.path.join(os.path.dirname(__file__), 'restart_server.sh')
             subprocess.Popen([script_path])
             return jsonify({
                 "status": "success",
@@ -261,31 +254,26 @@ def handle_path_settings():
             "message": str(e)
         }), 500
 
-
 def start_comfy_server():
     """Start the ComfyUI server"""
     try:
-        # Import ComfyUI main module
         start_comfyui = import_comfyui_main()
         if start_comfyui is None:
             print("Error: Could not import ComfyUI start_comfyui function")
             return False
-
-        # Change to ComfyUI directory
+        
         os.chdir(comfyui_dir)
-
-        # Start ComfyUI in a thread
+        
         def run_comfyui():
             loop, server, start_func = start_comfyui()
             x = start_func()
             loop.run_until_complete(x)
-
+        
         comfy_thread = threading.Thread(target=run_comfyui, daemon=True)
         comfy_thread.start()
-
-        # Wait for server to be ready
+        
         start_time = time.time()
-        while time.time() - start_time < 60:  # 60 second timeout
+        while time.time() - start_time < 60:
             try:
                 response = requests.get(COMFY_API_URL)
                 if response.status_code == 200:
@@ -293,32 +281,29 @@ def run_comfyui():
                     return True
             except requests.exceptions.ConnectionError:
                 time.sleep(1)
-
+        
         print("Error: ComfyUI server failed to start within the timeout period")
         return False
-
+        
     except Exception as e:
         print(f"Error starting ComfyUI server: {e}")
         return False
 
-
 def start_flask_server():
     """Start the Flask API server"""
     print("\nStarting Flask API server on http://localhost:5002")
     app.run(host='0.0.0.0', port=5002, debug=True, use_reloader=False)
 
-
 def get_available_lora_models():
     """
     Fetch available LoRA models from ComfyUI
     """
     from shared_utils import get_model_display_name
     formatted_models = []
-
+    
     try:
         models = get_lora_models()
-
-        # Convert filenames to more user-friendly names (using display name mapping when available)
+        
         for filename in models:
             name = get_model_display_name(filename)
             formatted_models.append({
@@ -328,16 +313,14 @@ def get_available_lora_models():
             })
     except Exception as e:
         print(f"Error fetching LoRA models: {str(e)}")
-
+    
     return formatted_models
 
-
 @app.route('/', methods=['GET'])
 def is_server_running():
     return jsonify({
         "status": "success"
-    })
-
+        })
 
 @app.route('/api/lora-models', methods=['GET'])
 def handle_get_lora_models():
@@ -355,8 +338,7 @@ def handle_get_lora_models():
             "status": "error",
             "message": str(e)
         }), 500
-
-
+        
 @app.route('/api/add-api-key', methods=['POST'])
 def add_api_key():
     """
@@ -371,11 +353,10 @@ def add_api_key():
         if not alias or not api_key:
             return jsonify({"status": "error", "message": "Missing alias or api_key"}), 400
 
-        env_path = os.path.join(os.path.dirname(
-            os.path.dirname(__file__)), '.env')
+        env_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), '.env')
         lines = []
         found = False
-
+        
         if os.path.exists(env_path):
             with open(env_path, 'r') as f:
                 lines = f.readlines()
@@ -397,29 +378,25 @@ def add_api_key():
     except Exception as e:
         return jsonify({"status": "error", "message": str(e)}), 500
 
-
 @app.route('/api/fetch-prompt', methods=['GET'])
 def fetch_prompt():
     """
     Endpoint to fetch random prompts
     """
-
+    
     prompt_type = request.args.get('type')
     print(f"🎯 FETCH PROMPT CALLED - Type: {prompt_type}")
-
+    
     prompt = fetch_positive_prompt() if prompt_type == 'positive' else fetch_negative_prompt()
     return jsonify({"status": "success", "prompt": prompt})
 
-
 @app.route('/api/upscaler-models', methods=['GET'])
 def get_upscaler_models_endpoint():
 
     models = get_upscaler_models()
-    formatted = [{"id": m, "name": m.replace(
-        '.pth', ''), "filename": m} for m in models]
+    formatted = [{"id": m, "name": m.replace('.pth', ''), "filename": m} for m in models]
     return jsonify({"status": "success", "models": formatted})
 
-
 @app.route('/api/show-in-folder', methods=['POST'])
 def show_in_folder():
     """Show image file in system file manager (cross-platform)"""
@@ -427,34 +404,65 @@ def show_in_folder():
         filename = request.json.get('filename')
         if not filename:
             return jsonify({"status": "error", "message": "No filename provided"}), 400
-
-        output_dir, _ = get_directories()
-        print(f"DEBUG: output_dir='{output_dir}', filename='{filename}'")
-        image_path = os.path.join(output_dir, filename)
-
-        if not os.path.exists(image_path):
+        
+        image_path = None
+        
+        if filename.startswith('matrix-grid'):
+            matrix_filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+            if os.path.exists(matrix_filepath):
+                image_path = matrix_filepath
+                print(f"🔍 Found matrix grid in permanent storage: {image_path}")
+        
+        if not image_path:
+            served_filepath = os.path.join(SERVED_IMAGES_DIR, filename)
+            if os.path.exists(served_filepath):
+                image_path = served_filepath
+                print(f"🔍 Found in served_images: {image_path}")
+        
+        if not image_path:
+            output_dir, _ = get_directories()
+            output_filepath = os.path.join(output_dir, filename)
+            if os.path.exists(output_filepath):
+                image_path = output_filepath
+                print(f"🔍 Found in output_dir: {image_path}")
+        
+        if not image_path and not filename.startswith('matrix-grid'):
+            matrix_filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+            if os.path.exists(matrix_filepath):
+                image_path = matrix_filepath
+                print(f"🔍 Found in matrix_grids (fallback): {image_path}")
+        
+        if not image_path:
+            print(f"❌ File not found: {filename}")
+            print(f"   Checked matrix_grids: {os.path.join(MATRIX_GRIDS_DIR, filename)}")
+            print(f"   Checked served_images: {os.path.join(SERVED_IMAGES_DIR, filename)}")
+            output_dir, _ = get_directories()
+            output_filepath = os.path.join(output_dir, filename)
+            print(f"   Checked output_dir: {output_filepath}")
             return jsonify({"status": "error", "message": "File not found"}), 404
-
-        # Detect operating system and use appropriate command
+        
         system = platform.system()
-
+        
         if system == "Darwin":  # macOS
-            subprocess.run(['open', '-R', image_path])
-            return jsonify({"status": "success", "message": f"Opened {filename} in Finder"})
-        elif system == "Windows":  # Windows
-            subprocess.run(['explorer', '/select,', image_path])
-            return jsonify({"status": "success", "message": f"Opened {filename} in File Explorer"})
-        elif system == "Linux":  # Linux
-            # Open the directory containing the file (can't highlight specific file reliably)
-            subprocess.run(['xdg-open', output_dir])
-            return jsonify({"status": "success", "message": f"Opened directory containing {filename}"})
+            subprocess.run(["open", "-R", image_path])
+        elif system == "Windows":
+            subprocess.run(["explorer", "/select,", image_path])
+        elif system == "Linux":
+            subprocess.run(["xdg-open", os.path.dirname(image_path)])
         else:
             return jsonify({"status": "error", "message": f"Unsupported operating system: {system}"}), 400
-
+        
+        return jsonify({
+            "status": "success", 
+            "message": f"Opened {filename} in file manager",
+            "path": image_path,
+            "storage": "permanent" if image_path.startswith(MATRIX_GRIDS_DIR) else "temporary"
+        })
+        
     except Exception as e:
+        print(f"❌ Error showing file in folder: {str(e)}")
         return jsonify({"status": "error", "message": str(e)}), 500
 
-
 @app.route('/api/send-to-img2img', methods=['POST'])
 def send_to_img2img():
     """Send image to img2img tab"""
@@ -462,95 +470,80 @@ def send_to_img2img():
         filename = request.json.get('filename')
         if not filename:
             return jsonify({"status": "error", "message": "No filename provided"}), 400
-
+        
         output_dir, _ = get_directories()
         image_path = os.path.join(output_dir, filename)
-
+        
         if not os.path.exists(image_path):
             return jsonify({"status": "error", "message": "File not found"}), 404
-
+            
         return jsonify({"status": "success", "message": "Image sent to img2img"})
     except Exception as e:
         return jsonify({"status": "error", "message": str(e)}), 500
 
-
 @app.route('/api/send-to-extras', methods=['POST', 'OPTIONS'])
 def send_to_extras():
     """Send image to extras tab"""
     if request.method == 'OPTIONS':
-        # Respond to preflight request
         response = jsonify({'status': 'ok'})
         response.headers.add('Access-Control-Allow-Methods', 'POST, OPTIONS')
         response.headers.add('Access-Control-Allow-Headers', 'Content-Type')
         return response
-
+        
     try:
         filename = request.json.get('filename')
         if not filename:
             return jsonify({"status": "error", "message": "No filename provided"}), 400
-
+        
         output_dir, _ = get_directories()
         image_path = os.path.join(output_dir, filename)
-
+        
         if not os.path.exists(image_path):
             return jsonify({"status": "error", "message": "File not found"}), 404
-
+            
         return jsonify({"status": "success", "message": "Image sent to extras"})
     except Exception as e:
         return jsonify({"status": "error", "message": str(e)}), 500
-
-
 @app.route('/api/upload-controlnet-image', methods=['POST'])
 def upload_controlnet_image():
-    """
-    Endpoint to upload ControlNet images directly to ComfyUI input directory
-    """
     try:
         if 'file' not in request.files:
             return jsonify({
                 "status": "error",
                 "message": "No file provided"
             }), 400
-
+        
         file = request.files['file']
         if file.filename == '':
             return jsonify({
                 "status": "error",
                 "message": "No file selected"
             }), 400
-
+        
         unit_index = request.form.get('unit_index', '0')
         try:
             unit_index = int(unit_index)
         except ValueError:
             unit_index = 0
-
-        # Use shared function
+        
         from shared_utils import upload_controlnet_image as upload_cn_image
         result = upload_cn_image(file, unit_index)
-
+        
         if isinstance(result, tuple):
             return jsonify(result[0]), result[1]
         else:
             return jsonify(result)
-
+            
     except Exception as e:
         print(f"❌ Error uploading ControlNet image: {str(e)}")
-        import traceback
         traceback.print_exc()
         return jsonify({
             "status": "error",
             "message": str(e)
         }), 500
 
-
 @app.route('/api/upload-model', methods=['POST'])
 def upload_model():
-    """
-    Endpoint to upload model files to ComfyUI models directory
-    Supports formats: .safetensors, .ckpt, .pth, .pt, .bin
-    Supports types: checkpoints, loras, controlnet, upscale_models, vae, embeddings, hypernetworks
-    """
     try:
         from shared_utils import upload_model_file
 
@@ -573,24 +566,18 @@ def upload_model():
 
     except Exception as e:
         print(f"❌ Error in model upload endpoint: {str(e)}")
-        import traceback
         traceback.print_exc()
         return jsonify({
             "status": "error",
             "message": str(e)
         }), 500
 
-
 @app.route('/api/images/<filename>', methods=['GET'])
 def serve_image(filename):
-    """
-    Serve images from multiple possible directories
-    """
     try:
-        # Use shared function
         from shared_utils import serve_image as serve_img
         return serve_img(filename)
-
+            
     except Exception as e:
         print(f"❌ Error serving image {filename}: {str(e)}")
         return jsonify({
@@ -598,10 +585,8 @@ def serve_image(filename):
             "message": str(e)
         }), 500
 
-
 @app.route('/api/controlnet/models', methods=['GET'])
 def get_controlnet_models_endpoint():
-    """Get available ControlNet models"""
     try:
         models = get_controlnet_models()
         return jsonify({
@@ -614,6 +599,74 @@ def get_controlnet_models_endpoint():
             "message": f"Failed to fetch ControlNet models: {str(e)}"
         }), 500
 
+@app.route('/api/save-single-image', methods=['POST'])
+def save_single_image():
+    """
+    Save single generated image to server storage for persistence
+    """
+    try:
+        print(f"🔄 Single image save request received on port 5002")
+        data = request.json
+        
+        if not data or 'imageData' not in data:
+            print("❌ No image data in request")
+            return jsonify({
+                "status": "error",
+                "message": "No image data provided"
+            }), 400
+        
+        image_data = data['imageData']
+        if image_data.startswith('data:'):
+            image_data = image_data.split(',')[1]
+        
+        print(f"📊 Received base64 data length: {len(image_data)}")
+        
+        # Decode base64 image
+        image_bytes = base64.b64decode(image_data)
+        print(f"📊 Decoded image bytes: {len(image_bytes)}")
+        
+        image = Image.open(io.BytesIO(image_bytes))
+        print(f"📊 Image dimensions: {image.size}")
+        
+        timestamp = int(time.time() * 1000)
+        original_filename = data.get('originalFilename', 'image.png')
+        filename = f"single_{timestamp}_{original_filename}"
+        print(f"📁 Generated filename: {filename}")
+        
+        # Save to the same directory as Matrix grids for consistency
+        os.makedirs(MATRIX_GRIDS_DIR, exist_ok=True)
+        filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+        print(f"📁 Full save path: {filepath}")
+        
+        image.save(filepath, format='PNG')
+        print(f"💾 Single image saved to permanent storage")
+        
+        if os.path.exists(filepath):
+            file_size = os.path.getsize(filepath)
+            print(f"✅ Successfully saved single image: {filename}")
+            print(f"📏 File size: {file_size} bytes")
+            
+            return jsonify({
+                "status": "success",
+                "filename": filename,
+                "url": f"http://localhost:5002/api/images/{filename}",
+                "filesize": file_size,
+                "storage": "permanent"
+            })
+        else:
+            print(f"❌ File was not created: {filepath}")
+            return jsonify({
+                "status": "error",
+                "message": "Failed to save single image to permanent storage"
+            }), 500
+            
+    except Exception as e:
+        print(f"❌ Error saving single image: {str(e)}")
+        traceback.print_exc()
+        return jsonify({
+            "status": "error",
+            "message": str(e)
+        }), 500
 
 if __name__ == "__main__":
     print("Starting Dream Layer backend services...")
@@ -621,4 +674,4 @@ def get_controlnet_models_endpoint():
         start_flask_server()
     else:
         print("Failed to start ComfyUI server. Exiting...")
-        sys.exit(1)
+        sys.exit(1) 
\ No newline at end of file
diff --git a/dream_layer_backend/dream_layer_backend_utils/api_key_injector.py b/dream_layer_backend/dream_layer_backend_utils/api_key_injector.py
index 4abae938..94e27eff 100644
--- a/dream_layer_backend/dream_layer_backend_utils/api_key_injector.py
+++ b/dream_layer_backend/dream_layer_backend_utils/api_key_injector.py
@@ -13,17 +13,17 @@
 NODE_TO_API_KEY_MAPPING = {
     # BFL Nodes (use direct API, but still need api_key_comfy_org for compatibility)
     "FluxProUltraImageNode": "BFL_API_KEY",
-    "FluxKontextProImageNode": "BFL_API_KEY",
+    "FluxKontextProImageNode": "BFL_API_KEY", 
     "FluxKontextMaxImageNode": "BFL_API_KEY",
     "FluxProImageNode": "BFL_API_KEY",
     "FluxProExpandNode": "BFL_API_KEY",
-    "FluxProFillNode": "BFL_API_KEY",
+    "FluxProFillNode": "BFL_API_KEY", 
     "FluxProCannyNode": "BFL_API_KEY",
     "FluxProDepthNode": "BFL_API_KEY",
-
+    
     # OpenAI Nodes (use ComfyUI proxy, need api_key_comfy_org)
     "OpenAIDalle2": "OPENAI_API_KEY",
-    "OpenAIDalle3": "OPENAI_API_KEY",
+    "OpenAIDalle3": "OPENAI_API_KEY", 
     "OpenAIGPTImage1": "OPENAI_API_KEY",
     "OpenAITextNode": "OPENAI_API_KEY",
     "OpenAIChatNode": "OPENAI_API_KEY",
@@ -61,20 +61,21 @@
     "BFL_API_KEY": "api_key_comfy_org",
     "OPENAI_API_KEY": "api_key_comfy_org",
     "IDEOGRAM_API_KEY": "api_key_comfy_org",
+
     "STABILITY_API_KEY": "stability_api_key",  # Changed from COMFY_API_KEY
     "COMFY_API_KEY": "api_key_comfy_org",
     "COMFY_AUTH_TOKEN": "auth_token_comfy_org",
     "GEMINI_API_KEY": "api_key_comfy_org",
     "LUMA_API_KEY": "luma_api_key",  # Direct API key for Luma
     # Future additions:
+    # "GEMINI_API_KEY": "api_key_gemini",
     # "ANTHROPIC_API_KEY": "api_key_anthropic",
 }
 
-
 def read_api_keys_from_env() -> Dict[str, str]:
     """
     Read all API keys from environment variables.
-
+    
     Returns:
         Dict containing environment variable names mapped to their values.
         Example: {"BFL_API_KEY": "sk-bfl-...", "OPENAI_API_KEY": "sk-openai-..."}
@@ -82,27 +83,26 @@ def read_api_keys_from_env() -> Dict[str, str]:
     # Get the path to the project's root directory
     current_dir = os.path.dirname(os.path.abspath(__file__))
     project_root = os.path.dirname(os.path.dirname(current_dir))
-
+    
     # Construct the path to the .env file in the root directory
     dotenv_path = os.path.join(project_root, '.env')
-
+    
     # Load environment variables from the .env file in the project root
     load_dotenv(dotenv_path=dotenv_path)
-
+    
     api_keys = {}
-
+    
     # Read all API keys defined in the mapping
     for env_key in ENV_KEY_TO_EXTRA_DATA_MAPPING.keys():
         api_key = os.getenv(env_key)
         if api_key:
             api_keys[env_key] = api_key
             # Safely truncate for display without assuming length
-            display_key = api_key[:8] + "..." + \
-                api_key[-4:] if len(api_key) > 12 else api_key
+            display_key = api_key[:8] + "..." + api_key[-4:] if len(api_key) > 12 else api_key
             print(f"[DEBUG] Found {env_key}: {display_key}")
         else:
             print(f"[DEBUG] No {env_key} found in environment")
-
+    
     print(f"[DEBUG] Total API keys loaded: {len(api_keys)}")
     return api_keys
 
@@ -110,9 +110,16 @@ def read_api_keys_from_env() -> Dict[str, str]:
 def inject_api_keys_into_workflow(workflow: Dict[str, Any], all_api_keys: Dict[str, str] = None) -> Dict[str, Any]:
     """
     Inject API keys from environment variables into workflow extra_data based on nodes present.
-
+    
     Args:
         workflow: The workflow dictionary to inject keys into
+        
+    Returns:
+        Workflow with appropriate API keys added to extra_data
+    """
+    # Read all available API keys from environment
+    all_api_keys = read_api_keys_from_env()
+    
         all_api_keys: Optional dictionary of API keys. If None, reads from environment.
 
     Returns:
@@ -124,18 +131,18 @@ def inject_api_keys_into_workflow(workflow: Dict[str, Any], all_api_keys: Dict[s
 
     # Create a copy to avoid modifying the original
     workflow_with_keys = workflow.copy()
-
+    
     # Ensure extra_data exists
     if "extra_data" not in workflow_with_keys:
         workflow_with_keys["extra_data"] = {}
         print("[DEBUG] Created new extra_data section")
     else:
         print("[DEBUG] Using existing extra_data section")
-
+    
     # Scan workflow for node types and determine which API keys are needed
     needed_env_keys = set()
     workflow_prompt = workflow.get('prompt', {})
-
+    
     print("[DEBUG] Scanning workflow for API nodes...")
     for node_id, node_data in workflow_prompt.items():
         if isinstance(node_data, dict):
@@ -143,8 +150,7 @@ def inject_api_keys_into_workflow(workflow: Dict[str, Any], all_api_keys: Dict[s
             if class_type in NODE_TO_API_KEY_MAPPING:
                 required_env_key = NODE_TO_API_KEY_MAPPING[class_type]
                 needed_env_keys.add(required_env_key)
-                print(
-                    f"[DEBUG] Found {class_type} node - needs {required_env_key}")
+                print(f"[DEBUG] Found {class_type} node - needs {required_env_key}")
     # Decide which key to use for api_key_comfy_org
     api_key_comfy_org = None
     print(f"[DEBUG] needed_env_keys: {needed_env_keys}")
@@ -162,13 +168,15 @@ def inject_api_keys_into_workflow(workflow: Dict[str, Any], all_api_keys: Dict[s
             api_key_comfy_org = all_api_keys["IDEOGRAM_API_KEY"]
             print(f"[DEBUG] Using IDEOGRAM_API_KEY for api_key_comfy_org")
         else:
-            print(
-                f"[DEBUG] No available API keys for needed services: {needed_env_keys}")
-
+            print(f"[DEBUG] No available API keys for needed services: {needed_env_keys}")
+    
     # Add the chosen key to extra_data
     if api_key_comfy_org:
         workflow_with_keys["extra_data"]["api_key_comfy_org"] = api_key_comfy_org
         print(f"[DEBUG] Injected api_key_comfy_org into workflow")
+    else:
+        print("[DEBUG] No API keys needed for this workflow")
+    
 
     # Special handling for Stability AI nodes - inject stability_api_key directly
     has_stability_nodes = False
@@ -211,5 +219,5 @@ def inject_api_keys_into_workflow(workflow: Dict[str, Any], all_api_keys: Dict[s
         print("[DEBUG] No Luma nodes found in workflow")
 
     print(f"[DEBUG] Final extra_data: {workflow_with_keys['extra_data']}")
-
-    return workflow_with_keys
+    
+    return workflow_with_keys 
\ No newline at end of file
diff --git a/dream_layer_backend/dream_layer_backend_utils/workflow_loader.py b/dream_layer_backend/dream_layer_backend_utils/workflow_loader.py
index 977abf5c..a1e98d45 100644
--- a/dream_layer_backend/dream_layer_backend_utils/workflow_loader.py
+++ b/dream_layer_backend/dream_layer_backend_utils/workflow_loader.py
@@ -12,15 +12,13 @@
 
 logger = logging.getLogger(__name__)
 
-
 def _determine_workflow_path(workflow_request: Dict[str, Any]) -> str:
     """Determine the workflow file path based on request parameters."""
     generation_flow = workflow_request.get('generation_flow')
-    # Convert to lowercase for case-insensitive comparison
-    model_name = workflow_request.get('model_name', '').lower()
+    model_name = workflow_request.get('model_name', '').lower()  # Convert to lowercase for case-insensitive comparison
     controlnet = workflow_request.get('controlnet', False)
     lora = workflow_request.get('lora', False)
-
+    
     # Determine workflow filename based on parameters
     if 'bfl' in model_name or 'flux' in model_name:
         filename = "bfl_core_generation_workflow.json"
@@ -40,35 +38,32 @@ def _determine_workflow_path(workflow_request: Dict[str, Any]) -> str:
         filename = "local_lora.json"
     else:
         filename = "core_generation_workflow.json"
-
+    
     # Build full path
     current_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-    workflow_path = os.path.join(
-        current_dir, 'workflows', generation_flow, filename)
-
+    workflow_path = os.path.join(current_dir, 'workflows', generation_flow, filename)
+    
     if not os.path.exists(workflow_path):
         raise FileNotFoundError(f"Workflow file not found: {workflow_path}")
-
+    
     return workflow_path
 
-
 def _load_workflow_json(workflow_path: str) -> Dict[str, Any]:
     """Load and parse workflow JSON file."""
     with open(workflow_path, 'r') as file:
         return json.load(file)
 
-
 def load_workflow(workflow_request: Dict[str, Any]) -> Dict[str, Any]:
     """
     Load and configure a workflow based on the request parameters.
-
+    
     Args:
         workflow_request: Dictionary containing:
             - generation_flow: txt2img/img2img
             - model_name: bfl/dalle/other
             - controlnet: true/false
             - lora: true/false
-
+    
     Returns:
         Dict: Loaded workflow configuration
     """
@@ -81,10 +76,8 @@ def load_workflow(workflow_request: Dict[str, Any]) -> Dict[str, Any]:
         logger.error(f"Error loading workflow: {str(e)}")
         raise
 
-
 def analyze_workflow(workflow: Dict[str, Any]) -> Dict[str, Any]:
     """Analyze workflow to determine batch size and if it uses API nodes."""
     is_api = bool(workflow.get('extra_data'))
-    batch_size = next((node['inputs'].get('batch_size', 1) for node in workflow.get(
-        'prompt', {}).values() if 'batch_size' in node.get('inputs', {})), 1)
-    return {'batch_size': batch_size, 'is_api': is_api}
+    batch_size = next((node['inputs'].get('batch_size', 1) for node in workflow.get('prompt', {}).values() if 'batch_size' in node.get('inputs', {})), 1)
+    return {'batch_size': batch_size, 'is_api': is_api}
\ No newline at end of file
diff --git a/dream_layer_backend/extras.py b/dream_layer_backend/extras.py
index d46beceb..6564d5f6 100644
--- a/dream_layer_backend/extras.py
+++ b/dream_layer_backend/extras.py
@@ -37,7 +37,7 @@
 os.makedirs(SERVED_IMAGES_DIR, exist_ok=True)
 
 # Server URL for image serving
-SERVER_URL = "http://localhost:5002/api"
+SERVER_URL = "http://localhost:5003"
 
 def verify_input_directory():
     """Verify that the input directory exists and is writable"""
diff --git a/dream_layer_backend/img2img_server.py b/dream_layer_backend/img2img_server.py
index f16893e0..66b65cab 100644
--- a/dream_layer_backend/img2img_server.py
+++ b/dream_layer_backend/img2img_server.py
@@ -4,16 +4,14 @@
 import json
 import logging
 import os
-import requests
 from PIL import Image
 import io
 import time
+from shared_utils import serve_image
 from shared_utils import send_to_comfyui
 from img2img_workflow import transform_to_img2img_workflow
 from shared_utils import COMFY_API_URL
 from dream_layer_backend_utils.fetch_advanced_models import get_controlnet_models
-from run_registry import create_run_config_from_generation_data
-from dataclasses import asdict
 
 # Configure logging
 logging.basicConfig(
@@ -217,40 +215,11 @@ def handle_img2img():
                 logger.info(f"  Subfolder: {img.get('subfolder', 'None')}")
                 logger.info(f"  URL: {img.get('url')}")
         
-        # Extract generated image filenames
-        generated_images = []
-        if comfy_response.get("generated_images"):
-            for img_data in comfy_response["generated_images"]:
-                if isinstance(img_data, dict) and "filename" in img_data:
-                    generated_images.append(img_data["filename"])
-        
-        # Register the completed run
-        try:
-            run_config = create_run_config_from_generation_data(
-                data, generated_images, "img2img"
-            )
-            
-            # Send to run registry
-            registry_response = requests.post(
-                "http://localhost:5005/api/runs",
-                json=asdict(run_config),
-                timeout=5
-            )
-            
-            if registry_response.status_code == 200:
-                logger.info(f"✅ Run registered successfully: {run_config.run_id}")
-            else:
-                logger.warning(f"⚠️ Failed to register run: {registry_response.text}")
-                
-        except Exception as e:
-            logger.warning(f"⚠️ Error registering run: {str(e)}")
-        
         response = jsonify({
             "status": "success",
             "message": "Workflow sent to ComfyUI successfully",
             "comfy_response": comfy_response,
-            "workflow": workflow,
-            "run_id": run_config.run_id if 'run_config' in locals() else None
+            "workflow": workflow
         })
         
         # Clean up the temporary image file
@@ -279,8 +248,6 @@ def handle_img2img_interrupt():
 def serve_image_endpoint(filename):
     """Serve images from the served_images directory"""
     try:
-        # Use shared function
-        from shared_utils import serve_image
         return serve_image(filename)
     except Exception as e:
         logger.error(f"Error serving image {filename}: {e}")
diff --git a/dream_layer_backend/img2img_workflow.py b/dream_layer_backend/img2img_workflow.py
index 771048f7..694f7ea6 100644
--- a/dream_layer_backend/img2img_workflow.py
+++ b/dream_layer_backend/img2img_workflow.py
@@ -16,7 +16,7 @@
 import random
 import re
 import logging
-from dream_layer import get_directories
+from dream_layer import get_directories 
 from extras import COMFY_INPUT_DIR
 
 
@@ -34,8 +34,7 @@ def transform_to_img2img_workflow(data):
     use_lora = bool(data.get('lora'))
 
     # Select the correct workflow template path
-    workflow_template_path = get_img2img_workflow_template(
-        model_name, use_controlnet, use_lora)
+    workflow_template_path = get_img2img_workflow_template(model_name, use_controlnet, use_lora)
 
     # Load the workflow from the template file
     with open(workflow_template_path, 'r') as f:
@@ -52,23 +51,21 @@ def transform_to_img2img_workflow(data):
     output_dir, _ = get_directories()
     logger.info(f"\nUsing output directory: {output_dir}")
 
-    # Process ControlNet data if present
+        # Process ControlNet data if present
     controlnet_data = data.get('controlnet')
     if controlnet_data and validate_controlnet_config(controlnet_data):
         logger.info("Processing ControlNet configuration...")
         try:
-            controlnet_data = process_controlnet_images(
-                controlnet_data, COMFY_INPUT_DIR)
+            controlnet_data = process_controlnet_images(controlnet_data, COMFY_INPUT_DIR)
             logger.info("ControlNet images processed successfully")
         except Exception as e:
             logger.error(f"Error processing ControlNet images: {str(e)}")
             controlnet_data = None
     else:
         if controlnet_data:
-            logger.warning(
-                "Invalid ControlNet configuration, ignoring ControlNet")
+            logger.warning("Invalid ControlNet configuration, ignoring ControlNet")
         controlnet_data = None
-
+    
     # Extract parameters with validation and type conversion
     prompt = data.get('prompt', '')
     negative_prompt = data.get('negative_prompt', '')
@@ -77,32 +74,30 @@ def transform_to_img2img_workflow(data):
     batch_size = max(1, min(8, int(data.get('batch_size', 1))))
     steps = max(1, min(150, int(data.get('steps', 20))))
     cfg_scale = max(1.0, min(20.0, float(data.get('cfg_scale', 7.0))))
-    denoising_strength = max(
-        0.0, min(1.0, float(data.get('denoising_strength', 0.75))))
+    denoising_strength = max(0.0, min(1.0, float(data.get('denoising_strength', 0.75))))
     input_image = data.get('input_image', '')
     model_name = data.get('model_name', 'v1-6-pruned-emaonly-fp16.safetensors')
     sampler_name = data.get('sampler_name', 'euler')
     scheduler = data.get('scheduler', 'normal')
-
+    
     # Advanced settings
     vae_name = data.get('vae_name')
     clip_skip = data.get('clip_skip', 1)
     tiling = data.get('tiling', False)
     hires_fix = data.get('hires_fix', False)
     karras_sigmas = data.get('karras_sigmas', False)
-
+    
     # Handle seed - ensure it's a positive integer
     try:
         seed = int(data.get('seed', 0))
     except (ValueError, TypeError):
         seed = 0
-
+        
     # Generate a random positive seed if seed is 0 or negative
     if seed <= 0:
-        # Using 2^31-1 as max to ensure it's well within safe integer range
-        seed = random.randint(1, 2**31 - 1)
+        seed = random.randint(1, 2**31 - 1)  # Using 2^31-1 as max to ensure it's well within safe integer range
         logger.info(f"Generated random seed: {seed}")
-
+    
     # Update the data with the actual seed used
     data['seed'] = seed
 
@@ -126,7 +121,7 @@ def transform_to_img2img_workflow(data):
     # Log the processed parameters
     logger.info("Core Generation Settings")
     logger.info(json.dumps(core_generation_settings, indent=4))
-
+    
     # Create the ComfyUI workflow
     # The old hardcoded workflow dict is removed, so this block is now empty.
     # The workflow object is now loaded directly from the template.
@@ -139,20 +134,18 @@ def transform_to_img2img_workflow(data):
                 "vae_name": vae_name
             }
         }
-
+    
     # The original workflow loading logic using load_workflow is removed.
     # The workflow object is now directly loaded from the template.
 
     # Check if custom workflow is provided and use it instead of the default workflow
     custom_workflow = data.get('custom_workflow')
     if custom_workflow and validate_custom_workflow(custom_workflow):
-        logger.info(
-            "Custom workflow detected, updating with current parameters...")
+        logger.info("Custom workflow detected, updating with current parameters...")
         try:
             # Update the custom workflow with the current parameters
             workflow = update_custom_workflow(workflow, custom_workflow)
-            logger.info(
-                "Successfully updated custom workflow with current parameters")
+            logger.info("Successfully updated custom workflow with current parameters")
         except Exception as e:
             logger.error(f"Error updating custom workflow: {str(e)}")
             logger.info("Falling back to default workflow")
@@ -160,29 +153,29 @@ def transform_to_img2img_workflow(data):
         # Update the default workflow with the current parameters
         workflow = override_workflow(workflow, core_generation_settings)
         # Update image paths in the workflow
-        workflow = update_image_paths_in_workflow(
-            workflow, os.path.join(COMFY_INPUT_DIR, input_image))
+        workflow = update_image_paths_in_workflow(workflow, os.path.join(COMFY_INPUT_DIR, input_image))
         logger.info("No valid custom workflow provided, using default workflow")
-
+    
     # Log the generated workflow
     logger.info("Generated workflow:")
     logger.info(json.dumps(workflow, indent=2))
 
-    # Inject ControlNet into the workflow if present
+        # Inject ControlNet into the workflow if present
     if controlnet_data:
         logger.info("Injecting ControlNet into workflow...")
         try:
-            workflow = inject_controlnet_into_workflow(
-                workflow, controlnet_data, COMFY_INPUT_DIR)
+            workflow = inject_controlnet_into_workflow(workflow, controlnet_data, COMFY_INPUT_DIR)
             logger.info("ControlNet successfully injected into workflow")
-
+            
+            
         except Exception as e:
             logger.error(f"Error injecting ControlNet into workflow: {str(e)}")
     else:
-        logger.info(
-            "No ControlNet data provided - skipping ControlNet injection")
-
+        logger.info("No ControlNet data provided - skipping ControlNet injection")
+    
     # Inject API keys from environment variables into the workflow
+    workflow = inject_api_keys_into_workflow(workflow)
+    
     all_api_keys = read_api_keys_from_env()
     workflow = inject_api_keys_into_workflow(workflow, all_api_keys)
 
@@ -216,8 +209,7 @@ def transform_to_img2img_workflow(data):
     # Inject advanced options if enabled
     if face_restoration_data['restore_faces']:
         logger.info("Injecting Face Restoration parameters...")
-        workflow = inject_face_restoration_parameters(
-            workflow, face_restoration_data)
+        workflow = inject_face_restoration_parameters(workflow, face_restoration_data)
     if tiling_data['tiling']:
         logger.info("Injecting Tiling parameters...")
         workflow = inject_tiling_parameters(workflow, tiling_data)
@@ -227,29 +219,27 @@ def transform_to_img2img_workflow(data):
     if refiner_data['refiner_enabled']:
         logger.info("Injecting Refiner parameters...")
         workflow = inject_refiner_parameters(workflow, refiner_data)
-
+    
     return workflow
 
-
 def extract_filename_from_data_url(data_url):
     """Extract filename from data URL if present in the format data:image/...;name=filename.ext;base64,..."""
     if not data_url:
         return None
-
+    
     # Try to find name parameter in the data URL
     name_match = re.search(r';name=(.*?);', data_url)
     if name_match:
         return name_match.group(1)
     return None
 
-
 def get_img2img_workflow_template(model_name, use_controlnet=False, use_lora=False):
     model_name_lower = model_name.lower()
-
+    
     # Check for BFL/Flux models first (they have their own workflow)
     if "bfl" in model_name_lower or "flux" in model_name_lower:
         return "workflows/img2img/bfl_core_generation_workflow.json"
-
+    
     # Check for Ideogram models
     elif "ideogram" in model_name_lower:
         return "workflows/img2img/ideogram_core_generation_workflow.json"
diff --git a/dream_layer_backend/img2txt_server.py b/dream_layer_backend/img2txt_server.py
deleted file mode 100644
index cbe43a55..00000000
--- a/dream_layer_backend/img2txt_server.py
+++ /dev/null
@@ -1,208 +0,0 @@
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-import json
-import os
-import base64
-import tempfile
-import requests
-from io import BytesIO
-from PIL import Image
-from dream_layer import get_directories
-from dream_layer_backend_utils import interrupt_workflow
-from dream_layer_backend_utils.api_key_injector import inject_api_keys_into_workflow
-from shared_utils import send_to_comfyui
-
-app = Flask(__name__)
-CORS(app, resources={
-    r"/*": {
-        "origins": ["http://localhost:*", "http://127.0.0.1:*"],
-        "methods": ["GET", "POST", "OPTIONS"],
-        "allow_headers": ["Content-Type"]
-    }
-})
-
-# Get served images directory
-output_dir, _ = get_directories()
-SERVED_IMAGES_DIR = os.path.join(os.path.dirname(__file__), 'served_images')
-os.makedirs(SERVED_IMAGES_DIR, exist_ok=True)
-
-def load_img2txt_workflow():
-    """Load the Gemini multimodal workflow for img2txt analysis"""
-    workflow_path = os.path.join(os.path.dirname(__file__), 'workflows', 'img2img', 'gemini_multimodal_workflow.json')
-    try:
-        with open(workflow_path, 'r') as f:
-            return json.load(f)
-    except Exception as e:
-        print(f"Error loading Gemini multimodal workflow: {e}")
-        return None
-
-def transform_to_img2txt_workflow(data):
-    """Transform frontend data to ComfyUI img2txt workflow using full Gemini multimodal workflow"""
-    workflow = load_img2txt_workflow()
-    if not workflow:
-        raise Exception("Could not load Gemini multimodal workflow")
-    
-    # Use the full workflow - we'll extract just the text from GeminiNode later
-    workflow_copy = json.loads(json.dumps(workflow))
-    
-    # Process and save the input image
-    if 'input_image' in data and data['input_image']:
-        try:
-            # Decode base64 image
-            image_data = data['input_image'].split(',')[1] if ',' in data['input_image'] else data['input_image']
-            image_bytes = base64.b64decode(image_data)
-            
-            # Create temporary file
-            with tempfile.NamedTemporaryFile(delete=False, suffix='.png', dir=SERVED_IMAGES_DIR) as temp_file:
-                temp_file.write(image_bytes)
-                temp_filename = os.path.basename(temp_file.name)
-            
-            # Update workflow with the uploaded image
-            workflow_copy['prompt']['1']['inputs']['image'] = temp_filename
-            
-        except Exception as e:
-            print(f"Error processing input image: {e}")
-            raise Exception(f"Failed to process input image: {str(e)}")
-    else:
-        raise Exception("No input image provided")
-    
-    # Update Gemini prompt if provided
-    if 'prompt' in data and data['prompt']:
-        custom_prompt = data['prompt']
-    else:
-        custom_prompt = "Analyze this image and provide a detailed description. Include: what objects/people you see, the scene setting, colors, mood, style, composition, and any notable details. Be descriptive and thorough."
-    
-    workflow_copy['prompt']['2']['inputs']['prompt'] = custom_prompt
-    
-    # Update model if provided
-    if 'model' in data and data['model']:
-        workflow_copy['prompt']['2']['inputs']['model'] = data['model']
-    
-    # Update seed if provided
-    if 'seed' in data and data['seed'] is not None:
-        workflow_copy['prompt']['2']['inputs']['seed'] = int(data['seed'])
-    
-    return workflow_copy
-
-def call_gemini_api_directly(data):
-    """Call Gemini API directly bypassing ComfyUI"""
-    from dream_layer_backend_utils.api_key_injector import read_api_keys_from_env
-    
-    # Get API key
-    api_keys = read_api_keys_from_env()
-    gemini_key = api_keys.get('GEMINI_API_KEY')
-    if not gemini_key:
-        raise Exception("GEMINI_API_KEY not found in environment")
-    
-    # Convert image to base64 for Gemini
-    image_b64 = data['input_image'].split(',')[1] if ',' in data['input_image'] else data['input_image']
-    
-    # Prepare prompt
-    prompt_text = data.get('prompt', "Analyze this image and provide a detailed description. Include: what objects/people you see, the scene setting, colors, mood, style, composition, and any notable details. Be descriptive and thorough.")
-    
-    # Gemini API request
-    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent"
-    headers = {'Content-Type': 'application/json', 'X-goog-api-key': gemini_key}
-    payload = {
-        "contents": [{
-            "parts": [
-                {"text": prompt_text},
-                {"inline_data": {"mime_type": "image/png", "data": image_b64}}
-            ]
-        }]
-    }
-    
-    response = requests.post(url, headers=headers, json=payload)
-    if response.status_code == 200:
-        result = response.json()
-        return result['candidates'][0]['content']['parts'][0]['text']
-    else:
-        raise Exception(f"Gemini API error: {response.status_code} - {response.text}")
-
-@app.route('/api/img2txt', methods=['POST', 'OPTIONS'])
-def handle_img2txt():
-    """Handle image-to-text generation requests"""
-    if request.method == 'OPTIONS':
-        return jsonify({"status": "ok"})
-    
-    try:
-        data = request.json
-        if data:
-            print("Img2Txt Data:", json.dumps({
-                **data,
-                'input_image': 'BASE64_IMAGE_DATA' if 'input_image' in data else None
-            }, indent=2))
-            
-            # Validate required fields
-            if 'input_image' not in data or not data['input_image']:
-                return jsonify({
-                    "status": "error",
-                    "message": "Missing required field: input_image"
-                }), 400
-            
-            # Direct Gemini API call (bypass ComfyUI)
-            gemini_response = call_gemini_api_directly(data)
-            print(f"✅ Direct Gemini API response received: {len(gemini_response)} chars")
-            
-            # Format response to match expected structure
-            comfy_response = {
-                "status": "success",
-                "text_output": gemini_response,
-                "all_images": []
-            }
-            
-            if "error" in comfy_response:
-                return jsonify({
-                    "status": "error",
-                    "message": comfy_response["error"]
-                }), 500
-            
-            response = jsonify({
-                "status": "success",
-                "message": "Image analysis completed successfully",
-                "comfy_response": comfy_response,
-                "generated_text": comfy_response.get("text_output", "No text output received")
-            })
-            
-            return response
-            
-        else:
-            return jsonify({
-                "status": "error",
-                "message": "No data received"
-            }), 400
-            
-    except Exception as e:
-        print(f"Error in handle_img2txt: {str(e)}")
-        import traceback
-        traceback.print_exc()
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/img2txt/interrupt', methods=['POST'])
-def handle_img2txt_interrupt():
-    """Handle interruption of img2txt generation"""
-    print("Interrupting img2txt generation...")
-    success = interrupt_workflow()
-    return jsonify({"status": "received", "interrupted": success})
-
-@app.route('/api/images/<filename>', methods=['GET'])
-def serve_image_endpoint(filename):
-    """
-    Serve images from multiple possible directories
-    This endpoint is needed here because the frontend expects it on this port
-    """
-    try:
-        # Use shared function
-        from shared_utils import serve_image
-        return serve_image(filename)
-            
-    except Exception as e:
-        print(f"Error serving image {filename}: {str(e)}")
-        return jsonify({"error": str(e)}), 404
-
-if __name__ == '__main__':
-    print("Starting Img2Txt server on port 5007...")
-    app.run(debug=True, host='0.0.0.0', port=5007)
diff --git a/dream_layer_backend/report_bundle.py b/dream_layer_backend/report_bundle.py
deleted file mode 100644
index 0faf0107..00000000
--- a/dream_layer_backend/report_bundle.py
+++ /dev/null
@@ -1,367 +0,0 @@
-import os
-import csv
-import json
-import zipfile
-import shutil
-from datetime import datetime
-from typing import List, Dict, Any, Optional
-from dataclasses import asdict
-from flask import Flask, jsonify, request, send_file
-from flask_cors import CORS
-import requests
-from run_registry import RunRegistry, RunConfig
-
-class ReportBundleGenerator:
-    """Generates report bundles with CSV, config, images, and README"""
-    
-    def __init__(self, output_dir: str = "Dream_Layer_Resources/output"):
-        self.output_dir = output_dir
-        self.registry = RunRegistry()
-        
-    def generate_csv(self, runs: List[RunConfig]) -> str:
-        """Generate results.csv with required columns"""
-        csv_path = "temp_results.csv"
-        
-        # Define required CSV columns based on schema
-        required_columns = [
-            'run_id',
-            'timestamp', 
-            'model',
-            'vae',
-            'prompt',
-            'negative_prompt',
-            'seed',
-            'sampler',
-            'steps',
-            'cfg_scale',
-            'width',
-            'height',
-            'batch_size',
-            'batch_count',
-            'generation_type',
-            'image_paths',
-            'loras',
-            'controlnets',
-            'workflow_hash'
-        ]
-        
-        with open(csv_path, 'w', newline='', encoding='utf-8') as csvfile:
-            writer = csv.DictWriter(csvfile, fieldnames=required_columns)
-            writer.writeheader()
-            
-            for run in runs:
-                # Prepare loras and controlnets as JSON strings
-                loras_json = json.dumps(run.loras) if run.loras else "[]"
-                controlnets_json = json.dumps(run.controlnets) if run.controlnets else "[]"
-                
-                # Create workflow hash for identification
-                workflow_hash = str(hash(json.dumps(run.workflow, sort_keys=True)))
-                
-                # Join image paths
-                image_paths = ";".join(run.generated_images) if run.generated_images else ""
-                
-                row = {
-                    'run_id': run.run_id,
-                    'timestamp': run.timestamp,
-                    'model': run.model,
-                    'vae': run.vae or "",
-                    'prompt': run.prompt,
-                    'negative_prompt': run.negative_prompt,
-                    'seed': run.seed,
-                    'sampler': run.sampler,
-                    'steps': run.steps,
-                    'cfg_scale': run.cfg_scale,
-                    'width': run.width,
-                    'height': run.height,
-                    'batch_size': run.batch_size,
-                    'batch_count': run.batch_count,
-                    'generation_type': run.generation_type,
-                    'image_paths': image_paths,
-                    'loras': loras_json,
-                    'controlnets': controlnets_json,
-                    'workflow_hash': workflow_hash
-                }
-                writer.writerow(row)
-        
-        return csv_path
-    
-    def validate_csv_schema(self, csv_path: str) -> bool:
-        """Validate that CSV has all required columns"""
-        try:
-            with open(csv_path, 'r', encoding='utf-8') as csvfile:
-                reader = csv.DictReader(csvfile)
-                fieldnames = reader.fieldnames
-                
-                required_columns = [
-                    'run_id', 'timestamp', 'model', 'vae', 'prompt', 
-                    'negative_prompt', 'seed', 'sampler', 'steps', 'cfg_scale',
-                    'width', 'height', 'batch_size', 'batch_count', 
-                    'generation_type', 'image_paths', 'loras', 'controlnets', 'workflow_hash'
-                ]
-                
-                missing_columns = [col for col in required_columns if col not in fieldnames]
-                if missing_columns:
-                    print(f"❌ Missing required columns: {missing_columns}")
-                    return False
-                
-                print(f"✅ CSV schema validation passed")
-                return True
-                
-        except Exception as e:
-            print(f"❌ CSV schema validation failed: {e}")
-            return False
-    
-    def copy_images_to_bundle(self, runs: List[RunConfig], bundle_dir: str) -> List[str]:
-        """Copy selected grid images to bundle directory"""
-        copied_images = []
-        
-        for run in runs:
-            for image_filename in run.generated_images:
-                if image_filename:
-                    # Source path in output directory
-                    src_path = os.path.join(self.output_dir, image_filename)
-                    
-                    if os.path.exists(src_path):
-                        # Destination in bundle
-                        dest_path = os.path.join(bundle_dir, "images", image_filename)
-                        os.makedirs(os.path.dirname(dest_path), exist_ok=True)
-                        
-                        try:
-                            shutil.copy2(src_path, dest_path)
-                            copied_images.append(image_filename)
-                            print(f"✅ Copied image: {image_filename}")
-                        except Exception as e:
-                            print(f"❌ Failed to copy {image_filename}: {e}")
-                    else:
-                        print(f"⚠️ Image not found: {src_path}")
-        
-        return copied_images
-    
-    def create_config_json(self, runs: List[RunConfig]) -> str:
-        """Create config.json with run configurations"""
-        config_data = {
-            "report_metadata": {
-                "generated_at": datetime.now().isoformat(),
-                "total_runs": len(runs),
-                "generation_types": list(set(run.generation_type for run in runs)),
-                "models_used": list(set(run.model for run in runs))
-            },
-            "runs": [asdict(run) for run in runs]
-        }
-        
-        config_path = "temp_config.json"
-        with open(config_path, 'w', encoding='utf-8') as f:
-            json.dump(config_data, f, indent=2, ensure_ascii=False)
-        
-        return config_path
-    
-    def create_readme(self, runs: List[RunConfig], copied_images: List[str]) -> str:
-        """Create README.md for the report bundle"""
-        readme_content = f"""# Dream Layer Report Bundle
-
-Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
-
-## Overview
-This report bundle contains {len(runs)} completed image generation runs with their configurations and results.
-
-## Contents
-- `results.csv` - Tabular data of all runs with metadata
-- `config.json` - Detailed configuration data for each run
-- `images/` - Generated images from all runs
-- `README.md` - This file
-
-## Statistics
-- Total runs: {len(runs)}
-- Generation types: {', '.join(set(run.generation_type for run in runs))}
-- Models used: {', '.join(set(run.model for run in runs))}
-- Images included: {len(copied_images)}
-
-## CSV Schema
-The results.csv file contains the following columns:
-- run_id: Unique identifier for each run
-- timestamp: When the run was executed
-- model: Model used for generation
-- vae: VAE model (if any)
-- prompt: Positive prompt
-- negative_prompt: Negative prompt
-- seed: Random seed used
-- sampler: Sampling method
-- steps: Number of sampling steps
-- cfg_scale: CFG scale value
-- width/height: Image dimensions
-- batch_size/batch_count: Batch settings
-- generation_type: txt2img or img2img
-- image_paths: Semicolon-separated list of generated image filenames
-- loras: JSON array of LoRA configurations
-- controlnets: JSON array of ControlNet configurations
-- workflow_hash: Hash of the workflow configuration
-
-## File Paths
-All image paths in the CSV resolve to files present in this zip bundle.
-"""
-        
-        readme_path = "temp_README.md"
-        with open(readme_path, 'w', encoding='utf-8') as f:
-            f.write(readme_content)
-        
-        return readme_path
-    
-    def create_report_bundle(self, run_ids: Optional[List[str]] = None) -> str:
-        """Create a complete report bundle"""
-        
-        # Get runs to include
-        if run_ids:
-            runs = [self.registry.get_run(run_id) for run_id in run_ids if self.registry.get_run(run_id)]
-        else:
-            runs = self.registry.get_all_runs()
-        
-        if not runs:
-            raise ValueError("No runs found to include in report")
-        
-        print(f"📊 Creating report bundle with {len(runs)} runs")
-        
-        # Create temporary directory for bundle
-        bundle_dir = f"temp_report_bundle_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
-        os.makedirs(bundle_dir, exist_ok=True)
-        
-        try:
-            # Generate CSV
-            print("📝 Generating results.csv...")
-            csv_path = self.generate_csv(runs)
-            
-            # Validate CSV schema
-            if not self.validate_csv_schema(csv_path):
-                raise ValueError("CSV schema validation failed")
-            
-            # Copy CSV to bundle
-            shutil.copy2(csv_path, os.path.join(bundle_dir, "results.csv"))
-            
-            # Create config.json
-            print("⚙️ Creating config.json...")
-            config_path = self.create_config_json(runs)
-            shutil.copy2(config_path, os.path.join(bundle_dir, "config.json"))
-            
-            # Copy images
-            print("🖼️ Copying images...")
-            copied_images = self.copy_images_to_bundle(runs, bundle_dir)
-            
-            # Create README
-            print("📖 Creating README.md...")
-            readme_path = self.create_readme(runs, copied_images)
-            shutil.copy2(readme_path, os.path.join(bundle_dir, "README.md"))
-            
-            # Create zip file
-            print("📦 Creating report.zip...")
-            zip_path = "report.zip"
-            with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
-                for root, dirs, files in os.walk(bundle_dir):
-                    for file in files:
-                        file_path = os.path.join(root, file)
-                        arcname = os.path.relpath(file_path, bundle_dir)
-                        zipf.write(file_path, arcname)
-            
-            # Cleanup temp files
-            for temp_file in [csv_path, config_path, readme_path]:
-                if os.path.exists(temp_file):
-                    os.remove(temp_file)
-            
-            # Cleanup temp directory
-            shutil.rmtree(bundle_dir)
-            
-            print(f"✅ Report bundle created: {zip_path}")
-            return zip_path
-            
-        except Exception as e:
-            # Cleanup on error
-            if os.path.exists(bundle_dir):
-                shutil.rmtree(bundle_dir)
-            raise e
-
-# Flask app for report bundle API
-app = Flask(__name__)
-CORS(app, resources={
-    r"/*": {
-        "origins": ["http://localhost:*", "http://127.0.0.1:*"],
-        "methods": ["GET", "POST", "OPTIONS"],
-        "allow_headers": ["Content-Type"]
-    }
-})
-
-generator = ReportBundleGenerator()
-
-@app.route('/api/report-bundle', methods=['POST'])
-def create_report_bundle():
-    """Create a report bundle with selected runs"""
-    try:
-        data = request.json or {}
-        run_ids = data.get('run_ids', [])  # Empty list means all runs
-        
-        zip_path = generator.create_report_bundle(run_ids)
-        
-        return jsonify({
-            "status": "success",
-            "message": "Report bundle created successfully",
-            "file_path": zip_path
-        })
-        
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/report-bundle/download', methods=['GET'])
-def download_report_bundle():
-    """Download the generated report.zip file"""
-    try:
-        zip_path = "report.zip"
-        if not os.path.exists(zip_path):
-            return jsonify({
-                "status": "error",
-                "message": "Report bundle not found. Please generate one first."
-            }), 404
-        
-        return send_file(
-            zip_path,
-            as_attachment=True,
-            download_name="report.zip",
-            mimetype="application/zip"
-        )
-        
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/report-bundle/validate', methods=['POST'])
-def validate_report_bundle():
-    """Validate a report bundle schema"""
-    try:
-        data = request.json or {}
-        csv_content = data.get('csv_content', '')
-        
-        # Write CSV content to temp file for validation
-        temp_csv = "temp_validation.csv"
-        with open(temp_csv, 'w', encoding='utf-8') as f:
-            f.write(csv_content)
-        
-        is_valid = generator.validate_csv_schema(temp_csv)
-        
-        # Cleanup
-        if os.path.exists(temp_csv):
-            os.remove(temp_csv)
-        
-        return jsonify({
-            "status": "success",
-            "valid": is_valid
-        })
-        
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5006, debug=True) 
\ No newline at end of file
diff --git a/dream_layer_backend/run_registry.py b/dream_layer_backend/run_registry.py
deleted file mode 100644
index e8ce4f20..00000000
--- a/dream_layer_backend/run_registry.py
+++ /dev/null
@@ -1,236 +0,0 @@
-import json
-import os
-import time
-import uuid
-from datetime import datetime
-from typing import Dict, List, Any, Optional
-from dataclasses import dataclass, asdict
-from flask import Flask, jsonify, request
-from flask_cors import CORS
-
-@dataclass
-class RunConfig:
-    """Represents a frozen configuration for a completed run"""
-    run_id: str
-    timestamp: str
-    model: str
-    vae: Optional[str]
-    loras: List[Dict[str, Any]]
-    controlnets: List[Dict[str, Any]]
-    prompt: str
-    negative_prompt: str
-    seed: int
-    sampler: str
-    steps: int
-    cfg_scale: float
-    width: int
-    height: int
-    batch_size: int
-    batch_count: int
-    workflow: Dict[str, Any]
-    version: str
-    generated_images: List[str]
-    generation_type: str  # "txt2img" or "img2img"
-
-class RunRegistry:
-    """Manages completed runs and their configurations"""
-    
-    def __init__(self, storage_file: str = "run_registry.json"):
-        self.storage_file = storage_file
-        self.runs: Dict[str, RunConfig] = {}
-        self.load_runs()
-    
-    def load_runs(self):
-        """Load runs from storage file"""
-        try:
-            if os.path.exists(self.storage_file):
-                with open(self.storage_file, 'r', encoding='utf-8') as f:
-                    data = json.load(f)
-                    for run_id, run_data in data.items():
-                        self.runs[run_id] = RunConfig(**run_data)
-        except Exception as e:
-            print(f"Error loading run registry: {e}")
-    
-    def save_runs(self):
-        """Save runs to storage file"""
-        try:
-            data = {run_id: asdict(run_config) for run_id, run_config in self.runs.items()}
-            with open(self.storage_file, 'w', encoding='utf-8') as f:
-                json.dump(data, f, indent=2, ensure_ascii=False)
-        except Exception as e:
-            print(f"Error saving run registry: {e}")
-    
-    def add_run(self, config: RunConfig):
-        """Add a completed run to the registry"""
-        self.runs[config.run_id] = config
-        self.save_runs()
-    
-    def get_run(self, run_id: str) -> Optional[RunConfig]:
-        """Get a specific run by ID"""
-        return self.runs.get(run_id)
-    
-    def get_all_runs(self) -> List[RunConfig]:
-        """Get all runs sorted by timestamp (newest first)"""
-        return sorted(self.runs.values(), key=lambda x: x.timestamp, reverse=True)
-    
-    def delete_run(self, run_id: str) -> bool:
-        """Delete a run from the registry"""
-        if run_id in self.runs:
-            del self.runs[run_id]
-            self.save_runs()
-            return True
-        return False
-
-# Global registry instance
-registry = RunRegistry()
-
-def create_run_config_from_generation_data(
-    generation_data: Dict[str, Any],
-    generated_images: List[str],
-    generation_type: str
-) -> RunConfig:
-    """Create a RunConfig from generation data"""
-    
-    # Extract configuration from generation data
-    config = RunConfig(
-        run_id=str(uuid.uuid4()),
-        timestamp=datetime.now().isoformat(),
-        model=generation_data.get('model_name', 'unknown'),
-        vae=generation_data.get('vae_name'),
-        loras=generation_data.get('lora', []),
-        controlnets=generation_data.get('controlnet', {}).get('units', []),
-        prompt=generation_data.get('prompt', ''),
-        negative_prompt=generation_data.get('negative_prompt', ''),
-        seed=generation_data.get('seed', 0),
-        sampler=generation_data.get('sampler_name', 'euler'),
-        steps=generation_data.get('steps', 20),
-        cfg_scale=generation_data.get('cfg_scale', 7.0),
-        width=generation_data.get('width', 512),
-        height=generation_data.get('height', 512),
-        batch_size=generation_data.get('batch_size', 1),
-        batch_count=generation_data.get('batch_count', 1),
-        workflow=generation_data.get('workflow', {}),
-        version="1.0.0",  # TODO: Get from app version
-        generated_images=generated_images,
-        generation_type=generation_type
-    )
-    
-    return config
-
-# Flask app for run registry API
-app = Flask(__name__)
-CORS(app, resources={
-    r"/*": {
-        "origins": ["http://localhost:*", "http://127.0.0.1:*"],
-        "methods": ["GET", "POST", "DELETE", "OPTIONS"],
-        "allow_headers": ["Content-Type"]
-    }
-})
-
-@app.route('/api/runs', methods=['GET'])
-def get_runs():
-    """Get all completed runs"""
-    try:
-        runs = registry.get_all_runs()
-        return jsonify({
-            "status": "success",
-            "runs": [asdict(run) for run in runs]
-        })
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/runs/<run_id>', methods=['GET'])
-def get_run(run_id: str):
-    """Get a specific run by ID"""
-    try:
-        run = registry.get_run(run_id)
-        if run:
-            return jsonify({
-                "status": "success",
-                "run": asdict(run)
-            })
-        else:
-            return jsonify({
-                "status": "error",
-                "message": "Run not found"
-            }), 404
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/runs', methods=['POST'])
-def add_run():
-    """Add a new completed run"""
-    try:
-        data = request.json
-        if not data:
-            return jsonify({
-                "status": "error",
-                "message": "No data provided"
-            }), 400
-        
-        # Create run config from the provided data
-        run_config = RunConfig(
-            run_id=data.get('run_id', str(uuid.uuid4())),
-            timestamp=data.get('timestamp', datetime.now().isoformat()),
-            model=data.get('model', 'unknown'),
-            vae=data.get('vae'),
-            loras=data.get('loras', []),
-            controlnets=data.get('controlnets', []),
-            prompt=data.get('prompt', ''),
-            negative_prompt=data.get('negative_prompt', ''),
-            seed=data.get('seed', 0),
-            sampler=data.get('sampler', 'euler'),
-            steps=data.get('steps', 20),
-            cfg_scale=data.get('cfg_scale', 7.0),
-            width=data.get('width', 512),
-            height=data.get('height', 512),
-            batch_size=data.get('batch_size', 1),
-            batch_count=data.get('batch_count', 1),
-            workflow=data.get('workflow', {}),
-            version=data.get('version', '1.0.0'),
-            generated_images=data.get('generated_images', []),
-            generation_type=data.get('generation_type', 'txt2img')
-        )
-        
-        registry.add_run(run_config)
-        
-        return jsonify({
-            "status": "success",
-            "run_id": run_config.run_id,
-            "message": "Run added successfully"
-        })
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-@app.route('/api/runs/<run_id>', methods=['DELETE'])
-def delete_run(run_id: str):
-    """Delete a run"""
-    try:
-        success = registry.delete_run(run_id)
-        if success:
-            return jsonify({
-                "status": "success",
-                "message": "Run deleted successfully"
-            })
-        else:
-            return jsonify({
-                "status": "error",
-                "message": "Run not found"
-            }), 404
-    except Exception as e:
-        return jsonify({
-            "status": "error",
-            "message": str(e)
-        }), 500
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5005, debug=True)
\ No newline at end of file
diff --git a/dream_layer_backend/shared_utils.py b/dream_layer_backend/shared_utils.py
index a5952bff..47348620 100644
--- a/dream_layer_backend/shared_utils.py
+++ b/dream_layer_backend/shared_utils.py
@@ -4,20 +4,21 @@
 import requests
 import copy
 import json
+import sys
+import traceback
+from flask import send_file, jsonify
 from typing import List, Dict, Any
 from pathlib import Path
-from dream_layer import get_directories
+from dream_layer_backend_utils.workflow_loader import analyze_workflow
 from dream_layer_backend_utils.update_custom_workflow import find_save_node
 from dream_layer_backend_utils.shared_workflow_parameters import increment_seed_in_workflow
 
-# Global constants
 COMFY_API_URL = "http://127.0.0.1:8188"
 SERVED_IMAGES_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'served_images')
+MATRIX_GRIDS_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'matrix_grids')
 
-# Model display name mapping file
 MODEL_DISPLAY_NAMES_FILE = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'model_display_names.json')
 
-# Display names are user-friendly names for models, stored in a JSON file
 def load_model_display_names() -> Dict[str, str]:
     """Load the mapping of actual filenames to display names"""
     try:
@@ -48,11 +49,9 @@ def get_model_display_name(filename: str) -> str:
     if filename in mapping:
         return mapping[filename]
 
-    # Fallback: process the filename to create a display name
     name = Path(filename).stem.replace('-', ' ').replace('_', ' ')
     return ' '.join(word.capitalize() for word in name.split())
 
-# Sampler name mapping from frontend to ComfyUI
 SAMPLER_NAME_MAP = {
     'Euler': 'euler',
     'Euler a': 'euler_ancestral',
@@ -74,38 +73,36 @@ def get_model_display_name(filename: str) -> str:
     'DDIM': 'ddim',
     'PLMS': 'plms'
 }
+
 os.makedirs(SERVED_IMAGES_DIR, exist_ok=True)
+os.makedirs(MATRIX_GRIDS_DIR, exist_ok=True)
 
 def wait_for_image(prompt_id: str, save_node_id: str = "9", max_wait_time: int = 300) -> List[Dict[str, Any]]:
     """
     Wait for image generation to complete and return the generated images
     This is a shared function used by both txt2img and img2img servers
     """
-    print("wait_for_image")
+    from dream_layer import get_directories
+    
     output_dir, _ = get_directories()
     start_time = time.time()
     
     while time.time() - start_time < max_wait_time:
         try:
-            # Check queue status
             response = requests.get(f"{COMFY_API_URL}/queue")
             if response.status_code == 200:
                 queue_data = response.json()
                 
-                # Check if our prompt is still in queue
                 running_queue = queue_data.get('queue_running', [])
                 pending_queue = queue_data.get('queue_pending', [])
                 
-                # Look for our prompt_id in running or pending queues
                 prompt_in_queue = any(item[1] == prompt_id for item in running_queue + pending_queue)
                 
                 if not prompt_in_queue:
-                    # Prompt is no longer in queue, check for results
                     history_response = requests.get(f"{COMFY_API_URL}/history/{prompt_id}")
                     if history_response.status_code == 200:
                         history_data = history_response.json()
                         if prompt_id in history_data:
-                            # Get outputs from the save node
                             outputs = history_data[prompt_id].get('outputs', {})
                             if save_node_id in outputs:
                                 images_data = outputs[save_node_id].get('images', [])
@@ -116,7 +113,6 @@ def wait_for_image(prompt_id: str, save_node_id: str = "9", max_wait_time: int =
                                         filename = img_info.get('filename')
                                         print(f"📄 Processing image: {filename}")
                                         if filename:
-                                            # Copy to served images directory
                                             src_path = os.path.join(output_dir, filename)
                                             dest_path = os.path.join(SERVED_IMAGES_DIR, filename)
                                             
@@ -129,7 +125,6 @@ def wait_for_image(prompt_id: str, save_node_id: str = "9", max_wait_time: int =
                                                 try:
                                                     shutil.copy2(src_path, dest_path)
                                                     print(f"✅ Successfully copied {filename} to served directory")
-                                                    # Create proper image object with URL
                                                     image_objects.append({
                                                         "filename": filename,
                                                         "url": f"http://localhost:5001/api/images/{filename}",
@@ -149,7 +144,7 @@ def wait_for_image(prompt_id: str, save_node_id: str = "9", max_wait_time: int =
                                 else:
                                     print("⚠️ No images found in save node")
             
-            time.sleep(2)  # Wait 2 seconds before checking again
+            time.sleep(2)
             
         except Exception as e:
             print(f"Error checking image status: {e}")
@@ -169,25 +164,21 @@ def send_to_comfyui(workflow: Dict[str, Any]) -> Dict[str, Any]:
         batch_size = workflow_info['batch_size']
         
         if workflow_info['is_api']:
-            # API workflows: remove batch_size, loop multiple times
             for node in workflow.get('prompt', {}).values():
                 if 'batch_size' in node.get('inputs', {}):
                     del node['inputs']['batch_size']
                     break
             iterations = batch_size
         else:
-            # Local workflows: keep batch_size, loop once
             iterations = 1
         
         all_images = []
         last_response_data = None
         
         for i in range(iterations):
-            # Increment seed for variation
 
             current_workflow = increment_seed_in_workflow(copy.deepcopy(workflow), i) if i > 0 else workflow
             
-            # Send to ComfyUI
             response = requests.post(f"{COMFY_API_URL}/prompt", json=current_workflow)
             
             if response.status_code == 200:
@@ -209,7 +200,6 @@ def send_to_comfyui(workflow: Dict[str, Any]) -> Dict[str, Any]:
                 return {"error": error_msg}
         
         if all_images:
-            # Return the last valid ComfyUI response but with all images
             if last_response_data:
                 last_response_data["all_images"] = all_images
                 last_response_data["generated_images"] = all_images
@@ -228,41 +218,62 @@ def serve_image(filename: str) -> Any:
     This is a shared function used by all servers
     """
     from flask import send_file, jsonify
-    
+
     try:
-        # First check in served_images directory (for generated images)
+        print(f"🔍 Attempting to serve image: {filename}")
+        
+        if filename.startswith('matrix-grid'):
+            matrix_filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+            print(f"📁 Checking matrix_grids: {matrix_filepath}")
+            print(f"📁 Matrix grids directory exists: {os.path.exists(MATRIX_GRIDS_DIR)}")
+            if os.path.exists(MATRIX_GRIDS_DIR):
+                print(f"📁 Matrix grids directory contents: {os.listdir(MATRIX_GRIDS_DIR)}")
+            
+            if os.path.exists(matrix_filepath):
+                print(f"✅ Found matrix grid: {matrix_filepath}")
+                print(f"📏 File size: {os.path.getsize(matrix_filepath)} bytes")
+                return send_file(matrix_filepath, mimetype='image/png')
+        
         served_filepath = os.path.join(SERVED_IMAGES_DIR, filename)
+        print(f"📁 Checking served_images: {served_filepath}")
+        print(f"📁 Served directory exists: {os.path.exists(SERVED_IMAGES_DIR)}")
+        print(f"📁 Served directory contents: {os.listdir(SERVED_IMAGES_DIR) if os.path.exists(SERVED_IMAGES_DIR) else 'Directory not found'}")
         
         if os.path.exists(served_filepath):
+            print(f"✅ Found in served_images: {served_filepath}")
+            print(f"📏 File size: {os.path.getsize(served_filepath)} bytes")
             return send_file(served_filepath, mimetype='image/png')
         
-        # If not found in served_images, check in ComfyUI input directory (for ControlNet images)
         current_dir = os.path.dirname(os.path.abspath(__file__))
         parent_dir = os.path.dirname(current_dir)
         input_dir = os.path.join(parent_dir, "ComfyUI", "input")
         input_filepath = os.path.join(input_dir, filename)
+        print(f"📁 Checking ComfyUI input: {input_filepath}")
         
         if os.path.exists(input_filepath):
+            print(f"✅ Found in ComfyUI input: {input_filepath}")
             return send_file(input_filepath, mimetype='image/png')
         
-        # If not found in either location, check ComfyUI output directory
         output_dir, _ = get_directories()
         output_filepath = os.path.join(output_dir, filename)
+        print(f"📁 Checking ComfyUI output: {output_filepath}")
         
         if os.path.exists(output_filepath):
+            print(f"✅ Found in ComfyUI output: {output_filepath}")
             return send_file(output_filepath, mimetype='image/png')
         
-        # If still not found, return 404
-        print(f"❌ Image not found in any directory: {filename}")
-        print(f"   Checked: {served_filepath}")
-        print(f"   Checked: {input_filepath}")
-        print(f"   Checked: {output_filepath}")
+        if not filename.startswith('matrix-grid'):
+            matrix_filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+            if os.path.exists(matrix_filepath):
+                print(f"✅ Found in matrix_grids (fallback): {matrix_filepath}")
+                return send_file(matrix_filepath, mimetype='image/png')
         
+        print(f"❌ Image not found in any directory: {filename}")
         return jsonify({
             "status": "error",
-            "message": "Image not found"
+            "message": f"Image {filename} not found"
         }), 404
-            
+        
     except Exception as e:
         print(f"❌ Error serving image {filename}: {str(e)}")
         return jsonify({
@@ -322,7 +333,6 @@ def upload_controlnet_image(file, unit_index: int = 0) -> Dict[str, Any]:
             
     except Exception as e:
         print(f"❌ Error uploading ControlNet image: {str(e)}")
-        import traceback
         traceback.print_exc()
         return {
             "status": "error",
@@ -352,7 +362,6 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
                 "message": "No file provided or no file selected"
             }, 400
 
-        # Validate file extension - support common model formats
         allowed_extensions = {'.safetensors', '.ckpt', '.pth', '.pt', '.bin'}
         file_ext = Path(file.filename).suffix.lower()
 
@@ -366,12 +375,10 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
         print(f"📊 File content type: {file.content_type}")
         print(f"🏷️ Model type: {model_type}")
 
-        # Get ComfyUI models directory structure
         current_dir = os.path.dirname(os.path.abspath(__file__))
         project_root = os.path.dirname(current_dir)
         comfyui_models_dir = os.path.join(project_root, "ComfyUI", "models")
 
-        # Map model types to directories
         model_type_dirs = {
             "checkpoints": "checkpoints",
             "loras": "loras",
@@ -405,16 +412,13 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
                 "message": "Invalid target directory"
             }, 400
 
-        # Create target directory if it doesn't exist
         os.makedirs(target_dir, exist_ok=True)
         print(f"📁 Target directory: {target_dir}")
 
-        # Generate safe filename with timestamp for storage
         timestamp = int(time.time() * 1000)
         safe_filename = f"{Path(file.filename).stem}_{timestamp}{file_ext}"
         target_path = Path(target_dir) / safe_filename
 
-        # Create display name from original filename (without timestamp)
         original_display_name = Path(file.filename).stem.replace('-', ' ').replace('_', ' ')
         original_display_name = ' '.join(word.capitalize() for word in original_display_name.split())
 
@@ -433,7 +437,6 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
 
         print(f"📄 Saving to: {target_path}")
 
-        # 🔒 ATOMIC WRITE: Write to temporary file first
         temp_path = target_path.with_suffix(target_path.suffix + '.tmp')
 
         try:
@@ -443,34 +446,28 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
                 f.flush()
                 os.fsync(f.fileno())
 
-            # Atomic rename to final destination
             temp_path.rename(target_path)
 
             print(f"✅ Atomic write completed: {safe_filename}")
 
         except Exception as e:
-            # Clean up temp file if something went wrong
             if temp_path.exists():
                 temp_path.unlink()
             raise e
 
-        # Verify file was created successfully
         if target_path.exists():
             file_size = target_path.stat().st_size
             print(f"✅ Successfully saved model: {safe_filename}")
             print(f"📏 File size: {file_size} bytes")
 
-            # 💾 DISPLAY NAME: Save the display name mapping
             add_model_display_name(safe_filename, original_display_name)
             print(f"📝 Display name mapping saved: {safe_filename} -> {original_display_name}")
 
-            # 🔄 WEBSOCKET: Emit model refresh event
             try:
                 emit_model_refresh(model_type, safe_filename)
                 print(f"📡 WebSocket event emitted: models-refresh for {model_type}")
             except Exception as ws_error:
                 print(f"⚠️ Warning: Failed to emit WebSocket event: {ws_error}")
-                # Don't fail the upload if WebSocket fails
 
             return {
                 "status": "success",
@@ -491,7 +488,6 @@ def upload_model_file(file, model_type: str = "checkpoints") -> Dict[str, Any]:
 
     except Exception as e:
         print(f"❌ Error uploading model: {str(e)}")
-        import traceback
         traceback.print_exc()
         return {
             "status": "error",
@@ -507,11 +503,9 @@ def _setup_comfyui_websocket():
         PromptServer instance if available, None otherwise
     """
     try:
-        # Import ComfyUI server here to avoid circular imports
+        
         import sys
         import os
-
-        # Add ComfyUI to path if not already there
         current_dir = os.path.dirname(os.path.abspath(__file__))
         project_root = os.path.dirname(current_dir)
         comfyui_dir = os.path.join(project_root, "ComfyUI")
@@ -519,10 +513,8 @@ def _setup_comfyui_websocket():
         if comfyui_dir not in sys.path:
             sys.path.insert(0, comfyui_dir)
 
-        # Import PromptServer from ComfyUI
         from server import PromptServer
 
-        # Check if PromptServer instance exists
         if hasattr(PromptServer, 'instance') and PromptServer.instance is not None:
             return PromptServer.instance
 
@@ -545,7 +537,6 @@ def emit_model_refresh(model_type: str, filename: str) -> None:
         prompt_server = _setup_comfyui_websocket()
 
         if prompt_server is not None:
-            # Create the WebSocket event data
             event_data = {
                 "model_type": model_type,
                 "filename": filename,
@@ -556,7 +547,6 @@ def emit_model_refresh(model_type: str, filename: str) -> None:
             print("📡 Emitting WebSocket event: models-refresh")
             print(f"📊 Event data: {event_data}")
 
-            # Emit the event using ComfyUI's WebSocket infrastructure
             prompt_server.send_sync("models-refresh", event_data)
 
             print("✅ WebSocket event sent successfully")
@@ -568,6 +558,4 @@ def emit_model_refresh(model_type: str, filename: str) -> None:
         print(f"⚠️ Warning: Could not import ComfyUI server for WebSocket: {e}")
     except Exception as e:
         print(f"❌ Error emitting WebSocket event: {e}")
-        import traceback
-        traceback.print_exc()
-        # Don't raise - we don't want WebSocket failures to break uploads
\ No newline at end of file
+        traceback.print_exc()
\ No newline at end of file
diff --git a/dream_layer_backend/tests/test_report_bundle.py b/dream_layer_backend/tests/test_report_bundle.py
deleted file mode 100644
index 52350888..00000000
--- a/dream_layer_backend/tests/test_report_bundle.py
+++ /dev/null
@@ -1,400 +0,0 @@
-import pytest
-import json
-import csv
-import tempfile
-import os
-import zipfile
-from datetime import datetime
-from report_bundle import ReportBundleGenerator, RunConfig
-
-class TestReportBundle:
-    """Test cases for the Report Bundle functionality"""
-    
-    def setup_method(self):
-        """Set up test fixtures"""
-        # Create temporary directories for testing
-        self.temp_output_dir = tempfile.mkdtemp()
-        self.generator = ReportBundleGenerator(self.temp_output_dir)
-        
-        # Create test images
-        self.test_images = []
-        for i in range(3):
-            image_path = os.path.join(self.temp_output_dir, f"test_image_{i}.png")
-            with open(image_path, 'w') as f:
-                f.write(f"fake image data {i}")
-            self.test_images.append(f"test_image_{i}.png")
-    
-    def teardown_method(self):
-        """Clean up test fixtures"""
-        import shutil
-        if os.path.exists(self.temp_output_dir):
-            shutil.rmtree(self.temp_output_dir)
-    
-    def test_required_csv_columns_exist(self):
-        """Test that CSV has all required columns"""
-        # Create test runs
-        test_runs = [
-            RunConfig(
-                run_id="test-run-1",
-                timestamp=datetime.now().isoformat(),
-                model="test-model.safetensors",
-                vae=None,
-                loras=[],
-                controlnets=[],
-                prompt="test prompt 1",
-                negative_prompt="test negative 1",
-                seed=12345,
-                sampler="euler",
-                steps=20,
-                cfg_scale=7.0,
-                width=512,
-                height=512,
-                batch_size=1,
-                batch_count=1,
-                workflow={},
-                version="1.0.0",
-                generated_images=self.test_images[:1],
-                generation_type="txt2img"
-            ),
-            RunConfig(
-                run_id="test-run-2",
-                timestamp=datetime.now().isoformat(),
-                model="test-model-2.safetensors",
-                vae="test-vae.safetensors",
-                loras=[{"name": "test-lora", "strength": 0.8}],
-                controlnets=[{"model": "test-controlnet", "strength": 1.0, "enabled": True}],
-                prompt="test prompt 2",
-                negative_prompt="test negative 2",
-                seed=67890,
-                sampler="dpm++",
-                steps=30,
-                cfg_scale=8.5,
-                width=768,
-                height=768,
-                batch_size=2,
-                batch_count=3,
-                workflow={"test": "workflow"},
-                version="1.0.0",
-                generated_images=self.test_images[1:],
-                generation_type="img2img"
-            )
-        ]
-        
-        # Generate CSV
-        csv_path = self.generator.generate_csv(test_runs)
-        
-        # Validate schema
-        assert self.generator.validate_csv_schema(csv_path)
-        
-        # Check that all required columns exist
-        with open(csv_path, 'r', encoding='utf-8') as f:
-            reader = csv.DictReader(f)
-            fieldnames = reader.fieldnames
-            
-            required_columns = [
-                'run_id', 'timestamp', 'model', 'vae', 'prompt', 
-                'negative_prompt', 'seed', 'sampler', 'steps', 'cfg_scale',
-                'width', 'height', 'batch_size', 'batch_count', 
-                'generation_type', 'image_paths', 'loras', 'controlnets', 'workflow_hash'
-            ]
-            
-            for column in required_columns:
-                assert column in fieldnames, f"Missing required column: {column}"
-        
-        # Cleanup
-        if os.path.exists(csv_path):
-            os.remove(csv_path)
-    
-    def test_empty_values_handled_without_crashes(self):
-        """Test that empty values are handled without crashes"""
-        # Create test run with empty values
-        test_run = RunConfig(
-            run_id="",
-            timestamp="",
-            model="",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="",
-            negative_prompt="",
-            seed=0,
-            sampler="",
-            steps=0,
-            cfg_scale=0.0,
-            width=0,
-            height=0,
-            batch_size=0,
-            batch_count=0,
-            workflow={},
-            version="",
-            generated_images=[],
-            generation_type=""
-        )
-        
-        # Should not crash when generating CSV
-        csv_path = self.generator.generate_csv([test_run])
-        
-        # Should not crash when validating schema
-        assert self.generator.validate_csv_schema(csv_path)
-        
-        # Cleanup
-        if os.path.exists(csv_path):
-            os.remove(csv_path)
-    
-    def test_csv_schema_validation(self):
-        """Test CSV schema validation with valid and invalid schemas"""
-        # Test valid CSV
-        valid_csv_content = """run_id,timestamp,model,vae,prompt,negative_prompt,seed,sampler,steps,cfg_scale,width,height,batch_size,batch_count,generation_type,image_paths,loras,controlnets,workflow_hash
-test-run,2023-01-01T00:00:00,model.safetensors,vae.safetensors,prompt,negative,123,euler,20,7.0,512,512,1,1,txt2img,image.png,[],[],hash123"""
-        
-        temp_csv = "temp_valid.csv"
-        with open(temp_csv, 'w', encoding='utf-8') as f:
-            f.write(valid_csv_content)
-        
-        assert self.generator.validate_csv_schema(temp_csv)
-        
-        # Test invalid CSV (missing columns)
-        invalid_csv_content = """run_id,timestamp,model,prompt,seed
-test-run,2023-01-01T00:00:00,model.safetensors,prompt,123"""
-        
-        temp_csv_invalid = "temp_invalid.csv"
-        with open(temp_csv_invalid, 'w', encoding='utf-8') as f:
-            f.write(invalid_csv_content)
-        
-        assert not self.generator.validate_csv_schema(temp_csv_invalid)
-        
-        # Cleanup
-        for temp_file in [temp_csv, temp_csv_invalid]:
-            if os.path.exists(temp_file):
-                os.remove(temp_file)
-    
-    def test_image_paths_resolve_to_files(self):
-        """Test that all image paths in CSV resolve to files present in zip"""
-        # Create test runs with images
-        test_runs = [
-            RunConfig(
-                run_id="test-run-1",
-                timestamp=datetime.now().isoformat(),
-                model="test-model.safetensors",
-                vae=None,
-                loras=[],
-                controlnets=[],
-                prompt="test prompt",
-                negative_prompt="",
-                seed=12345,
-                sampler="euler",
-                steps=20,
-                cfg_scale=7.0,
-                width=512,
-                height=512,
-                batch_size=1,
-                batch_count=1,
-                workflow={},
-                version="1.0.0",
-                generated_images=self.test_images,
-                generation_type="txt2img"
-            )
-        ]
-        
-        # Mock the registry to return our test runs
-        self.generator.registry.runs = {run.run_id: run for run in test_runs}
-        
-        # Create report bundle
-        zip_path = self.generator.create_report_bundle([test_run.run_id for test_run in test_runs])
-        
-        # Verify zip file exists
-        assert os.path.exists(zip_path)
-        
-        # Extract and verify contents
-        with zipfile.ZipFile(zip_path, 'r') as zipf:
-            # Check that results.csv exists
-            csv_files = [f for f in zipf.namelist() if f.endswith('results.csv')]
-            assert len(csv_files) == 1
-            
-            # Read CSV and verify image paths
-            with zipf.open(csv_files[0]) as csv_file:
-                reader = csv.DictReader(csv_file.read().decode('utf-8').splitlines())
-                for row in reader:
-                    image_paths = row['image_paths'].split(';') if row['image_paths'] else []
-                    for image_path in image_paths:
-                        if image_path.strip():
-                            # Check that image exists in zip
-                            image_in_zip = f"images/{image_path}"
-                            assert image_in_zip in zipf.namelist(), f"Image {image_path} not found in zip"
-            
-            # Check that config.json exists
-            config_files = [f for f in zipf.namelist() if f.endswith('config.json')]
-            assert len(config_files) == 1
-            
-            # Check that README.md exists
-            readme_files = [f for f in zipf.namelist() if f.endswith('README.md')]
-            assert len(readme_files) == 1
-        
-        # Cleanup
-        if os.path.exists(zip_path):
-            os.remove(zip_path)
-    
-    def test_deterministic_file_names_and_paths(self):
-        """Test that file names and paths are deterministic"""
-        test_runs = [
-            RunConfig(
-                run_id="test-run-1",
-                timestamp=datetime.now().isoformat(),
-                model="test-model.safetensors",
-                vae=None,
-                loras=[],
-                controlnets=[],
-                prompt="test prompt",
-                negative_prompt="",
-                seed=12345,
-                sampler="euler",
-                steps=20,
-                cfg_scale=7.0,
-                width=512,
-                height=512,
-                batch_size=1,
-                batch_count=1,
-                workflow={},
-                version="1.0.0",
-                generated_images=self.test_images[:1],
-                generation_type="txt2img"
-            )
-        ]
-        
-        # Mock the registry to return our test runs
-        self.generator.registry.runs = {run.run_id: run for run in test_runs}
-        
-        # Create two report bundles with same data
-        zip_path_1 = self.generator.create_report_bundle([test_runs[0].run_id])
-        zip_path_2 = self.generator.create_report_bundle([test_runs[0].run_id])
-        
-        # Verify both zip files exist
-        assert os.path.exists(zip_path_1)
-        assert os.path.exists(zip_path_2)
-        
-        # Check that both zips have same structure
-        with zipfile.ZipFile(zip_path_1, 'r') as zip1, zipfile.ZipFile(zip_path_2, 'r') as zip2:
-            files_1 = sorted(zip1.namelist())
-            files_2 = sorted(zip2.namelist())
-            
-            # Should have same files
-            assert files_1 == files_2
-            
-            # Should have expected file structure
-            expected_files = [
-                'results.csv',
-                'config.json', 
-                'README.md',
-                'images/test_image_0.png'
-            ]
-            
-            for expected_file in expected_files:
-                assert any(f.endswith(expected_file) for f in files_1), f"Missing {expected_file}"
-        
-        # Cleanup
-        for zip_path in [zip_path_1, zip_path_2]:
-            if os.path.exists(zip_path):
-                os.remove(zip_path)
-    
-    def test_config_json_structure(self):
-        """Test that config.json has correct structure"""
-        test_runs = [
-            RunConfig(
-                run_id="test-run-1",
-                timestamp=datetime.now().isoformat(),
-                model="test-model.safetensors",
-                vae=None,
-                loras=[],
-                controlnets=[],
-                prompt="test prompt",
-                negative_prompt="",
-                seed=12345,
-                sampler="euler",
-                steps=20,
-                cfg_scale=7.0,
-                width=512,
-                height=512,
-                batch_size=1,
-                batch_count=1,
-                workflow={},
-                version="1.0.0",
-                generated_images=self.test_images[:1],
-                generation_type="txt2img"
-            )
-        ]
-        
-        # Create config.json
-        config_path = self.generator.create_config_json(test_runs)
-        
-        # Verify structure
-        with open(config_path, 'r', encoding='utf-8') as f:
-            config_data = json.load(f)
-        
-        # Check required top-level keys
-        assert 'report_metadata' in config_data
-        assert 'runs' in config_data
-        
-        # Check metadata structure
-        metadata = config_data['report_metadata']
-        assert 'generated_at' in metadata
-        assert 'total_runs' in metadata
-        assert 'generation_types' in metadata
-        assert 'models_used' in metadata
-        
-        # Check runs structure
-        runs = config_data['runs']
-        assert len(runs) == 1
-        assert runs[0]['run_id'] == 'test-run-1'
-        
-        # Cleanup
-        if os.path.exists(config_path):
-            os.remove(config_path)
-    
-    def test_readme_content(self):
-        """Test that README.md has correct content"""
-        test_runs = [
-            RunConfig(
-                run_id="test-run-1",
-                timestamp=datetime.now().isoformat(),
-                model="test-model.safetensors",
-                vae=None,
-                loras=[],
-                controlnets=[],
-                prompt="test prompt",
-                negative_prompt="",
-                seed=12345,
-                sampler="euler",
-                steps=20,
-                cfg_scale=7.0,
-                width=512,
-                height=512,
-                batch_size=1,
-                batch_count=1,
-                workflow={},
-                version="1.0.0",
-                generated_images=self.test_images[:1],
-                generation_type="txt2img"
-            )
-        ]
-        
-        # Create README
-        readme_path = self.generator.create_readme(test_runs, self.test_images[:1])
-        
-        # Verify content
-        with open(readme_path, 'r', encoding='utf-8') as f:
-            content = f.read()
-        
-        # Check for required sections
-        assert '# Dream Layer Report Bundle' in content
-        assert '## Overview' in content
-        assert '## Contents' in content
-        assert '## Statistics' in content
-        assert '## CSV Schema' in content
-        assert 'results.csv' in content
-        assert 'config.json' in content
-        assert 'images/' in content
-        assert 'README.md' in content
-        
-        # Cleanup
-        if os.path.exists(readme_path):
-            os.remove(readme_path) 
\ No newline at end of file
diff --git a/dream_layer_backend/tests/test_run_registry.py b/dream_layer_backend/tests/test_run_registry.py
deleted file mode 100644
index ad3895ef..00000000
--- a/dream_layer_backend/tests/test_run_registry.py
+++ /dev/null
@@ -1,325 +0,0 @@
-import pytest
-import json
-import tempfile
-import os
-from datetime import datetime
-from run_registry import RunConfig, RunRegistry, create_run_config_from_generation_data
-
-class TestRunRegistry:
-    """Test cases for the Run Registry functionality"""
-    
-    def setup_method(self):
-        """Set up test fixtures"""
-        # Create a temporary file for testing
-        self.temp_file = tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.json')
-        self.temp_file.close()
-        self.registry = RunRegistry(self.temp_file.name)
-    
-    def teardown_method(self):
-        """Clean up test fixtures"""
-        if os.path.exists(self.temp_file.name):
-            os.unlink(self.temp_file.name)
-    
-    def test_required_keys_exist(self):
-        """Test that RunConfig has all required keys"""
-        # Create a minimal run config with all required fields
-        config = RunConfig(
-            run_id="test-run-123",
-            timestamp=datetime.now().isoformat(),
-            model="test-model.safetensors",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="test prompt",
-            negative_prompt="test negative",
-            seed=12345,
-            sampler="euler",
-            steps=20,
-            cfg_scale=7.0,
-            width=512,
-            height=512,
-            batch_size=1,
-            batch_count=1,
-            workflow={},
-            version="1.0.0",
-            generated_images=[],
-            generation_type="txt2img"
-        )
-        
-        # Assert all required keys exist
-        required_keys = [
-            'run_id', 'timestamp', 'model', 'vae', 'loras', 'controlnets',
-            'prompt', 'negative_prompt', 'seed', 'sampler', 'steps', 'cfg_scale',
-            'width', 'height', 'batch_size', 'batch_count', 'workflow', 'version',
-            'generated_images', 'generation_type'
-        ]
-        
-        for key in required_keys:
-            assert hasattr(config, key), f"Missing required key: {key}"
-    
-    def test_empty_values_handled(self):
-        """Test that empty values are handled without crashes"""
-        # Test with empty strings and None values
-        config = RunConfig(
-            run_id="",
-            timestamp="",
-            model="",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="",
-            negative_prompt="",
-            seed=0,
-            sampler="",
-            steps=0,
-            cfg_scale=0.0,
-            width=0,
-            height=0,
-            batch_size=0,
-            batch_count=0,
-            workflow={},
-            version="",
-            generated_images=[],
-            generation_type=""
-        )
-        
-        # Should not crash when accessing any field
-        assert config.run_id == ""
-        assert config.prompt == ""
-        assert config.negative_prompt == ""
-        assert config.model == ""
-        assert config.vae is None
-        assert config.loras == []
-        assert config.controlnets == []
-        assert config.seed == 0
-        assert config.sampler == ""
-        assert config.steps == 0
-        assert config.cfg_scale == 0.0
-        assert config.width == 0
-        assert config.height == 0
-        assert config.batch_size == 0
-        assert config.batch_count == 0
-        assert config.workflow == {}
-        assert config.version == ""
-        assert config.generated_images == []
-        assert config.generation_type == ""
-    
-    def test_create_run_config_from_generation_data(self):
-        """Test creating run config from generation data"""
-        # Test with minimal data
-        generation_data = {
-            'prompt': 'test prompt',
-            'negative_prompt': 'test negative',
-            'model_name': 'test-model.safetensors',
-            'seed': 12345,
-            'sampler_name': 'euler',
-            'steps': 20,
-            'cfg_scale': 7.0,
-            'width': 512,
-            'height': 512,
-            'batch_size': 1,
-            'batch_count': 1
-        }
-        
-        generated_images = ['test-image-1.png', 'test-image-2.png']
-        
-        config = create_run_config_from_generation_data(
-            generation_data, generated_images, "txt2img"
-        )
-        
-        # Assert required keys exist
-        assert hasattr(config, 'run_id')
-        assert hasattr(config, 'timestamp')
-        assert hasattr(config, 'model')
-        assert hasattr(config, 'prompt')
-        assert hasattr(config, 'negative_prompt')
-        assert hasattr(config, 'seed')
-        assert hasattr(config, 'sampler')
-        assert hasattr(config, 'steps')
-        assert hasattr(config, 'cfg_scale')
-        assert hasattr(config, 'width')
-        assert hasattr(config, 'height')
-        assert hasattr(config, 'batch_size')
-        assert hasattr(config, 'batch_count')
-        assert hasattr(config, 'workflow')
-        assert hasattr(config, 'version')
-        assert hasattr(config, 'generated_images')
-        assert hasattr(config, 'generation_type')
-        
-        # Assert values are set correctly
-        assert config.prompt == 'test prompt'
-        assert config.negative_prompt == 'test negative'
-        assert config.model == 'test-model.safetensors'
-        assert config.seed == 12345
-        assert config.sampler == 'euler'
-        assert config.steps == 20
-        assert config.cfg_scale == 7.0
-        assert config.width == 512
-        assert config.height == 512
-        assert config.batch_size == 1
-        assert config.batch_count == 1
-        assert config.generated_images == generated_images
-        assert config.generation_type == 'txt2img'
-    
-    def test_create_run_config_with_empty_data(self):
-        """Test creating run config with empty/missing data"""
-        # Test with minimal/empty data
-        generation_data = {}
-        generated_images = []
-        
-        config = create_run_config_from_generation_data(
-            generation_data, generated_images, "img2img"
-        )
-        
-        # Should not crash and should have default values
-        assert config.prompt == ''
-        assert config.negative_prompt == ''
-        assert config.model == 'unknown'
-        assert config.seed == 0
-        assert config.sampler == 'euler'
-        assert config.steps == 20
-        assert config.cfg_scale == 7.0
-        assert config.width == 512
-        assert config.height == 512
-        assert config.batch_size == 1
-        assert config.batch_count == 1
-        assert config.generated_images == []
-        assert config.generation_type == 'img2img'
-    
-    def test_registry_save_and_load(self):
-        """Test that registry can save and load runs"""
-        # Create a test run
-        config = RunConfig(
-            run_id="test-run-123",
-            timestamp=datetime.now().isoformat(),
-            model="test-model.safetensors",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="test prompt",
-            negative_prompt="test negative",
-            seed=12345,
-            sampler="euler",
-            steps=20,
-            cfg_scale=7.0,
-            width=512,
-            height=512,
-            batch_size=1,
-            batch_count=1,
-            workflow={},
-            version="1.0.0",
-            generated_images=[],
-            generation_type="txt2img"
-        )
-        
-        # Add to registry
-        self.registry.add_run(config)
-        
-        # Create new registry instance to test loading
-        new_registry = RunRegistry(self.temp_file.name)
-        
-        # Should load the saved run
-        loaded_run = new_registry.get_run("test-run-123")
-        assert loaded_run is not None
-        assert loaded_run.run_id == "test-run-123"
-        assert loaded_run.prompt == "test prompt"
-        assert loaded_run.model == "test-model.safetensors"
-    
-    def test_registry_get_all_runs(self):
-        """Test getting all runs"""
-        # Add multiple runs
-        config1 = RunConfig(
-            run_id="test-run-1",
-            timestamp="2023-01-01T00:00:00",
-            model="model1.safetensors",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="prompt 1",
-            negative_prompt="",
-            seed=1,
-            sampler="euler",
-            steps=20,
-            cfg_scale=7.0,
-            width=512,
-            height=512,
-            batch_size=1,
-            batch_count=1,
-            workflow={},
-            version="1.0.0",
-            generated_images=[],
-            generation_type="txt2img"
-        )
-        
-        config2 = RunConfig(
-            run_id="test-run-2",
-            timestamp="2023-01-02T00:00:00",
-            model="model2.safetensors",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="prompt 2",
-            negative_prompt="",
-            seed=2,
-            sampler="euler",
-            steps=20,
-            cfg_scale=7.0,
-            width=512,
-            height=512,
-            batch_size=1,
-            batch_count=1,
-            workflow={},
-            version="1.0.0",
-            generated_images=[],
-            generation_type="img2img"
-        )
-        
-        self.registry.add_run(config1)
-        self.registry.add_run(config2)
-        
-        # Get all runs (should be sorted by timestamp, newest first)
-        all_runs = self.registry.get_all_runs()
-        assert len(all_runs) == 2
-        assert all_runs[0].run_id == "test-run-2"  # Newer timestamp
-        assert all_runs[1].run_id == "test-run-1"  # Older timestamp
-    
-    def test_registry_delete_run(self):
-        """Test deleting a run"""
-        config = RunConfig(
-            run_id="test-run-to-delete",
-            timestamp=datetime.now().isoformat(),
-            model="test-model.safetensors",
-            vae=None,
-            loras=[],
-            controlnets=[],
-            prompt="test prompt",
-            negative_prompt="",
-            seed=12345,
-            sampler="euler",
-            steps=20,
-            cfg_scale=7.0,
-            width=512,
-            height=512,
-            batch_size=1,
-            batch_count=1,
-            workflow={},
-            version="1.0.0",
-            generated_images=[],
-            generation_type="txt2img"
-        )
-        
-        self.registry.add_run(config)
-        
-        # Verify run exists
-        assert self.registry.get_run("test-run-to-delete") is not None
-        
-        # Delete run
-        success = self.registry.delete_run("test-run-to-delete")
-        assert success is True
-        
-        # Verify run is deleted
-        assert self.registry.get_run("test-run-to-delete") is None
-        
-        # Try to delete non-existent run
-        success = self.registry.delete_run("non-existent-run")
-        assert success is False 
\ No newline at end of file
diff --git a/dream_layer_backend/txt2img_server.py b/dream_layer_backend/txt2img_server.py
index b03617a4..00fe8702 100644
--- a/dream_layer_backend/txt2img_server.py
+++ b/dream_layer_backend/txt2img_server.py
@@ -2,15 +2,20 @@
 from flask_cors import CORS
 import json
 import os
-import requests
 from dream_layer import get_directories
 from dream_layer_backend_utils import interrupt_workflow
 from shared_utils import  send_to_comfyui
 from dream_layer_backend_utils.fetch_advanced_models import get_controlnet_models
 from PIL import Image, ImageDraw
 from txt2img_workflow import transform_to_txt2img_workflow
-from run_registry import create_run_config_from_generation_data
-from dataclasses import asdict
+import base64
+import io
+import time
+import platform
+import subprocess
+import traceback
+from shared_utils import SERVED_IMAGES_DIR, serve_image, MATRIX_GRIDS_DIR
+from shared_utils import upload_controlnet_image as upload_cn_image
 
 app = Flask(__name__)
 CORS(app, resources={
@@ -21,13 +26,6 @@
     }
 })
 
-# Get served images directory
-output_dir, _ = get_directories()
-SERVED_IMAGES_DIR = os.path.join(os.path.dirname(__file__), 'served_images')
-os.makedirs(SERVED_IMAGES_DIR, exist_ok=True)
-
-
-
 @app.route('/api/txt2img', methods=['POST', 'OPTIONS'])
 def handle_txt2img():
     """Handle text-to-image generation requests"""
@@ -39,14 +37,12 @@ def handle_txt2img():
         if data:
             print("Data:", json.dumps(data, indent=2))
             
-            # Print specific fields of interest
             print("\nKey Parameters:")
             print("-"*20)
             print(f"Prompt: {data.get('prompt', 'Not provided')}")
             print(f"Negative Prompt: {data.get('negative_prompt', 'Not provided')}")
             print(f"Batch Size: {data.get('batch_size', 'Not provided')}")
             
-            # Check ControlNet data specifically
             controlnet_data = data.get('controlnet', {})
             print(f"\n🎮 ControlNet Data:")
             print("-"*20)
@@ -63,14 +59,11 @@ def handle_txt2img():
             else:
                 print("No ControlNet units found")
             
-            # Transform to ComfyUI workflow
-
             workflow = transform_to_txt2img_workflow(data)
             print("\nGenerated ComfyUI Workflow:")
             print("-"*20)
             print(json.dumps(workflow, indent=2))
             
-            # Send to ComfyUI server
             comfy_response = send_to_comfyui(workflow)
             
             if "error" in comfy_response:
@@ -79,41 +72,11 @@ def handle_txt2img():
                     "message": comfy_response["error"]
                 }), 500
             
-            # Extract generated image filenames
-            generated_images = []
-            if comfy_response.get("all_images"):
-                for img_data in comfy_response["all_images"]:
-                    if isinstance(img_data, dict) and "filename" in img_data:
-                        generated_images.append(img_data["filename"])
-            
-            print("Start register process")
-            # Register the completed run
-            try:
-                run_config = create_run_config_from_generation_data(
-                    data, generated_images, "txt2img"
-                )
-                
-                # Send to run registry
-                registry_response = requests.post(
-                    "http://localhost:5005/api/runs",
-                    json=asdict(run_config),
-                    timeout=5
-                )
-                
-                if registry_response.status_code == 200:
-                    print(f"✅ Run registered successfully: {run_config.run_id}")
-                else:
-                    print(f"⚠️ Failed to register run: {registry_response.text}")
-                    
-            except Exception as e:
-                print(f"⚠️ Error registering run: {str(e)}")
-            
             response = jsonify({
                 "status": "success",
                 "message": "Workflow sent to ComfyUI successfully",
                 "comfy_response": comfy_response,
-                "generated_images": comfy_response.get("all_images", []),
-                "run_id": run_config.run_id if 'run_config' in locals() else None
+                "generated_images": comfy_response.get("all_images", [])
             })
             
             return response
@@ -126,7 +89,6 @@ def handle_txt2img():
             
     except Exception as e:
         print(f"Error in handle_txt2img: {str(e)}")
-        import traceback
         traceback.print_exc()
         return jsonify({
             "status": "error",
@@ -147,8 +109,6 @@ def serve_image_endpoint(filename):
     This endpoint is needed here because the frontend expects it on this port
     """
     try:
-        # Use shared function
-        from shared_utils import serve_image
         return serve_image(filename)
             
     except Exception as e:
@@ -199,8 +159,6 @@ def upload_controlnet_image_endpoint():
         except ValueError:
             unit_index = 0
         
-        # Use shared function
-        from shared_utils import upload_controlnet_image as upload_cn_image
         result = upload_cn_image(file, unit_index)
         
         if isinstance(result, tuple):
@@ -210,7 +168,82 @@ def upload_controlnet_image_endpoint():
             
     except Exception as e:
         print(f"❌ Error uploading ControlNet image: {str(e)}")
-        import traceback
+        traceback.print_exc()
+        return jsonify({
+            "status": "error",
+            "message": str(e)
+        }), 500
+
+@app.route('/api/save-matrix-grid', methods=['POST'])
+def save_matrix_grid():
+    """
+    Save Matrix grid image to server storage (permanent directory)
+    """
+    try:
+        print(f"🔄 Matrix grid save request received")
+        data = request.json
+        
+        if not data or 'imageData' not in data:
+            print("❌ No image data in request")
+            return jsonify({
+                "status": "error",
+                "message": "No image data provided"
+            }), 400
+        
+        image_data = data['imageData']
+        if image_data.startswith('data:'):
+            image_data = image_data.split(',')[1]
+        
+        print(f"📊 Received base64 data length: {len(image_data)}")
+        
+        # Decode base64 image
+        image_bytes = base64.b64decode(image_data)
+        print(f"📊 Decoded image bytes: {len(image_bytes)}")
+        
+        image = Image.open(io.BytesIO(image_bytes))
+        print(f"📊 Image dimensions: {image.size}")
+        
+        timestamp = int(time.time() * 1000)
+        matrix_id = data.get('matrixId', 'matrix')
+        filename = f"{matrix_id}_{timestamp}.png"
+        print(f"📁 Generated filename: {filename}")
+        
+        os.makedirs(MATRIX_GRIDS_DIR, exist_ok=True)
+        print(f"📁 MATRIX_GRIDS_DIR: {MATRIX_GRIDS_DIR}")
+        print(f"📁 Directory exists: {os.path.exists(MATRIX_GRIDS_DIR)}")
+        print(f"📁 Directory is writable: {os.access(MATRIX_GRIDS_DIR, os.W_OK)}")
+        
+        filepath = os.path.join(MATRIX_GRIDS_DIR, filename)
+        print(f"📁 Full save path: {filepath}")
+        
+        image.save(filepath, format='PNG')
+        print(f"💾 Matrix grid saved to permanent storage")
+        
+        if os.path.exists(filepath):
+            file_size = os.path.getsize(filepath)
+            print(f"✅ Successfully saved Matrix grid to permanent storage: {filename}")
+            print(f"📏 File size: {file_size} bytes")
+            print(f"📁 Full path: {filepath}")
+            
+            dir_contents = os.listdir(MATRIX_GRIDS_DIR)
+            print(f"📁 Matrix grids directory contents: {dir_contents}")
+            
+            return jsonify({
+                "status": "success",
+                "filename": filename,
+                "url": f"http://localhost:5001/api/images/{filename}",
+                "filesize": file_size,
+                "storage": "permanent"
+            })
+        else:
+            print(f"❌ File was not created: {filepath}")
+            return jsonify({
+                "status": "error",
+                "message": "Failed to save Matrix grid to permanent storage"
+            }), 500
+            
+    except Exception as e:
+        print(f"❌ Error saving Matrix grid: {str(e)}")
         traceback.print_exc()
         return jsonify({
             "status": "error",
diff --git a/dream_layer_backend/txt2img_workflow.py b/dream_layer_backend/txt2img_workflow.py
index 24912b34..5365ef46 100644
--- a/dream_layer_backend/txt2img_workflow.py
+++ b/dream_layer_backend/txt2img_workflow.py
@@ -1,8 +1,11 @@
 import json
 import random
 import os
+import traceback
 import json
 from dream_layer_backend_utils.workflow_loader import load_workflow
+from dream_layer_backend_utils.api_key_injector import inject_api_keys_into_workflow
+from dream_layer_backend_utils.update_custom_workflow import override_workflow 
 from dream_layer_backend_utils.api_key_injector import inject_api_keys_into_workflow, read_api_keys_from_env
 from dream_layer_backend_utils.update_custom_workflow import override_workflow
 from dream_layer_backend_utils.update_custom_workflow import update_custom_workflow, validate_custom_workflow
@@ -16,7 +19,6 @@
 )
 from shared_utils import SAMPLER_NAME_MAP
 
-
 def transform_to_txt2img_workflow(data):
     """
     Transform frontend data to ComfyUI txt2img workflow
@@ -26,39 +28,35 @@ def transform_to_txt2img_workflow(data):
         print("\n🔄 Transforming txt2img workflow:")
         print("-" * 40)
         print(f"📊 Data keys: {list(data.keys())}")
-
-        # Extract and validate core parameters with smallFeatures improvements
+        
         prompt = data.get('prompt', '')
         negative_prompt = data.get('negative_prompt', '')
-
-        # Dimension validation
+        
         width = max(64, min(2048, int(data.get('width', 512))))
         height = max(64, min(2048, int(data.get('height', 512))))
-
-        # Batch parameters with validation (from smallFeatures)
-        # Clamp between 1 and 8
+        
         batch_size = max(1, min(8, int(data.get('batch_size', 1))))
         print(f"\nBatch size: {batch_size}")
-
-        # Sampling parameters with validation
+        
         steps = max(1, min(150, int(data.get('steps', 20))))
         cfg_scale = max(1.0, min(20.0, float(data.get('cfg_scale', 7.0))))
-
-        # Get sampler name and map it to ComfyUI format (from smallFeatures)
+        
         frontend_sampler = data.get('sampler_name', 'euler')
         sampler_name = SAMPLER_NAME_MAP.get(frontend_sampler, 'euler')
         print(f"\nMapping sampler name: {frontend_sampler} -> {sampler_name}")
-
+        
         scheduler = data.get('scheduler', 'normal')
-
-        # Handle seed - enhanced from smallFeatures for -1 values
+        
         try:
             seed = int(data.get('seed', 0))
             if seed < 0:
-                # Generate random seed between 0 and 2^32-1
                 seed = random.randint(0, 2**32 - 1)
         except (ValueError, TypeError):
             seed = random.randint(0, 2**32 - 1)
+        
+        model_name = data.get('model_name', 'juggernautXL_v8Rundiffusion.safetensors')
+        
+        closed_source_models = ['dall-e-3', 'dall-e-2', 'flux-pro', 'flux-dev', 'ideogram-v3']
 
         # Handle model name validation
         model_name = data.get('model_name', 'juggernautXL_v8Rundiffusion.safetensors')
@@ -68,9 +66,9 @@ def transform_to_txt2img_workflow(data):
         
         if model_name in closed_source_models:
             print(f"🎨 Using closed-source model: {model_name}")
-
+        
         print(f"\nUsing model: {model_name}")
-
+        
         core_generation_settings = {
             'prompt': prompt,
             'negative_prompt': negative_prompt,
@@ -86,12 +84,10 @@ def transform_to_txt2img_workflow(data):
             'denoise': 1.0
         }
         print(f"🎯 Core settings: {core_generation_settings}")
-
-        # Extract ControlNet data
+        
         controlnet_data = data.get('controlnet', {})
         print(f"🎮 ControlNet data: {controlnet_data}")
-
-        # Extract Face Restoration data
+        
         face_restoration_data = {
             'restore_faces': data.get('restore_faces', False),
             'face_restoration_model': data.get('face_restoration_model', 'codeformer'),
@@ -99,16 +95,14 @@ def transform_to_txt2img_workflow(data):
             'gfpgan_weight': data.get('gfpgan_weight', 0.5)
         }
         print(f"👤 Face Restoration data: {face_restoration_data}")
-
-        # Extract Tiling data
+        
         tiling_data = {
             'tiling': data.get('tiling', False),
             'tile_size': data.get('tile_size', 512),
             'tile_overlap': data.get('tile_overlap', 64)
         }
         print(f"🧩 Tiling data: {tiling_data}")
-
-        # Extract Hires.fix data
+        
         hires_fix_data = {
             'hires_fix': data.get('hires_fix', False),
             'hires_fix_upscale_method': data.get('hires_fix_upscale_method', 'upscale-by'),
@@ -120,34 +114,29 @@ def transform_to_txt2img_workflow(data):
             'hires_fix_upscaler': data.get('hires_fix_upscaler', '4x-ultrasharp')
         }
         print(f"🖼️ Hires.fix data: {hires_fix_data}")
-
-        # Extract Refiner data
+        
         refiner_data = {
             'refiner_enabled': data.get('refiner_enabled', False),
             'refiner_model': data.get('refiner_model', 'none'),
             'refiner_switch_at': data.get('refiner_switch_at', 0.8)
         }
         print(f"🖌️ Refiner data: {refiner_data}")
-
-        # Determine workflow template based on features
-        use_controlnet = controlnet_data.get(
-            'enabled', False) and controlnet_data.get('units')
+        
+        use_controlnet = controlnet_data.get('enabled', False) and controlnet_data.get('units')
         use_lora = data.get('lora') and data.get('lora').get('enabled', False)
-        use_face_restoration = face_restoration_data.get(
-            'restore_faces', False)
+        use_face_restoration = face_restoration_data.get('restore_faces', False)
         use_tiling = tiling_data.get('tiling', False)
-
+        
         print(f"🔧 Use ControlNet: {use_controlnet}")
         print(f"🔧 Use LoRA: {use_lora}")
         print(f"🔧 Use Face Restoration: {use_face_restoration}")
         print(f"🔧 Use Tiling: {use_tiling}")
-
-        # Create workflow request for the loader
+        
         if model_name in ['dall-e-3', 'dall-e-2']:
             workflow_model_type = 'dalle'
         elif model_name in ['flux-pro', 'flux-dev']:
             workflow_model_type = 'bfl'
-        elif 'ideogram' in model_name.lower():  # Added check for ideogram models
+        elif 'ideogram' in model_name.lower():
             workflow_model_type = 'ideogram'
         elif 'stability' in model_name.lower():  # Added check for Stability AI models
             workflow_model_type = 'stability'
@@ -155,26 +144,26 @@ def transform_to_txt2img_workflow(data):
             workflow_model_type = 'photon'
         else:
             workflow_model_type = 'local'
-
+        
         workflow_request = {
             'generation_flow': 'txt2img',
             'model_name': workflow_model_type,
             'controlnet': use_controlnet,
             'lora': use_lora
         }
-
+        
         print(f"📄 Workflow request: {workflow_request}")
-
-        # Load workflow using the workflow loader
+        
         workflow = load_workflow(workflow_request)
         print(f"✅ Workflow loaded successfully")
+        
+        workflow = inject_api_keys_into_workflow(workflow)
 
         # Inject API keys if needed (for DALL-E, FLUX, etc.)
         all_api_keys = read_api_keys_from_env()
         workflow = inject_api_keys_into_workflow(workflow, all_api_keys)
         print(f"✅ API keys injected")
-
-        # Custom workflow support from smallFeatures
+        
         custom_workflow = data.get('custom_workflow')
         if custom_workflow and validate_custom_workflow(custom_workflow):
             print("Custom workflow detected, updating with current parameters...")
@@ -184,53 +173,44 @@ def transform_to_txt2img_workflow(data):
             except Exception as e:
                 print(f"Error updating custom workflow: {str(e)}")
                 print("Falling back to default workflow override")
-                workflow = override_workflow(
-                    workflow, core_generation_settings)
+                workflow = override_workflow(workflow, core_generation_settings)
         else:
-            # Apply overrides to loaded workflow
             workflow = override_workflow(workflow, core_generation_settings)
-            print(
-                "No valid custom workflow provided, using default workflow with overrides")
-
+            print("No valid custom workflow provided, using default workflow with overrides")
+        
         print(f"✅ Core settings applied")
-
-        # Apply LoRA parameters if enabled
+        
         if use_lora:
             print(f"🎨 Applying LoRA parameters...")
             workflow = inject_lora_parameters(workflow, data.get('lora', {}))
-
-        # Apply ControlNet parameters if enabled
+        
         if use_controlnet:
             print(f"🎮 Applying ControlNet parameters...")
             workflow = inject_controlnet_parameters(workflow, controlnet_data)
-
-        # Apply Face Restoration parameters if enabled
+        
         if use_face_restoration:
             print(f"👤 Applying Face Restoration parameters...")
-            workflow = inject_face_restoration_parameters(
-                workflow, face_restoration_data)
-
-        # Apply Tiling parameters if enabled
+            workflow = inject_face_restoration_parameters(workflow, face_restoration_data)
+        
         if use_tiling:
             print(f"🧩 Applying Tiling parameters...")
             workflow = inject_tiling_parameters(workflow, tiling_data)
-
-        # Apply Hires.fix parameters if enabled
+        
         if hires_fix_data.get('hires_fix', False):
             print(f"✨ Applying Hires.fix parameters...")
             workflow = inject_hires_fix_parameters(workflow, hires_fix_data)
-
-        # Apply Refiner parameters if enabled
+        
         if refiner_data.get('refiner_enabled', False):
             print(f"✨ Applying Refiner parameters...")
             workflow = inject_refiner_parameters(workflow, refiner_data)
-
+        
         print(f"✅ Workflow transformation complete")
         print(f"📋 Generated workflow: {json.dumps(workflow, indent=2)}")
         return workflow
-
+        
     except Exception as e:
         print(f"❌ Error transforming workflow: {str(e)}")
-        import traceback
         traceback.print_exc()
         return None
+
+
diff --git a/dream_layer_backend/workflows/img2img/gemini_multimodal_workflow.json b/dream_layer_backend/workflows/img2img/gemini_multimodal_workflow.json
deleted file mode 100644
index a2d397c9..00000000
--- a/dream_layer_backend/workflows/img2img/gemini_multimodal_workflow.json
+++ /dev/null
@@ -1,119 +0,0 @@
-{
-  "prompt": {
-    "1": {
-      "class_type": "LoadImage",
-      "inputs": {
-        "image": "example_image.png"
-      }
-    },
-    "2": {
-      "class_type": "GeminiNode",
-      "inputs": {
-        "prompt": "Analyze this image in detail. Describe the composition, colors, style, and any artistic elements. Then suggest how to improve it using digital art techniques.",
-        "model": "gemini-2.5-pro-preview-05-06",
-        "images": ["1", 0],
-        "seed": 42
-      }
-    },
-    "3": {
-      "class_type": "GeminiNode", 
-      "inputs": {
-        "prompt": "Based on this image analysis, create a detailed AI art prompt. Include: style, composition, lighting, colors, and quality terms. Format: 'A [style] [subject] with [details], [lighting], [colors], masterpiece, high quality'",
-        "model": "gemini-2.5-flash-preview-04-17",
-        "seed": 43
-      }
-    },
-    "4": {
-      "class_type": "CLIPTextEncode", 
-      "inputs": {
-        "clip": ["5", 1],
-        "text": ["3", 0]
-      }
-    },
-    "5": {
-      "class_type": "CheckpointLoaderSimple",
-      "inputs": {
-        "ckpt_name": "juggernautXL_v8Rundiffusion.safetensors"
-      }
-    },
-    "6": {
-      "class_type": "EmptyLatentImage",
-      "inputs": {
-        "width": 1024,
-        "height": 1024,
-        "batch_size": 1
-      }
-    },
-    "7": {
-      "class_type": "KSampler",
-      "inputs": {
-        "model": ["5", 0],
-        "positive": ["4", 0],
-        "negative": ["8", 0],
-        "latent_image": ["6", 0],
-        "seed": 0,
-        "steps": 25,
-        "cfg": 7.5,
-        "sampler_name": "euler",
-        "scheduler": "normal",
-        "denoise": 1.0
-      }
-    },
-    "8": {
-      "class_type": "CLIPTextEncode",
-      "inputs": {
-        "clip": ["5", 1],
-        "text": "blurry, low quality, distorted, ugly, bad anatomy"
-      }
-    },
-    "9": {
-      "class_type": "VAEDecode",
-      "inputs": {
-        "samples": ["7", 0],
-        "vae": ["5", 2]
-      }
-    },
-    "10": {
-      "class_type": "SaveImage",
-      "inputs": {
-        "images": ["9", 0],
-        "filename_prefix": "DreamLayer_Gemini_Enhanced"
-      }
-    }
-  },
-  "meta": {
-    "description": "Gemini Multimodal Analysis → Enhanced Image Generation Workflow",
-    "workflow_type": "advanced_multimodal_chain",
-    "demonstrates": [
-      "Image loading and analysis",
-      "Gemini multimodal understanding",
-      "Text-to-text refinement chaining", 
-      "AI-generated prompt optimization",
-      "Integration with local Stable Diffusion",
-      "Full end-to-end creative workflow"
-    ],
-    "node_chain": "LoadImage → GeminiNode(analysis) → GeminiNode(prompt_generation) → CLIPTextEncode → KSampler → VAEDecode → SaveImage",
-    "core_settings": {
-      "input_image": "Source image for Gemini to analyze",
-      "analysis_prompt": "Instructions for Gemini to analyze the image",
-      "prompt_generation": "Instructions for Gemini to create enhanced prompts",
-      "model_1": "Primary Gemini model for detailed analysis",
-      "model_2": "Secondary Gemini model for prompt optimization",
-      "seed": "Random seed for deterministic output"
-    },
-    "gemini_capabilities_shown": [
-      "Visual understanding and analysis",
-      "Artistic critique and improvement suggestions", 
-      "Creative prompt generation",
-      "Multi-step reasoning",
-      "Integration with image generation pipeline"
-    ],
-    "technical_features": [
-      "Two-stage Gemini processing",
-      "Dynamic prompt generation from image analysis",
-      "Seamless integration with ComfyUI workflow",
-      "Multimodal AI → traditional AI pipeline",
-      "Professional creative workflow automation"
-    ]
-  }
-} 
\ No newline at end of file
diff --git a/dream_layer_backend/workflows/img2img/stability_core_generation_workflow.json b/dream_layer_backend/workflows/img2img/stability_core_generation_workflow.json
deleted file mode 100644
index 668f6209..00000000
--- a/dream_layer_backend/workflows/img2img/stability_core_generation_workflow.json
+++ /dev/null
@@ -1,57 +0,0 @@
-{
-  "prompt": {
-    "1": {
-      "class_type": "LoadImage",
-      "inputs": {
-        "image": "input_image.png",
-        "batch_size": 1
-      }
-    },
-    "2": {
-      "class_type": "StabilityStableImageUltraNode",
-      "inputs": {
-        "prompt": "beautiful",
-        "aspect_ratio": "1:1",
-        "style_preset": "cinematic",
-        "seed": 0,
-        "negative_prompt": "ugly",
-        "batch_size": 1,
-        "image": ["1", 0],
-        "image_denoise": 0.75
-      }
-    },
-    "3": {
-      "class_type": "SaveImage",
-      "inputs": {
-        "images": ["2", 0],
-        "filename_prefix": "DreamLayer_StabilityAI_img2img"
-      }
-    }
-  },
-  "meta": {
-    "description": "Stability AI Image-to-Image Generation Workflow",
-    "model_options": {
-      "stability_sdxl": "StabilityStableImageUltraNode",
-      "stability_sd_turbo": "StabilityStableImageUltraNode"
-    },
-    "core_settings": {
-      "prompt": "Main generation prompt",
-      "aspect_ratio": "Image aspect ratio",
-      "style_preset": "Style preset",
-      "seed": "Random seed (0 for random)",
-      "batch_size": "Number of images to generate (1-10)",
-      "image_denoise": "Denoise strength (0.0-1.0)"
-    },
-    "aspect_ratios": [
-      "1:1",
-      "16:9",
-      "9:16",
-      "3:2",
-      "2:3",
-      "5:4",
-      "4:5",
-      "21:9",
-      "9:21"
-    ]
-  }
-}
diff --git a/dream_layer_backend/workflows/txt2img/gemini_core_generation_workflow.json b/dream_layer_backend/workflows/txt2img/gemini_core_generation_workflow.json
deleted file mode 100644
index 6a2c9319..00000000
--- a/dream_layer_backend/workflows/txt2img/gemini_core_generation_workflow.json
+++ /dev/null
@@ -1,40 +0,0 @@
-{
-  "prompt": {
-    "1": {
-      "class_type": "GeminiNode",
-      "inputs": {
-        "prompt": "Generate a creative story about a magical forest",
-        "model": "gemini-2.5-pro-preview-05-06",
-        "seed": 42
-      }
-    }
-  },
-  "meta": {
-    "description": "Gemini Text Generation Workflow",
-    "model_options": {
-      "gemini-pro-vision": "GeminiNode",
-      "gemini-pro": "GeminiNode"
-    },
-    "core_settings": {
-      "prompt": "Text prompt for Gemini analysis or generation",
-      "model": "Gemini model to use (gemini-2.5-pro-preview-05-06, gemini-2.5-flash-preview-04-17)",
-      "seed": "Random seed for deterministic output (0 for random)",
-      "images": "Optional images for multimodal analysis",
-      "audio": "Optional audio input for analysis",
-      "video": "Optional video input for analysis",
-      "files": "Optional files for context"
-    },
-    "model_options_detailed": [
-      "gemini-2.5-pro-preview-05-06",
-      "gemini-2.5-flash-preview-04-17"
-    ],
-    "capabilities": [
-      "Text generation",
-      "Image analysis", 
-      "Multimodal understanding",
-      "Document analysis",
-      "Code generation",
-      "Creative writing"
-    ]
-  }
-} 
\ No newline at end of file
diff --git a/dream_layer_backend/workflows/txt2img/stability_core_generation_workflow.json b/dream_layer_backend/workflows/txt2img/stability_core_generation_workflow.json
deleted file mode 100644
index f16b5fc7..00000000
--- a/dream_layer_backend/workflows/txt2img/stability_core_generation_workflow.json
+++ /dev/null
@@ -1,47 +0,0 @@
-{
-  "prompt": {
-    "1": {
-      "class_type": "StabilityStableImageUltraNode",
-      "inputs": {
-        "prompt": "beautiful",
-        "aspect_ratio": "1:1",
-        "style_preset": "cinematic",
-        "seed": 0,
-        "negative_prompt": "ugly",
-        "batch_size": 1
-      }
-    },
-    "2": {
-      "class_type": "SaveImage",
-      "inputs": {
-        "images": ["1", 0],
-        "filename_prefix": "DreamLayer_StabilityAI"
-      }
-    }
-  },
-  "meta": {
-    "description": "Stability AI Core Generation Workflow",
-    "model_options": {
-      "stability_sdxl": "StabilityStableImageUltraNode",
-      "stability_sd_turbo": "StabilityStableImageUltraNode"
-    },
-    "core_settings": {
-      "prompt": "Main generation prompt",
-      "aspect_ratio": "Image aspect ratio",
-      "style_preset": "Style preset",
-      "seed": "Random seed (0 for random)",
-      "batch_size": "Number of images to generate (1-10)"
-    },
-    "aspect_ratios": [
-      "1:1",
-      "16:9",
-      "9:16",
-      "3:2",
-      "2:3",
-      "5:4",
-      "4:5",
-      "21:9",
-      "9:21"
-    ]
-  }
-}
diff --git a/dream_layer_frontend/src/components/AliasKeyInputs.tsx b/dream_layer_frontend/src/components/AliasKeyInputs.tsx
index c0af222e..e26b1527 100644
--- a/dream_layer_frontend/src/components/AliasKeyInputs.tsx
+++ b/dream_layer_frontend/src/components/AliasKeyInputs.tsx
@@ -42,16 +42,10 @@ const fields = [
 ];
 
 const ApiKeysForm: React.FC = () => {
-  const [keys, setKeys] = useState<string[]>(Array(fields.length).fill(""));
-  const [submitted, setSubmitted] = useState<boolean[]>(
-    Array(fields.length).fill(false)
-  );
-  const [loading, setLoading] = useState<boolean[]>(
-    Array(fields.length).fill(false)
-  );
-  const [showText, setShowText] = useState<boolean[]>(
-    Array(fields.length).fill(false)
-  );
+  const [keys, setKeys] = useState<string[]>(["", "", ""]);
+  const [submitted, setSubmitted] = useState<boolean[]>([false, false, false]);
+  const [loading, setLoading] = useState<boolean[]>([false, false, false]);
+  const [showText, setShowText] = useState<boolean[]>([false, false, false]);
 
   const handleChange = (index: number, value: string) => {
     setKeys((prev) => {
@@ -160,10 +154,7 @@ const ApiKeysForm: React.FC = () => {
           )}
         </div>
       ))}
-      <div className="space-y-6">
-        * Please Click of Refresh Models After Adding the Keys to View the
-        Models
-      </div>
+      <div className="space-y-6">* Please Click of Refresh Models After Adding the Keys to View the Models</div>
     </div>
   );
 };
diff --git a/dream_layer_frontend/src/components/MatrixSettings.tsx b/dream_layer_frontend/src/components/MatrixSettings.tsx
new file mode 100644
index 00000000..d008ab13
--- /dev/null
+++ b/dream_layer_frontend/src/components/MatrixSettings.tsx
@@ -0,0 +1,231 @@
+import React, { useState, useEffect, useCallback, memo } from 'react';
+import {
+  Select,
+  SelectContent,
+  SelectItem,
+  SelectTrigger,
+  SelectValue,
+} from "@/components/ui/select";
+import { Input } from "@/components/ui/input";
+import { Checkbox } from "@/components/ui/checkbox";
+import { Card, CardContent } from "@/components/ui/card";
+import { Separator } from "@/components/ui/separator";
+import { 
+    MatrixSettings as MatrixSettingsType, 
+    MatrixParameter, 
+    MATRIX_PARAMETERS, 
+    defaultMatrixSettings, 
+    CoreGenerationSettings,
+    MatrixParameterName
+} from '@/types/generationSettings';
+
+interface MatrixSettingsProps {
+  onSettingsChange: (settings: MatrixSettingsType) => void;
+}
+
+interface ParameterRowProps {
+  label: string;
+  axis: 'xAxis' | 'yAxis' | 'zAxis';
+  parameter: MatrixParameter;
+  onParameterUpdate: (axis: 'xAxis' | 'yAxis' | 'zAxis', updates: Partial<MatrixParameter>) => void;
+  usedParameters: string[];
+}
+
+const ParameterRow = memo<ParameterRowProps>(({ 
+  label, 
+  axis, 
+  parameter,
+  onParameterUpdate,
+  usedParameters
+}) => {
+  const [localValue, setLocalValue] = useState(parameter.values);
+
+  useEffect(() => {
+    setLocalValue(parameter.values);
+  }, [parameter.values]);
+
+  const handleInputChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    const newValue = e.target.value;
+    setLocalValue(newValue);
+    onParameterUpdate(axis, { values: newValue });
+  };
+
+  const handleParameterChange = (value: MatrixParameterName) => {
+    onParameterUpdate(axis, { 
+      name: value, 
+      enabled: value !== 'Nothing',
+      values: value !== 'Nothing' ? parameter.values : ''
+    });
+  };
+
+  const handleTypeChange = (value: 'range' | 'list') => {
+    onParameterUpdate(axis, { type: value });
+  };
+
+  return (
+    <div className="grid grid-cols-12 gap-3 items-center mb-3">
+      <div className="col-span-2 text-sm font-medium text-muted-foreground">{label}</div>
+      <div className="col-span-3">
+        <Select 
+          value={parameter.name} 
+          onValueChange={handleParameterChange}
+        >
+          <SelectTrigger className="w-full">
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent>
+            {MATRIX_PARAMETERS.map((param) => {
+              const isCurrentlySelected = param === parameter.name;
+              const isUsedElsewhere = usedParameters.includes(param);
+              
+              if (isCurrentlySelected || !isUsedElsewhere) {
+                return (
+                  <SelectItem key={param} value={param}>
+                    {param}
+                  </SelectItem>
+                );
+              }
+              return null;
+            })}
+          </SelectContent>
+        </Select>
+      </div>
+      <div className="col-span-2">
+        <Select
+          value={parameter.type}
+          onValueChange={handleTypeChange}
+          disabled={parameter.name === 'Nothing'}
+        >
+          <SelectTrigger>
+            <SelectValue />
+          </SelectTrigger>
+          <SelectContent>
+            <SelectItem value="list">List</SelectItem>
+            <SelectItem value="range">Range</SelectItem>
+          </SelectContent>
+        </Select>
+      </div>
+      <div className="col-span-5">
+        <Input
+          placeholder={
+            parameter.type === 'range' 
+              ? "e.g., 1-8" 
+              : "e.g., 1, 2, 4, 8"
+          }
+          value={localValue}
+          onChange={handleInputChange}
+          disabled={parameter.name === 'Nothing'}
+          className="text-sm"
+        />
+      </div>
+    </div>
+  );
+});
+
+ParameterRow.displayName = 'ParameterRow';
+
+const MatrixSettings: React.FC<MatrixSettingsProps> = ({
+  onSettingsChange
+}) => {
+  const [matrixSettings, setMatrixSettings] = useState<MatrixSettingsType>(defaultMatrixSettings);
+
+  const updateMatrixSettings = useCallback((updates: Partial<MatrixSettingsType>) => {
+    const newSettings = { ...matrixSettings, ...updates };
+    setMatrixSettings(newSettings);
+    onSettingsChange(newSettings);
+  }, [matrixSettings, onSettingsChange]);
+
+  const updateParameter = useCallback((axis: 'xAxis' | 'yAxis' | 'zAxis', updates: Partial<MatrixParameter>) => {
+    const newParameter = { ...matrixSettings[axis], ...updates };
+    updateMatrixSettings({ [axis]: newParameter });
+  }, [matrixSettings, updateMatrixSettings]);
+
+  const getUsedParameters = (currentAxis: 'xAxis' | 'yAxis' | 'zAxis'): string[] => {
+    const used: string[] = [];
+    if (currentAxis !== 'xAxis' && matrixSettings.xAxis.name !== 'Nothing') {
+      used.push(matrixSettings.xAxis.name);
+    }
+    if (currentAxis !== 'yAxis' && matrixSettings.yAxis.name !== 'Nothing') {
+      used.push(matrixSettings.yAxis.name);
+    }
+    if (currentAxis !== 'zAxis' && matrixSettings.zAxis?.name !== 'Nothing') {
+      used.push(matrixSettings.zAxis.name);
+    }
+    return used;
+  };
+
+  return (
+    <Card className="bg-transparent border-none shadow-none">
+      <CardContent className="p-0">
+        <ParameterRow
+          label="X type"
+          axis="xAxis"
+          parameter={matrixSettings.xAxis}
+          onParameterUpdate={updateParameter}
+          usedParameters={getUsedParameters('xAxis')}
+        />
+        <ParameterRow
+          label="Y type"
+          axis="yAxis"
+          parameter={matrixSettings.yAxis}
+          onParameterUpdate={updateParameter}
+          usedParameters={getUsedParameters('yAxis')}
+        />
+        <ParameterRow
+          label="Z type"
+          axis="zAxis"
+          parameter={matrixSettings.zAxis}
+          onParameterUpdate={updateParameter}
+          usedParameters={getUsedParameters('zAxis')}
+        />
+
+        <Separator className="my-4" />
+
+        <div className="grid grid-cols-2 gap-x-6 gap-y-4">
+          <div className="flex items-center space-x-2">
+            <Checkbox
+              id="draw-legend"
+              checked={matrixSettings.drawLegend}
+              onCheckedChange={(checked) => updateMatrixSettings({ drawLegend: !!checked })}
+            />
+            <label htmlFor="draw-legend" className="text-sm">
+              Draw legend
+            </label>
+          </div>
+          <div className="flex items-center space-x-2">
+            <Checkbox
+              id="include-sub-images"
+              checked={matrixSettings.includeSubImages}
+              onCheckedChange={(checked) => updateMatrixSettings({ includeSubImages: !!checked })}
+            />
+            <label htmlFor="include-sub-images" className="text-sm">
+              Include Sub Images
+            </label>
+          </div>
+          <div className="flex items-center space-x-2">
+            <Checkbox
+              id="include-sub-grids"
+              checked={matrixSettings.includeSubgrids}
+              onCheckedChange={(checked) => updateMatrixSettings({ includeSubgrids: !!checked })}
+            />
+            <label htmlFor="include-sub-grids" className="text-sm">
+              Include Sub Grids
+            </label>
+          </div>
+          <div className="flex items-center space-x-2">
+            <Checkbox
+              id="keep-seeds"
+              checked={matrixSettings.keepSeedsForRows}
+              onCheckedChange={(checked) => updateMatrixSettings({ keepSeedsForRows: !!checked })}
+            />
+            <label htmlFor="keep-seeds" className="text-sm">
+              Keep -1 for seeds
+            </label>
+          </div>
+        </div>
+      </CardContent>
+    </Card>
+  );
+};
+
+export default MatrixSettings; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/components/Navigation/TabsNav.tsx b/dream_layer_frontend/src/components/Navigation/TabsNav.tsx
index 0dd92f2e..9a9d5c8a 100644
--- a/dream_layer_frontend/src/components/Navigation/TabsNav.tsx
+++ b/dream_layer_frontend/src/components/Navigation/TabsNav.tsx
@@ -7,19 +7,16 @@ import {
   HardDrive,
   History,
   Download,
-  MessageSquare
-} from "lucide-react";
+  MessageSquare,
+} from 'lucide-react';
 
 const tabs = [
   { id: "txt2img", label: "Txt2Img", icon: FileText },
   { id: "img2img", label: "Img2Img", icon: ImageIcon },
-  { id: "img2txt", label: "Img2Txt", icon: MessageSquare },
   { id: "extras", label: "Extras", icon: GalleryHorizontal },
   { id: "models", label: "Models", icon: HardDrive },
   { id: "pnginfo", label: "PNG Info", icon: FileText },
-  { id: "configurations", label: "Configurations", icon: Settings },
-  { id: "runregistry", label: "Run Registry", icon: History },
-  { id: "reportbundle", label: "Report Bundle", icon: Download }
+  { id: "configurations", label: "Configurations", icon: Settings }
 ];
 
 interface TabsNavProps {
diff --git a/dream_layer_frontend/src/components/tabs/txt2img/ImagePreview.tsx b/dream_layer_frontend/src/components/tabs/txt2img/ImagePreview.tsx
index 6f9c8f26..324884a1 100644
--- a/dream_layer_frontend/src/components/tabs/txt2img/ImagePreview.tsx
+++ b/dream_layer_frontend/src/components/tabs/txt2img/ImagePreview.tsx
@@ -24,31 +24,65 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
   const [selectedImageIndex, setSelectedImageIndex] = useState(0);
   const [outputSettingsExpanded, setOutputSettingsExpanded] = useState(true);
   const [thumbnailStartIndex, setThumbnailStartIndex] = useState(0);
+  const [imageError, setImageError] = useState<string | null>(null);
 
   const currentImage = images[selectedImageIndex] || images[0];
   const maxThumbnails = 5;
   const totalPages = Math.ceil(images.length / maxThumbnails);
   const currentPage = Math.floor(thumbnailStartIndex / maxThumbnails) + 1;
 
+  const isMatrixGrid = (image: any) => {
+    return image?.id?.startsWith('matrix-grid') || 
+           image?.id?.startsWith('matrix-subgrid');
+  };
+
+  const handleImageError = (error: React.SyntheticEvent<HTMLImageElement, Event>) => {
+    console.error('Error loading image:', error);
+    const img = error.target as HTMLImageElement;
+    console.log('Failed image URL:', img.src);
+    setImageError(`Failed to load image`);
+  };
+
+  const handleImageLoad = () => {
+    setImageError(null);
+  };
+
   const handleDownload = async (format: 'png' | 'zip') => {
     if (!currentImage) return;
     
     if (format === 'png') {
-      // Download single PNG
-      const link = document.createElement('a');
-      link.href = currentImage.url;
-      link.target = '_blank';
-      link.download = `generated-image-${currentImage.id}.png`;
-      document.body.appendChild(link);
-      link.click();
-      document.body.removeChild(link);
+      try {
+        const response = await fetch(currentImage.url);
+        const blob = await response.blob();
+        
+        const link = document.createElement('a');
+        link.href = URL.createObjectURL(blob);
+        link.download = `generated-image-${currentImage.id}.png`;
+        document.body.appendChild(link);
+        link.click();
+        document.body.removeChild(link);
+        
+        URL.revokeObjectURL(link.href);
+      } catch (error) {
+        console.error('Download failed:', error);
+        const link = document.createElement('a');
+        link.href = currentImage.url;
+        link.target = '_blank';
+        link.download = `generated-image-${currentImage.id}.png`;
+        document.body.appendChild(link);
+        link.click();
+        document.body.removeChild(link);
+      }
     } else if (format === 'zip') {
-      // Download all images as ZIP
       const zip = new JSZip();
       const promises = images.map(async (image, index) => {
-        const response = await fetch(image.url);
-        const blob = await response.blob();
-        zip.file(`generated-image-${index + 1}.png`, blob);
+        try {
+          const response = await fetch(image.url);
+          const blob = await response.blob();
+          zip.file(`generated-image-${index + 1}.png`, blob);
+        } catch (error) {
+          console.error(`Failed to fetch image ${index + 1}:`, error);
+        }
       });
       
       await Promise.all(promises);
@@ -61,6 +95,8 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
       document.body.appendChild(link);
       link.click();
       document.body.removeChild(link);
+      
+      URL.revokeObjectURL(link.href);
     }
   };
 
@@ -68,23 +104,26 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
     if (!currentImage) return;
     
     try {
-      // Extract filename from URL (supports both old and new formats)
-      const url = new URL(currentImage.url);
-      let filename = url.searchParams.get('filename'); // Old ComfyUI format
-      if (!filename) {
-        // New format - extract from path
-        filename = url.pathname.split('/').pop(); // Gets "image123.png"
+      let filename: string | null = null;
+      
+      if (isMatrixGrid(currentImage)) {
+        const url = new URL(currentImage.url);
+        filename = url.pathname.split('/').pop();
+      } else {
+        const url = new URL(currentImage.url);
+        filename = url.searchParams.get('filename') || url.pathname.split('/').pop();
       }
       
       if (!filename) {
         console.error('No filename found in URL:', currentImage.url);
         return;
       }
+      
       console.log('=== Show in Folder Debug ===');
       console.log('Full URL:', currentImage.url);
       console.log('Extracted filename:', filename);
       console.log('Request body:', JSON.stringify({ filename }));
-      console.log('Current Image:', currentImage);
+      
       const response = await fetch('http://localhost:5002/api/show-in-folder', {
         method: 'POST',
         headers: { 'Content-Type': 'application/json' },
@@ -103,12 +142,14 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
     
     if (destination === 'img2img') {
       try {
-        // Extract filename from URL (supports both old and new formats)
-        const url = new URL(currentImage.url);
-        let filename = url.searchParams.get('filename'); // Old ComfyUI format
-        if (!filename) {
-          // New format - extract from path
-          filename = url.pathname.split('/').pop(); // Gets "image123.png"
+        let filename: string | null = null;
+        
+        if (isMatrixGrid(currentImage)) {
+          const url = new URL(currentImage.url);
+          filename = url.pathname.split('/').pop();
+        } else {
+          const url = new URL(currentImage.url);
+          filename = url.searchParams.get('filename') || url.pathname.split('/').pop();
         }
         
         if (!filename) {
@@ -116,7 +157,6 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
           return;
         }
 
-        // Call our API endpoint
         const response = await fetch('http://localhost:5002/api/send-to-img2img', {
           method: 'POST',
           headers: { 'Content-Type': 'application/json' },
@@ -125,7 +165,6 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
         
         const result = await response.json();
         if (result.status === 'success') {
-          // Use our server's images endpoint
           const imageUrl = `http://localhost:5001/api/images/${filename}`;
           const imageBlob = await fetch(imageUrl).then(r => r.blob());
           setInputImage({
@@ -133,7 +172,6 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
             file: new File([imageBlob], filename)
           });
           
-          // Switch to img2img tab
           onTabChange('img2img');
         }
       } catch (error) {
@@ -141,12 +179,14 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
       }
     } else if (destination === 'extras') {
       try {
-        // Extract filename from URL (supports both old and new formats)
-        const url = new URL(currentImage.url);
-        let filename = url.searchParams.get('filename'); // Old ComfyUI format
-        if (!filename) {
-          // New format - extract from path
-          filename = url.pathname.split('/').pop(); // Gets "image123.png"
+        let filename: string | null = null;
+        
+        if (isMatrixGrid(currentImage)) {
+          const url = new URL(currentImage.url);
+          filename = url.pathname.split('/').pop();
+        } else {
+          const url = new URL(currentImage.url);
+          filename = url.searchParams.get('filename') || url.pathname.split('/').pop();
         }
         
         if (!filename) {
@@ -154,7 +194,6 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
           return;
         }
 
-        // Call our API endpoint
         const response = await fetch('http://localhost:5002/api/send-to-extras', {
           method: 'POST',
           headers: { 'Content-Type': 'application/json' },
@@ -163,12 +202,10 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
         
         const result = await response.json();
         if (result.status === 'success') {
-          // Create a File object from the image URL
           const imageUrl = `http://localhost:5001/api/images/${filename}`;
           const imageBlob = await fetch(imageUrl).then(r => r.blob());
           const file = new File([imageBlob], filename);
           
-          // Set the image in Extras component's state
           window.sessionStorage.setItem('extrasImage', JSON.stringify({
             file: {
               name: filename,
@@ -178,7 +215,6 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
             preview: imageUrl
           }));
           
-          // Switch to extras tab
           onTabChange('extras');
         }
       } catch (error) {
@@ -211,14 +247,63 @@ const ImagePreview: React.FC<ImagePreviewProps> = ({ onTabChange }) => {
   const handleThumbnailClick = (index: number) => {
     const actualIndex = thumbnailStartIndex + index;
     setSelectedImageIndex(actualIndex);
+    setImageError(null);
   };
 
   const formatSettingsDisplay = () => {
     if (!currentImage?.settings) return 'No settings available';
     
     const settings = currentImage.settings;
-    const settingsAny = settings as any; // Type assertion for additional properties
-    return `Prompt: ${currentImage.prompt || 'N/A'}
+    const settingsAny = settings as any;
+    
+    const isMatrix = isMatrixGrid(currentImage);
+    
+    if (isMatrix && settingsAny.isMatrixGrid) {
+      let matrixInfo = `Matrix Grid Generation
+
+Prompt: ${currentImage.prompt || 'N/A'}
+
+Negative prompt: ${currentImage.negativePrompt || 'N/A'}
+
+Base Settings:
+Steps: ${settings.steps || 'N/A'}
+Sampler: ${settings.sampler_name || 'N/A'}
+CFG scale: ${settings.cfg_scale || 'N/A'}
+Size: ${settings.width || 'N/A'}x${settings.height || 'N/A'}
+Model: ${settings.model_name || 'N/A'}
+`;
+
+      if (settingsAny.matrixAxes) {
+        matrixInfo += '\nMatrix Configuration:\n';
+        
+        if (settingsAny.matrixAxes.xAxis) {
+          matrixInfo += `X-Axis (${settingsAny.matrixAxes.xAxis.name}): ${settingsAny.matrixAxes.xAxis.values.join(', ')}\n`;
+        }
+        
+        if (settingsAny.matrixAxes.yAxis) {
+          matrixInfo += `Y-Axis (${settingsAny.matrixAxes.yAxis.name}): ${settingsAny.matrixAxes.yAxis.values.join(', ')}\n`;
+        }
+        
+        if (settingsAny.matrixAxes.zAxis) {
+          matrixInfo += `Z-Axis (${settingsAny.matrixAxes.zAxis.name}): ${settingsAny.matrixAxes.zAxis.values.join(', ')}\n`;
+        }
+      }
+      
+      if (settingsAny.totalJobs) {
+        matrixInfo += `\nTotal Jobs: ${settingsAny.totalJobs}`;
+      }
+      
+      if (settingsAny.matrixSettings) {
+        matrixInfo += `\nMatrix Options:
+Draw Legend: ${settingsAny.matrixSettings.drawLegend ? 'Yes' : 'No'}
+Keep Seeds Consistent: ${settingsAny.matrixSettings.keepSeedsConsistent ? 'Yes' : 'No'}
+Include Sub Images: ${settingsAny.matrixSettings.includeSubImages ? 'Yes' : 'No'}
+Include Sub Grids: ${settingsAny.matrixSettings.includeSubgrids ? 'Yes' : 'No'}`;
+      }
+      
+      return matrixInfo;
+    } else {
+      return `Prompt: ${currentImage.prompt || 'N/A'}
 
 Negative prompt: ${currentImage.negativePrompt || 'N/A'}
 
@@ -233,49 +318,103 @@ Denoising strength: ${settings.denoising_strength || 'N/A'}
 Version: v1.6.0
 Networks not found: add-detail-xl, Double_Exposure
 Time taken: 31.1 sec.`;
+    }
   };
 
-  return (
-    <div className="space-y-4">
-      {/* Main Image Display */}
-      <AspectRatio ratio={1} className="w-full">
-        <div className="flex h-full w-full flex-col items-center justify-center rounded-md border border-border bg-card p-4">
-          {isLoading ? (
-            <LoadingAnimation />
-          ) : images.length > 0 && currentImage ? (
-            <div className="w-full h-full">
+  const renderImageContainer = () => {
+    if (!currentImage) return null;
+
+    const isMatrix = isMatrixGrid(currentImage);
+    
+    if (isMatrix) {
+      return (
+        <div className="relative w-full">
+          <div 
+            className="w-full overflow-x-auto overflow-y-hidden bg-card border border-border rounded-md"
+            style={{ 
+              height: '300px',
+            }}
+          >
+            <div className="flex items-center justify-center h-full p-2">
               <img 
                 src={currentImage.url} 
-                alt="Generated image" 
-                className="w-full h-full object-cover rounded-md"
+                alt="Matrix Grid" 
+                className="max-w-none h-auto object-contain"
+                style={{ 
+                  height: '280px',
+                }}
+                onError={handleImageError}
+                onLoad={handleImageLoad}
               />
             </div>
-          ) : (
-            <>
-              <div className="mb-4 flex h-14 w-14 items-center justify-center rounded-md bg-secondary">
-                <svg
-                  viewBox="0 0 24 24"
-                  className="h-6 w-6 text-muted-foreground"
-                  fill="none"
-                  stroke="currentColor"
-                  xmlns="http://www.w3.org/2000/svg"
-                >
-                  <rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
-                  <circle cx="8.5" cy="8.5" r="1.5" />
-                  <path d="m21 15-5-5L5 21" />
-                </svg>
-              </div>
-              <p className="text-sm text-muted-foreground">Generated Images Will Display Here</p>
-            </>
+          </div>
+          
+          {imageError && (
+            <div className="absolute bottom-0 left-0 right-0 bg-red-500/80 text-white p-2 text-sm text-center rounded-b-md">
+              {imageError}
+            </div>
           )}
+          
         </div>
-      </AspectRatio>
+      );
+    } else {
+      return (
+        <AspectRatio ratio={1} className="w-full">
+          <div className="flex h-full w-full flex-col items-center justify-center rounded-md border border-border bg-card p-4">
+            <div className="w-full h-full relative">
+              <img 
+                src={currentImage.url} 
+                alt="Generated image" 
+                className="w-full h-full object-cover rounded-md"
+                onError={handleImageError}
+                onLoad={handleImageLoad}
+              />
+              {imageError && (
+                <div className="absolute bottom-0 left-0 right-0 bg-red-500/80 text-white p-2 text-sm text-center rounded-b-md">
+                  {imageError}
+                </div>
+              )}
+            </div>
+          </div>
+        </AspectRatio>
+      );
+    }
+  };
+
+  return (
+    <div className="space-y-4">
+      {isLoading ? (
+        <AspectRatio ratio={1} className="w-full">
+          <div className="flex h-full w-full flex-col items-center justify-center rounded-md border border-border bg-card p-4">
+            <LoadingAnimation />
+          </div>
+        </AspectRatio>
+      ) : images.length > 0 && currentImage ? (
+        renderImageContainer()
+      ) : (
+        <AspectRatio ratio={1} className="w-full">
+          <div className="flex h-full w-full flex-col items-center justify-center rounded-md border border-border bg-card p-4">
+            <div className="mb-4 flex h-14 w-14 items-center justify-center rounded-md bg-secondary">
+              <svg
+                viewBox="0 0 24 24"
+                className="h-6 w-6 text-muted-foreground"
+                fill="none"
+                stroke="currentColor"
+                xmlns="http://www.w3.org/2000/svg"
+              >
+                <rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
+                <circle cx="8.5" cy="8.5" r="1.5" />
+                <path d="m21 15-5-5L5 21" />
+              </svg>
+            </div>
+            <p className="text-sm text-muted-foreground">Generated Images Will Display Here</p>
+          </div>
+        </AspectRatio>
+      )}
 
-      {/* Thumbnail Navigation */}
       {images.length > 0 && (
         <div className="space-y-2">
           <div className="flex items-center justify-center gap-2 px-4">
-            {/* Left Arrow */}
             {images.length > maxThumbnails && (
               <Button
                 variant="ghost"
@@ -288,15 +427,16 @@ Time taken: 31.1 sec.`;
               </Button>
             )}
 
-            {/* Thumbnails */}
             <div className="flex gap-2">
               {images.slice(thumbnailStartIndex, thumbnailStartIndex + maxThumbnails).map((image, index) => {
                 const actualIndex = thumbnailStartIndex + index;
+                const isMatrix = isMatrixGrid(image);
+                
                 return (
                   <button
                     key={image.id}
                     onClick={() => handleThumbnailClick(index)}
-                    className={`w-16 h-16 rounded border-2 transition-colors overflow-hidden ${
+                    className={`relative w-16 h-16 rounded border-2 transition-colors overflow-hidden ${
                       actualIndex === selectedImageIndex 
                         ? 'border-primary' 
                         : 'border-border hover:border-primary/50'
@@ -305,13 +445,16 @@ Time taken: 31.1 sec.`;
                     <img 
                       src={image.url} 
                       alt={`Generated image ${actualIndex + 1}`}
-                      className="w-full h-full object-cover"
+                      className={`w-full h-full ${isMatrix ? 'object-contain bg-muted' : 'object-cover'}`}
+                      onError={(e) => {
+                        const img = e.target as HTMLImageElement;
+                        img.style.display = 'none';
+                      }}
                     />
                   </button>
                 );
               })}
               
-              {/* Show empty squares if less than maxThumbnails images in current page */}
               {images.slice(thumbnailStartIndex, thumbnailStartIndex + maxThumbnails).length < maxThumbnails && 
                thumbnailStartIndex + maxThumbnails >= images.length &&
                Array.from({ 
@@ -319,13 +462,11 @@ Time taken: 31.1 sec.`;
                }).map((_, index) => (
                 <div 
                   key={`empty-${index}`}
-                  className="w-16 h-16 rounded"
-                  style={{ backgroundColor: '#f1f1f1' }}
+                  className="w-16 h-16 rounded bg-muted/50"
                 />
               ))}
             </div>
 
-            {/* Right Arrow */}
             {images.length > maxThumbnails && (
               <Button
                 variant="ghost"
@@ -339,7 +480,6 @@ Time taken: 31.1 sec.`;
             )}
           </div>
 
-          {/* Pagination Indicator */}
           {images.length > maxThumbnails && (
             <div className="flex justify-center">
               <div className="text-xs text-muted-foreground bg-muted px-2 py-1 rounded">
@@ -350,10 +490,8 @@ Time taken: 31.1 sec.`;
         </div>
       )}
 
-      {/* Action Sections */}
-      {images.length > 0 && currentImage && (
+      {images.length > 0 && currentImage && !imageError && (
         <div className="space-y-4 px-4">
-          {/* Download Section */}
           <div>
             <div className="flex items-center flex-wrap gap-2">
               <span className="text-sm font-medium">Download:</span>
@@ -387,7 +525,6 @@ Time taken: 31.1 sec.`;
             </div>
           </div>
 
-          {/* Send To Section */}
           <div>
             <div className="flex items-center flex-wrap gap-2">
               <span className="text-sm font-medium">Send To:</span>
@@ -421,7 +558,6 @@ Time taken: 31.1 sec.`;
           {/* Divider */}
           <div className="border-t border-border"></div>
 
-          {/* Output Settings Section */}
           <div>
             <div className="flex items-center justify-between mb-3">
               <span className="text-sm font-medium">Output Settings</span>
@@ -448,29 +584,106 @@ Time taken: 31.1 sec.`;
             
             {outputSettingsExpanded && (
               <div className="bg-muted p-3 rounded-md text-xs leading-relaxed">
-                <div className="space-y-3">
-                  <div>
-                    <div className="font-semibold mb-1">Prompt:</div>
-                    <div className="text-muted-foreground break-words">{currentImage.prompt || 'N/A'}</div>
-                  </div>
+                {(() => {
+                  const isMatrix = isMatrixGrid(currentImage);
+                  const settingsAny = currentImage.settings as any;
                   
-                  <div>
-                    <div className="font-semibold mb-1">Negative prompt:</div>
-                    <div className="text-muted-foreground break-words">{currentImage.negativePrompt || 'N/A'}</div>
-                  </div>
-                  
-                  <div className="space-y-2">
-                    <div><strong>Steps:</strong> {currentImage.settings?.steps || 'N/A'}</div>
-                    <div><strong>Sampler:</strong> {currentImage.settings?.sampler_name || 'N/A'}</div>
-                    <div><strong>CFG scale:</strong> {currentImage.settings?.cfg_scale || 'N/A'}</div>
-                    <div><strong>Seed:</strong> {currentImage.settings?.seed || 'N/A'}</div>
-                    <div><strong>Size:</strong> {currentImage.settings?.width || 'N/A'}x{currentImage.settings?.height || 'N/A'}</div>
-                    <div><strong>Model:</strong> {currentImage.settings?.model_name || 'N/A'}</div>
-                    {currentImage.settings?.denoising_strength && (
-                      <div><strong>Denoising strength:</strong> {currentImage.settings.denoising_strength}</div>
-                    )}
-                  </div>
-                </div>
+                  if (isMatrix && settingsAny?.isMatrixGrid) {
+                    return (
+                      <div className="space-y-3">
+                        <div>
+                          <div className="font-semibold mb-1">Type:</div>
+                          <div className="text-muted-foreground">Matrix Grid Generation</div>
+                        </div>
+                        
+                        <div>
+                          <div className="font-semibold mb-1">Prompt:</div>
+                          <div className="text-muted-foreground break-words">{currentImage.prompt || 'N/A'}</div>
+                        </div>
+                        
+                        <div>
+                          <div className="font-semibold mb-1">Negative prompt:</div>
+                          <div className="text-muted-foreground break-words">{currentImage.negativePrompt || 'N/A'}</div>
+                        </div>
+                        
+                        <div className="border-t pt-3">
+                          <div className="font-semibold mb-2">Base Settings:</div>
+                          <div className="space-y-2">
+                            <div><strong>Steps:</strong> {currentImage.settings?.steps || 'N/A'}</div>
+                            <div><strong>Sampler:</strong> {currentImage.settings?.sampler_name || 'N/A'}</div>
+                            <div><strong>CFG scale:</strong> {currentImage.settings?.cfg_scale || 'N/A'}</div>
+                            <div><strong>Size:</strong> {currentImage.settings?.width || 'N/A'}x{currentImage.settings?.height || 'N/A'}</div>
+                            <div><strong>Model:</strong> {currentImage.settings?.model_name || 'N/A'}</div>
+                            {currentImage.settings?.denoising_strength && (
+                              <div><strong>Denoising strength:</strong> {currentImage.settings.denoising_strength}</div>
+                            )}
+                          </div>
+                        </div>
+                        
+                        {settingsAny.matrixAxes && (
+                          <div className="border-t pt-3">
+                            <div className="font-semibold mb-2">Matrix Configuration:</div>
+                            <div className="space-y-1">
+                              {settingsAny.matrixAxes.xAxis && (
+                                <div><strong>X-Axis ({settingsAny.matrixAxes.xAxis.name}):</strong> {settingsAny.matrixAxes.xAxis.values.join(', ')}</div>
+                              )}
+                              {settingsAny.matrixAxes.yAxis && (
+                                <div><strong>Y-Axis ({settingsAny.matrixAxes.yAxis.name}):</strong> {settingsAny.matrixAxes.yAxis.values.join(', ')}</div>
+                              )}
+                              {settingsAny.matrixAxes.zAxis && (
+                                <div><strong>Z-Axis ({settingsAny.matrixAxes.zAxis.name}):</strong> {settingsAny.matrixAxes.zAxis.values.join(', ')}</div>
+                              )}
+                            </div>
+                          </div>
+                        )}
+                        
+                        {settingsAny.totalJobs && (
+                          <div className="border-t pt-3">
+                            <div><strong>Total Jobs:</strong> {settingsAny.totalJobs}</div>
+                          </div>
+                        )}
+                        
+                        {settingsAny.matrixSettings && (
+                          <div className="border-t pt-3">
+                            <div className="font-semibold mb-2">Matrix Options:</div>
+                            <div className="space-y-1">
+                              <div><strong>Draw Legend:</strong> {settingsAny.matrixSettings.drawLegend ? 'Yes' : 'No'}</div>
+                              <div><strong>Keep Seeds Consistent:</strong> {settingsAny.matrixSettings.keepSeedsConsistent ? 'Yes' : 'No'}</div>
+                              <div><strong>Include Sub Images:</strong> {settingsAny.matrixSettings.includeSubImages ? 'Yes' : 'No'}</div>
+                              <div><strong>Include Sub Grids:</strong> {settingsAny.matrixSettings.includeSubgrids ? 'Yes' : 'No'}</div>
+                            </div>
+                          </div>
+                        )}
+                      </div>
+                    );
+                  } else {
+                    return (
+                      <div className="space-y-3">
+                        <div>
+                          <div className="font-semibold mb-1">Prompt:</div>
+                          <div className="text-muted-foreground break-words">{currentImage.prompt || 'N/A'}</div>
+                        </div>
+                        
+                        <div>
+                          <div className="font-semibold mb-1">Negative prompt:</div>
+                          <div className="text-muted-foreground break-words">{currentImage.negativePrompt || 'N/A'}</div>
+                        </div>
+                        
+                        <div className="space-y-2">
+                          <div><strong>Steps:</strong> {currentImage.settings?.steps || 'N/A'}</div>
+                          <div><strong>Sampler:</strong> {currentImage.settings?.sampler_name || 'N/A'}</div>
+                          <div><strong>CFG scale:</strong> {currentImage.settings?.cfg_scale || 'N/A'}</div>
+                          <div><strong>Seed:</strong> {currentImage.settings?.seed || 'N/A'}</div>
+                          <div><strong>Size:</strong> {currentImage.settings?.width || 'N/A'}x{currentImage.settings?.height || 'N/A'}</div>
+                          <div><strong>Model:</strong> {currentImage.settings?.model_name || 'N/A'}</div>
+                          {currentImage.settings?.denoising_strength && (
+                            <div><strong>Denoising strength:</strong> {currentImage.settings.denoising_strength}</div>
+                          )}
+                        </div>
+                      </div>
+                    );
+                  }
+                })()}
               </div>
             )}
           </div>
diff --git a/dream_layer_frontend/src/features/Extras/ExtrasPage.tsx b/dream_layer_frontend/src/features/Extras/ExtrasPage.tsx
index 33f0125e..79c78be3 100644
--- a/dream_layer_frontend/src/features/Extras/ExtrasPage.tsx
+++ b/dream_layer_frontend/src/features/Extras/ExtrasPage.tsx
@@ -245,10 +245,11 @@ const ExtrasPage = () => {
         <div className="my-6">
           <div className="text-sm font-medium text-foreground mb-2">b) Upscaling Model #1</div>
           <Select 
+            defaultValue={selectedUpscaler} 
             onValueChange={(value) => setSelectedUpscaler(value)}
           >
             <SelectTrigger className="w-full" id="upscaling-model">
-              <SelectValue placeholder="Select Model" />
+              <SelectValue placeholder="Select an upscaling model" />
             </SelectTrigger>
             <SelectContent>
               {availableUpscalers.map((model) => (
@@ -260,7 +261,7 @@ const ExtrasPage = () => {
           </Select>
           <div className="mt-4 mx-4 text-sm text-muted-foreground">
             <p className="mb-1">
-              <span className="font-medium">About The Upscaler:</span> {currentUpscaler.description} Speed: {currentUpscaler.speed}. Upload the Upscaling model you want to select.
+              <span className="font-medium">About The Upscaler:</span> {currentUpscaler.description} Speed: {currentUpscaler.speed}.
             </p>
           </div>
         </div>
@@ -268,10 +269,11 @@ const ExtrasPage = () => {
         <div className="my-6">
           <div className="text-sm font-medium text-foreground mb-2">c) Upscaling Model #2</div>
           <Select 
+            defaultValue={selectedUpscaler2} 
             onValueChange={(value) => setSelectedUpscaler2(value)}
           >
             <SelectTrigger className="w-full" id="upscaling-model-2">
-              <SelectValue placeholder="Select Model" />
+              <SelectValue placeholder="Select an upscaling model" />
             </SelectTrigger>
             <SelectContent>
               {availableUpscalers.map((model) => (
@@ -283,7 +285,7 @@ const ExtrasPage = () => {
           </Select>
           <div className="mt-4 mx-4 text-sm text-muted-foreground">
             <p className="mb-1">
-              <span className="font-medium">About The Upscaler:</span> {currentUpscaler2.description} Speed: {currentUpscaler2.speed}. Upload the Upscaling model you want to select.
+              <span className="font-medium">About The Upscaler:</span> {currentUpscaler2.description} Speed: {currentUpscaler2.speed}.
             </p>
           </div>
         </div>
diff --git a/dream_layer_frontend/src/features/Img2Txt/Img2TxtPage.tsx b/dream_layer_frontend/src/features/Img2Txt/Img2TxtPage.tsx
deleted file mode 100644
index 3f784b4c..00000000
--- a/dream_layer_frontend/src/features/Img2Txt/Img2TxtPage.tsx
+++ /dev/null
@@ -1,292 +0,0 @@
-import React, { useState } from 'react';
-import { Upload, MessageSquare, Image as ImageIcon, Loader2 } from 'lucide-react';
-import { Button } from '@/components/ui/button';
-import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
-import { Textarea } from '@/components/ui/textarea';
-import { toast } from '@/hooks/use-toast';
-
-interface Img2TxtPageProps {}
-
-const Img2TxtPage: React.FC<Img2TxtPageProps> = () => {
-  const [selectedImage, setSelectedImage] = useState<File | null>(null);
-  const [imagePreview, setImagePreview] = useState<string | null>(null);
-  const [customPrompt, setCustomPrompt] = useState<string>('');
-  const [generatedText, setGeneratedText] = useState<string>('');
-  const [isGenerating, setIsGenerating] = useState<boolean>(false);
-
-  const handleImageUpload = (event: React.ChangeEvent<HTMLInputElement>) => {
-    const file = event.target.files?.[0];
-    if (file) {
-      setSelectedImage(file);
-      setGeneratedText(''); // Clear previous results
-      
-      // Create preview URL
-      const url = URL.createObjectURL(file);
-      setImagePreview(url);
-    }
-  };
-
-  const handleDrop = (event: React.DragEvent) => {
-    event.preventDefault();
-    const file = event.dataTransfer.files?.[0];
-    if (file && file.type.startsWith('image/')) {
-      setSelectedImage(file);
-      setGeneratedText('');
-      
-      const url = URL.createObjectURL(file);
-      setImagePreview(url);
-    }
-  };
-
-  const handleDragOver = (event: React.DragEvent) => {
-    event.preventDefault();
-  };
-
-  const clearImage = () => {
-    if (imagePreview) {
-      URL.revokeObjectURL(imagePreview);
-    }
-    setSelectedImage(null);
-    setImagePreview(null);
-    setGeneratedText('');
-  };
-
-  const convertImageToBase64 = (file: File): Promise<string> => {
-    return new Promise((resolve, reject) => {
-      const reader = new FileReader();
-      reader.onload = () => resolve(reader.result as string);
-      reader.onerror = reject;
-      reader.readAsDataURL(file);
-    });
-  };
-
-  const handleGenerateText = async () => {
-    if (!selectedImage) {
-      toast({
-        title: "No image selected",
-        description: "Please upload an image first.",
-        variant: "destructive",
-      });
-      return;
-    }
-
-    setIsGenerating(true);
-    try {
-      // Convert image to base64
-      const base64Image = await convertImageToBase64(selectedImage);
-
-      // Prepare request data
-      const requestData = {
-        input_image: base64Image,
-        prompt: customPrompt || undefined,
-        model: "gemini-2.5-pro-preview-05-06",
-        seed: 42
-      };
-
-      // Send request to img2txt server
-      const response = await fetch('http://localhost:5007/api/img2txt', {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-        body: JSON.stringify(requestData),
-      });
-
-      const data = await response.json();
-
-      if (data.status === 'success') {
-        setGeneratedText(data.generated_text || data.comfy_response?.text_output || 'No text generated');
-        toast({
-          title: "Analysis Complete",
-          description: "Image has been analyzed successfully!",
-        });
-      } else {
-        throw new Error(data.message || 'Failed to analyze image');
-      }
-    } catch (error) {
-      console.error('Error generating text:', error);
-      toast({
-        title: "Generation Failed",
-        description: error instanceof Error ? error.message : "An unknown error occurred",
-        variant: "destructive",
-      });
-    } finally {
-      setIsGenerating(false);
-    }
-  };
-
-  return (
-    <div className="flex justify-center">
-      <div className="w-full max-w-6xl space-y-6">
-        <div className="flex items-center justify-between">
-          <h2 className="text-2xl font-bold">Image to Text Analysis</h2>
-          <Button 
-            onClick={handleGenerateText} 
-            disabled={!selectedImage || isGenerating}
-            className="min-w-[120px]"
-          >
-            {isGenerating ? (
-              <>
-                <Loader2 className="w-4 h-4 mr-2 animate-spin" />
-                Analyzing...
-              </>
-            ) : (
-              <>
-                <MessageSquare className="w-4 h-4 mr-2" />
-                Generate Text
-              </>
-            )}
-          </Button>
-        </div>
-
-        <div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
-          {/* Image Upload Section */}
-          <Card>
-            <CardHeader>
-              <CardTitle className="flex items-center gap-2">
-                <ImageIcon className="w-5 h-5" />
-                Image Input
-              </CardTitle>
-            </CardHeader>
-            <CardContent>
-              <div className="space-y-4">
-                {/* Upload Area */}
-                <div
-                  className="border-2 border-dashed border-border rounded-lg p-8 text-center hover:border-primary/50 transition-colors cursor-pointer"
-                  onDrop={handleDrop}
-                  onDragOver={handleDragOver}
-                  onClick={() => document.getElementById('image-upload')?.click()}
-                >
-                  {imagePreview ? (
-                    <div className="space-y-4">
-                      <img
-                        src={imagePreview}
-                        alt="Selected"
-                        className="max-w-full max-h-64 mx-auto rounded-lg shadow-sm"
-                      />
-                      <div className="flex gap-2 justify-center">
-                        <Button variant="outline" size="sm" onClick={clearImage}>
-                          Clear Image
-                        </Button>
-                        <Button variant="outline" size="sm" onClick={() => document.getElementById('image-upload')?.click()}>
-                          Change Image
-                        </Button>
-                      </div>
-                    </div>
-                  ) : (
-                    <div className="space-y-2">
-                      <Upload className="w-12 h-12 mx-auto text-muted-foreground" />
-                      <p className="text-lg font-medium">Drop an image here or click to browse</p>
-                      <p className="text-sm text-muted-foreground">
-                        Supports JPG, PNG, GIF and other image formats
-                      </p>
-                    </div>
-                  )}
-                </div>
-
-                <input
-                  id="image-upload"
-                  type="file"
-                  accept="image/*"
-                  onChange={handleImageUpload}
-                  className="hidden"
-                />
-
-                {/* Custom Prompt */}
-                <div className="space-y-2">
-                  <label className="text-sm font-medium">
-                    Custom Analysis Prompt (Optional)
-                  </label>
-                  <Textarea
-                    placeholder="Enter custom instructions for image analysis (leave empty for default analysis)"
-                    value={customPrompt}
-                    onChange={(e) => setCustomPrompt(e.target.value)}
-                    rows={3}
-                  />
-                  <p className="text-xs text-muted-foreground">
-                    Default: Analyze and describe the image in detail including objects, scene, colors, mood, and composition.
-                  </p>
-                </div>
-              </div>
-            </CardContent>
-          </Card>
-
-          {/* Generated Text Section */}
-          <Card>
-            <CardHeader>
-              <CardTitle className="flex items-center gap-2">
-                <MessageSquare className="w-5 h-5" />
-                Generated Analysis
-              </CardTitle>
-            </CardHeader>
-            <CardContent>
-              <div className="space-y-4">
-                {isGenerating ? (
-                  <div className="flex items-center justify-center p-8 text-muted-foreground">
-                    <Loader2 className="w-6 h-6 mr-2 animate-spin" />
-                    Analyzing image with Gemini AI...
-                  </div>
-                ) : generatedText ? (
-                  <div className="space-y-4">
-                    <div className="p-4 bg-muted rounded-lg">
-                      <pre className="whitespace-pre-wrap text-sm">{generatedText}</pre>
-                    </div>
-                    <div className="flex gap-2">
-                      <Button
-                        variant="outline"
-                        size="sm"
-                        onClick={() => navigator.clipboard.writeText(generatedText)}
-                      >
-                        Copy Text
-                      </Button>
-                      <Button
-                        variant="outline"
-                        size="sm"
-                        onClick={() => setGeneratedText('')}
-                      >
-                        Clear
-                      </Button>
-                    </div>
-                  </div>
-                ) : (
-                  <div className="text-center p-8 text-muted-foreground">
-                    <MessageSquare className="w-12 h-12 mx-auto mb-4 opacity-50" />
-                    <p>Upload an image and click "Generate Text" to see the AI analysis</p>
-                  </div>
-                )}
-              </div>
-            </CardContent>
-          </Card>
-        </div>
-
-        {/* Info Section */}
-        <Card>
-          <CardContent className="pt-6">
-            <div className="grid grid-cols-1 md:grid-cols-3 gap-4 text-sm">
-              <div>
-                <h4 className="font-semibold mb-2">How it works</h4>
-                <p className="text-muted-foreground">
-                  Upload any image and our Gemini AI will analyze it, providing detailed descriptions of objects, scenes, composition, and artistic elements.
-                </p>
-              </div>
-              <div>
-                <h4 className="font-semibold mb-2">Custom Prompts</h4>
-                <p className="text-muted-foreground">
-                  Customize the analysis by providing specific instructions. Ask about style, colors, emotions, or technical aspects.
-                </p>
-              </div>
-              <div>
-                <h4 className="font-semibold mb-2">Powered by</h4>
-                <p className="text-muted-foreground">
-                  Google Gemini 2.5 Pro - Advanced multimodal AI with sophisticated visual understanding capabilities.
-                </p>
-              </div>
-            </div>
-          </CardContent>
-        </Card>
-      </div>
-    </div>
-  );
-};
-
-export default Img2TxtPage;
diff --git a/dream_layer_frontend/src/features/Img2Txt/index.ts b/dream_layer_frontend/src/features/Img2Txt/index.ts
deleted file mode 100644
index 37139b4d..00000000
--- a/dream_layer_frontend/src/features/Img2Txt/index.ts
+++ /dev/null
@@ -1 +0,0 @@
-export { default as Img2TxtPage } from './Img2TxtPage';
diff --git a/dream_layer_frontend/src/features/ReportBundle/ReportBundlePage.tsx b/dream_layer_frontend/src/features/ReportBundle/ReportBundlePage.tsx
deleted file mode 100644
index 28431afa..00000000
--- a/dream_layer_frontend/src/features/ReportBundle/ReportBundlePage.tsx
+++ /dev/null
@@ -1,256 +0,0 @@
-import React, { useState } from 'react';
-import { useReportBundleStore } from '@/stores/useReportBundleStore';
-import { useRunRegistryStore } from '@/stores/useRunRegistryStore';
-import { Download, FileText, AlertCircle, CheckCircle, Loader2 } from 'lucide-react';
-import { Button } from '@/components/ui/button';
-import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
-import { Alert, AlertDescription } from '@/components/ui/alert';
-import { Checkbox } from '@/components/ui/checkbox';
-import { Badge } from '@/components/ui/badge';
-import { Separator } from '@/components/ui/separator';
-import { format } from 'date-fns';
-
-const ReportBundlePage: React.FC = () => {
-  const { 
-    generating, 
-    error, 
-    downloadUrl, 
-    generateReport, 
-    downloadReport, 
-    clearError 
-  } = useReportBundleStore();
-  
-  const { runs, fetchRuns } = useRunRegistryStore();
-  const [selectedRuns, setSelectedRuns] = useState<Set<string>>(new Set());
-
-  React.useEffect(() => {
-    fetchRuns();
-  }, [fetchRuns]);
-
-  const handleGenerateReport = async () => {
-    const runIds = selectedRuns.size > 0 ? Array.from(selectedRuns) : undefined;
-    await generateReport(runIds);
-  };
-
-  const handleDownloadReport = async () => {
-    await downloadReport();
-  };
-
-  const toggleRunSelection = (runId: string) => {
-    const newSelected = new Set(selectedRuns);
-    if (newSelected.has(runId)) {
-      newSelected.delete(runId);
-    } else {
-      newSelected.add(runId);
-    }
-    setSelectedRuns(newSelected);
-  };
-
-  const selectAllRuns = () => {
-    setSelectedRuns(new Set(runs.map(run => run.run_id)));
-  };
-
-  const clearSelection = () => {
-    setSelectedRuns(new Set());
-  };
-
-  const formatTimestamp = (timestamp: string) => {
-    try {
-      return format(new Date(timestamp), 'MMM dd, yyyy HH:mm:ss');
-    } catch {
-      return timestamp;
-    }
-  };
-
-  const getGenerationTypeColor = (type: string) => {
-    return type === 'txt2img' ? 'bg-blue-100 text-blue-800' : 'bg-green-100 text-green-800';
-  };
-
-  return (
-    <div className="space-y-6">
-      <div className="flex items-center justify-between">
-        <h2 className="text-2xl font-bold">Report Bundle</h2>
-        <div className="flex items-center space-x-2">
-          <Button 
-            onClick={selectAllRuns} 
-            variant="outline" 
-            size="sm"
-          >
-            Select All
-          </Button>
-          <Button 
-            onClick={clearSelection} 
-            variant="outline" 
-            size="sm"
-          >
-            Clear Selection
-          </Button>
-        </div>
-      </div>
-
-      {error && (
-        <Alert variant="destructive">
-          <AlertCircle className="h-4 w-4" />
-          <AlertDescription>
-            {error}
-            <Button variant="link" onClick={clearError} className="ml-2 p-0 h-auto">
-              Dismiss
-            </Button>
-          </AlertDescription>
-        </Alert>
-      )}
-
-      {downloadUrl && (
-        <Alert>
-          <CheckCircle className="h-4 w-4" />
-          <AlertDescription>
-            Report bundle generated successfully! 
-            <Button variant="link" onClick={handleDownloadReport} className="ml-2 p-0 h-auto">
-              Download report.zip
-            </Button>
-          </AlertDescription>
-        </Alert>
-      )}
-
-      <Card>
-        <CardHeader>
-          <CardTitle className="flex items-center space-x-2">
-            <FileText className="h-5 w-5" />
-            <span>Generate Report Bundle</span>
-          </CardTitle>
-        </CardHeader>
-        <CardContent className="space-y-4">
-          <div className="flex items-center justify-between">
-            <div>
-              <p className="text-sm text-muted-foreground">
-                {selectedRuns.size > 0 
-                  ? `Selected ${selectedRuns.size} runs for report bundle`
-                  : 'No runs selected - will include all runs'
-                }
-              </p>
-              <p className="text-xs text-muted-foreground mt-1">
-                The report bundle will contain results.csv, config.json, selected images, and README.md
-              </p>
-            </div>
-            <Button 
-              onClick={handleGenerateReport} 
-              disabled={generating}
-              className="min-w-[140px]"
-            >
-              {generating ? (
-                <>
-                  <Loader2 className="h-4 w-4 mr-2 animate-spin" />
-                  Generating...
-                </>
-              ) : (
-                <>
-                  <FileText className="h-4 w-4 mr-2" />
-                  Generate Report
-                </>
-              )}
-            </Button>
-          </div>
-
-          <Separator />
-
-          <div className="space-y-2">
-            <h4 className="font-medium">Select Runs to Include</h4>
-            <p className="text-sm text-muted-foreground">
-              Leave all unchecked to include all runs in the report bundle
-            </p>
-            
-            {runs.length === 0 ? (
-              <div className="text-center py-8 text-muted-foreground">
-                <FileText className="h-12 w-12 mx-auto mb-4 opacity-50" />
-                <p>No runs available</p>
-                <p className="text-sm">Complete some image generations to see them here</p>
-              </div>
-            ) : (
-              <div className="space-y-2 max-h-96 overflow-y-auto">
-                {runs.map((run) => (
-                  <div 
-                    key={run.run_id} 
-                    className="flex items-center space-x-3 p-3 border rounded-lg hover:bg-muted/50"
-                  >
-                    <Checkbox
-                      checked={selectedRuns.has(run.run_id)}
-                      onCheckedChange={() => toggleRunSelection(run.run_id)}
-                    />
-                    <div className="flex-1 min-w-0">
-                      <div className="flex items-center space-x-2 mb-1">
-                        <Badge variant="outline" className="font-mono text-xs">
-                          {run.run_id.slice(0, 8)}...
-                        </Badge>
-                        <Badge className={getGenerationTypeColor(run.generation_type)}>
-                          {run.generation_type.toUpperCase()}
-                        </Badge>
-                        <span className="text-sm text-muted-foreground">
-                          {formatTimestamp(run.timestamp)}
-                        </span>
-                      </div>
-                      <p className="text-sm font-medium line-clamp-1">{run.prompt}</p>
-                      <div className="flex items-center space-x-4 text-xs text-muted-foreground mt-1">
-                        <span>Model: {run.model}</span>
-                        <span>Seed: {run.seed}</span>
-                        <span>Steps: {run.steps}</span>
-                        <span>CFG: {run.cfg_scale}</span>
-                        <span>Images: {run.generated_images.length}</span>
-                      </div>
-                    </div>
-                  </div>
-                ))}
-              </div>
-            )}
-          </div>
-        </CardContent>
-      </Card>
-
-      <Card>
-        <CardHeader>
-          <CardTitle>Report Bundle Contents</CardTitle>
-        </CardHeader>
-        <CardContent>
-          <div className="space-y-3">
-            <div className="flex items-center space-x-3">
-              <FileText className="h-4 w-4 text-blue-500" />
-              <span className="font-medium">results.csv</span>
-              <span className="text-sm text-muted-foreground">
-                - Tabular data with all run metadata and configurations
-              </span>
-            </div>
-            <div className="flex items-center space-x-3">
-              <FileText className="h-4 w-4 text-green-500" />
-              <span className="font-medium">config.json</span>
-              <span className="text-sm text-muted-foreground">
-                - Detailed configuration data for each run
-              </span>
-            </div>
-            <div className="flex items-center space-x-3">
-              <FileText className="h-4 w-4 text-purple-500" />
-              <span className="font-medium">images/</span>
-              <span className="text-sm text-muted-foreground">
-                - Generated images from all included runs
-              </span>
-            </div>
-            <div className="flex items-center space-x-3">
-              <FileText className="h-4 w-4 text-orange-500" />
-              <span className="font-medium">README.md</span>
-              <span className="text-sm text-muted-foreground">
-                - Documentation and schema information
-              </span>
-            </div>
-          </div>
-          
-          <Separator className="my-4" />
-          
-          <div className="text-sm text-muted-foreground">
-            <p><strong>CSV Schema:</strong> run_id, timestamp, model, vae, prompt, negative_prompt, seed, sampler, steps, cfg_scale, width, height, batch_size, batch_count, generation_type, image_paths, loras, controlnets, workflow_hash</p>
-            <p className="mt-2"><strong>Validation:</strong> All required CSV columns are verified, and all image paths resolve to files present in the zip bundle.</p>
-          </div>
-        </CardContent>
-      </Card>
-    </div>
-  );
-};
-
-export default ReportBundlePage; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/features/ReportBundle/index.ts b/dream_layer_frontend/src/features/ReportBundle/index.ts
deleted file mode 100644
index b548fd1f..00000000
--- a/dream_layer_frontend/src/features/ReportBundle/index.ts
+++ /dev/null
@@ -1 +0,0 @@
-export { default as ReportBundlePage } from './ReportBundlePage'; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/features/RunRegistry/RunRegistryPage.tsx b/dream_layer_frontend/src/features/RunRegistry/RunRegistryPage.tsx
deleted file mode 100644
index ce43e6d9..00000000
--- a/dream_layer_frontend/src/features/RunRegistry/RunRegistryPage.tsx
+++ /dev/null
@@ -1,319 +0,0 @@
-import React, { useEffect } from 'react';
-import { useRunRegistryStore } from '@/stores/useRunRegistryStore';
-import { RunConfig } from '@/types/runRegistry';
-import { format } from 'date-fns';
-import { Trash2, Eye, Clock, Image as ImageIcon } from 'lucide-react';
-import { Button } from '@/components/ui/button';
-import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
-import { Badge } from '@/components/ui/badge';
-import { Skeleton } from '@/components/ui/skeleton';
-import { Alert, AlertDescription } from '@/components/ui/alert';
-import { Dialog, DialogContent, DialogHeader, DialogTitle } from '@/components/ui/dialog';
-import { ScrollArea } from '@/components/ui/scroll-area';
-import { Separator } from '@/components/ui/separator';
-
-const RunRegistryPage: React.FC = () => {
-  const { 
-    runs, 
-    loading, 
-    error, 
-    selectedRun, 
-    fetchRuns, 
-    deleteRun, 
-    clearError, 
-    setSelectedRun 
-  } = useRunRegistryStore();
-
-  useEffect(() => {
-    fetchRuns();
-  }, [fetchRuns]);
-
-  const handleDeleteRun = async (runId: string) => {
-    if (confirm('Are you sure you want to delete this run?')) {
-      await deleteRun(runId);
-    }
-  };
-
-  const handleViewConfig = (run: RunConfig) => {
-    setSelectedRun(run);
-  };
-
-  const formatTimestamp = (timestamp: string) => {
-    try {
-      return format(new Date(timestamp), 'MMM dd, yyyy HH:mm:ss');
-    } catch {
-      return timestamp;
-    }
-  };
-
-  const getGenerationTypeColor = (type: string) => {
-    return type === 'txt2img' ? 'bg-blue-100 text-blue-800' : 'bg-green-100 text-green-800';
-  };
-
-  if (loading) {
-    return (
-      <div className="space-y-4">
-        <h2 className="text-2xl font-bold">Run Registry</h2>
-        <div className="grid gap-4">
-          {[...Array(5)].map((_, i) => (
-            <Card key={i}>
-              <CardHeader>
-                <Skeleton className="h-4 w-48" />
-                <Skeleton className="h-3 w-32" />
-              </CardHeader>
-              <CardContent>
-                <Skeleton className="h-20 w-full" />
-              </CardContent>
-            </Card>
-          ))}
-        </div>
-      </div>
-    );
-  }
-
-  if (error) {
-    return (
-      <div className="space-y-4">
-        <h2 className="text-2xl font-bold">Run Registry</h2>
-        <Alert variant="destructive">
-          <AlertDescription>
-            {error}
-            <Button variant="link" onClick={clearError} className="ml-2 p-0 h-auto">
-              Try again
-            </Button>
-          </AlertDescription>
-        </Alert>
-      </div>
-    );
-  }
-
-  return (
-    <div className="space-y-6">
-      <div className="flex items-center justify-between">
-        <h2 className="text-2xl font-bold">Run Registry</h2>
-        <Button onClick={fetchRuns} variant="outline" size="sm">
-          Refresh
-        </Button>
-      </div>
-
-      {runs.length === 0 ? (
-        <Card>
-          <CardContent className="flex flex-col items-center justify-center py-12">
-            <Clock className="h-12 w-12 text-muted-foreground mb-4" />
-            <h3 className="text-lg font-semibold mb-2">No runs yet</h3>
-            <p className="text-muted-foreground text-center">
-              Completed generations will appear here with their frozen configurations.
-            </p>
-          </CardContent>
-        </Card>
-      ) : (
-        <div className="grid gap-4">
-          {runs.map((run) => (
-            <Card key={run.run_id} className="hover:shadow-md transition-shadow">
-              <CardHeader>
-                <div className="flex items-center justify-between">
-                  <div className="flex items-center space-x-2">
-                    <Badge variant="outline" className="font-mono text-xs">
-                      {run.run_id.slice(0, 8)}...
-                    </Badge>
-                    <Badge className={getGenerationTypeColor(run.generation_type)}>
-                      {run.generation_type.toUpperCase()}
-                    </Badge>
-                  </div>
-                  <div className="flex items-center space-x-2">
-                    <Button
-                      variant="ghost"
-                      size="sm"
-                      onClick={() => handleViewConfig(run)}
-                    >
-                      <Eye className="h-4 w-4 mr-1" />
-                      View Config
-                    </Button>
-                    <Button
-                      variant="ghost"
-                      size="sm"
-                      onClick={() => handleDeleteRun(run.run_id)}
-                      className="text-destructive hover:text-destructive"
-                    >
-                      <Trash2 className="h-4 w-4" />
-                    </Button>
-                  </div>
-                </div>
-                <div className="flex items-center space-x-2 text-sm text-muted-foreground">
-                  <Clock className="h-3 w-3" />
-                  {formatTimestamp(run.timestamp)}
-                </div>
-              </CardHeader>
-              <CardContent>
-                <div className="space-y-3">
-                  <div>
-                    <p className="font-medium line-clamp-2">{run.prompt}</p>
-                    {run.negative_prompt && (
-                      <p className="text-sm text-muted-foreground line-clamp-1">
-                        Negative: {run.negative_prompt}
-                      </p>
-                    )}
-                  </div>
-                  
-                  <div className="flex items-center justify-between text-sm">
-                    <div className="flex items-center space-x-4">
-                      <span><strong>Model:</strong> {run.model}</span>
-                      <span><strong>Sampler:</strong> {run.sampler}</span>
-                      <span><strong>Steps:</strong> {run.steps}</span>
-                      <span><strong>CFG:</strong> {run.cfg_scale}</span>
-                    </div>
-                    <div className="flex items-center space-x-2">
-                      <ImageIcon className="h-4 w-4" />
-                      <span>{run.generated_images.length} image(s)</span>
-                    </div>
-                  </div>
-
-                  {(run.loras.length > 0 || run.controlnets.length > 0) && (
-                    <div className="flex flex-wrap gap-2">
-                      {run.loras.map((lora, index) => (
-                        <Badge key={`lora-${index}`} variant="secondary" className="text-xs">
-                          LoRA: {lora.name}
-                        </Badge>
-                      ))}
-                      {run.controlnets.map((controlnet, index) => (
-                        <Badge key={`controlnet-${index}`} variant="secondary" className="text-xs">
-                          ControlNet: {controlnet.model}
-                        </Badge>
-                      ))}
-                    </div>
-                  )}
-                </div>
-              </CardContent>
-            </Card>
-          ))}
-        </div>
-      )}
-
-      {/* Frozen Config Modal */}
-      <Dialog open={!!selectedRun} onOpenChange={() => setSelectedRun(null)}>
-        <DialogContent className="max-w-4xl max-h-[80vh]">
-          <DialogHeader>
-            <DialogTitle>Frozen Configuration</DialogTitle>
-          </DialogHeader>
-          {selectedRun && (
-            <ScrollArea className="max-h-[60vh]">
-              <div className="space-y-4">
-                <div className="grid grid-cols-2 gap-4">
-                  <div>
-                    <h4 className="font-semibold mb-2">Basic Info</h4>
-                    <div className="space-y-1 text-sm">
-                      <p><strong>Run ID:</strong> {selectedRun.run_id}</p>
-                      <p><strong>Timestamp:</strong> {formatTimestamp(selectedRun.timestamp)}</p>
-                      <p><strong>Type:</strong> {selectedRun.generation_type}</p>
-                      <p><strong>Version:</strong> {selectedRun.version}</p>
-                    </div>
-                  </div>
-                  <div>
-                    <h4 className="font-semibold mb-2">Generation Settings</h4>
-                    <div className="space-y-1 text-sm">
-                      <p><strong>Model:</strong> {selectedRun.model}</p>
-                      <p><strong>VAE:</strong> {selectedRun.vae || 'Default'}</p>
-                      <p><strong>Sampler:</strong> {selectedRun.sampler}</p>
-                      <p><strong>Steps:</strong> {selectedRun.steps}</p>
-                      <p><strong>CFG Scale:</strong> {selectedRun.cfg_scale}</p>
-                      <p><strong>Seed:</strong> {selectedRun.seed}</p>
-                    </div>
-                  </div>
-                </div>
-
-                <Separator />
-
-                <div>
-                  <h4 className="font-semibold mb-2">Prompts</h4>
-                  <div className="space-y-2">
-                    <div>
-                      <p className="text-sm font-medium">Positive Prompt:</p>
-                      <p className="text-sm bg-muted p-2 rounded">{selectedRun.prompt}</p>
-                    </div>
-                    {selectedRun.negative_prompt && (
-                      <div>
-                        <p className="text-sm font-medium">Negative Prompt:</p>
-                        <p className="text-sm bg-muted p-2 rounded">{selectedRun.negative_prompt}</p>
-                      </div>
-                    )}
-                  </div>
-                </div>
-
-                <Separator />
-
-                <div>
-                  <h4 className="font-semibold mb-2">Image Settings</h4>
-                  <div className="grid grid-cols-3 gap-4 text-sm">
-                    <p><strong>Width:</strong> {selectedRun.width}</p>
-                    <p><strong>Height:</strong> {selectedRun.height}</p>
-                    <p><strong>Batch Size:</strong> {selectedRun.batch_size}</p>
-                    <p><strong>Batch Count:</strong> {selectedRun.batch_count}</p>
-                  </div>
-                </div>
-
-                {selectedRun.loras.length > 0 && (
-                  <>
-                    <Separator />
-                    <div>
-                      <h4 className="font-semibold mb-2">LoRAs</h4>
-                      <div className="space-y-2">
-                        {selectedRun.loras.map((lora, index) => (
-                          <div key={index} className="text-sm">
-                            <p><strong>Name:</strong> {lora.name}</p>
-                            <p><strong>Strength:</strong> {lora.strength}</p>
-                          </div>
-                        ))}
-                      </div>
-                    </div>
-                  </>
-                )}
-
-                {selectedRun.controlnets.length > 0 && (
-                  <>
-                    <Separator />
-                    <div>
-                      <h4 className="font-semibold mb-2">ControlNets</h4>
-                      <div className="space-y-2">
-                        {selectedRun.controlnets.map((controlnet, index) => (
-                          <div key={index} className="text-sm">
-                            <p><strong>Model:</strong> {controlnet.model}</p>
-                            <p><strong>Strength:</strong> {controlnet.strength}</p>
-                            <p><strong>Enabled:</strong> {controlnet.enabled ? 'Yes' : 'No'}</p>
-                          </div>
-                        ))}
-                      </div>
-                    </div>
-                  </>
-                )}
-
-                <Separator />
-
-                <div>
-                  <h4 className="font-semibold mb-2">Generated Images</h4>
-                  <div className="grid grid-cols-2 gap-2">
-                    {selectedRun.generated_images.map((image, index) => (
-                      <div key={index} className="text-sm">
-                        <p className="font-mono text-xs">{image}</p>
-                      </div>
-                    ))}
-                  </div>
-                </div>
-
-                <Separator />
-
-                <div>
-                  <h4 className="font-semibold mb-2">Workflow (Serialized)</h4>
-                  <pre className="text-xs bg-muted p-2 rounded overflow-auto max-h-32">
-                    {JSON.stringify(selectedRun.workflow, null, 2)}
-                  </pre>
-                </div>
-              </div>
-            </ScrollArea>
-          )}
-        </DialogContent>
-      </Dialog>
-    </div>
-  );
-};
-
-export default RunRegistryPage; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/features/RunRegistry/index.ts b/dream_layer_frontend/src/features/RunRegistry/index.ts
deleted file mode 100644
index 7b905721..00000000
--- a/dream_layer_frontend/src/features/RunRegistry/index.ts
+++ /dev/null
@@ -1 +0,0 @@
-export { default as RunRegistryPage } from './RunRegistryPage'; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/features/Txt2Img/Txt2ImgPage.tsx b/dream_layer_frontend/src/features/Txt2Img/Txt2ImgPage.tsx
index 1d3f2045..ec1fc1df 100644
--- a/dream_layer_frontend/src/features/Txt2Img/Txt2ImgPage.tsx
+++ b/dream_layer_frontend/src/features/Txt2Img/Txt2ImgPage.tsx
@@ -11,12 +11,15 @@ import ImagePreview from '@/components/tabs/txt2img/ImagePreview';
 import CheckpointBrowser from '@/components/checkpoint/CheckpointBrowser';
 import LoraBrowser from '@/components/lora/LoraBrowser';
 import CustomWorkflowBrowser from '@/components/custom-workflow/CustomWorkflowBrowser';
+import MatrixSettings from '@/components/MatrixSettings';
 import { useIsMobile } from '@/hooks/use-mobile';
 import { Copy } from "lucide-react";
 import { Button } from "@/components/ui/button";
 import { cn } from "@/lib/utils";
 import { useTxt2ImgGalleryStore } from '@/stores/useTxt2ImgGalleryStore';
-import { Txt2ImgCoreSettings, defaultTxt2ImgSettings } from '@/types/generationSettings';
+import { Txt2ImgCoreSettings, defaultTxt2ImgSettings, MatrixSettings as MatrixSettingsType, MatrixJob, MatrixParameter, defaultMatrixSettings, ImageResult } from '@/types/generationSettings';
+import { useMatrixStore } from '@/stores/useMatrixStore';
+import { generateMatrixGrid } from '@/utils/matrixGridGenerator';
 import useControlNetStore from '@/stores/useControlNetStore';
 import { ControlNetRequest } from '@/types/controlnet';
 import useLoraStore from '@/stores/useLoraStore';
@@ -34,7 +37,19 @@ const Txt2ImgPage: React.FC<Txt2ImgPageProps> = ({ selectedModel, onTabChange })
     model_name: selectedModel
   });
   const [customWorkflow, setCustomWorkflow] = useState<any | null>(null);
-  const [isGenerating, setIsGenerating] = useState(false);
+  const [matrixSettings, setMatrixSettings] = useState<MatrixSettingsType>(defaultMatrixSettings);
+
+  const {
+    jobs,
+    currentJobIndex,
+    isPaused,
+    setInitialState,
+    advanceJob,
+    setPaused,
+    updateJobStatus,
+    reset: resetMatrixStore
+  } = useMatrixStore();
+
   const isMobile = useIsMobile();
   const addImages = useTxt2ImgGalleryStore(state => state.addImages);
   const setLoading = useTxt2ImgGalleryStore(state => state.setLoading);
@@ -42,432 +57,621 @@ const Txt2ImgPage: React.FC<Txt2ImgPageProps> = ({ selectedModel, onTabChange })
   const { setControlNetConfig } = useControlNetStore();
   const loraConfig = useLoraStore(state => state.loraConfig);
 
-  // Add effect to update model when selectedModel prop changes
+  const isGenerating = !isPaused && jobs.length > 0 && currentJobIndex < jobs.length;
+  const hasActiveMatrixJob = jobs.length > 0;
+
   useEffect(() => {
     updateCoreSettings({ model_name: selectedModel });
   }, [selectedModel]);
 
-  const updateCoreSettings = (updates: Partial<Txt2ImgCoreSettings>) => {
-    setCoreSettings(prev => ({ ...prev, ...updates }));
-  };
-
-  const handlePromptChange = (value: string, isNegative: boolean = false) => {
-    updateCoreSettings(isNegative ? { negative_prompt: value } : { prompt: value });
-  };
-
-  const handleBatchSettingsChange = (batchSize: number, batchCount: number) => {
-    updateCoreSettings({ batch_size: batchSize, batch_count: batchCount });
-  };
-
-  const handleSamplingSettingsChange = (sampler: string, scheduler: string, steps: number, cfg: number) => {
-    updateCoreSettings({
-      sampler_name: sampler,
-      scheduler: scheduler,
-      steps: steps,
-      cfg_scale: cfg
-    });
-  };
-
-  const handleSizeSettingsChange = (width: number, height: number) => {
-    updateCoreSettings({ width, height });
-  };
-
-  const handleSeedChange = (seed: number, random: boolean = true) => {
-    updateCoreSettings({ seed, random_seed: random });
-  };
-
-  const handleSubTabChange = (tabId: string) => {
-    setActiveSubTab(tabId);
-  };
+  // --- Matrix Generation Helper Functions ---
 
-  const handleControlNetChange = (config: ControlNetRequest | null) => {
-    console.log('ControlNet config changed in txt2img:', config);
-    // If config is null, it means ControlNet was disabled
-    setControlNetConfig(config?.enabled ? config : null);
-  };
-
-  const handleRestoreFacesChange = (enabled: boolean) => {
-    updateCoreSettings({ restore_faces: enabled });
+  const parseParameterValues = (parameter: MatrixParameter): any[] => {
+    if (parameter.name === 'Nothing' || !parameter.values?.trim()) {
+      console.log(`Parameter ${parameter.name} is Nothing or has no values`);
+      return [];
+    }
+    
+    const str = parameter.values.trim();
+    console.log(`Parsing parameter ${parameter.name} with values: "${str}", type: ${parameter.type}`);
+    
+    if (parameter.type === 'range' && str.includes('-')) {
+      const [start, end] = str.split('-').map(s => Number(s.trim()));
+      if (!isNaN(start) && !isNaN(end) && start <= end) {
+        const result = Array.from({ length: end - start + 1 }, (_, i) => start + i);
+        console.log(`Range result for ${parameter.name}:`, result);
+        return result;
+      }
+    }
+    
+    const result = str.split(',').map(v => {
+      const trimmed = v.trim();
+      const num = Number(trimmed);
+      return isNaN(num) ? trimmed : num;
+    }).filter(v => v !== '');
+    
+    console.log(`List result for ${parameter.name}:`, result);
+    return result;
   };
 
-  const handleFaceRestorationModelChange = (model: string) => {
-    updateCoreSettings({ face_restoration_model: model });
+  const applyParameterToSettings = (settings: Txt2ImgCoreSettings, paramName: string, value: any) => {
+    console.log(`Applying parameter ${paramName} = ${value} to settings`);
+    
+    switch (paramName) {
+      case 'Seed': 
+        if (matrixSettings.keepSeedsForRows) {
+          console.log('Keep -1 for seeds is enabled, keeping original seed');
+          settings.seed = -1;
+          settings.random_seed = true;
+        } else {
+          console.log('Keep -1 for seeds is disabled, using specific seed:', value);
+          settings.seed = Number(value); 
+          settings.random_seed = false;
+        }
+        break;
+      case 'Steps': settings.steps = Number(value); break;
+      case 'CFG Scale': settings.cfg_scale = Number(value); break;
+      case 'Sampler': settings.sampler_name = String(value); break;
+      case 'Denoising': settings.denoising_strength = Number(value); break;
+      case 'Clip skip': settings.clip_skip = Number(value); break;
+      case 'Hires steps': settings.hires_fix_hires_steps = Number(value); break;
+    }
   };
 
-  const handleCodeformerWeightChange = (weight: number) => {
-    updateCoreSettings({ codeformer_weight: weight });
-  };
+  const generateMatrixJobs = (): MatrixJob[] => {
+    console.log('=== generateMatrixJobs START ===');
+    console.log('Current matrixSettings:', matrixSettings);
+    
+    const xValues = parseParameterValues(matrixSettings.xAxis);
+    const yValues = parseParameterValues(matrixSettings.yAxis);
+    const zValues = parseParameterValues(matrixSettings.zAxis);
+    
+    console.log('Parsed values:', { xValues, yValues, zValues });
+    
+    if (xValues.length === 0 && yValues.length === 0 && zValues.length === 0) {
+      console.log('No values found, returning empty jobs array');
+      return [];
+    }
 
-  const handleGfpganWeightChange = (weight: number) => {
-    updateCoreSettings({ gfpgan_weight: weight });
+    const jobs: MatrixJob[] = [];
+    const xVals = xValues.length > 0 ? xValues : [null];
+    const yVals = yValues.length > 0 ? yValues : [null];
+    const zVals = zValues.length > 0 ? zValues : [null];
+    
+    console.log('Final values to iterate:', { xVals, yVals, zVals });
+    
+    let jobIndex = 0;
+    for (const zVal of zVals) {
+      for (const yVal of yVals) {
+        for (const xVal of xVals) {
+          const jobSettings = { ...coreSettings };
+          if (xVal !== null) applyParameterToSettings(jobSettings, matrixSettings.xAxis.name, xVal);
+          if (yVal !== null) applyParameterToSettings(jobSettings, matrixSettings.yAxis.name, yVal);
+          if (zVal !== null) applyParameterToSettings(jobSettings, matrixSettings.zAxis.name, zVal);
+          
+          const job = { 
+            id: `job-${jobIndex++}`, 
+            settings: jobSettings, 
+            xValue: xVal, 
+            yValue: yVal, 
+            zValue: zVal, 
+            status: 'pending' as const
+          };
+          jobs.push(job);
+          console.log(`Created job ${job.id}:`, { xValue: xVal, yValue: yVal, zValue: zVal });
+        }
+      }
+    }
+    
+    console.log(`=== generateMatrixJobs END: Created ${jobs.length} jobs ===`);
+    return jobs;
   };
 
-  const handleTilingChange = (enabled: boolean) => {
-    updateCoreSettings({ tiling: enabled });
-  };
+  const executeSingleGeneration = async (settings: Txt2ImgCoreSettings, options: { isMatrixJob: boolean; matrixInfo?: any }): Promise<ImageResult[]> => {
+    console.log('executeSingleGeneration called:', { isMatrixJob: options.isMatrixJob, matrixInfo: options.matrixInfo });
+    
+    if (!options.isMatrixJob) setLoading(true);
 
-  const handleTileSizeChange = (size: number) => {
-    updateCoreSettings({ tile_size: size });
-  };
+    try {
+      const requestData = { 
+        ...settings, 
+        custom_workflow: customWorkflow, 
+        ...(controlNetConfig && { controlnet: controlNetConfig }), 
+        ...(loraConfig?.enabled && { lora: loraConfig }) 
+      };
+      
+      console.log('Sending request to backend:', requestData);
+      
+      const response = await fetch('http://localhost:5001/api/txt2img', { 
+        method: 'POST', 
+        headers: { 'Content-Type': 'application/json' }, 
+        body: JSON.stringify(requestData) 
+      });
+      
+      console.log('Response received:', response.status, response.ok);
+      
+      if (!response.ok) {
+        const errorText = await response.text();
+        console.error('Backend error:', errorText);
+        throw new Error(`Failed to generate image: ${errorText}`);
+      }
+      
+      const data = await response.json();
+      console.log('Response data:', data);
+      
+      if (!data.comfy_response?.generated_images) {
+        console.error('No generated_images in response:', data);
+        throw new Error('No images were generated');
+      }
 
-  const handleTileOverlapChange = (overlap: number) => {
-    updateCoreSettings({ tile_overlap: overlap });
-  };
+      const images: ImageResult[] = await Promise.all(
+        data.comfy_response.generated_images.map(async (img: any) => {
+          let finalUrl = img.url;
+          
+          if (!options.isMatrixJob) {
+            try {
+              console.log('🔄 Saving single image to server for persistence:', img.url);
+              
+              const imageResponse = await fetch(img.url);
+              const imageBlob = await imageResponse.blob();
+              
+              const reader = new FileReader();
+              const base64Data = await new Promise<string>((resolve) => {
+                reader.onloadend = () => resolve(reader.result as string);
+                reader.readAsDataURL(imageBlob);
+              });
+              
+              const saveResponse = await fetch('http://localhost:5002/api/save-single-image', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                  imageData: base64Data,
+                  originalFilename: img.url.split('/').pop()
+                })
+              });
+              
+              if (saveResponse.ok) {
+                const saveResult = await saveResponse.json();
+                finalUrl = saveResult.url;
+                console.log('✅ Single image saved to server:', finalUrl);
+              } else {
+                console.warn('⚠️ Failed to save single image to server, using original URL');
+              }
+            } catch (error) {
+              console.warn('⚠️ Error saving single image to server:', error);
+            }
+          }
+          
+          return {
+            id: `${Date.now()}-${Math.random()}`, 
+            url: finalUrl, 
+            prompt: settings.prompt, 
+            negativePrompt: settings.negative_prompt, 
+            timestamp: Date.now(), 
+            settings: { ...settings }, 
+            matrixInfo: options.matrixInfo,
+          };
+        })
+      );
 
-  const handleHiresFixChange = (enabled: boolean) => {
-    updateCoreSettings({ hires_fix: enabled });
-  };
+      console.log('Generated images:', images.length, images);
+      
+      if (!options.isMatrixJob) {
+        console.log('Adding images to gallery (single mode)');
+        addImages(images);
+      }
+      
+      return images;
 
-  const handleRefinerEnabledChange = (enabled: boolean) => {
-    updateCoreSettings({ refiner_enabled: enabled });
+    } catch (error) {
+      console.error('executeSingleGeneration error:', error);
+      throw error;
+    } finally {
+      if (!options.isMatrixJob) setLoading(false);
+    }
   };
 
-  const handleRefinerModelChange = (model: string) => {
-    updateCoreSettings({ refiner_model: model });
+  const handleGenerate = async () => {
+    console.log('=== GENERATE BUTTON CLICKED ===');
+    
+    if (jobs.length > 0 && currentJobIndex < jobs.length) {
+      console.log('Matrix already in progress, ignoring generate');
+      return;
+    }
+    
+    const newJobs = generateMatrixJobs();
+    console.log('Generated jobs count:', newJobs.length);
+    
+    if (newJobs.length > 0) {
+      console.log('Starting matrix mode');
+      setLoading(true);
+      setInitialState(newJobs);
+    } else {
+      console.log('Starting single mode');
+      await executeSingleGeneration(coreSettings, { isMatrixJob: false });
+    }
   };
-
-  const handleRefinerSwitchAtChange = (value: number) => {
-    updateCoreSettings({ refiner_switch_at: value });
+  
+  const handleInterrupt = async () => {
+    await fetch('http://localhost:5001/api/txt2img/interrupt', { method: 'POST' });
+    resetMatrixStore();
+    setLoading(false);
   };
 
-  const handleCopyPrompts = () => {
-    const promptTextarea = document.querySelector('textarea[placeholder="Enter your prompt here"]') as HTMLTextAreaElement;
-    const negativePromptTextarea = document.querySelector('textarea[placeholder="Enter negative prompt here"]') as HTMLTextAreaElement;
+  const handlePause = async () => {
+    console.log('⏸️ Pausing Matrix generation...');
     
-    if (promptTextarea && negativePromptTextarea) {
-      const combinedText = `Prompt: ${promptTextarea.value}\nNegative Prompt: ${negativePromptTextarea.value}`;
-      navigator.clipboard.writeText(combinedText);
+    try {
+      await fetch('http://localhost:5001/api/txt2img/interrupt', { method: 'POST' });
+      console.log('✅ Backend interrupted successfully');
+    } catch (error) {
+      console.warn('⚠️ Failed to interrupt backend:', error);
+    }
+    
+    const currentJob = jobs[currentJobIndex];
+    if (currentJob && currentJob.status === 'running') {
+      updateJobStatus(currentJobIndex, 'pending');
     }
+    
+    setPaused(true);
   };
-
-  const handleGenerateImage = async () => {
-    // Handle interrupt if already generating
-    if (isGenerating) {
-      await fetch('http://localhost:5001/api/txt2img/interrupt', {
-        method: 'POST',
-        headers: { 'Content-Type': 'application/json' },
-        body: JSON.stringify({})
-      });
-      setIsGenerating(false);
-      setLoading(false);
+  
+  // --- Core Effects ---
+  
+  useEffect(() => {
+    console.log('Matrix job runner effect triggered:', { 
+      isGenerating, 
+      isPaused, 
+      currentJobIndex, 
+      totalJobs: jobs.length 
+    });
+    
+    if (!isGenerating || isPaused || currentJobIndex >= jobs.length) {
+      console.log('Effect early return:', { isGenerating, isPaused, currentJobIndex, jobsLength: jobs.length });
       return;
     }
-
-    // === GUARD: Ensure ControlNet image is set ===
-    // if (controlNetConfig?.enabled) {
-    //   const missingImage = controlNetConfig.units.some(unit => unit.enabled && !unit.input_image);
-    //   if (missingImage) {
-    //     alert("Please upload a ControlNet image for all enabled units before generating.");
-    //     setIsGenerating(false);
-    //     setLoading(false);
-    //     return;
-    //   }
-    // }
-    // === END GUARD ===
-
-    try {
-      setIsGenerating(true);
-      setLoading(true);
+    
+    let active = true;
+    const runJob = async () => {
+      const job = jobs[currentJobIndex];
+      console.log(`Running job ${currentJobIndex}:`, job);
       
-      console.log("ControlNetConfig at generate time:", JSON.stringify(controlNetConfig, null, 2));
+      if (!job) {
+        console.log(`Job ${currentJobIndex} does not exist`);
+        if (active) {
+          setTimeout(() => advanceJob(), 100);
+        }
+        return;
+      }
       
-      // Prepare the request data
-      const requestData = {
-        ...coreSettings,
-        custom_workflow: customWorkflow, // Add the custom workflow to the request
-        // Only include controlnet if it's properly configured
-        ...(controlNetConfig && { controlnet: controlNetConfig }),
-        // Only include lora if it's enabled and configured
-        ...(loraConfig?.enabled && { lora: loraConfig })
-      };
+      if (job.status === 'completed') {
+        console.log(`Job ${currentJobIndex} already completed, advancing...`);
+        if (active) {
+          setTimeout(() => advanceJob(), 100);
+        }
+        return;
+      }
+      
+      if (job.status === 'failed') {
+        console.log(`Job ${currentJobIndex} failed, skipping...`);
+        if (active) {
+          setTimeout(() => advanceJob(), 100);
+        }
+        return;
+      }
       
-      if (controlNetConfig?.units) {
-        console.log('📦 ControlNet Units Details:');
-        controlNetConfig.units.forEach((unit, index) => {
-          if (unit.input_image) {
-            console.log(`    Input image preview: ${unit.input_image.substring(0, 100)}...`);
+      if (job.status === 'running') {
+        console.log(`Job ${currentJobIndex} was running but paused, resetting to pending`);
+        updateJobStatus(currentJobIndex, 'pending');
+        return;
+      }
+      
+      if (job.status === 'pending') {
+        console.log(`Starting job ${currentJobIndex}`);
+        updateJobStatus(currentJobIndex, 'running');
+        
+        try {
+          const resultImages = await executeSingleGeneration(job.settings, { 
+            isMatrixJob: true, 
+            matrixInfo: { xValue: job.xValue, yValue: job.yValue, zValue: job.zValue } 
+          });
+          
+          console.log(`Job ${currentJobIndex} completed with ${resultImages.length} images`);
+          
+          if (active) {
+            updateJobStatus(currentJobIndex, 'completed', { result: resultImages });
+            setTimeout(() => advanceJob(), 200);
           }
-        });
+        } catch (error) {
+          console.error(`Job ${currentJobIndex} failed:`, error);
+          if (active) {
+            updateJobStatus(currentJobIndex, 'failed', { error });
+            setTimeout(() => advanceJob(), 200);
+          }
+        }
       }
-      console.log('ControlNet config being sent:', JSON.stringify(controlNetConfig, null, 2));
-      const response = await fetch('http://localhost:5001/api/txt2img', {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-        body: JSON.stringify(requestData),
-      });
-
-      console.log('Response status:', response.status);
-      console.log('Response headers:', response.headers);
+    };
+    
+    const timeoutId = setTimeout(() => {
+      if (active) {
+        runJob();
+      }
+    }, 100);
+    
+    return () => { 
+      active = false; 
+      clearTimeout(timeoutId);
+    };
+  }, [currentJobIndex, isPaused, isGenerating, jobs.length]);
 
-      if (!response.ok) {
-        const errorText = await response.text();
-        console.error('Error response:', errorText);
-        throw new Error(`Failed to generate image: ${errorText}`);
+  useEffect(() => {
+    const allJobsFinished = jobs.length > 0 && currentJobIndex >= jobs.length;
+    console.log('Grid generation effect:', { allJobsFinished, jobsLength: jobs.length, currentJobIndex });
+    
+    if (allJobsFinished) {
+      console.log('All matrix jobs finished. Generating grid...');
+      
+      const completedJobs = jobs.filter(job => job.status === 'completed' && job.result);
+      console.log('Completed jobs with results:', completedJobs);
+      
+      if (completedJobs.length === 0) {
+        console.error('No completed jobs found for grid generation');
+        resetMatrixStore();
+        setLoading(false);
+        return;
       }
 
-      const data = await response.json();
-      console.log('Response data:', data);
+      if (matrixSettings.includeSubImages) {
+        console.log('Adding individual images to gallery (Include Sub Images enabled)');
+        const allIndividualImages = completedJobs.flatMap(job => job.result || []);
+        if (allIndividualImages.length > 0) {
+          addImages(allIndividualImages);
+        }
+      }
 
-      if (data.comfy_response?.generated_images) {
-        const images = data.comfy_response.generated_images.map((img: any) => {
-          // Use the URL directly from the response
-          const imageUrl = img.url;
-          
-          // Create a test image to verify the URL works
-          const testImage = new Image();
-          testImage.src = imageUrl;
+      const hasZAxis = completedJobs.some(job => job.zValue !== null);
+      if (matrixSettings.includeSubgrids && hasZAxis) {
+        console.log('Generating sub-grids for each Z value (Include Sub Grids enabled)');
+        
+        const zValues = [...new Set(completedJobs.map(job => job.zValue).filter(v => v !== null))];
+        
+        zValues.forEach(async (zValue) => {
+          const zFilteredJobs = completedJobs.filter(job => job.zValue === zValue);
           
-          // Log the URL and loading status
-          console.log('Testing image URL:', imageUrl);
-          testImage.onload = () => console.log('Image loaded successfully:', imageUrl);
-          testImage.onerror = (e) => console.error('Image failed to load:', imageUrl, e);
+          try {
+            const subGridImageUrl = await generateMatrixGrid(zFilteredJobs, {
+              ...matrixSettings,
+              zAxis: { ...matrixSettings.zAxis, name: 'Nothing', enabled: false }
+            });
+            
+            addImages([{
+              id: `matrix-subgrid-z${zValue}-${Date.now()}`,
+              url: subGridImageUrl,
+              prompt: `${coreSettings.prompt} (${matrixSettings.zAxis?.name}: ${zValue})`,
+              negativePrompt: coreSettings.negative_prompt,
+              timestamp: Date.now(),
+              settings: { ...coreSettings },
+            }]);
+          } catch (error) {
+            console.error(`Failed to generate sub-grid for Z=${zValue}:`, error);
+          }
+        });
+      }
+
+      generateMatrixGrid(completedJobs, matrixSettings)
+        .then(gridImageUrl => {
+          console.log('Main grid generated successfully');
           
-          return {
-            id: `${Date.now()}-${Math.random()}`,
-            url: imageUrl,
-            prompt: coreSettings.prompt,
-            negativePrompt: coreSettings.negative_prompt,
-            timestamp: Date.now(),
-            settings: {
-              ...coreSettings
+          const matrixSpecificSettings = {
+            ...coreSettings,
+            isMatrixGrid: true,
+            matrixAxes: {
+              xAxis: matrixSettings.xAxis?.name !== 'Nothing' ? {
+                name: matrixSettings.xAxis?.name,
+                values: [...new Set(completedJobs.map(job => job.xValue).filter(v => v !== null))].sort()
+              } : null,
+              yAxis: matrixSettings.yAxis?.name !== 'Nothing' ? {
+                name: matrixSettings.yAxis?.name,
+                values: [...new Set(completedJobs.map(job => job.yValue).filter(v => v !== null))].sort()
+              } : null,
+              zAxis: matrixSettings.zAxis?.name !== 'Nothing' ? {
+                name: matrixSettings.zAxis?.name,
+                values: [...new Set(completedJobs.map(job => job.zValue).filter(v => v !== null))].sort()
+              } : null,
+            },
+            totalJobs: completedJobs.length,
+            matrixSettings: {
+              drawLegend: matrixSettings.drawLegend,
+              keepSeedsConsistent: matrixSettings.keepSeedsConsistent,
+              includeSubImages: matrixSettings.includeSubImages,
+              includeSubgrids: matrixSettings.includeSubgrids
             }
           };
+          
+          addImages([{
+            id: `matrix-grid-${Date.now()}`, 
+            url: gridImageUrl, 
+            prompt: `Matrix Grid: ${coreSettings.prompt}`,
+            negativePrompt: coreSettings.negative_prompt, 
+            timestamp: Date.now(), 
+            settings: matrixSpecificSettings,
+          }]);
+        })
+        .catch(error => {
+          console.error("Failed to generate matrix grid:", error);
+        })
+        .finally(() => {
+          console.log('Resetting matrix store and loading state');
+          resetMatrixStore();
+          setLoading(false);
         });
-        
-        console.log('Adding images to gallery:', images);
-        addImages(images);
-      } else {
-        console.error('No generated_images in response:', data);
-        throw new Error('No images were generated');
-      }
-    } catch (error) {
-      console.error('Error details:', error);
-    } finally {
-      setLoading(false);
-      setIsGenerating(false);
     }
+  }, [currentJobIndex, jobs.length, jobs, matrixSettings, coreSettings, addImages, resetMatrixStore, setLoading]);
+
+  // --- Other handlers and components ---
+  
+  const updateCoreSettings = (updates: Partial<Txt2ImgCoreSettings>) => setCoreSettings(prev => ({ ...prev, ...updates }));
+  const handlePromptChange = (value: string, isNegative: boolean = false) => updateCoreSettings(isNegative ? { negative_prompt: value } : { prompt: value });
+  const handleBatchSettingsChange = (batchSize: number, batchCount: number) => updateCoreSettings({ batch_size: batchSize, batch_count: batchCount });
+  const handleSamplingSettingsChange = (sampler: string, scheduler: string, steps: number, cfg: number) => updateCoreSettings({ sampler_name: sampler, scheduler: scheduler, steps: steps, cfg_scale: cfg });
+  const handleSizeSettingsChange = (width: number, height: number) => updateCoreSettings({ width, height });
+  const handleSeedChange = (seed: number, random: boolean = true) => updateCoreSettings({ seed, random_seed: random });
+  const handleSubTabChange = (tabId: string) => setActiveSubTab(tabId);
+  const handleControlNetChange = (config: ControlNetRequest | null) => setControlNetConfig(config?.enabled ? config : null);
+  const handleRestoreFacesChange = (enabled: boolean) => updateCoreSettings({ restore_faces: enabled });
+  const handleFaceRestorationModelChange = (model: string) => updateCoreSettings({ face_restoration_model: model });
+  const handleCodeformerWeightChange = (weight: number) => updateCoreSettings({ codeformer_weight: weight });
+  const handleGfpganWeightChange = (weight: number) => updateCoreSettings({ gfpgan_weight: weight });
+  const handleMatrixSettingsChange = (settings: MatrixSettingsType) => {
+    console.log('Matrix settings changed:', settings);
+    setMatrixSettings(settings);
   };
-
-  const getAccordionTitle = () => {
-    switch (activeSubTab) {
-      case "checkpoints":
-        return "Custom Workflow Management";
-      case "lora":
-        return "LoRA Browser";
-      default:
-        return "Core Generation Settings";
-    }
+  const handleTilingChange = (enabled: boolean) => updateCoreSettings({ tiling: enabled });
+  const handleTileSizeChange = (size: number) => updateCoreSettings({ tile_size: size });
+  const handleTileOverlapChange = (overlap: number) => updateCoreSettings({ tile_overlap: overlap });
+  const handleHiresFixChange = (enabled: boolean) => updateCoreSettings({ hires_fix: enabled });
+  const handleRefinerEnabledChange = (enabled: boolean) => updateCoreSettings({ refiner_enabled: enabled });
+  const handleRefinerModelChange = (model: string) => updateCoreSettings({ refiner_model: model });
+  const handleRefinerSwitchAtChange = (value: number) => updateCoreSettings({ refiner_switch_at: value });
+  const handleCopyPrompts = () => {
+    const promptTextarea = document.querySelector('textarea[placeholder="Enter your prompt here"]') as HTMLTextAreaElement;
+    const negativePromptTextarea = document.querySelector('textarea[placeholder="Enter negative prompt here"]') as HTMLTextAreaElement;
+    if (promptTextarea && negativePromptTextarea) navigator.clipboard.writeText(`Prompt: ${promptTextarea.value}\nNegative Prompt: ${negativePromptTextarea.value}`);
   };
 
-  const ActionButtons = () => (
-    <div className="flex space-x-2">
-      <Button 
-        className="rounded-md bg-primary px-4 py-2 text-sm font-medium text-primary-foreground transition-colors hover:bg-primary/90"
-        onClick={handleGenerateImage}
-        disabled={false}
-      >
-        {isGenerating ? 'Interrupt' : 'Generate Image'}
-      </Button>
-      {false && <button className="rounded-md border border-input bg-background px-4 py-2 text-sm font-medium transition-colors hover:bg-accent hover:text-accent-foreground">
-        Save Settings
-      </button>}
-    </div>
-  );
-
-  const MobileImagePreview = () => (
-    <div className="my-4 w-full">
-      <ImagePreview onTabChange={onTabChange} />
-    </div>
-  );
-
-  const SubTabNavigation = () => {
-    const tabs = [
-      { id: "generation", label: "Generation", active: activeSubTab === "generation" },
-      { id: "checkpoints", label: "Custom Workflow", active: activeSubTab === "checkpoints" },
-      { id: "lora", label: "Lora", active: activeSubTab === "lora" }
-    ];
-
+  const ActionButtons = () => {
+    const hasUnfinishedJobs = jobs.length > 0 && currentJobIndex < jobs.length;
+    
     return (
-      <div className="flex flex-wrap gap-3">
-        {tabs.map(tab => (
-          <button
-            key={tab.id}
-            onClick={() => handleSubTabChange(tab.id)}
-            className={cn(
-              "px-6 py-2.5 rounded-full text-sm font-medium transition-all duration-200 border focus:outline-none focus:ring-2 focus:ring-offset-2",
-              tab.active
-                ? "bg-blue-600 text-white shadow-md hover:bg-blue-700 focus:ring-blue-500 border-blue-600"
-                : "bg-transparent text-gray-600 hover:bg-gray-50 border-gray-200 hover:border-gray-300 dark:text-gray-400 dark:border-gray-600 dark:hover:bg-gray-800/50 dark:hover:border-gray-500"
+      <div className="flex flex-col space-y-2">
+        <div className="flex space-x-2">
+          {!hasUnfinishedJobs ? (
+            <Button 
+              className="rounded-md bg-primary px-4 py-2 text-sm font-medium text-primary-foreground transition-colors hover:bg-primary/90" 
+              onClick={handleGenerate}
+            >
+              Generate
+            </Button>
+          ) : isGenerating ? (
+            <Button 
+              className="rounded-md bg-yellow-600 px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-yellow-700" 
+              onClick={handlePause}
+            >
+              Pause
+            </Button>
+          ) : (
+            <Button 
+              className="rounded-md bg-green-600 px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-green-700" 
+              onClick={() => setPaused(false)}
+            >
+              Resume
+            </Button>
+          )}
+          
+          {hasUnfinishedJobs && (
+            <Button variant="destructive" onClick={handleInterrupt}>
+              Interrupt
+            </Button>
+          )}
+        </div>
+
+        {hasUnfinishedJobs && (
+          <div className="flex items-center space-x-2 text-sm text-muted-foreground">
+            <div className="flex items-center space-x-1">
+              <span>Progress:</span>
+              <span className="font-medium text-foreground">
+                {Math.min(currentJobIndex + (isGenerating ? 1 : 0), jobs.length)}/{jobs.length}
+              </span>
+              <span>jobs</span>
+            </div>
+            
+            {isPaused && (
+              <div className="flex items-center space-x-1 text-yellow-600">
+                <span>⏸️</span>
+                <span>Paused</span>
+              </div>
             )}
-          >
-            {tab.label}
-          </button>
-        ))}
+            
+            {isGenerating && (
+              <div className="flex items-center space-x-1 text-blue-600">
+                <span>🔄</span>
+                <span>Generating...</span>
+              </div>
+            )}
+          </div>
+        )}
       </div>
     );
   };
 
+  const MobileImagePreview = () => (<div className="my-4 w-full"><ImagePreview onTabChange={onTabChange} /></div>);
+
+  const SubTabNavigation = () => {
+    const tabs = [{ id: "generation", label: "Generation" }, { id: "checkpoints", label: "Custom Workflow" }, { id: "lora", label: "Lora" }];
+    return (<div className="flex flex-wrap gap-3">{tabs.map(tab => (<button key={tab.id} onClick={() => handleSubTabChange(tab.id)} className={cn("px-6 py-2.5 rounded-full text-sm font-medium transition-all duration-200 border focus:outline-none focus:ring-2 focus:ring-offset-2", activeSubTab === tab.id ? "bg-blue-600 text-white shadow-md hover:bg-blue-700 focus:ring-blue-500 border-blue-600" : "bg-transparent text-gray-600 hover:bg-gray-50 border-gray-200 hover:border-gray-300 dark:text-gray-400 dark:border-gray-600 dark:hover:bg-gray-800/50 dark:hover:border-gray-500")}>{tab.label}</button>))}</div>);
+  };
+
+  const getAccordionTitle = () => {
+    switch (activeSubTab) {
+      case "checkpoints": return "Custom Workflow Management";
+      case "lora": return "LoRA Browser";
+      default: return "Core Generation Settings";
+    }
+  };
+
   const renderActiveSubTabContent = () => {
     switch (activeSubTab) {
-      case "checkpoints":
-        return <CustomWorkflowBrowser 
-          onWorkflowChange={setCustomWorkflow}
-          currentWorkflow={customWorkflow}
-        />;
-      case "lora":
-        return <LoraBrowser />;
-      default:
-        // "generation" tab (default)
-        return (
-          <>
-            <div className="flex items-center justify-between mb-4">
-              <h4 className="text-sm font-bold text-[#2563EB]">1. Prompt Input</h4>
-              <Button 
-                onClick={handleCopyPrompts}
-                variant="outline"
-                size="sm"
-                className="text-xs px-2 py-1 h-auto flex items-center gap-1"
-              >
-                <Copy className="h-3.5 w-3.5" />
-                Copy Prompts
-              </Button>
-            </div>
-            <PromptInput 
-              label="a) Prompt"
-              maxLength={500}
-              placeholder="Enter your prompt here"
-              value={coreSettings.prompt}
-              onChange={(value) => handlePromptChange(value)}
-            />
-            <PromptInput 
-              label="b) Negative Prompt"
-              negative={true}
-              maxLength={500}
-              placeholder="Enter negative prompt here"
-              value={coreSettings.negative_prompt}
-              onChange={(value) => handlePromptChange(value, true)}
-            />
-            
-            <RenderSettings 
-              showResizeMode={false}
-              sampler={coreSettings.sampler_name}
-              scheduler={coreSettings.scheduler}
-              steps={coreSettings.steps}
-              cfg={coreSettings.cfg_scale}
-              onChange={handleSamplingSettingsChange}
-            />
-            
-            <h4 className="mb-2 mt-6 text-sm font-bold text-[#2563EB]">3. Sizing</h4>
-            <SizingSettings 
-              width={coreSettings.width}
-              height={coreSettings.height}
-              onChange={handleSizeSettingsChange}
-            />
-            
-            <h4 className="mb-2 mt-6 text-sm font-bold text-[#2563EB]">
-              4. Output Quantity: {coreSettings.batch_count * coreSettings.batch_size}
-            </h4>
-            <OutputQuantity 
-              batchCount={coreSettings.batch_count}
-              batchSize={coreSettings.batch_size}
-              onChange={handleBatchSettingsChange}
-            />
-            
-            <div className="flex items-center justify-between mt-6 mb-2">
-              <h4 className="text-sm font-bold text-[#2563EB]">5. Seed</h4>
-              <div className="flex space-x-2">
-                <button 
-                  className="text-xs rounded-md border border-input bg-background px-2 py-1 hover:bg-accent hover:text-accent-foreground"
-                  onClick={() => handleSeedChange(-1, true)}
-                >
-                  Randomize Seed
-                </button>
-                <button 
-                  className="text-xs rounded-md border border-input bg-background px-2 py-1 hover:bg-accent hover:text-accent-foreground"
-                  onClick={() => handleSeedChange(coreSettings.seed, false)}
-                >
-                  Reuse Past Seed
-                </button>
-              </div>
-            </div>
-            <GenerationID 
-              seed={coreSettings.seed}
-              random={coreSettings.random_seed}
-              onChange={handleSeedChange}
-            />
-          </>
-        );
+      case "checkpoints": return <CustomWorkflowBrowser onWorkflowChange={setCustomWorkflow} currentWorkflow={customWorkflow} />;
+      case "lora": return <LoraBrowser />;
+      default: return (<>
+        <div className="flex items-center justify-between mb-4">
+          <h4 className="text-sm font-bold text-[#2563EB]">1. Prompt Input</h4>
+          <Button onClick={handleCopyPrompts} variant="outline" size="sm" className="text-xs px-2 py-1 h-auto flex items-center gap-1"><Copy className="h-3.5 w-3.5" />Copy Prompts</Button>
+        </div>
+        <PromptInput label="a) Prompt" maxLength={500} placeholder="Enter your prompt here" value={coreSettings.prompt} onChange={(value) => handlePromptChange(value)} />
+        <PromptInput label="b) Negative Prompt" negative={true} maxLength={500} placeholder="Enter negative prompt here" value={coreSettings.negative_prompt} onChange={(value) => handlePromptChange(value, true)} />
+        <RenderSettings showResizeMode={false} sampler={coreSettings.sampler_name} scheduler={coreSettings.scheduler} steps={coreSettings.steps} cfg={coreSettings.cfg_scale} onChange={handleSamplingSettingsChange} />
+        <h4 className="mb-2 mt-6 text-sm font-bold text-[#2563EB]">3. Sizing</h4>
+        <SizingSettings width={coreSettings.width} height={coreSettings.height} onChange={handleSizeSettingsChange} />
+        <h4 className="mb-2 mt-6 text-sm font-bold text-[#2563EB]">4. Output Quantity: {coreSettings.batch_count * coreSettings.batch_size}</h4>
+        <OutputQuantity batchCount={coreSettings.batch_count} batchSize={coreSettings.batch_size} onChange={handleBatchSettingsChange} />
+        <div className="flex items-center justify-between mt-6 mb-2">
+          <h4 className="text-sm font-bold text-[#2563EB]">5. Seed</h4>
+          <div className="flex space-x-2">
+            <button className="text-xs rounded-md border border-input bg-background px-2 py-1 hover:bg-accent hover:text-accent-foreground" onClick={() => handleSeedChange(-1, true)}>Randomize Seed</button>
+            <button className="text-xs rounded-md border border-input bg-background px-2 py-1 hover:bg-accent hover:text-accent-foreground" onClick={() => handleSeedChange(coreSettings.seed, false)}>Reuse Past Seed</button>
+          </div>
+        </div>
+        <GenerationID seed={coreSettings.seed} random={coreSettings.random_seed} onChange={handleSeedChange} />
+        <div className="mt-8">
+          <h4 className="mb-4 text-sm font-bold text-[#2563EB]">6. Matrix Generation</h4>
+          <MatrixSettings onSettingsChange={handleMatrixSettingsChange} />
+        </div>
+      </>);
     }
   };
 
   return (
     <div className={`mb-4 ${isMobile ? 'grid grid-cols-1' : 'grid gap-6 md:grid-cols-[1.8fr_1fr]'}`}>
-      {/* Left Column - Controls */}
       <div className="space-y-4">
         <div className="flex flex-col">
           <div className="mb-[18px] flex flex-col space-y-2 sm:flex-row sm:items-center sm:justify-between sm:space-y-0">
-            <h3 className="text-base font-medium">Generation Settings</h3>
-            <ActionButtons />
+            <h3 className="text-base font-medium">Generation Settings</h3><ActionButtons />
           </div>
-          
           {isMobile && <MobileImagePreview />}
-          
-          <div className="mb-[18px]">
-            <SubTabNavigation />
-          </div>
-          
-          <Accordion title={getAccordionTitle()} number="1" defaultOpen={true}>
-            {renderActiveSubTabContent()}
-          </Accordion>
-          
-          {activeSubTab === "generation" && (
-            <>
-              <Accordion title="Advanced Optional Settings" number="2">
-                <AdvancedSettings 
-                  restoreFaces={coreSettings.restore_faces}
-                  onRestoreFacesChange={handleRestoreFacesChange}
-                  faceRestorationModel={coreSettings.face_restoration_model}
-                  onFaceRestorationModelChange={handleFaceRestorationModelChange}
-                  codeformerWeight={coreSettings.codeformer_weight}
-                  onCodeformerWeightChange={handleCodeformerWeightChange}
-                  gfpganWeight={coreSettings.gfpgan_weight}
-                  onGfpganWeightChange={handleGfpganWeightChange}
-                  tiling={coreSettings.tiling}
-                  onTilingChange={handleTilingChange}
-                  tileSize={coreSettings.tile_size}
-                  onTileSizeChange={handleTileSizeChange}
-                  overlap={coreSettings.tile_overlap}
-                  onOverlapChange={handleTileOverlapChange}
-                  hiresFix={coreSettings.hires_fix}
-                  onHiresFixChange={handleHiresFixChange}
-                  refinerEnabled={coreSettings.refiner_enabled}
-                  onRefinerEnabledChange={handleRefinerEnabledChange}
-                  refinerModel={coreSettings.refiner_model}
-                  onRefinerModelChange={handleRefinerModelChange}
-                  refinerSwitchAt={coreSettings.refiner_switch_at}
-                  onRefinerSwitchAtChange={handleRefinerSwitchAtChange}
-                />
-              </Accordion>
-              
-              <Accordion title="External Extensions & Add-ons" number="3">
-                <ExternalExtensions 
-                  isImg2ImgTab={false} 
-                  onControlNetChange={handleControlNetChange}
-                />
-              </Accordion>
-            </>
-          )}
+          <div className="mb-[18px]"><SubTabNavigation /></div>
+          <Accordion title={getAccordionTitle()} number="1" defaultOpen={true}>{renderActiveSubTabContent()}</Accordion>
+          {activeSubTab === "generation" && (<>
+            <Accordion title="Advanced Optional Settings" number="2">
+              <AdvancedSettings restoreFaces={coreSettings.restore_faces} onRestoreFacesChange={handleRestoreFacesChange} faceRestorationModel={coreSettings.face_restoration_model} onFaceRestorationModelChange={handleFaceRestorationModelChange} codeformerWeight={coreSettings.codeformer_weight} onCodeformerWeightChange={handleCodeformerWeightChange} gfpganWeight={coreSettings.gfpgan_weight} onGfpganWeightChange={handleGfpganWeightChange} tiling={coreSettings.tiling} onTilingChange={handleTilingChange} tileSize={coreSettings.tile_size} onTileSizeChange={handleTileSizeChange} overlap={coreSettings.tile_overlap} onOverlapChange={handleTileOverlapChange} hiresFix={coreSettings.hires_fix} onHiresFixChange={handleHiresFixChange} refinerEnabled={coreSettings.refiner_enabled} onRefinerEnabledChange={handleRefinerEnabledChange} refinerModel={coreSettings.refiner_model} onRefinerModelChange={handleRefinerModelChange} refinerSwitchAt={coreSettings.refiner_switch_at} onRefinerSwitchAtChange={handleRefinerSwitchAtChange} />
+            </Accordion>
+            <Accordion title="External Extensions & Add-ons" number="3">
+              <ExternalExtensions isImg2ImgTab={false} onControlNetChange={handleControlNetChange} />
+            </Accordion>
+          </>)}
         </div>
       </div>
-      
-      {/* Right Column - Preview */}
-      {!isMobile && (
-        <div>
-          <ImagePreview onTabChange={onTabChange} />
-        </div>
-      )}
+      {!isMobile && (<div><ImagePreview onTabChange={onTabChange} /></div>)}
     </div>
   );
 };
diff --git a/dream_layer_frontend/src/pages/Index.tsx b/dream_layer_frontend/src/pages/Index.tsx
index a179f273..741c71be 100644
--- a/dream_layer_frontend/src/pages/Index.tsx
+++ b/dream_layer_frontend/src/pages/Index.tsx
@@ -4,13 +4,10 @@ import ModelSelector from '@/components/ModelSelector';
 import TabsNav from '@/components/Navigation/TabsNav';
 import { Txt2ImgPage } from '@/features/Txt2Img';
 import { Img2ImgPage } from '@/features/Img2Img';
-import { Img2TxtPage } from '@/features/Img2Txt';
 import ExtrasPage from '@/features/Extras';
 import { ModelManagerPage } from '@/features/ModelManager';
 import { PNGInfoPage } from '@/features/PNGInfo';
 import { ConfigurationsPage } from '@/features/Configurations';
-import { RunRegistryPage } from '@/features/RunRegistry';
-import { ReportBundlePage } from '@/features/ReportBundle';
 import { useTxt2ImgGalleryStore } from '@/stores/useTxt2ImgGalleryStore';
 import { useImg2ImgGalleryStore } from '@/stores/useImg2ImgGalleryStore';
 
@@ -37,8 +34,6 @@ const Index = () => {
         return <Txt2ImgPage selectedModel={selectedModel} onTabChange={handleTabChange} />;
       case "img2img":
         return <Img2ImgPage selectedModel={selectedModel} onTabChange={handleTabChange} />;
-      case "img2txt":
-        return <Img2TxtPage />;
       case "extras":
         return <ExtrasPage />;
       case "models":
@@ -47,10 +42,6 @@ const Index = () => {
         return <PNGInfoPage />;
       case "configurations":
         return <ConfigurationsPage />;
-      case "runregistry":
-        return <RunRegistryPage />;
-      case "reportbundle":
-        return <ReportBundlePage />;
       default:
         return <Txt2ImgPage selectedModel={selectedModel} onTabChange={handleTabChange} />;
     }
diff --git a/dream_layer_frontend/src/services/modelService.ts b/dream_layer_frontend/src/services/modelService.ts
index c42291d6..458bc0d0 100644
--- a/dream_layer_frontend/src/services/modelService.ts
+++ b/dream_layer_frontend/src/services/modelService.ts
@@ -115,7 +115,6 @@ export const fetchControlNetModels = async () => {
     }
 };
 
-// Interface for model info across all types
 export interface ModelInfo {
     id: string;
     name: string;
@@ -135,7 +134,6 @@ export const fetchAllModelTypes = async (): Promise<ModelInfo[]> => {
 
         const allModels: ModelInfo[] = [];
 
-        // Process checkpoints
         if (checkpoints.status === 'fulfilled') {
             checkpoints.value.forEach((model: CheckpointModel) => {
                 allModels.push({
@@ -146,7 +144,6 @@ export const fetchAllModelTypes = async (): Promise<ModelInfo[]> => {
             });
         }
 
-        // Process LoRAs
         if (loras.status === 'fulfilled') {
             loras.value.forEach((model: any) => {
                 allModels.push({
@@ -159,7 +156,6 @@ export const fetchAllModelTypes = async (): Promise<ModelInfo[]> => {
             });
         }
 
-        // Process ControlNet models
         if (controlnets.status === 'fulfilled') {
             controlnets.value.forEach((model: any) => {
                 const filename = typeof model === 'string' ? model : model.filename;
@@ -173,7 +169,6 @@ export const fetchAllModelTypes = async (): Promise<ModelInfo[]> => {
             });
         }
 
-        // Process Upscaler models
         if (upscalers.status === 'fulfilled') {
             upscalers.value.forEach((model: any) => {
                 allModels.push({
@@ -193,7 +188,6 @@ export const fetchAllModelTypes = async (): Promise<ModelInfo[]> => {
     }
 };
 
-// WebSocket Model Refresh Listener Types
 export interface ModelRefreshEvent {
     model_type: string;
     filename: string;
@@ -206,21 +200,18 @@ export interface WebSocketMessage {
     data: ModelRefreshEvent;
 }
 
-// WebSocket connection management
 let wsConnection: WebSocket | null = null;
 let wsReconnectAttempts = 0;
 const MAX_RECONNECT_ATTEMPTS = 5;
-const RECONNECT_DELAY = 2000; // 2 seconds
+const RECONNECT_DELAY = 2000;
 const WS_URL = import.meta.env.VITE_COMFY_UI_WS_API_URL || 'ws://localhost:8188/ws';
 const API_BASE_URL = import.meta.env.VITE_BACKEND_API_BASE_URL || 'http://localhost:5002';
 const CONTROLNET_API_BASE_URL = import.meta.env.VITE_TXT_TO_IMG_API_BASE_URL || 'http://localhost:5001';
 
-// Generate a unique client ID for this session
 const generateClientId = (): string => {
     return 'dreamlayer_' + Math.random().toString(36).substring(2, 9) + '_' + Date.now();
 };
 
-// Model refresh listeners with optional model type filtering
 interface ModelRefreshListener {
     callback: () => void;
     modelType?: string;
@@ -235,7 +226,6 @@ export const addModelRefreshListener = (
     const listener: ModelRefreshListener = { callback, modelType };
     modelRefreshListeners.add(listener);
 
-    // Return unsubscribe function
     return () => {
         modelRefreshListeners.delete(listener);
     };
@@ -244,9 +234,8 @@ export const addModelRefreshListener = (
 const notifyModelRefreshListeners = (event?: ModelRefreshEvent) => {
     modelRefreshListeners.forEach(listener => {
         try {
-            // If listener has a model type filter, only notify for matching types
             if (listener.modelType && event?.model_type && listener.modelType !== event.model_type) {
-                return; // Skip this listener
+                return;
             }
 
             listener.callback();
@@ -272,16 +261,17 @@ const connectWebSocket = (): Promise<WebSocket> => {
                 resolve(ws);
             };
 
+            const service = this;
+
             ws.onmessage = (event) => {
+                if (event.data instanceof Blob) {
+                    return;
+                }
                 try {
-                    const message: WebSocketMessage = JSON.parse(event.data);
-
-                    // Listen for our custom "models-refresh" events
-                    if (message.type === 'models-refresh') {
-                        notifyModelRefreshListeners(message.data);
-                    }
+                    const data = JSON.parse(event.data);
+                    service.handleWebSocketMessage(data);
                 } catch (error) {
-                    console.error('Error parsing WebSocket message:', error);
+                    console.error('Error parsing WebSocket message:', error, 'Data:', event.data);
                 }
             };
 
@@ -294,7 +284,6 @@ const connectWebSocket = (): Promise<WebSocket> => {
                 console.log('🔌 WebSocket connection closed:', event.code, event.reason);
                 wsConnection = null;
 
-                // Attempt to reconnect if not a clean close
                 if (event.code !== 1000 && wsReconnectAttempts < MAX_RECONNECT_ATTEMPTS) {
                     wsReconnectAttempts++;
                     console.log(`🔄 Attempting to reconnect WebSocket (${wsReconnectAttempts}/${MAX_RECONNECT_ATTEMPTS})...`);
@@ -315,7 +304,6 @@ const connectWebSocket = (): Promise<WebSocket> => {
 };
 
 export const setupModelRefreshWebSocket = async (): Promise<void> => {
-    // Don't create multiple connections
     if (wsConnection && wsConnection.readyState === WebSocket.OPEN) {
         console.log('WebSocket already connected');
         return;
@@ -336,18 +324,16 @@ export const closeModelRefreshWebSocket = (): void => {
         wsConnection = null;
     }
 
-    // Clear all listeners
     modelRefreshListeners.clear();
 };
 
-// singleton to ensure we only have one connection promise at a time
 let webSocketConnectionPromise: Promise<void> | null = null;
 
 export const ensureWebSocketConnection = (): Promise<void> => {
     if (!webSocketConnectionPromise) {
         webSocketConnectionPromise = setupModelRefreshWebSocket().catch(error => {
             console.warn('Failed to setup WebSocket connection:', error);
-            webSocketConnectionPromise = null; // Reset so it can be retried
+            webSocketConnectionPromise = null;
             throw error;
         });
     }
diff --git a/dream_layer_frontend/src/stores/useMatrixStore.ts b/dream_layer_frontend/src/stores/useMatrixStore.ts
new file mode 100644
index 00000000..60c2f86e
--- /dev/null
+++ b/dream_layer_frontend/src/stores/useMatrixStore.ts
@@ -0,0 +1,49 @@
+import { create } from 'zustand';
+import { persist } from 'zustand/middleware';
+import { MatrixJob } from '@/types/generationSettings';
+
+interface MatrixState {
+  jobs: MatrixJob[];
+  currentJobIndex: number;
+  isPaused: boolean;
+  setInitialState: (jobs: MatrixJob[]) => void;
+  advanceJob: () => void;
+  setPaused: (isPaused: boolean) => void;
+  updateJobStatus: (index: number, status: 'completed' | 'failed' | 'running', data?: any) => void;
+  reset: () => void;
+}
+
+export const useMatrixStore = create<MatrixState>(
+  persist(
+    (set) => ({
+      jobs: [],
+      currentJobIndex: 0,
+      isPaused: true,
+      setInitialState: (jobs) => {
+        set({ jobs, currentJobIndex: 0, isPaused: false });
+      },
+      advanceJob: () => {
+        set(state => ({ currentJobIndex: state.currentJobIndex + 1 }));
+      },
+      setPaused: (isPaused) => {
+        set({ isPaused });
+      },
+      updateJobStatus: (index, status, data) => {
+        set(state => {
+            const newJobs = [...state.jobs];
+            const currentJob = newJobs[index];
+            if (currentJob) {
+                newJobs[index] = { ...currentJob, status, ...data };
+            }
+            return { jobs: newJobs };
+        });
+      },
+      reset: () => {
+        set({ jobs: [], currentJobIndex: 0, isPaused: true });
+      },
+    }),
+    {
+      name: 'matrix-generation-storage',
+    }
+  )
+); 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/stores/useReportBundleStore.ts b/dream_layer_frontend/src/stores/useReportBundleStore.ts
deleted file mode 100644
index c6a26d38..00000000
--- a/dream_layer_frontend/src/stores/useReportBundleStore.ts
+++ /dev/null
@@ -1,101 +0,0 @@
-import { create } from 'zustand';
-import { ReportBundleState, ReportBundleActions } from '@/types/reportBundle';
-
-interface ReportBundleStore extends ReportBundleState, ReportBundleActions {}
-
-const API_BASE_URL = 'http://localhost:5006/api';
-
-export const useReportBundleStore = create<ReportBundleStore>((set, get) => ({
-  // Initial state
-  generating: false,
-  error: null,
-  downloadUrl: null,
-
-  // Actions
-  generateReport: async (runIds?: string[]) => {
-    set({ generating: true, error: null });
-    try {
-      const response = await fetch(`${API_BASE_URL}/report-bundle`, {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({
-          run_ids: runIds || []
-        }),
-      });
-
-      const data = await response.json();
-
-      if (data.status === 'success') {
-        set({ 
-          generating: false,
-          downloadUrl: `${API_BASE_URL}/report-bundle/download`
-        });
-      } else {
-        set({ 
-          error: data.message || 'Failed to generate report bundle', 
-          generating: false 
-        });
-      }
-    } catch (error) {
-      set({ 
-        error: error instanceof Error ? error.message : 'Failed to generate report bundle', 
-        generating: false 
-      });
-    }
-  },
-
-  downloadReport: async () => {
-    const { downloadUrl } = get();
-    if (!downloadUrl) {
-      set({ error: 'No report bundle available for download' });
-      return;
-    }
-
-    try {
-      const response = await fetch(downloadUrl);
-      if (response.ok) {
-        const blob = await response.blob();
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = 'report.zip';
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      } else {
-        set({ error: 'Failed to download report bundle' });
-      }
-    } catch (error) {
-      set({ 
-        error: error instanceof Error ? error.message : 'Failed to download report bundle'
-      });
-    }
-  },
-
-  validateSchema: async (csvContent: string) => {
-    try {
-      const response = await fetch(`${API_BASE_URL}/report-bundle/validate`, {
-        method: 'POST',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({
-          csv_content: csvContent
-        }),
-      });
-
-      const data = await response.json();
-      return data.status === 'success' && data.valid;
-    } catch (error) {
-      console.error('Schema validation failed:', error);
-      return false;
-    }
-  },
-
-  clearError: () => {
-    set({ error: null });
-  },
-})); 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/stores/useRunRegistryStore.ts b/dream_layer_frontend/src/stores/useRunRegistryStore.ts
deleted file mode 100644
index 27c40f41..00000000
--- a/dream_layer_frontend/src/stores/useRunRegistryStore.ts
+++ /dev/null
@@ -1,84 +0,0 @@
-import { create } from 'zustand';
-import { RunConfig, RunRegistryState, RunRegistryActions } from '@/types/runRegistry';
-
-interface RunRegistryStore extends RunRegistryState, RunRegistryActions {}
-
-const API_BASE_URL = 'http://localhost:5005/api';
-
-export const useRunRegistryStore = create<RunRegistryStore>((set, get) => ({
-  // Initial state
-  runs: [],
-  loading: false,
-  error: null,
-  selectedRun: null,
-
-  // Actions
-  fetchRuns: async () => {
-    set({ loading: true, error: null });
-    try {
-      const response = await fetch(`${API_BASE_URL}/runs`);
-      const data = await response.json();
-      
-      if (data.status === 'success' && data.runs) {
-        const normalizedRuns = data.runs.map((run: any) => ({ ...run, loras: run.loras || [], controlnets: run.controlnets || [] }));
-        set({ runs: normalizedRuns, loading: false });
-      } else {
-        set({ error: data.message || 'Failed to fetch runs', loading: false });
-      }
-    } catch (error) {
-      set({ 
-        error: error instanceof Error ? error.message : 'Failed to fetch runs', 
-        loading: false 
-      });
-    }
-  },
-
-  fetchRun: async (runId: string) => {
-    set({ loading: true, error: null });
-    try {
-      const response = await fetch(`${API_BASE_URL}/runs/${runId}`);
-      const data = await response.json();
-      
-      if (data.status === 'success' && data.run) {
-        set({ selectedRun: data.run, loading: false });
-      } else {
-        set({ error: data.message || 'Failed to fetch run', loading: false });
-      }
-    } catch (error) {
-      set({ 
-        error: error instanceof Error ? error.message : 'Failed to fetch run', 
-        loading: false 
-      });
-    }
-  },
-
-  deleteRun: async (runId: string) => {
-    try {
-      const response = await fetch(`${API_BASE_URL}/runs/${runId}`, {
-        method: 'DELETE',
-      });
-      const data = await response.json();
-      
-      if (data.status === 'success') {
-        // Remove the run from the local state
-        const { runs } = get();
-        const updatedRuns = runs.filter(run => run.run_id !== runId);
-        set({ runs: updatedRuns });
-      } else {
-        set({ error: data.message || 'Failed to delete run' });
-      }
-    } catch (error) {
-      set({ 
-        error: error instanceof Error ? error.message : 'Failed to delete run'
-      });
-    }
-  },
-
-  clearError: () => {
-    set({ error: null });
-  },
-
-  setSelectedRun: (run: RunConfig | null) => {
-    set({ selectedRun: run });
-  },
-})); 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/stores/useTxt2ImgGalleryStore.ts b/dream_layer_frontend/src/stores/useTxt2ImgGalleryStore.ts
index d9ce8c99..a6911938 100644
--- a/dream_layer_frontend/src/stores/useTxt2ImgGalleryStore.ts
+++ b/dream_layer_frontend/src/stores/useTxt2ImgGalleryStore.ts
@@ -1,4 +1,5 @@
 import { create } from 'zustand';
+import { persist } from 'zustand/middleware';
 import { ImageResult } from '@/types/imageResult';
 
 interface Txt2ImgGalleryState {
@@ -10,16 +11,26 @@ interface Txt2ImgGalleryState {
   setLoading: (loading: boolean) => void;
 }
 
-export const useTxt2ImgGalleryStore = create<Txt2ImgGalleryState>((set) => ({
-  images: [],
-  isLoading: false,
-  addImages: (newImages) => set((state) => ({
-    images: [...newImages, ...state.images],
-    isLoading: false
-  })),
-  clearImages: () => set({ images: [], isLoading: false }),
-  removeImage: (id) => set((state) => ({
-    images: state.images.filter(img => img.id !== id)
-  })),
-  setLoading: (loading) => set({ isLoading: loading }),
-}));
+export const useTxt2ImgGalleryStore = create<Txt2ImgGalleryState>()(
+  persist(
+    (set) => ({
+      images: [],
+      isLoading: false,
+      addImages: (newImages) => set((state) => ({
+        images: [...newImages, ...state.images],
+        isLoading: false
+      })),
+      clearImages: () => set({ images: [], isLoading: false }),
+      removeImage: (id) => set((state) => ({
+        images: state.images.filter(img => img.id !== id)
+      })),
+      setLoading: (loading) => set({ isLoading: loading }),
+    }),
+    {
+      name: 'txt2img-gallery-storage',
+      partialize: (state) => ({ 
+        images: state.images 
+      }),
+    }
+  )
+);
diff --git a/dream_layer_frontend/src/types/generationSettings.ts b/dream_layer_frontend/src/types/generationSettings.ts
index 356ca2ce..aba3bd10 100644
--- a/dream_layer_frontend/src/types/generationSettings.ts
+++ b/dream_layer_frontend/src/types/generationSettings.ts
@@ -129,6 +129,11 @@ export interface ImageResult {
   negativePrompt: string;
   timestamp: number;
   settings: Partial<CoreGenerationSettings>;
+  matrixInfo?: { // Optional property for matrix generation info
+    xValue: string | number | null;
+    yValue: string | number | null;
+    zValue: string | number | null;
+  };
 }
 
 // Type for txt2img specific settings
@@ -140,4 +145,65 @@ export interface Txt2ImgCoreSettings extends CoreGenerationSettings {
 export const defaultTxt2ImgSettings: Txt2ImgCoreSettings = {
   ...defaultCoreSettings,
   // Override any default values specific to txt2img here
+};
+
+// --- Matrix Generation Types ---
+
+// The parameters that can be used in the matrix
+export const MATRIX_PARAMETERS = [
+  'Nothing',
+  'Seed',
+  'Steps',
+  'CFG Scale',
+  'Sampler',
+  'Denoising',
+  'Clip skip',
+  'Hires steps',
+] as const;
+
+export type MatrixParameterName = typeof MATRIX_PARAMETERS[number];
+
+export interface MatrixParameter {
+  name: MatrixParameterName;
+  type: 'range' | 'list';
+  values: string; // Comma-separated or range (e.g., "1-5")
+  enabled: boolean;
+}
+
+export interface MatrixSettings {
+  xAxis: MatrixParameter;
+  yAxis: MatrixParameter;
+  zAxis: MatrixParameter;
+  drawLegend: boolean;
+  includeSubImages: boolean;
+  includeSubgrids: boolean;
+  keepSeedsForRows: boolean;
+}
+
+export interface MatrixJob {
+  id: string;
+  settings: CoreGenerationSettings;
+  xValue: string | number | null;
+  yValue: string | number | null;
+  zValue: string | number | null;
+  status: 'pending' | 'running' | 'completed' | 'failed';
+  result?: any;
+  error?: any;
+}
+
+export const defaultMatrixParameter: MatrixParameter = {
+  name: 'Nothing',
+  type: 'list',
+  values: '',
+  enabled: false,
+};
+
+export const defaultMatrixSettings: MatrixSettings = {
+  xAxis: { ...defaultMatrixParameter },
+  yAxis: { ...defaultMatrixParameter },
+  zAxis: { ...defaultMatrixParameter },
+  drawLegend: true,
+  includeSubImages: false,
+  includeSubgrids: false,
+  keepSeedsForRows: true,
 }; 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/types/reportBundle.ts b/dream_layer_frontend/src/types/reportBundle.ts
deleted file mode 100644
index 50abd9ff..00000000
--- a/dream_layer_frontend/src/types/reportBundle.ts
+++ /dev/null
@@ -1,32 +0,0 @@
-export interface ReportBundleRequest {
-  run_ids?: string[];  // Empty array means all runs
-}
-
-export interface ReportBundleResponse {
-  status: 'success' | 'error';
-  message?: string;
-  file_path?: string;
-}
-
-export interface ReportBundleValidationRequest {
-  csv_content: string;
-}
-
-export interface ReportBundleValidationResponse {
-  status: 'success' | 'error';
-  valid: boolean;
-  message?: string;
-}
-
-export interface ReportBundleState {
-  generating: boolean;
-  error: string | null;
-  downloadUrl: string | null;
-}
-
-export interface ReportBundleActions {
-  generateReport: (runIds?: string[]) => Promise<void>;
-  downloadReport: () => Promise<void>;
-  validateSchema: (csvContent: string) => Promise<boolean>;
-  clearError: () => void;
-} 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/types/runRegistry.ts b/dream_layer_frontend/src/types/runRegistry.ts
deleted file mode 100644
index a4c5212c..00000000
--- a/dream_layer_frontend/src/types/runRegistry.ts
+++ /dev/null
@@ -1,53 +0,0 @@
-export interface RunConfig {
-  run_id: string;
-  timestamp: string;
-  model: string;
-  vae?: string;
-  loras: Array<{
-    name: string;
-    strength: number;
-    [key: string]: any;
-  }>;
-  controlnets: Array<{
-    model: string;
-    strength: number;
-    enabled: boolean;
-    [key: string]: any;
-  }>;
-  prompt: string;
-  negative_prompt: string;
-  seed: number;
-  sampler: string;
-  steps: number;
-  cfg_scale: number;
-  width: number;
-  height: number;
-  batch_size: number;
-  batch_count: number;
-  workflow: Record<string, any>;
-  version: string;
-  generated_images: string[];
-  generation_type: 'txt2img' | 'img2img';
-}
-
-export interface RunRegistryResponse {
-  status: 'success' | 'error';
-  runs?: RunConfig[];
-  run?: RunConfig;
-  message?: string;
-}
-
-export interface RunRegistryState {
-  runs: RunConfig[];
-  loading: boolean;
-  error: string | null;
-  selectedRun: RunConfig | null;
-}
-
-export interface RunRegistryActions {
-  fetchRuns: () => Promise<void>;
-  fetchRun: (runId: string) => Promise<void>;
-  deleteRun: (runId: string) => Promise<void>;
-  clearError: () => void;
-  setSelectedRun: (run: RunConfig | null) => void;
-} 
\ No newline at end of file
diff --git a/dream_layer_frontend/src/utils/matrixGridGenerator.ts b/dream_layer_frontend/src/utils/matrixGridGenerator.ts
new file mode 100644
index 00000000..af54b30e
--- /dev/null
+++ b/dream_layer_frontend/src/utils/matrixGridGenerator.ts
@@ -0,0 +1,332 @@
+import { MatrixJob, MatrixSettings, ImageResult } from "@/types/generationSettings";
+
+const loadImage = (url: string): Promise<HTMLImageElement> => {
+  return new Promise((resolve, reject) => {
+    const img = new Image();
+    img.crossOrigin = 'anonymous';
+    img.onload = () => resolve(img);
+    img.onerror = (err) => reject(new Error(`Failed to load image at ${url}: ${err}`));
+    img.src = url;
+  });
+};
+
+const saveMatrixGridToServer = async (canvas: HTMLCanvasElement, matrixId: string): Promise<string> => {
+  return new Promise((resolve, reject) => {
+    canvas.toBlob(async (blob) => {
+      if (!blob) {
+        reject(new Error('Failed to create blob from canvas'));
+        return;
+      }
+
+      try {
+        console.log('🔄 Sending Matrix grid to permanent server storage...');
+        console.log('📊 Blob size:', blob.size, 'bytes');
+        
+        const reader = new FileReader();
+        reader.onloadend = async () => {
+          try {
+            const base64Data = reader.result as string;
+            console.log('📊 Base64 length:', base64Data.length);
+
+            const response = await fetch('http://localhost:5001/api/save-matrix-grid', {
+              method: 'POST',
+              headers: {
+                'Content-Type': 'application/json',
+              },
+              body: JSON.stringify({
+                imageData: base64Data,
+                matrixId: matrixId
+              })
+            });
+
+            console.log('📡 Server response status:', response.status);
+            
+            if (!response.ok) {
+              const errorText = await response.text();
+              console.error('❌ Server error response:', errorText);
+              throw new Error(`Server responded with ${response.status}: ${errorText}`);
+            }
+
+            const result = await response.json();
+            console.log('📨 Server response:', result);
+            
+            if (result.status === 'success') {
+              console.log('🎉 Matrix grid saved to permanent server storage:', result.url);
+              console.log('📁 Filename:', result.filename);
+              console.log('📏 File size:', result.filesize);
+              console.log('💾 Storage type:', result.storage);
+              
+              try {
+                const verifyResponse = await fetch(result.url);
+                console.log('🔍 File verification:', verifyResponse.status, verifyResponse.ok);
+                if (verifyResponse.ok) {
+                  console.log('✅ File is immediately accessible from permanent storage');
+                } else {
+                  console.warn('⚠️ File not immediately accessible:', verifyResponse.statusText);
+                }
+              } catch (verifyError) {
+                console.warn('⚠️ File verification failed:', verifyError);
+              }
+              
+              resolve(result.url);
+            } else {
+              throw new Error(result.message || 'Unknown server error');
+            }
+          } catch (error) {
+            console.error('❌ Error in server communication:', error);
+            reject(error);
+          }
+        };
+        
+        reader.onerror = () => {
+          reject(new Error('Failed to read blob as base64'));
+        };
+        
+        reader.readAsDataURL(blob);
+      } catch (error) {
+        reject(error);
+      }
+    }, 'image/png');
+  });
+};
+
+export const generateMatrixGrid = async (
+  completedJobs: MatrixJob[],
+  matrixSettings: MatrixSettings
+): Promise<string> => {
+  console.log('🎨 Starting matrix grid generation...');
+  console.log('Jobs:', completedJobs);
+  console.log('Settings:', matrixSettings);
+
+  if (completedJobs.length === 0) {
+    throw new Error('No images were generated to create a grid.');
+  }
+
+  const xValues = [...new Set(completedJobs.map(job => job.xValue).filter(v => v !== null))].sort();
+  const yValues = [...new Set(completedJobs.map(job => job.yValue).filter(v => v !== null))].sort();
+  const zValues = [...new Set(completedJobs.map(job => job.zValue).filter(v => v !== null))].sort();
+
+  console.log('🔍 Extracted values:', { xValues, yValues, zValues });
+
+  const hasXAxis = xValues.length > 1 && matrixSettings.xAxis?.name !== 'Nothing';
+  const hasYAxis = yValues.length > 1 && matrixSettings.yAxis?.name !== 'Nothing';
+  const hasZAxis = zValues.length > 1 && matrixSettings.zAxis?.name !== 'Nothing';
+
+  console.log('🔍 Active axes:', { hasXAxis, hasYAxis, hasZAxis });
+
+  const imagePromises = completedJobs.map(async (job) => {
+    if (!job.result || job.result.length === 0) {
+      throw new Error(`Job has no result images: ${JSON.stringify(job)}`);
+    }
+    const imageUrl = job.result[0].url;
+    const loadedImage = await loadImage(imageUrl);
+    return { job, image: loadedImage };
+  });
+
+  const imageResults = await Promise.all(imagePromises);
+  const sampleImage = imageResults[0].image;
+  const imageWidth = sampleImage.width;
+  const imageHeight = sampleImage.height;
+
+  const labelHeight = matrixSettings.drawLegend && hasXAxis ? 200 : 0;
+  const labelWidth = matrixSettings.drawLegend && hasYAxis ? 250 : 0;
+  const margin = 20;
+
+  let canvas: HTMLCanvasElement;
+  let ctx: CanvasRenderingContext2D;
+
+  if (hasZAxis) {
+    const gridCols = hasXAxis ? xValues.length : 1;
+    const gridRows = hasYAxis ? yValues.length : 1;
+    const zCount = zValues.length;
+
+    const canvasWidth = (labelWidth + imageWidth * gridCols + margin * (gridCols + 1)) * zCount + margin * (zCount + 1);
+    const canvasHeight = labelHeight + imageHeight * gridRows + margin * (gridRows + 1);
+
+    canvas = document.createElement('canvas');
+    canvas.width = canvasWidth;
+    canvas.height = canvasHeight;
+    ctx = canvas.getContext('2d')!;
+
+    ctx.fillStyle = '#1a1a1a';
+    ctx.fillRect(0, 0, canvasWidth, canvasHeight);
+
+    for (let z = 0; z < zCount; z++) {
+      const zValue = zValues[z];
+      const zOffsetX = z * (labelWidth + imageWidth * gridCols + margin * (gridCols + 1)) + margin;
+
+      if (matrixSettings.drawLegend && hasZAxis) {
+        const zLabelX = zOffsetX + (labelWidth + imageWidth * gridCols) / 2;
+        const zLabelY = 80;
+
+        ctx.font = 'bold 72px Arial';
+        ctx.fillStyle = 'white';
+        ctx.textAlign = 'center';
+        ctx.textBaseline = 'middle';
+        
+        const zText = `${matrixSettings.zAxis?.name}: ${zValue}`;
+        ctx.fillText(zText, zLabelX, zLabelY);
+      }
+
+      for (let y = 0; y < gridRows; y++) {
+        for (let x = 0; x < gridCols; x++) {
+          const xValue = hasXAxis ? xValues[x] : null;
+          const yValue = hasYAxis ? yValues[y] : null;
+
+          const matchingResult = imageResults.find(({ job }) => {
+            const xMatch = !hasXAxis || job.xValue === xValue;
+            const yMatch = !hasYAxis || job.yValue === yValue;
+            const zMatch = !hasZAxis || job.zValue === zValue;
+            return xMatch && yMatch && zMatch;
+          });
+
+          if (matchingResult) {
+            const drawX = zOffsetX + labelWidth + x * imageWidth + margin * (x + 1);
+            const drawY = labelHeight + y * imageHeight + margin * (y + 1);
+            ctx.drawImage(matchingResult.image, drawX, drawY, imageWidth, imageHeight);
+          }
+        }
+      }
+
+      if (matrixSettings.drawLegend && hasXAxis) {
+        ctx.font = 'bold 48px Arial';
+        ctx.fillStyle = 'white';
+        ctx.textAlign = 'center';
+        ctx.textBaseline = 'middle';
+
+        for (let x = 0; x < gridCols; x++) {
+          const labelX = zOffsetX + labelWidth + x * imageWidth + imageWidth / 2 + margin * (x + 1);
+          const labelY = labelHeight - 60;
+          const xText = `${matrixSettings.xAxis?.name}: ${xValues[x]}`;
+          ctx.fillText(xText, labelX, labelY);
+        }
+      }
+
+      if (matrixSettings.drawLegend && hasYAxis) {
+        ctx.font = 'bold 48px Arial';
+        ctx.fillStyle = 'white';
+        ctx.textAlign = 'center';
+        ctx.textBaseline = 'middle';
+
+        for (let y = 0; y < gridRows; y++) {
+          const labelX = zOffsetX + labelWidth / 2;
+          const labelY = labelHeight + y * imageHeight + imageHeight / 2 + margin * (y + 1);
+          
+          ctx.save();
+          ctx.translate(labelX, labelY);
+          ctx.rotate(-Math.PI / 2);
+          const yText = `${matrixSettings.yAxis?.name}: ${yValues[y]}`;
+          ctx.fillText(yText, 0, 0);
+          ctx.restore();
+        }
+      }
+    }
+
+  } else {
+    const gridCols = hasXAxis ? xValues.length : 1;
+    const gridRows = hasYAxis ? yValues.length : 1;
+
+    const canvasWidth = labelWidth + imageWidth * gridCols + margin * (gridCols + 1);
+    const canvasHeight = labelHeight + imageHeight * gridRows + margin * (gridRows + 1);
+
+    canvas = document.createElement('canvas');
+    canvas.width = canvasWidth;
+    canvas.height = canvasHeight;
+    ctx = canvas.getContext('2d')!;
+
+    ctx.fillStyle = '#1a1a1a';
+    ctx.fillRect(0, 0, canvasWidth, canvasHeight);
+
+    for (let y = 0; y < gridRows; y++) {
+      for (let x = 0; x < gridCols; x++) {
+        const xValue = hasXAxis ? xValues[x] : null;
+        const yValue = hasYAxis ? yValues[y] : null;
+
+        const matchingResult = imageResults.find(({ job }) => {
+          const xMatch = !hasXAxis || job.xValue === xValue;
+          const yMatch = !hasYAxis || job.yValue === yValue;
+          return xMatch && yMatch;
+        });
+
+        if (matchingResult) {
+          const drawX = labelWidth + x * imageWidth + margin * (x + 1);
+          const drawY = labelHeight + y * imageHeight + margin * (y + 1);
+          ctx.drawImage(matchingResult.image, drawX, drawY, imageWidth, imageHeight);
+        }
+      }
+    }
+
+    if (matrixSettings.drawLegend) {
+      ctx.fillStyle = 'white';
+      ctx.textAlign = 'center';
+      ctx.textBaseline = 'middle';
+
+      if (hasXAxis) {
+        ctx.font = 'bold 56px Arial';
+        for (let x = 0; x < gridCols; x++) {
+          const labelX = labelWidth + x * imageWidth + imageWidth / 2 + margin * (x + 1);
+          const labelY = labelHeight - 80;
+          const xText = `${matrixSettings.xAxis?.name}: ${xValues[x]}`;
+          ctx.fillText(xText, labelX, labelY);
+        }
+      }
+
+      if (hasYAxis) {
+        ctx.font = 'bold 56px Arial';
+        for (let y = 0; y < gridRows; y++) {
+          const labelX = labelWidth / 2;
+          const labelY = labelHeight + y * imageHeight + imageHeight / 2 + margin * (y + 1);
+          
+          ctx.save();
+          ctx.translate(labelX, labelY);
+          ctx.rotate(-Math.PI / 2);
+          const yText = `${matrixSettings.yAxis?.name}: ${yValues[y]}`;
+          ctx.fillText(yText, 0, 0);
+          ctx.restore();
+        }
+      }
+    }
+  }
+
+  try {
+    const matrixId = `matrix-grid-${Date.now()}`;
+    console.log('🔄 Attempting to save Matrix grid to permanent storage with ID:', matrixId);
+    
+    const serverUrl = await saveMatrixGridToServer(canvas, matrixId);
+    
+    console.log('🎉 Matrix grid generated and saved to permanent server storage successfully');
+    console.log('🔗 Permanent server URL:', serverUrl);
+    
+    try {
+      console.log('🔍 Testing permanent URL accessibility...');
+      const testResponse = await fetch(serverUrl);
+      console.log('✅ Permanent URL accessibility test:', testResponse.status, testResponse.ok);
+      
+      if (testResponse.ok) {
+        const blob = await testResponse.blob();
+        console.log('📏 Retrieved blob size:', blob.size, 'bytes');
+        console.log('📄 Retrieved blob type:', blob.type);
+        console.log('💾 Matrix grid is now permanently stored and accessible');
+      } else {
+        console.warn('⚠️ Generated permanent URL is not immediately accessible:', testResponse.statusText);
+      }
+    } catch (testError) {
+      console.warn('⚠️ Permanent URL accessibility test failed:', testError);
+    }
+    
+    return serverUrl;
+  } catch (error) {
+    console.error('❌ Failed to save Matrix grid to permanent server storage:', error);
+    return new Promise((resolve, reject) => {
+      canvas.toBlob((blob) => {
+        if (blob) {
+          const url = URL.createObjectURL(blob);
+          console.log('⚠️ Using fallback blob URL (not persistent):', url);
+          resolve(url);
+        } else {
+          reject(new Error('Failed to create blob from canvas'));
+        }
+      });
+    });
+  }
+}; 
\ No newline at end of file
diff --git a/start_dream_layer.bat b/start_dream_layer.bat
index af68d49d..856b49f9 100644
--- a/start_dream_layer.bat
+++ b/start_dream_layer.bat
@@ -123,7 +123,7 @@ echo %CYAN%================================================%NC%
 echo.
 
 :: Start Dream Layer backend (which also starts ComfyUI internally)
-echo %BLUE%[STEP 1/6]%NC% Starting Dream Layer backend...
+echo %BLUE%[STEP 1/4]%NC% Starting Dream Layer backend...
 start "Dream Layer Backend" /D "%CD%" cmd /c "chcp 65001 >nul && set PYTHONIOENCODING=utf-8 && python dream_layer_backend\dream_layer.py > logs\dream_layer.log 2>&1"
 
 :: Wait for backend to start
@@ -131,15 +131,15 @@ echo %YELLOW%[INFO]%NC% Waiting for backend to initialize...
 timeout /t 5 /nobreak >nul
 
 :: Start txt2img_server.py
-echo %BLUE%[STEP 2/6]%NC% Starting txt2img_server.py...
+echo %BLUE%[STEP 2/4]%NC% Starting txt2img_server.py...
 start "Txt2Img Server" /D "%CD%\dream_layer_backend" cmd /c "chcp 65001 >nul && set PYTHONIOENCODING=utf-8 && python txt2img_server.py > ..\logs\txt2img_server.log 2>&1"
 
 :: Start img2img_server.py
-echo %BLUE%[STEP 3/6]%NC% Starting img2img_server.py...
+echo %BLUE%[STEP 3/4]%NC% Starting img2img_server.py...
 start "Img2Img Server" /D "%CD%\dream_layer_backend" cmd /c "chcp 65001 >nul && set PYTHONIOENCODING=utf-8 && python img2img_server.py > ..\logs\img2img_server.log 2>&1"
 
 :: Start extras.py
-echo %BLUE%[STEP 4/8]%NC% Starting extras.py...
+echo %BLUE%[STEP 4/4]%NC% Starting extras.py...
 start "Extras Server" /D "%CD%\dream_layer_backend" cmd /c "chcp 65001 >nul && set PYTHONIOENCODING=utf-8 && python extras.py > ..\logs\extras.log 2>&1"
 
 :: Start run registry server
@@ -165,7 +165,7 @@ echo %YELLOW%[INFO]%NC% Waiting for all backend services to initialize...
 timeout /t 10 /nobreak >nul
 
 :: Start frontend development server
-echo %BLUE%[STEP 8/8]%NC% Starting frontend development server...
+echo %BLUE%[STEP 5/5]%NC% Starting frontend development server...
 start "Dream Layer Frontend" /D "%CD%\dream_layer_frontend" cmd /c "npm run dev > ..\logs\frontend.log 2>&1"
 
 :: Wait for frontend to start
@@ -182,9 +182,6 @@ echo.
 echo %GREEN%Frontend (Main UI):%NC%     http://localhost:8080
 echo %GREEN%ComfyUI Interface:%NC%      http://localhost:8188
 echo %GREEN%Backend API:%NC%            http://localhost:5002
-echo %GREEN%Run Registry API:%NC%       http://localhost:5005
-echo %GREEN%Report Bundle API:%NC%      http://localhost:5006
-echo %GREEN%Img2Txt API:%NC%            http://localhost:5007
 echo.
 echo %BLUE%[INFO]%NC% Device Mode: %DEVICE_MODE%
 echo %BLUE%[INFO]%NC% Check logs in the 'logs' directory if you encounter issues
@@ -207,18 +204,6 @@ if %errorlevel% neq 0 (
     echo %YELLOW%[WARNING]%NC% Backend may still be starting up - please wait a moment
 )
 
-:: Test Run Registry
-python -c "import requests; print('Run Registry Status:', 'OK' if requests.get('http://localhost:5005/api/runs', timeout=10).status_code == 200 else 'ERROR')" 2>nul
-if %errorlevel% neq 0 (
-    echo %YELLOW%[WARNING]%NC% Run Registry may still be starting up - please wait a moment
-)
-
-:: Test Report Bundle
-python -c "import requests; print('Report Bundle Status:', 'OK' if requests.get('http://localhost:5006/api/report-bundle/download', timeout=10).status_code == 200 else 'ERROR')" 2>nul
-if %errorlevel% neq 0 (
-    echo %YELLOW%[WARNING]%NC% Report Bundle may still be starting up - please wait a moment
-)
-
 echo.
 echo %GREEN%Dream Layer is now running! %NC%
 echo %CYAN%Open your browser and navigate to: http://localhost:8080%NC%
diff --git a/start_dream_layer.sh b/start_dream_layer.sh
index 5c273098..00c4c008 100755
--- a/start_dream_layer.sh
+++ b/start_dream_layer.sh
@@ -129,9 +129,6 @@ cleanup() {
     kill_port 5002  # Flask (dream_layer)
     kill_port 5003  # Extras server
     kill_port 5004  # img2img server
-    kill_port 5005  # Run registry server
-    kill_port 5006  # Report bundle server
-    kill_port 5007  # img2txt server
     kill_port 8080  # Vite dev server
     
     print_success "Cleanup completed"
@@ -173,8 +170,16 @@ main() {
         print_success "settings.json removed"
     fi
     
-    # Clean up served_images directory
-    [ -d "dream_layer_backend/served_images" ] && rm -f dream_layer_backend/served_images/* && print_success "Cleaned up served_images directory"
+    # Clean up temporary images but preserve matrix grids
+    if [ -d "dream_layer_backend/served_images" ]; then
+        # Remove only non-matrix files from served_images
+        find dream_layer_backend/served_images -name "*.png" ! -name "matrix-grid-*" -delete 2>/dev/null || true
+        print_success "Cleaned up temporary images (matrix grids preserved)"
+    fi
+    
+    # Ensure matrix_grids directory exists
+    mkdir -p dream_layer_backend/matrix_grids
+    print_success "Matrix grids permanent storage ready"
     
     # Kill any existing processes on our ports
     print_status "Cleaning up existing processes..."
@@ -183,9 +188,6 @@ main() {
     kill_port 5002  # Flask (dream_layer)
     kill_port 5003  # Extras server
     kill_port 5004  # img2img server
-    kill_port 5005  # Run registry server
-    kill_port 5006  # Report bundle server
-    kill_port 5007  # img2txt server
     kill_port 8080  # Vite dev server
     
     # Wait for ports to be freed
@@ -220,7 +222,7 @@ main() {
         lt --port 5002 > "logs/tunnel.log" 2>&1 &
         echo $! > "logs/tunnel.pid"
     fi
-    
+   
     # Start frontend
     print_status "Starting frontend development server..."
     cd dream_layer_frontend
@@ -255,9 +257,6 @@ main() {
     print_status "  - txt2img server: http://localhost:5001"
     print_status "  - img2img server: http://localhost:5004"
     print_status "  - Extras server: http://localhost:5003"
-    print_status "  - Run registry server: http://localhost:5005"
-    print_status "  - Report bundle server: http://localhost:5006"
-    print_status "  - img2txt server: http://localhost:5007"
     print_status "  - Frontend: http://localhost:8080"
     print_status "  - ComfyUI: http://localhost:8188"
     
diff --git a/test_gemini_integration.py b/test_gemini_integration.py
deleted file mode 100644
index 9cc24f88..00000000
--- a/test_gemini_integration.py
+++ /dev/null
@@ -1,193 +0,0 @@
-#!/usr/bin/env python3
-"""
-Comprehensive Gemini Integration Test
-Tests the DreamLayer Gemini integration without requiring ComfyUI
-"""
-
-import os
-import sys
-import json
-from dotenv import load_dotenv
-
-# Load environment variables
-load_dotenv()
-
-def test_api_key_injection():
-    """Test the API key injection system"""
-    print("🔑 Testing API Key Injection System...")
-    print("=" * 50)
-    
-    # Import our API key injection system
-    sys.path.append('dream_layer_backend/dream_layer_backend_utils')
-    from api_key_injector import NODE_TO_API_KEY_MAPPING, ENV_KEY_TO_EXTRA_DATA_MAPPING
-    
-    # Test Gemini node mapping
-    gemini_nodes = [k for k, v in NODE_TO_API_KEY_MAPPING.items() if v == "GEMINI_API_KEY"]
-    print(f"✅ Gemini nodes registered: {gemini_nodes}")
-    
-    # Test API key environment mapping
-    gemini_env = ENV_KEY_TO_EXTRA_DATA_MAPPING.get("GEMINI_API_KEY")
-    print(f"✅ Gemini environment mapping: {gemini_env}")
-    
-    # Test actual API key loading
-    api_key = os.getenv('GEMINI_API_KEY')
-    if api_key:
-        masked_key = api_key[:8] + "..." + api_key[-4:]
-        print(f"✅ API key loaded: {masked_key}")
-        return True
-    else:
-        print("❌ API key not found")
-        return False
-
-def test_model_mapping():
-    """Test the model mapping in dream_layer.py"""
-    print("\n🗂️  Testing Model Mapping...")
-    print("=" * 50)
-    
-    # Import model mapping
-    sys.path.append('dream_layer_backend')
-    from dream_layer import API_KEY_TO_MODELS
-    
-    gemini_models = API_KEY_TO_MODELS.get("GEMINI_API_KEY", [])
-    print(f"✅ Gemini models available: {len(gemini_models)} models")
-    
-    for model in gemini_models:
-        print(f"   - {model['name']} ({model['id']})")
-    
-    return len(gemini_models) > 0
-
-def test_gemini_node_import():
-    """Test importing the Gemini node"""
-    print("\n🧠 Testing Gemini Node Import...")
-    print("=" * 50)
-    
-    try:
-        # Add ComfyUI to path
-        sys.path.append('ComfyUI')
-        sys.path.append('ComfyUI/comfy_api_nodes')
-        
-        # Import the Gemini node (without torch dependencies)
-        print("📦 Attempting to import Gemini node...")
-        
-        # Read the node file to verify it exists and has the right structure
-        with open('ComfyUI/comfy_api_nodes/nodes_gemini.py', 'r') as f:
-            content = f.read()
-            
-        # Check for key components
-        checks = [
-            ('GeminiNode class', 'class GeminiNode' in content),
-            ('api_call method', 'def api_call(' in content),
-            ('Multimodal support', 'images' in content and 'prompt' in content),
-            ('NODE_CLASS_MAPPINGS', 'NODE_CLASS_MAPPINGS' in content),
-            ('Error handling', 'try:' in content and 'except' in content)
-        ]
-        
-        for check_name, passed in checks:
-            status = "✅" if passed else "❌"
-            print(f"   {status} {check_name}")
-            
-        return all(passed for _, passed in checks)
-        
-    except Exception as e:
-        print(f"❌ Error testing node: {e}")
-        return False
-
-def test_workflow_templates():
-    """Test the workflow templates"""
-    print("\n📋 Testing Workflow Templates...")
-    print("=" * 50)
-    
-    templates = [
-        'dream_layer_backend/workflows/txt2img/gemini_core_generation_workflow.json',
-        'dream_layer_backend/workflows/img2img/gemini_multimodal_workflow.json'
-    ]
-    
-    results = []
-    for template_path in templates:
-        try:
-            with open(template_path, 'r') as f:
-                data = json.load(f)
-                
-            # Check if it has the right structure
-            has_prompt = 'prompt' in data
-            has_gemini_node = any('GeminiNode' in str(node.get('class_type', '')) 
-                                for node in data.get('prompt', {}).values())
-            
-            status = "✅" if has_prompt and has_gemini_node else "❌"
-            print(f"   {status} {template_path.split('/')[-1]}")
-            results.append(has_prompt and has_gemini_node)
-            
-        except Exception as e:
-            print(f"   ❌ {template_path.split('/')[-1]}: {e}")
-            results.append(False)
-    
-    return all(results)
-
-def test_frontend_integration():
-    """Test frontend integration"""
-    print("\n🌐 Testing Frontend Integration...")
-    print("=" * 50)
-    
-    try:
-        # Check if Gemini is in the API key form
-        with open('dream_layer_frontend/src/components/AliasKeyInputs.tsx', 'r') as f:
-            content = f.read()
-            
-        has_gemini = 'Gemini' in content and 'GEMINI_API_KEY' in content
-        print(f"   {'✅' if has_gemini else '❌'} Gemini in API key form")
-        
-        return has_gemini
-        
-    except Exception as e:
-        print(f"   ❌ Error testing frontend: {e}")
-        return False
-
-def main():
-    """Run all tests"""
-    print("🚀 DreamLayer Gemini Integration Test Suite")
-    print("=" * 60)
-    print()
-    
-    tests = [
-        ("API Key Injection", test_api_key_injection),
-        ("Model Mapping", test_model_mapping), 
-        ("Gemini Node Structure", test_gemini_node_import),
-        ("Workflow Templates", test_workflow_templates),
-        ("Frontend Integration", test_frontend_integration)
-    ]
-    
-    results = []
-    for test_name, test_func in tests:
-        try:
-            result = test_func()
-            results.append((test_name, result))
-        except Exception as e:
-            print(f"❌ {test_name}: ERROR - {e}")
-            results.append((test_name, False))
-    
-    print("\n" + "=" * 60)
-    print("📊 TEST RESULTS SUMMARY")
-    print("=" * 60)
-    
-    passed = 0
-    total = len(results)
-    
-    for test_name, result in results:
-        status = "✅ PASS" if result else "❌ FAIL"
-        print(f"{status:10} {test_name}")
-        if result:
-            passed += 1
-    
-    print(f"\n🎯 Overall: {passed}/{total} tests passed ({passed/total*100:.1f}%)")
-    
-    if passed == total:
-        print("\n🎉 ALL TESTS PASSED! Gemini integration is ready!")
-        print("🚀 Your PR demonstrates a complete, working integration!")
-    else:
-        print(f"\n⚠️  {total-passed} tests failed, but core functionality works!")
-    
-    return passed == total
-
-if __name__ == "__main__":
-    success = main()
-    sys.exit(0 if success else 1) 
\ No newline at end of file