v1.2.0

.github/workflows/ci.yml

@@ -1,33 +1,33 @@
 name: CI
 
 on:
-    push:
-        branches:
-            - dev
-    pull_request:
-        branches:
-            - main
+  push:
+    branches:
+      - dev
+  pull_request:
+    branches:
+      - main
 
 jobs:
-    build:
-        name: Build Check
-        runs-on: ubuntu-latest
-        steps:
-            - name: Checkout code
-              uses: actions/checkout@v4
+  build:
+    name: Build Check
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
 
-            - name: Setup Node.js
-              uses: actions/setup-node@v4
-              with:
-                  node-version: "20"
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "20"
 
-            - name: Install pnpm
-              uses: pnpm/action-setup@v2
-              with:
-                  version: 9
+      - name: Install pnpm
+        uses: pnpm/action-setup@v2
+        with:
+          version: 9
 
-            - name: Install dependencies
-              run: pnpm install
+      - name: Install dependencies
+        run: pnpm install
 
-            - name: Build frontend
-              run: pnpm build
+      - name: Build frontend
+        run: pnpm build

__init__.py

@@ -6,6 +6,11 @@
 
 from .nodes.EmbeddrUploadImage import EmbeddrSaveToFolderNode
 from .nodes.EmbeddrLoadImage import EmbeddrLoadImageNode
+from .nodes.EmbeddrLoadImages import EmbeddrLoadImagesNode
+from .nodes.EmbeddrMergeIDs import EmbeddrMergeIDsNode
+from .nodes.EmbeddrFindSimilar import EmbeddrFindSimilarNode
+from .nodes.EmbeddrFindSimilarText import EmbeddrFindSimilarTextNode
+from .nodes.EmbeddrUploadVideo import EmbeddrUploadVideo
 
 CONFIG_PATH = os.path.join(os.path.dirname(__file__), "config.json")
 
@@ -81,8 +86,13 @@ async def get_config(request):
 class EmbeddrComfyUIExtension(ComfyExtension):
     async def get_node_list(self) -> list[type[io.ComfyNode]]:
         return [
-            EmbeddrSaveToFolderNode,
+            EmbeddrFindSimilarNode,
+            EmbeddrFindSimilarTextNode,
             EmbeddrLoadImageNode,
+            EmbeddrLoadImagesNode,
+            EmbeddrMergeIDsNode,
+            EmbeddrSaveToFolderNode,
+            EmbeddrUploadVideo,
         ]
 
 

nodes/EmbeddrFindSimilar.py

@@ -0,0 +1,111 @@
+import requests
+import torch
+import numpy as np
+from PIL import Image
+import io as pyio
+from comfy_api.latest import io, ui
+from .utils import get_config
+from .utils.api import get_libraries, get_collections
+
+
+class EmbeddrFindSimilarNode(io.ComfyNode):
+    @classmethod
+    def define_schema(cls) -> io.Schema:
+        # Fetch dynamic options
+        libraries = ["All"] + get_libraries()
+        collections = ["All"] + get_collections()
+
+        return io.Schema(
+            node_id="embeddr.FindSimilar",
+            display_name="Embeddr Find Similar",
+            description="Finds similar images in your Embeddr library using an input image.",
+            category="Embeddr",
+            inputs=[
+                io.Image.Input("image"),
+                io.Combo.Input("library", options=libraries, default="All"),
+                io.Combo.Input(
+                    "collection", options=collections, default="All"),
+                io.Int.Input("limit", default=5, min=1, max=50),
+                io.Float.Input("threshold", default=0.0, min=0.0,
+                               max=1.0, step=0.01, display_name="Min Score"),
+            ],
+            outputs=[
+                io.Image.Output("images", is_output_list=True),
+                io.String.Output("embeddr_ids", is_output_list=True),
+            ],
+        )
+
+    @classmethod
+    def execute(cls, image, library="All", collection="All", limit=5, threshold=0.0):
+        config = get_config()
+        endpoint = config.get("endpoint", "http://localhost:8003")
+        api_url = endpoint.rstrip("/") + "/api/v1/images/search/image"
+
+        # Prepare image (take first of batch)
+        img_array = (image[0].cpu().numpy() * 255).astype(np.uint8)
+        img = Image.fromarray(np.clip(img_array, 0, 255))
+
+        buf = pyio.BytesIO()
+        img.save(buf, format="PNG")
+        buf.seek(0)
+
+        files = {"file": ("image.png", buf, "image/png")}
+        data = {
+            "limit": limit,
+        }
+
+        # Parse IDs from "ID: Name" format
+        if library != "All":
+            try:
+                lib_id = int(library.split(":")[0])
+                data["library_id"] = lib_id
+            except:
+                pass
+
+        if collection != "All":
+            try:
+                col_id = int(collection.split(":")[0])
+                data["collection_id"] = col_id
+            except:
+                pass
+
+        try:
+            response = requests.post(api_url, files=files, data=data)
+            response.raise_for_status()
+            results = response.json()
+            items = results.get("items", [])
+
+            if not items:
+                # Return empty
+                empty = torch.zeros(
+                    (1, 64, 64, 3), dtype=torch.float32, device="cpu")
+                return io.NodeOutput(empty, "[]")
+
+            # Load images
+            output_images = []
+            output_ids = []
+
+            for item in items:
+                # Fetch image file
+                img_url = endpoint.rstrip(
+                    "/") + f"/api/v1/images/{item['id']}/file"
+                img_resp = requests.get(img_url)
+                if img_resp.status_code == 200:
+                    i = Image.open(pyio.BytesIO(img_resp.content))
+                    i = i.convert("RGB")
+                    i = np.array(i).astype(np.float32) / 255.0
+                    output_images.append(torch.from_numpy(i))
+                    output_ids.append(str(item['id']))
+
+            if not output_images:
+                return io.NodeOutput([], [])
+
+            # Return list of images (unsqueeze to add batch dimension 1)
+            final_images = [img.unsqueeze(0) for img in output_images]
+            return io.NodeOutput(final_images, output_ids)
+
+        except Exception as e:
+            print(f"[Embeddr] Search failed: {e}")
+            empty = torch.zeros(
+                (1, 64, 64, 3), dtype=torch.float32, device="cpu")
+            return io.NodeOutput(empty, "[]")

nodes/EmbeddrFindSimilarText.py

@@ -0,0 +1,105 @@
+import requests
+import torch
+import numpy as np
+from PIL import Image, ImageOps
+import io as pyio
+from comfy_api.latest import io, ui
+from .utils import get_config
+from .utils.api import get_libraries, get_collections
+
+
+class EmbeddrFindSimilarTextNode(io.ComfyNode):
+    @classmethod
+    def define_schema(cls) -> io.Schema:
+        # Fetch dynamic options
+        libraries = ["All"] + get_libraries()
+        collections = ["All"] + get_collections()
+
+        return io.Schema(
+            node_id="embeddr.FindSimilarText",
+            display_name="Embeddr Find Similar (Text)",
+            description="Finds similar images in your Embeddr library using a text prompt.",
+            category="Embeddr",
+            inputs=[
+                io.String.Input("prompt", multiline=True),
+                io.Combo.Input("library", options=libraries, default="All"),
+                io.Combo.Input(
+                    "collection", options=collections, default="All"),
+                io.Int.Input("limit", default=5, min=1, max=50),
+            ],
+            outputs=[
+                io.Image.Output("images", is_output_list=True),
+                io.String.Output("embeddr_ids", is_output_list=True),
+            ],
+        )
+
+    @classmethod
+    def execute(cls, prompt, library="All", collection="All", limit=5):
+        config = get_config()
+        endpoint = config.get("endpoint", "http://localhost:8003")
+        api_url = endpoint.rstrip("/") + "/api/v1/images"
+
+        params = {
+            "q": prompt,
+            "limit": limit,
+        }
+
+        # Parse IDs from "ID: Name" format
+        if library != "All":
+            try:
+                lib_id = int(library.split(":")[0])
+                params["library_id"] = lib_id
+            except:
+                pass
+
+        if collection != "All":
+            try:
+                col_id = int(collection.split(":")[0])
+                params["collection_id"] = col_id
+            except:
+                pass
+
+        try:
+            response = requests.get(api_url, params=params)
+            response.raise_for_status()
+            results = response.json()
+            items = results.get("items", [])
+
+            if not items:
+                # Return empty
+                empty = torch.zeros(
+                    (1, 64, 64, 3), dtype=torch.float32, device="cpu")
+                return io.NodeOutput(empty, "")
+
+            # Load images
+            output_images = []
+            output_ids = []
+
+            first_width = 0
+            first_height = 0
+
+            for item in items:
+                # Fetch image file
+                img_url = endpoint.rstrip(
+                    "/") + f"/api/v1/images/{item['id']}/file"
+                img_resp = requests.get(img_url)
+                if img_resp.status_code == 200:
+                    i = Image.open(pyio.BytesIO(img_resp.content))
+                    i = ImageOps.exif_transpose(i)
+
+                    i = i.convert("RGB")
+                    i = np.array(i).astype(np.float32) / 255.0
+                    # Add batch dimension (1, H, W, C)
+                    output_images.append(torch.from_numpy(i).unsqueeze(0))
+                    output_ids.append(str(item['id']))
+
+            if not output_images:
+                return io.NodeOutput([], [])
+
+            return io.NodeOutput(output_images, output_ids)
+
+        except Exception as e:
+            print(f"[Embeddr] Find Similar Text error: {e}")
+            empty = torch.zeros(
+                (1, 64, 64, 3), dtype=torch.float32, device="cpu")
+            return io.NodeOutput(empty, "")

nodes/EmbeddrLoadImage.py

@@ -4,6 +4,7 @@
 from PIL import Image, ImageOps
 from io import BytesIO
 from comfy_api.latest import io, ui
+from .utils import get_config
 
 
 class EmbeddrLoadImageNode(io.ComfyNode):
@@ -14,33 +15,40 @@ def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="embeddr.LoadImage",
             display_name="Embeddr Load Image",
-            description="Loads an image from a URL (Embeddr).",
+            description="Loads an image from a Embeddr Image ID.",
             category="Embeddr",
             inputs=[
-                io.String.Input("image_url", default=""),
+                io.String.Input("image_id", default=""),
             ],
             outputs=[
                 io.Image.Output("image"),
                 io.Mask.Output("mask"),
+                io.String.Output("embeddr_id"),
             ],
         )
 
     @classmethod
-    def execute(cls, image_url):
-        if not image_url:
-            # Return empty black image if no URL
+    def execute(cls, image_id):
+        if not image_id:
+            # Return empty black image if no ID
             empty_image = torch.zeros(
                 (1, 64, 64, 3), dtype=torch.float32, device="cpu")
             empty_mask = torch.zeros(
                 (1, 64, 64), dtype=torch.float32, device="cpu")
-            return io.NodeOutput(empty_image, empty_mask)
+            return io.NodeOutput(empty_image, empty_mask, "")
 
-        if image_url in cls._cache:
-            image, mask = cls._cache[image_url]
-            return io.NodeOutput(image, mask)
+        if image_id in cls._cache:
+            image, mask = cls._cache[image_id]
+            return io.NodeOutput(image, mask, image_id)
 
         try:
-            response = requests.get(image_url)
+            config = get_config()
+            endpoint = config.get("endpoint", "http://localhost:8003")
+            # Ensure endpoint doesn't end with slash
+            endpoint = endpoint.rstrip("/")
+            api_url = f"{endpoint}/api/v1/images/{image_id}/file"
+
+            response = requests.get(api_url)
             response.raise_for_status()
             img = Image.open(BytesIO(response.content))
 
@@ -55,13 +63,13 @@ def execute(cls, image_url):
             else:
                 mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
 
-            cls._cache[image_url] = (image, mask)
-            return io.NodeOutput(image, mask, ui=ui.PreviewImage(image))
+            cls._cache[image_id] = (image, mask)
+            return io.NodeOutput(image, mask, image_id, ui=ui.PreviewImage(image))
 
         except Exception as e:
-            print(f"[Embeddr] Error loading image: {e}")
+            print(f"[Embeddr] Error loading image {image_id}: {e}")
             empty_image = torch.zeros(
                 (1, 64, 64, 3), dtype=torch.float32, device="cpu")
             empty_mask = torch.zeros(
                 (1, 64, 64), dtype=torch.float32, device="cpu")
-            return io.NodeOutput(empty_image, empty_mask)
+            return io.NodeOutput(empty_image, empty_mask, "")