Update Dockerfile

adding Postgres port env var

comfy-nodes/external_image_batch.py

@@ -1,85 +0,0 @@
-import folder_paths
-from PIL import Image, ImageOps
-import numpy as np
-import torch
-import json
-import comfy
-
-class ComfyUIDeployExternalImageBatch:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "input_id": (
-                    "STRING",
-                    {"multiline": False, "default": "input_images"},
-                ),
-                "images": (
-                    "STRING",
-                    {"multiline": False, "default": "[]"},
-                ),
-            },
-            "optional": {
-                "default_value": ("IMAGE",),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("image",)
-
-    FUNCTION = "run"
-
-    CATEGORY = "image"
-    
-    def run(self, input_id, images=None, default_value=None):
-        processed_images = []
-        try:
-            images_list = json.loads(images)  # Assuming images is a JSON array string
-            print(images_list)
-            for img_input in images_list:
-                if img_input.startswith('http'):
-                    import requests
-                    from io import BytesIO
-                    print("Fetching image from url: ", img_input)
-                    response = requests.get(img_input)
-                    image = Image.open(BytesIO(response.content))
-                elif img_input.startswith('data:image/png;base64,') or img_input.startswith('data:image/jpeg;base64,') or img_input.startswith('data:image/jpg;base64,'):
-                    import base64
-                    from io import BytesIO
-                    print("Decoding base64 image")
-                    base64_image = img_input[img_input.find(",")+1:]
-                    decoded_image = base64.b64decode(base64_image)
-                    image = Image.open(BytesIO(decoded_image))
-                else:
-                    raise ValueError("Invalid image url or base64 data provided.")
-
-                image = ImageOps.exif_transpose(image)
-                image = image.convert("RGB")
-                image = np.array(image).astype(np.float32) / 255.0
-                image_tensor = torch.from_numpy(image)[None,]
-                processed_images.append(image_tensor)
-        except Exception as e:
-            print(f"Error processing images: {e}")
-            pass
-            
-        if default_value is not None and len(images_list) == 0:
-            processed_images.append(default_value)  # Assuming default_value is a pre-processed image tensor
-
-        # Resize images if necessary and concatenate from MakeImageBatch in ImpactPack
-        if processed_images:
-            base_shape = processed_images[0].shape[1:]  # Get the shape of the first image for comparison
-            batch_tensor = processed_images[0]
-            for i in range(1, len(processed_images)):
-                if processed_images[i].shape[1:] != base_shape:
-                    # Resize to match the first image's dimensions
-                    processed_images[i] = comfy.utils.common_upscale(processed_images[i].movedim(-1, 1), base_shape[1], base_shape[0], "lanczos", "center").movedim(1, -1)
-
-                batch_tensor = torch.cat((batch_tensor, processed_images[i]), dim=0)
-            # Concatenate using torch.cat
-        else:
-            batch_tensor = None  # or handle the empty case as needed
-        return (batch_tensor, )
-
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImageBatch": ComfyUIDeployExternalImageBatch}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalImageBatch": "External Image Batch (ComfyUI Deploy)"}

comfy-nodes/external_lora.py

@@ -32,12 +32,7 @@ class ComfyUIDeployExternalLora:
         import os
         import uuid
 
-        print('external lora using')
-        print("input id: ", input_id)
-        print("default lora : ", default_lora_name)
-
-        if input_id:
-            if input_id.startswith('http'):
+        if input_id and input_id.startswith('http'):
             unique_filename = str(uuid.uuid4()) + ".safetensors"
             print(unique_filename)
             print(folder_paths.folder_names_and_paths["loras"][0][0])
@@ -49,8 +44,6 @@ class ComfyUIDeployExternalLora:
                 out_file.write(response.content)
             return (unique_filename,)
         else:
-                return (input_id,)
-
             return (default_lora_name,)
         
 

custom_routes.py

@@ -13,6 +13,7 @@ import traceback
 import uuid
 import asyncio
 import logging
+from enum import Enum
 from urllib.parse import quote
 import threading
 import hashlib
@@ -23,11 +24,30 @@ from PIL import Image
 import copy
 import struct
 
-from globals import StreamingPrompt, Status, sockets, SimplePrompt, streaming_prompt_metadata, prompt_metadata
+from globals import StreamingPrompt, sockets, streaming_prompt_metadata, BaseModel
+
+class Status(Enum):
+    NOT_STARTED = "not-started"
+    RUNNING = "running"
+    SUCCESS = "success"
+    FAILED = "failed"
+    UPLOADING = "uploading"
+    
+class SimplePrompt(BaseModel):
+    status_endpoint: str
+    file_upload_endpoint: str
+    workflow_api: dict
+    status: Status = Status.NOT_STARTED
+    progress: set = set()
+    last_updated_node: Optional[str] = None,
+    uploading_nodes: set = set()
+    done: bool = False
+    is_realtime: bool = False,
+    start_time: Optional[float] = None,
 
 api = None
 api_task = None
-
+prompt_metadata: dict[str, SimplePrompt] = {}
 cd_enable_log = os.environ.get('CD_ENABLE_LOG', 'false').lower() == 'true'
 cd_enable_run_log = os.environ.get('CD_ENABLE_RUN_LOG', 'false').lower() == 'true'
 
@@ -106,38 +126,6 @@ def apply_random_seed_to_workflow(workflow_api):
                 continue
             workflow_api[key]['inputs']['seed'] = randomSeed();
 
-def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
-    # Loop through each of the inputs and replace them
-    for key, value in workflow_api.items():
-        if 'inputs' in value:
-            
-            # Support websocket
-            if sid is not None:
-                if (value["class_type"] == "ComfyDeployWebscoketImageOutput"):
-                    value['inputs']["client_id"] = sid
-                if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
-                    value['inputs']["client_id"] = sid
-                    
-            if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs:
-                new_value = inputs[value['inputs']['input_id']]
-                
-                # Lets skip it if its an image
-                if isinstance(new_value, Image.Image):
-                    continue
-                
-                # Backward compactibility
-                value['inputs']["input_id"] = new_value
-            
-                # Fix for external text default value
-                if (value["class_type"] == "ComfyUIDeployExternalText"):
-                    value['inputs']["default_value"] = new_value
-                    
-                if (value["class_type"] == "ComfyUIDeployExternalCheckpoint"):
-                    value['inputs']["default_value"] = new_value
-                    
-                if (value["class_type"] == "ComfyUIDeployExternalImageBatch"):
-                    value['inputs']["images"] = new_value
-
 def send_prompt(sid: str, inputs: StreamingPrompt):
     # workflow_api = inputs.workflow_api
     workflow_api = copy.deepcopy(inputs.workflow_api)
@@ -147,7 +135,30 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
             
     print("getting inputs" , inputs.inputs)
             
-    apply_inputs_to_workflow(workflow_api, inputs.inputs, sid=sid)
+    # Loop through each of the inputs and replace them
+    for key, value in workflow_api.items():
+        if 'inputs' in value:
+            if (value["class_type"] == "ComfyDeployWebscoketImageOutput"):
+                value['inputs']["client_id"] = sid
+            if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
+                value['inputs']["client_id"] = sid
+                
+            if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs.inputs:
+                new_value = inputs.inputs[value['inputs']['input_id']]
+                
+                # Lets skip it if its an image
+                if isinstance(new_value, Image.Image):
+                    continue
+                
+                value['inputs']["input_id"] = new_value
+            
+                # Fix for external text default value
+                if (value["class_type"] == "ComfyUIDeployExternalText"):
+                    value['inputs']["default_value"] = new_value
+                    
+                if (value["class_type"] == "ComfyUIDeployExternalCheckpoint"):
+                    value['inputs']["default_value"] = new_value
+
                 
     print(workflow_api)
                 
@@ -180,15 +191,15 @@ async def comfy_deploy_run(request):
     prompt_server = server.PromptServer.instance
     data = await request.json()
 
-    # In older version, we use workflow_api, but this has inputs already swapped in nextjs frontend, which is tricky
-    workflow_api = data.get("workflow_api_raw")
+    workflow_api = data.get("workflow_api")
+
     # The prompt id generated from comfy deploy, can be None
     prompt_id = data.get("prompt_id")
-    inputs = data.get("inputs")
 
-    # Now it handles directly in here
     apply_random_seed_to_workflow(workflow_api)
-    apply_inputs_to_workflow(workflow_api, inputs)
+    # for key in workflow_api:
+    #     if 'inputs' in workflow_api[key] and 'seed' in workflow_api[key]['inputs']:
+    #         workflow_api[key]['inputs']['seed'] = randomSeed()
 
     prompt = {
         "prompt": workflow_api,
@@ -371,58 +382,26 @@ async def upload_file_endpoint(request):
     }, status=500)
         
 
-script_dir = os.path.dirname(os.path.abspath(__file__))
-# Assuming the cache file is stored in the same directory as this script
-CACHE_FILE_PATH = script_dir + '/file-hash-cache.json'
-
-# Global in-memory cache
-file_hash_cache = {}
-
-# Load cache from disk at startup
-def load_cache():
-    global file_hash_cache
-    try:
-        with open(CACHE_FILE_PATH, 'r') as cache_file:
-            file_hash_cache = json.load(cache_file)
-    except (FileNotFoundError, json.JSONDecodeError):
-        file_hash_cache = {}
-
-# Save cache to disk
-def save_cache():
-    with open(CACHE_FILE_PATH, 'w') as cache_file:
-        json.dump(file_hash_cache, cache_file)
-
-# Initialize cache on application start
-load_cache()
-
 @server.PromptServer.instance.routes.get('/comfyui-deploy/get-file-hash')
 async def get_file_hash(request):
     file_path = request.rel_url.query.get('file_path', '')
 
-    if not file_path:
+    if file_path is None:
         return web.json_response({
             "error": "file_path is required"
         }, status=400)
     
     try:
         base = folder_paths.base_path
-        full_file_path = os.path.join(base, file_path)
-
-        # Check if the file hash is in the cache
-        if full_file_path in file_hash_cache:
-            file_hash = file_hash_cache[full_file_path]
-        else:
-            start_time = time.time()
-            file_hash = await compute_sha256_checksum(full_file_path)
-            end_time = time.time()
-            elapsed_time = end_time - start_time
-            print(f"Cache miss -> Execution time: {elapsed_time} seconds")
-
-            # Update the in-memory cache
-            file_hash_cache[full_file_path] = file_hash
-            
-            save_cache()
-
+        file_path = os.path.join(base, file_path)
+        # print("file_path", file_path)
+        start_time = time.time()  # Capture the start time
+        file_hash = await compute_sha256_checksum(
+            file_path
+        )
+        end_time = time.time()  # Capture the end time after the code execution
+        elapsed_time = end_time - start_time  # Calculate the elapsed time
+        print(f"Execution time: {elapsed_time} seconds")
         return web.json_response({
             "file_hash": file_hash
         })
@@ -674,15 +653,6 @@ async def send_json_override(self, event, data, sid=None):
         # await update_run_with_output(prompt_id, data)
 
     if event == 'executed' and 'node' in data and 'output' in data:
-        print("executed", data)
-        if prompt_id in prompt_metadata:
-            node = data.get('node')
-            class_type = prompt_metadata[prompt_id].workflow_api[node]['class_type']
-            print("executed", class_type)
-            if class_type == "PreviewImage":
-                print("skipping preview image")
-                return
-            
         await update_run_with_output(prompt_id, data.get('output'), node_id=data.get('node'))
         # await update_run_with_output(prompt_id, data.get('output'), node_id=data.get('node'))
         # update_run_with_output(prompt_id, data.get('output'))
@@ -726,7 +696,7 @@ def update_run(prompt_id: str, status: Status):
     if (prompt_metadata[prompt_id].status != status):
 
         # when the status is already failed, we don't want to update it to success
-        if (prompt_metadata[prompt_id].status is Status.FAILED):
+        if ('status' in prompt_metadata[prompt_id] and prompt_metadata[prompt_id].status == Status.FAILED):
             return
 
         status_endpoint = prompt_metadata[prompt_id].status_endpoint
@@ -922,9 +892,6 @@ async def update_file_status(prompt_id: str, data, uploading, have_error=False,
 async def handle_upload(prompt_id: str, data, key: str, content_type_key: str, default_content_type: str):
     items = data.get(key, [])
     for item in items:
-        # # Skipping temp files
-        if item.get("type") == "temp":
-            continue
         await upload_file(
             prompt_id,
             item.get("filename"),
@@ -933,6 +900,7 @@ async def handle_upload(prompt_id: str, data, key: str, content_type_key: str, d
             content_type=item.get(content_type_key, default_content_type)
         )
 
+
 # Upload files in the background
 async def upload_in_background(prompt_id: str, data, node_id=None, have_upload=True):
     try:

docker-compose.yaml

@@ -0,0 +1,55 @@
+version: '3.9'
+services:
+
+  comfy-deploy:
+    build:
+      context: .
+      dockerfile: ./local/Dockerfile
+    restart: unless-stopped
+    volumes:
+      - ./local/scripts/entrypoint.sh:/comfyui-deploy/web/deploy_entrypoint.sh
+    entrypoint: /comfyui-deploy/web/deploy_entrypoint.sh
+    ports:
+      - 3000:3000
+    depends_on:
+      - postgres
+      - pg_proxy
+      - localstack
+    environment:
+      VSCODE_DEV_CONTAINER: true
+
+
+### comfy-deploy services
+
+  postgres:
+      image: "postgres:15.2-alpine"
+      environment:
+        POSTGRES_USER: postgres
+        POSTGRES_PASSWORD: postgres
+        POSTGRES_DB: verceldb
+        POSTGRES_PORT: 5480
+      expose:
+        - 5480
+
+
+  pg_proxy:
+    image: ghcr.io/neondatabase/wsproxy:latest
+    environment:
+      APPEND_PORT: "postgres:5480"
+      ALLOW_ADDR_REGEX: ".*"
+      LOG_TRAFFIC: "true"
+    expose:
+      - 80
+    depends_on:
+      - postgres
+
+
+  localstack:
+    image: localstack/localstack:latest
+    environment:
+      SERVICES: s3
+    ports:
+      - 4566:4566
+    volumes:
+      - ../localstack/aws:/etc/localstack/init/ready.d
+      - ../localstack/aws:/app/web/aws

globals.py

@@ -1,22 +1,17 @@
 import struct
-from enum import Enum
+
 import aiohttp
+
 from typing import List, Union, Any, Optional
 from PIL import Image, ImageOps
 from io import BytesIO
+
 from pydantic import BaseModel as PydanticBaseModel
 
 class BaseModel(PydanticBaseModel):
     class Config:
         arbitrary_types_allowed = True
 
-class Status(Enum):
-    NOT_STARTED = "not-started"
-    RUNNING = "running"
-    SUCCESS = "success"
-    FAILED = "failed"
-    UPLOADING = "uploading"
-
 class StreamingPrompt(BaseModel):
     workflow_api: Any
     auth_token: str
@@ -25,20 +20,7 @@ class StreamingPrompt(BaseModel):
     status_endpoint: str
     file_upload_endpoint: str
 
-class SimplePrompt(BaseModel):
-    status_endpoint: str
-    file_upload_endpoint: str
-    workflow_api: dict
-    status: Status = Status.NOT_STARTED
-    progress: set = set()
-    last_updated_node: Optional[str] = None,
-    uploading_nodes: set = set()
-    done: bool = False
-    is_realtime: bool = False,
-    start_time: Optional[float] = None,
-
 sockets = dict()
-prompt_metadata: dict[str, SimplePrompt] = {}
 streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
 
 class BinaryEventTypes:

local/Dockerfile

@@ -0,0 +1,18 @@
+FROM node:21-bullseye AS comfy_deploy
+
+RUN apt-get update && apt-get install -y python3 make g++
+
+RUN npm install -g bun
+
+COPY ./web /web
+
+
+WORKDIR /web
+
+RUN cp .env.example .env.local
+
+RUN bunx node-gyp
+
+RUN bun i
+
+ENTRYPOINT [ "bun", "dev" ]

local/scripts/entrypoint.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+echo "comfy deploy container starting.."
+
+echo "Running migrations.."
+bun migrate-local
+
+echo "Starting comfy deploy.."
+bun dev

prestartup_script.py

@@ -58,9 +58,6 @@ if cd_enable_log:
    print("** Comfy Deploy logging enabled")
    setup() 
 
-
-# Store the original working directory
-original_cwd = os.getcwd()
 try:
     # Get the absolute path of the script's directory
     script_dir = os.path.dirname(os.path.abspath(__file__))
@@ -70,6 +67,3 @@ try:
     print(f"** Comfy Deploy Revision: {current_git_commit}")
 except Exception as e:
     print(f"** Comfy Deploy failed to get current git commit: {str(e)}")
-finally:
-    # Change back to the original directory
-    os.chdir(original_cwd)

web-plugin/index.js

@@ -1,18 +1,10 @@
 import { app } from "./app.js";
 import { api } from "./api.js";
 import { ComfyWidgets, LGraphNode } from "./widgets.js";
-import { generateDependencyGraph } from "https://esm.sh/[email protected]5";
+import { generateDependencyGraph } from "https://esm.sh/[email protected]2";
 
 const loadingIcon = `<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" viewBox="0 0 24 24"><g fill="none" stroke="#888888" stroke-linecap="round" stroke-width="2"><path stroke-dasharray="60" stroke-dashoffset="60" stroke-opacity=".3" d="M12 3C16.9706 3 21 7.02944 21 12C21 16.9706 16.9706 21 12 21C7.02944 21 3 16.9706 3 12C3 7.02944 7.02944 3 12 3Z"><animate fill="freeze" attributeName="stroke-dashoffset" dur="1.3s" values="60;0"/></path><path stroke-dasharray="15" stroke-dashoffset="15" d="M12 3C16.9706 3 21 7.02944 21 12"><animate fill="freeze" attributeName="stroke-dashoffset" dur="0.3s" values="15;0"/><animateTransform attributeName="transform" dur="1.5s" repeatCount="indefinite" type="rotate" values="0 12 12;360 12 12"/></path></g></svg>`;
 
-function sendEventToCD(event, data) {
-  const message = {
-    type: event,
-    data: data,
-  };
-  window.parent.postMessage(JSON.stringify(message), "*");
-}
-
 /** @typedef {import('../../../web/types/comfy.js').ComfyExtension} ComfyExtension*/
 /** @type {ComfyExtension} */
 const ext = {
@@ -26,11 +18,6 @@ const ext = {
     const auth_token = queryParams.get("auth_token");
     const org_display = queryParams.get("org_display");
     const origin = queryParams.get("origin");
-    const workspace_mode = queryParams.get("workspace_mode");
-
-    if (workspace_mode) {
-      document.querySelector(".comfy-menu").style.display = "none";
-    }
 
     const data = getData();
     let endpoint = data.endpoint;
@@ -165,32 +152,9 @@ const ext = {
   async setup() {
     // const graphCanvas = document.getElementById("graph-canvas");
 
-    window.addEventListener("message", async (event) => {
-      try {
-        const message = JSON.parse(event.data);
-        if (message.type === "graph_load") {
-          const comfyUIWorkflow = message.data;
-          console.log("recieved: ", comfyUIWorkflow);
-          // Assuming there's a method to load the workflow data into the ComfyUI
-          // This part of the code would depend on how the ComfyUI expects to receive and process the workflow data
-          // For demonstration, let's assume there's a loadWorkflow method in the ComfyUI API
-          if (comfyUIWorkflow && app && app.loadGraphData) {
-            app.loadGraphData(comfyUIWorkflow);
-          }
-        } else if (message.type === "deploy") {
-          // deployWorkflow();
-          const prompt = await app.graphToPrompt();
-          sendEventToCD("cd_plugin_onDeployChanges", prompt);
-        } else if (message.type === "queue_prompt") {
-          const prompt = await app.graphToPrompt();
-          sendEventToCD("cd_plugin_onQueuePrompt", prompt);
-        }
-      } catch (error) {
-        // console.error("Error processing message:", error);
-      }
-
-      // if (!event.data.flow || Object.entries(event.data.flow).length <= 0)
-      //   return;
+    window.addEventListener("message", (event) => {
+      if (!event.data.flow || Object.entries(event.data.flow).length <= 0)
+        return;
       //   updateBlendshapesPrompts(event.data.flow);
     });
 
@@ -203,17 +167,6 @@ const ext = {
 
       //   }
     });
-
-    app.graph.onAfterChange = ((originalFunction) => async function () {
-        const prompt = await app.graphToPrompt();
-        sendEventToCD("cd_plugin_onAfterChange", prompt);
-
-        if (typeof originalFunction === "function") {
-          originalFunction.apply(this, arguments);
-        }
-      })(app.graph.onAfterChange);
-
-    sendEventToCD("cd_plugin_setup");
   },
 };
 
@@ -314,9 +267,14 @@ function createDynamicUIHtml(data) {
   return html;
 }
 
-async function deployWorkflow() {
-  const deploy = document.getElementById("deploy-button");
+function addButton() {
+  const menu = document.querySelector(".comfy-menu");
 
+  const deploy = document.createElement("button");
+  deploy.style.position = "relative";
+  deploy.style.display = "block";
+  deploy.innerHTML = "<div id='button-title'>Deploy</div>";
+  deploy.onclick = async () => {
     /** @type {LGraph} */
     const graph = app.graph;
 
@@ -597,18 +555,6 @@ async function deployWorkflow() {
         title.style.color = "white";
       }, 1000);
     }
-}
-
-function addButton() {
-  const menu = document.querySelector(".comfy-menu");
-
-  const deploy = document.createElement("button");
-  deploy.id = "deploy-button";
-  deploy.style.position = "relative";
-  deploy.style.display = "block";
-  deploy.innerHTML = "<div id='button-title'>Deploy</div>";
-  deploy.onclick = async () => {
-    await deployWorkflow()
   };
 
   const config = document.createElement("img");

web/src/db/db.ts

@@ -9,10 +9,10 @@ if (process.env.VERCEL_ENV !== "production") {
   // Set the WebSocket proxy to work with the local instance
   if (isDevContainer) {
     // Running inside a VS Code devcontainer
-    neonConfig.wsProxy = (host) => "host.docker.internal:5481/v1";
+    neonConfig.wsProxy = (host) => "pg_proxy:80/v1";
   } else {
     // Not running inside a VS Code devcontainer
-    neonConfig.wsProxy = (host) => `${host}:5481/v1`;
+    neonConfig.wsProxy = (host) => "pg_proxy:80/v1";
   }
   // Disable all authentication and encryption
   neonConfig.useSecureWebSocket = false;