fix(upload outputs): skip images/gifs/files/mesh when env var is true

The env var is `CD_BYPASS_UPLOAD`.
When that variables is `True`, we don't upload the media to our comfy
deploy s3 bucket.

There are 2 steps.
1. save the file into our s3 bucket
2. save the saving into our database.

When `CD_BYPASS_UPLOAD` is True:
1. Skip the save file into our s3 bucket
2. Skip the save into our database

Previously we were skipping the step 1, but not the step 2. So that is
the reason of why we keep seeing the comfy deploy URL when fetching the
run details:

```
outputs: [
  {
    data:{
      gifs: [
        {
          url: "https://comfy-deploy-output.s3.amazonaws.com/video.mp4"
        }
      ],
      text: [
        "A text that you displayed with show text node"
      ]
    }
  }
]
```

With the new changes we don't save that into our database, and fetching
the details of a run will look like this:
```
outputs: [
  {
    data:{
      text: [
        "A text that you displayed with show text node"
      ]
    }
  }
]
```

.gitignore

@@ -1,3 +1,2 @@
 __pycache__
 .DS_Store
-file-hash-cache.json

builder/modal-builder/src/main.py

@@ -0,0 +1,504 @@
+from typing import Union, Optional, Dict, List
+from pydantic import BaseModel, Field, field_validator
+from fastapi import FastAPI, HTTPException, WebSocket, BackgroundTasks, WebSocketDisconnect
+from fastapi.responses import JSONResponse
+from fastapi.logger import logger as fastapi_logger
+import os
+from enum import Enum
+import json
+import subprocess
+import time
+from contextlib import asynccontextmanager
+import asyncio
+import threading
+import signal
+import logging
+from fastapi.logger import logger as fastapi_logger
+import requests
+from urllib.parse import parse_qs
+from starlette.middleware.base import BaseHTTPMiddleware
+from starlette.types import ASGIApp, Scope, Receive, Send
+
+from concurrent.futures import ThreadPoolExecutor
+
+# executor = ThreadPoolExecutor(max_workers=5)
+
+gunicorn_error_logger = logging.getLogger("gunicorn.error")
+gunicorn_logger = logging.getLogger("gunicorn")
+uvicorn_access_logger = logging.getLogger("uvicorn.access")
+uvicorn_access_logger.handlers = gunicorn_error_logger.handlers
+
+fastapi_logger.handlers = gunicorn_error_logger.handlers
+
+if __name__ != "__main__":
+    fastapi_logger.setLevel(gunicorn_logger.level)
+else:
+    fastapi_logger.setLevel(logging.DEBUG)
+
+logger = logging.getLogger("uvicorn")
+logger.setLevel(logging.INFO)
+
+last_activity_time = time.time()
+global_timeout = 60 * 4
+
+machine_id_websocket_dict = {}
+machine_id_status = {}
+
+fly_instance_id = os.environ.get('FLY_ALLOC_ID', 'local').split('-')[0]
+
+
+class FlyReplayMiddleware(BaseHTTPMiddleware):
+    """
+    If the wrong instance was picked by the fly.io load balancer we use the fly-replay header
+    to repeat the request again on the right instance.
+
+    This only works if the right instance is provided as a query_string parameter.
+    """
+
+    def __init__(self, app: ASGIApp) -> None:
+        self.app = app
+
+    async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
+        query_string = scope.get('query_string', b'').decode()
+        query_params = parse_qs(query_string)
+        target_instance = query_params.get(
+            'fly_instance_id', [fly_instance_id])[0]
+
+        async def send_wrapper(message):
+            if target_instance != fly_instance_id:
+                if message['type'] == 'websocket.close' and 'Invalid session' in message['reason']:
+                    # fly.io only seems to look at the fly-replay header if websocket is accepted
+                    message = {'type': 'websocket.accept'}
+                if 'headers' not in message:
+                    message['headers'] = []
+                message['headers'].append(
+                    [b'fly-replay', f'instance={target_instance}'.encode()])
+            await send(message)
+        await self.app(scope, receive, send_wrapper)
+
+
+async def check_inactivity():
+    global last_activity_time
+    while True:
+        # logger.info("Checking inactivity...")
+        if time.time() - last_activity_time > global_timeout:
+            if len(machine_id_status) == 0:
+                # The application has been inactive for more than 60 seconds.
+                # Scale it down to zero here.
+                logger.info(
+                    f"No activity for {global_timeout} seconds, exiting...")
+                # os._exit(0)
+                os.kill(os.getpid(), signal.SIGINT)
+                break
+            else:
+                pass
+                # logger.info(f"Timeout but still in progress")
+
+        await asyncio.sleep(1)  # Check every second
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    thread = run_in_new_thread(check_inactivity())
+    yield
+    logger.info("Cancelling")
+
+#
+app = FastAPI(lifespan=lifespan)
+app.add_middleware(FlyReplayMiddleware)
+# MODAL_ORG = os.environ.get("MODAL_ORG")
+
+
+@app.get("/")
+def read_root():
+    global last_activity_time
+    last_activity_time = time.time()
+    logger.info(f"Extended inactivity time to {global_timeout}")
+    return {"Hello": "World"}
+
+# create a post route called /create takes in a json of example
+# {
+#     name: "my first image",
+#     deps: {
+#         "comfyui": "d0165d819afe76bd4e6bdd710eb5f3e571b6a804",
+#         "git_custom_nodes": {
+#             "https://github.com/cubiq/ComfyUI_IPAdapter_plus": {
+#                 "hash": "2ca0c6dd0b2ad64b1c480828638914a564331dcd",
+#                 "disabled": true
+#             },
+#             "https://github.com/ltdrdata/ComfyUI-Manager.git": {
+#                 "hash": "9c86f62b912f4625fe2b929c7fc61deb9d16f6d3",
+#                 "disabled": false
+#             },
+#         },
+#         "file_custom_nodes": []
+#     }
+# }
+
+
+class GitCustomNodes(BaseModel):
+    hash: str
+    disabled: bool
+
+class FileCustomNodes(BaseModel):
+    filename: str
+    disabled: bool
+
+
+class Snapshot(BaseModel):
+    comfyui: str
+    git_custom_nodes: Dict[str, GitCustomNodes]
+    file_custom_nodes: List[FileCustomNodes]
+
+class Model(BaseModel):
+    name: str
+    type: str
+    base: str
+    save_path: str
+    description: str
+    reference: str
+    filename: str
+    url: str
+
+
+class GPUType(str, Enum):
+    T4 = "T4"
+    A10G = "A10G"
+    A100 = "A100"
+    L4 = "L4"
+
+
+class Item(BaseModel):
+    machine_id: str
+    name: str
+    snapshot: Snapshot
+    models: List[Model]
+    callback_url: str
+    gpu: GPUType = Field(default=GPUType.T4)
+
+    @field_validator('gpu')
+    @classmethod
+    def check_gpu(cls, value):
+        if value not in GPUType.__members__:
+            raise ValueError(
+                f"Invalid GPU option. Choose from: {', '.join(GPUType.__members__.keys())}")
+        return GPUType(value)
+
+
+@app.websocket("/ws/{machine_id}")
+async def websocket_endpoint(websocket: WebSocket, machine_id: str):
+    await websocket.accept()
+    machine_id_websocket_dict[machine_id] = websocket
+    # Send existing logs
+    if machine_id in machine_logs_cache:
+        combined_logs = "\n".join(
+            log_entry['logs'] for log_entry in machine_logs_cache[machine_id])
+        await websocket.send_text(json.dumps({"event": "LOGS", "data": {
+            "machine_id": machine_id,
+            "logs": combined_logs,
+            "timestamp": time.time()
+        }}))
+    try:
+        while True:
+            data = await websocket.receive_text()
+            global last_activity_time
+            last_activity_time = time.time()
+            logger.info(f"Extended inactivity time to {global_timeout}")
+            # You can handle received messages here if needed
+    except WebSocketDisconnect:
+        if machine_id in machine_id_websocket_dict:
+            machine_id_websocket_dict.pop(machine_id)
+
+# @app.get("/test")
+# async def test():
+#     machine_id_status["123"] = True
+#     global last_activity_time
+#     last_activity_time = time.time()
+#     logger.info(f"Extended inactivity time to {global_timeout}")
+
+#     await asyncio.sleep(10)
+
+#     machine_id_status["123"] = False
+#     machine_id_status.pop("123")
+
+#     return {"Hello": "World"}
+
+
+@app.post("/create")
+async def create_machine(item: Item):
+    global last_activity_time
+    last_activity_time = time.time()
+    logger.info(f"Extended inactivity time to {global_timeout}")
+
+    if item.machine_id in machine_id_status and machine_id_status[item.machine_id]:
+        return JSONResponse(status_code=400, content={"error": "Build already in progress."})
+
+    # Run the building logic in a separate thread
+    # future = executor.submit(build_logic, item)
+    task = asyncio.create_task(build_logic(item))
+
+    return JSONResponse(status_code=200, content={"message": "Build Queued", "build_machine_instance_id": fly_instance_id})
+
+
+class StopAppItem(BaseModel):
+    machine_id: str
+
+
+def find_app_id(app_list, app_name):
+    for app in app_list:
+        if app['Name'] == app_name:
+            return app['App ID']
+    return None
+
+@app.post("/stop-app")
+async def stop_app(item: StopAppItem):
+    # cmd = f"modal app list | grep {item.machine_id} | awk -F '│' '{{print $2}}'"
+    cmd = f"modal app list --json"
+
+    env = os.environ.copy()
+    env["COLUMNS"] = "10000"  # Set the width to a large value
+    find_id_process = await asyncio.subprocess.create_subprocess_shell(cmd,
+                                                                      stdout=asyncio.subprocess.PIPE,
+                                                                      stderr=asyncio.subprocess.PIPE,
+                                                                      env=env)
+    await find_id_process.wait()
+
+    stdout, stderr = await find_id_process.communicate()
+    if stdout:
+        app_id = stdout.decode().strip()
+        app_list = json.loads(app_id)
+        app_id = find_app_id(app_list, item.machine_id)
+        logger.info(f"cp_process stdout: {app_id}")
+    if stderr:
+        logger.info(f"cp_process stderr: {stderr.decode()}")
+
+    cp_process = await asyncio.subprocess.create_subprocess_exec("modal", "app", "stop", app_id,
+                                                                 stdout=asyncio.subprocess.PIPE,
+                                                                 stderr=asyncio.subprocess.PIPE,)
+    await cp_process.wait()
+    logger.info(f"Stopping app {item.machine_id}")
+    stdout, stderr = await cp_process.communicate()
+    if stdout:
+        logger.info(f"cp_process stdout: {stdout.decode()}")
+    if stderr:
+        logger.info(f"cp_process stderr: {stderr.decode()}")
+
+    if cp_process.returncode == 0:
+        return JSONResponse(status_code=200, content={"status": "success"})
+    else:
+        return JSONResponse(status_code=500, content={"status": "error", "error": stderr.decode()})
+
+# Initialize the logs cache
+machine_logs_cache = {}
+
+
+async def build_logic(item: Item):
+    # Deploy to modal
+    folder_path = f"/app/builds/{item.machine_id}"
+    machine_id_status[item.machine_id] = True
+
+    # Ensure the os path is same as the current directory
+    # os.chdir(os.path.dirname(os.path.realpath(__file__)))
+    # print(
+    #     f"builder - Current working directory: {os.getcwd()}"
+    # )
+
+    # Copy the app template
+    # os.system(f"cp -r template {folder_path}")
+    cp_process = await asyncio.subprocess.create_subprocess_exec("cp", "-r", "/app/src/template", folder_path)
+    await cp_process.wait()
+
+    # Write the config file
+    config = {
+        "name": item.name,
+        "deploy_test": os.environ.get("DEPLOY_TEST_FLAG", "False"),
+        "gpu": item.gpu,
+        "civitai_token": os.environ.get("CIVITAI_TOKEN", "")
+    }
+    with open(f"{folder_path}/config.py", "w") as f:
+        f.write("config = " + json.dumps(config))
+
+    with open(f"{folder_path}/data/snapshot.json", "w") as f:
+        f.write(item.snapshot.json())
+
+    with open(f"{folder_path}/data/models.json", "w") as f:
+        models_json_list = [model.dict() for model in item.models]
+        models_json_string = json.dumps(models_json_list)
+        f.write(models_json_string)
+
+    # os.chdir(folder_path)
+    # process = subprocess.Popen(f"modal deploy {folder_path}/app.py", stdout=subprocess.PIPE, stderr=subprocess.STDOUT, shell=True)
+    process = await asyncio.subprocess.create_subprocess_shell(
+        f"modal deploy app.py",
+        stdout=asyncio.subprocess.PIPE,
+        stderr=asyncio.subprocess.PIPE,
+        cwd=folder_path,
+        env={**os.environ, "COLUMNS": "10000"}
+    )
+
+    url = None
+
+    if item.machine_id not in machine_logs_cache:
+        machine_logs_cache[item.machine_id] = []
+
+    machine_logs = machine_logs_cache[item.machine_id]
+
+    url_queue = asyncio.Queue()
+
+    async def read_stream(stream, isStderr, url_queue: asyncio.Queue):
+        while True:
+            line = await stream.readline()
+            if line:
+                l = line.decode('utf-8').strip()
+
+                if l == "":
+                    continue
+
+                if not isStderr:
+                    logger.info(l)
+                    machine_logs.append({
+                        "logs": l,
+                        "timestamp": time.time()
+                    })
+
+                    if item.machine_id in machine_id_websocket_dict:
+                        await machine_id_websocket_dict[item.machine_id].send_text(json.dumps({"event": "LOGS", "data": {
+                            "machine_id": item.machine_id,
+                            "logs": l,
+                            "timestamp": time.time()
+                        }}))
+
+                    if "Created comfyui_api =>" in l or ((l.startswith("https://") or l.startswith("│")) and l.endswith(".modal.run")):
+                        if "Created comfyui_api =>" in l:
+                            url = l.split("=>")[1].strip()
+                        # making sure it is a url
+                        elif "comfyui-api" in l:
+                            # Some case it only prints the url on a blank line
+                            if l.startswith("│"):
+                                url = l.split("│")[1].strip()
+                            else:
+                                url = l
+
+                        if url:
+                            machine_logs.append({
+                                "logs": f"App image built, url: {url}",
+                                "timestamp": time.time()
+                            })
+
+                            await url_queue.put(url)
+
+                            if item.machine_id in machine_id_websocket_dict:
+                                await machine_id_websocket_dict[item.machine_id].send_text(json.dumps({"event": "LOGS", "data": {
+                                    "machine_id": item.machine_id,
+                                    "logs": f"App image built, url: {url}",
+                                    "timestamp": time.time()
+                                }}))
+                                await machine_id_websocket_dict[item.machine_id].send_text(json.dumps({"event": "FINISHED", "data": {
+                                    "status": "succuss",
+                                }}))
+
+                else:
+                    # is error
+                    logger.error(l)
+                    machine_logs.append({
+                        "logs": l,
+                        "timestamp": time.time()
+                    })
+
+                    if item.machine_id in machine_id_websocket_dict:
+                        await machine_id_websocket_dict[item.machine_id].send_text(json.dumps({"event": "LOGS", "data": {
+                            "machine_id": item.machine_id,
+                            "logs": l,
+                            "timestamp": time.time()
+                        }}))
+                        await machine_id_websocket_dict[item.machine_id].send_text(json.dumps({"event": "FINISHED", "data": {
+                            "status": "failed",
+                        }}))
+            else:
+                break
+
+    stdout_task = asyncio.create_task(
+        read_stream(process.stdout, False, url_queue))
+    stderr_task = asyncio.create_task(
+        read_stream(process.stderr, True, url_queue))
+
+    await asyncio.wait([stdout_task, stderr_task])
+
+    # Wait for the subprocess to finish
+    await process.wait()
+
+    if not url_queue.empty():
+        # The queue is not empty, you can get an item
+        url = await url_queue.get()
+
+    # Close the ws connection and also pop the item
+    if item.machine_id in machine_id_websocket_dict and machine_id_websocket_dict[item.machine_id] is not None:
+        await machine_id_websocket_dict[item.machine_id].close()
+
+    if item.machine_id in machine_id_websocket_dict:
+        machine_id_websocket_dict.pop(item.machine_id)
+
+    if item.machine_id in machine_id_status:
+        machine_id_status[item.machine_id] = False
+
+    # Check for errors
+    if process.returncode != 0:
+        logger.info("An error occurred.")
+        # Send a post request with the json body machine_id to the callback url
+        machine_logs.append({
+            "logs": "Unable to build the app image.",
+            "timestamp": time.time()
+        })
+        requests.post(item.callback_url, json={
+                      "machine_id": item.machine_id, "build_log": json.dumps(machine_logs)})
+
+        if item.machine_id in machine_logs_cache:
+            del machine_logs_cache[item.machine_id]
+
+        return
+        # return JSONResponse(status_code=400, content={"error": "Unable to build the app image."})
+
+    # app_suffix = "comfyui-app"
+
+    if url is None:
+        machine_logs.append({
+            "logs": "App image built, but url is None, unable to parse the url.",
+            "timestamp": time.time()
+        })
+        requests.post(item.callback_url, json={
+                      "machine_id": item.machine_id, "build_log": json.dumps(machine_logs)})
+
+        if item.machine_id in machine_logs_cache:
+            del machine_logs_cache[item.machine_id]
+
+        return
+        # return JSONResponse(status_code=400, content={"error": "App image built, but url is None, unable to parse the url."})
+    # example https://bennykok--my-app-comfyui-app.modal.run/
+    # my_url = f"https://{MODAL_ORG}--{item.container_id}-{app_suffix}.modal.run"
+
+    requests.post(item.callback_url, json={
+                  "machine_id": item.machine_id, "endpoint": url, "build_log": json.dumps(machine_logs)})
+    if item.machine_id in machine_logs_cache:
+        del machine_logs_cache[item.machine_id]
+
+    logger.info("done")
+    logger.info(url)
+
+
+def start_loop(loop):
+    asyncio.set_event_loop(loop)
+    loop.run_forever()
+
+
+def run_in_new_thread(coroutine):
+    new_loop = asyncio.new_event_loop()
+    t = threading.Thread(target=start_loop, args=(new_loop,), daemon=True)
+    t.start()
+    asyncio.run_coroutine_threadsafe(coroutine, new_loop)
+    return t
+
+
+if __name__ == "__main__":
+    import uvicorn
+    # , log_level="debug"
+    uvicorn.run("main:app", host="0.0.0.0", port=8080, lifespan="on")

builder/modal-builder/src/main1.py

@@ -1,448 +0,0 @@
-import modal
-from typing import Union, Optional, Dict, List
-from pydantic import BaseModel, Field, field_validator
-from fastapi import FastAPI, HTTPException, WebSocket, BackgroundTasks, WebSocketDisconnect
-from fastapi.responses import JSONResponse
-from fastapi.logger import logger as fastapi_logger
-import os
-from enum import Enum
-import json
-import subprocess
-import time
-from contextlib import asynccontextmanager
-import asyncio
-import threading
-import signal
-import logging
-from fastapi.logger import logger as fastapi_logger
-import requests
-from urllib.parse import parse_qs
-from starlette.middleware.base import BaseHTTPMiddleware
-from starlette.types import ASGIApp, Scope, Receive, Send
-
-# Modal应用实例
-modal_app = modal.App(name="comfyui-deploy")
-
-gunicorn_error_logger = logging.getLogger("gunicorn.error")
-gunicorn_logger = logging.getLogger("gunicorn")
-uvicorn_access_logger = logging.getLogger("uvicorn.access")
-uvicorn_access_logger.handlers = gunicorn_error_logger.handlers
-
-fastapi_logger.handlers = gunicorn_error_logger.handlers
-
-if __name__ != "__main__":
-    fastapi_logger.setLevel(gunicorn_logger.level)
-else:
-    fastapi_logger.setLevel(logging.DEBUG)
-
-logger = logging.getLogger("uvicorn")
-logger.setLevel(logging.INFO)
-
-last_activity_time = time.time()
-global_timeout = 60 * 4
-
-machine_id_websocket_dict = {}
-machine_id_status = {}
-machine_logs_cache = {}
-
-fly_instance_id = os.environ.get('FLY_ALLOC_ID', 'local').split('-')[0]
-
-class FlyReplayMiddleware(BaseHTTPMiddleware):
-    def __init__(self, app: ASGIApp) -> None:
-        super().__init__(app)
-
-    async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
-        query_string = scope.get('query_string', b'').decode()
-        query_params = parse_qs(query_string)
-        target_instance = query_params.get('fly_instance_id', [fly_instance_id])[0]
-
-        async def send_wrapper(message):
-            if target_instance != fly_instance_id:
-                if message['type'] == 'websocket.close' and 'Invalid session' in message.get('reason', ''):
-                    message = {'type': 'websocket.accept'}
-                if 'headers' not in message:
-                    message['headers'] = []
-                message['headers'].append([b'fly-replay', f'instance={target_instance}'.encode()])
-            await send(message)
-        await self.app(scope, receive, send_wrapper)
-
-async def check_inactivity():
-    global last_activity_time
-    while True:
-        if time.time() - last_activity_time > global_timeout:
-            if len(machine_id_status) == 0:
-                logger.info(f"No activity for {global_timeout} seconds, exiting...")
-                os.kill(os.getpid(), signal.SIGINT)
-                break
-        await asyncio.sleep(1)
-
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    thread = run_in_new_thread(check_inactivity())
-    yield
-    logger.info("Cancelling")
-
-# FastAPI实例
-fastapi_app = FastAPI(lifespan=lifespan)
-fastapi_app.add_middleware(FlyReplayMiddleware)
-
-class GitCustomNodes(BaseModel):
-    hash: str
-    disabled: bool
-
-class FileCustomNodes(BaseModel):
-    filename: str
-    disabled: bool
-
-class Snapshot(BaseModel):
-    comfyui: str
-    git_custom_nodes: Dict[str, GitCustomNodes]
-    file_custom_nodes: List[FileCustomNodes]
-
-class Model(BaseModel):
-    name: str
-    type: str
-    base: str
-    save_path: str
-    description: str
-    reference: str
-    filename: str
-    url: str
-
-class GPUType(str, Enum):
-    T4 = "T4"
-    A10G = "A10G"
-    A100 = "A100"
-    L4 = "L4"
-
-class Item(BaseModel):
-    machine_id: str
-    name: str
-    snapshot: Snapshot
-    models: List[Model]
-    callback_url: str
-    gpu: GPUType = Field(default=GPUType.T4)
-
-    @field_validator('gpu')
-    @classmethod
-    def check_gpu(cls, value):
-        if value not in GPUType.__members__:
-            raise ValueError(f"Invalid GPU option. Choose from: {', '.join(GPUType.__members__.keys())}")
-        return GPUType(value)
-
-class StopAppItem(BaseModel):
-    machine_id: str
-
-@fastapi_app.get("/")
-def read_root():
-    global last_activity_time
-    last_activity_time = time.time()
-    logger.info(f"Extended inactivity time to {global_timeout}")
-    return {"Hello": "World"}
-
-@fastapi_app.websocket("/ws/{machine_id}")
-async def websocket_endpoint(websocket: WebSocket, machine_id: str):
-    await websocket.accept()
-    machine_id_websocket_dict[machine_id] = websocket
-    if machine_id in machine_logs_cache:
-        combined_logs = "\n".join(log_entry['logs'] for log_entry in machine_logs_cache[machine_id])
-        await websocket.send_text(json.dumps({
-            "event": "LOGS", 
-            "data": {
-                "machine_id": machine_id,
-                "logs": combined_logs,
-                "timestamp": time.time()
-            }
-        }))
-    try:
-        while True:
-            data = await websocket.receive_text()
-            global last_activity_time
-            last_activity_time = time.time()
-            logger.info(f"Extended inactivity time to {global_timeout}")
-    except WebSocketDisconnect:
-        if machine_id in machine_id_websocket_dict:
-            del machine_id_websocket_dict[machine_id]
-
-@fastapi_app.post("/create")
-async def create_machine(item: Item):
-    global last_activity_time
-    last_activity_time = time.time()
-    logger.info(f"Extended inactivity time to {global_timeout}")
-
-    if item.machine_id in machine_id_status and machine_id_status[item.machine_id]:
-        return JSONResponse(status_code=400, content={"error": "Build already in progress."})
-
-    task = asyncio.create_task(build_logic(item))
-    return JSONResponse(
-        status_code=200, 
-        content={
-            "message": "Build Queued",
-            "build_machine_instance_id": fly_instance_id
-        }
-    )
-
-def find_app_id(app_list, app_name):
-    for app in app_list:
-        if app['Name'] == app_name:
-            return app['App ID']
-    return None
-
-@fastapi_app.post("/stop-app")
-async def stop_app(item: StopAppItem):
-    cmd = f"modal app list --json"
-    env = os.environ.copy()
-    env["COLUMNS"] = "10000"
-    
-    find_id_process = await asyncio.subprocess.create_subprocess_shell(
-        cmd,
-        stdout=asyncio.subprocess.PIPE,
-        stderr=asyncio.subprocess.PIPE,
-        env=env
-    )
-    
-    stdout, stderr = await find_id_process.communicate()
-    if stdout:
-        app_list = json.loads(stdout.decode().strip())
-        app_id = find_app_id(app_list, item.machine_id)
-        logger.info(f"cp_process stdout: {app_id}")
-    if stderr:
-        logger.info(f"cp_process stderr: {stderr.decode()}")
-
-    cp_process = await asyncio.subprocess.create_subprocess_exec(
-        "modal", "app", "stop", app_id,
-        stdout=asyncio.subprocess.PIPE,
-        stderr=asyncio.subprocess.PIPE,
-    )
-    
-    await cp_process.wait()
-    stdout, stderr = await cp_process.communicate()
-    
-    if stdout:
-        logger.info(f"cp_process stdout: {stdout.decode()}")
-    if stderr:
-        logger.info(f"cp_process stderr: {stderr.decode()}")
-
-    if cp_process.returncode == 0:
-        return JSONResponse(status_code=200, content={"status": "success"})
-    else:
-        return JSONResponse(
-            status_code=500, 
-            content={"status": "error", "error": stderr.decode()}
-        )
-
-async def build_logic(item: Item):
-    folder_path = f"/app/builds/{item.machine_id}"
-    machine_id_status[item.machine_id] = True
-
-    cp_process = await asyncio.subprocess.create_subprocess_exec(
-        "cp", "-r", "/app/src/template", folder_path
-    )
-    await cp_process.wait()
-
-    config = {
-        "name": item.name,
-        "deploy_test": os.environ.get("DEPLOY_TEST_FLAG", "False"),
-        "gpu": item.gpu,
-        "civitai_token": os.environ.get("CIVITAI_TOKEN", "833b4ded5c7757a06a803763500bab58")
-    }
-    
-    with open(f"{folder_path}/config.py", "w") as f:
-        f.write("config = " + json.dumps(config))
-
-    with open(f"{folder_path}/data/snapshot.json", "w") as f:
-        f.write(item.snapshot.json())
-
-    with open(f"{folder_path}/data/models.json", "w") as f:
-        models_json_list = [model.dict() for model in item.models]
-        f.write(json.dumps(models_json_list))
-
-    process = await asyncio.subprocess.create_subprocess_shell(
-        f"modal deploy app.py",
-        stdout=asyncio.subprocess.PIPE,
-        stderr=asyncio.subprocess.PIPE,
-        cwd=folder_path,
-        env={**os.environ, "COLUMNS": "10000"}
-    )
-
-    if item.machine_id not in machine_logs_cache:
-        machine_logs_cache[item.machine_id] = []
-
-    machine_logs = machine_logs_cache[item.machine_id]
-    url_queue = asyncio.Queue()
-
-    async def read_stream(stream, isStderr, url_queue: asyncio.Queue):
-        while True:
-            line = await stream.readline()
-            if not line:
-                break
-
-            l = line.decode('utf-8').strip()
-            if not l:
-                continue
-
-            if not isStderr:
-                logger.info(l)
-                machine_logs.append({
-                    "logs": l,
-                    "timestamp": time.time()
-                })
-
-                if item.machine_id in machine_id_websocket_dict:
-                    await machine_id_websocket_dict[item.machine_id].send_text(
-                        json.dumps({
-                            "event": "LOGS",
-                            "data": {
-                                "machine_id": item.machine_id,
-                                "logs": l,
-                                "timestamp": time.time()
-                            }
-                        })
-                    )
-
-                if "Created comfyui_api =>" in l or ((l.startswith("https://") or l.startswith("│")) and l.endswith(".modal.run")):
-                    if "Created comfyui_api =>" in l:
-                        url = l.split("=>")[1].strip()
-                    elif "comfyui-api" in l:
-                        url = l.split("│")[1].strip() if l.startswith("│") else l
-
-                    if url:
-                        machine_logs.append({
-                            "logs": f"App image built, url: {url}",
-                            "timestamp": time.time()
-                        })
-
-                        await url_queue.put(url)
-
-                        if item.machine_id in machine_id_websocket_dict:
-                            await machine_id_websocket_dict[item.machine_id].send_text(
-                                json.dumps({
-                                    "event": "LOGS",
-                                    "data": {
-                                        "machine_id": item.machine_id,
-                                        "logs": f"App image built, url: {url}",
-                                        "timestamp": time.time()
-                                    }
-                                })
-                            )
-                            await machine_id_websocket_dict[item.machine_id].send_text(
-                                json.dumps({
-                                    "event": "FINISHED",
-                                    "data": {
-                                        "status": "success",
-                                    }
-                                })
-                            )
-
-            else:
-                logger.error(l)
-                machine_logs.append({
-                    "logs": l,
-                    "timestamp": time.time()
-                })
-
-                if item.machine_id in machine_id_websocket_dict:
-                    await machine_id_websocket_dict[item.machine_id].send_text(
-                        json.dumps({
-                            "event": "LOGS",
-                            "data": {
-                                "machine_id": item.machine_id,
-                                "logs": l,
-                                "timestamp": time.time()
-                            }
-                        })
-                    )
-                    await machine_id_websocket_dict[item.machine_id].send_text(
-                        json.dumps({
-                            "event": "FINISHED",
-                            "data": {
-                                "status": "failed",
-                            }
-                        })
-                    )
-
-    stdout_task = asyncio.create_task(read_stream(process.stdout, False, url_queue))
-    stderr_task = asyncio.create_task(read_stream(process.stderr, True, url_queue))
-
-    await asyncio.wait([stdout_task, stderr_task])
-    await process.wait()
-
-    url = await url_queue.get() if not url_queue.empty() else None
-
-    if item.machine_id in machine_id_websocket_dict and machine_id_websocket_dict[item.machine_id] is not None:
-        await machine_id_websocket_dict[item.machine_id].close()
-
-    if item.machine_id in machine_id_websocket_dict:
-        del machine_id_websocket_dict[item.machine_id]
-
-    if item.machine_id in machine_id_status:
-        machine_id_status[item.machine_id] = False
-
-    if process.returncode != 0:
-        logger.info("An error occurred.")
-        machine_logs.append({
-            "logs": "Unable to build the app image.",
-            "timestamp": time.time()
-        })
-        requests.post(
-            item.callback_url,
-            json={
-                "machine_id": item.machine_id,
-                "build_log": json.dumps(machine_logs)
-            }
-        )
-        if item.machine_id in machine_logs_cache:
-            del machine_logs_cache[item.machine_id]
-        return
-
-    if url is None:
-        machine_logs.append({
-            "logs": "App image built, but url is None, unable to parse the url.",
-            "timestamp": time.time()
-        })
-        requests.post(
-            item.callback_url,
-            json={
-                "machine_id": item.machine_id,
-                "build_log": json.dumps(machine_logs)
-            }
-        )
-        if item.machine_id in machine_logs_cache:
-            del machine_logs_cache[item.machine_id]
-        return
-
-    requests.post(
-        item.callback_url,
-        json={
-            "machine_id": item.machine_id,
-            "endpoint": url,
-            "build_log": json.dumps(machine_logs)
-        }
-    )
-    
-    if item.machine_id in machine_logs_cache:
-        del machine_logs_cache[item.machine_id]
-
-    logger.info("done")
-    logger.info(url)
-
-def start_loop(loop):
-    asyncio.set_event_loop(loop)
-    loop.run_forever()
-
-def run_in_new_thread(coroutine):
-    new_loop = asyncio.new_event_loop()
-    t = threading.Thread(target=start_loop, args=(new_loop,), daemon=True)
-    t.start()
-    asyncio.run_coroutine_threadsafe(coroutine, new_loop)
-    return t
-
-# Modal endpoint
-@modal_app.function()
-@modal.asgi_app()
-def app():
-    return fastapi_app
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(fastapi_app, host="0.0.0.0", port=8080, lifespan="on")

builder/modal-builder/src/template/app.py

@@ -307,5 +307,4 @@ def comfyui_app():
         },
     )()
 
-    proxy_app = make_simple_proxy_app(ProxyContext(config)) # Assign to variable
+    return make_simple_proxy_app(ProxyContext(config))
-    return proxy_app # Return the variable

comfy-nodes/external_audio.py

@@ -1,57 +0,0 @@
-import os
-import io
-import torchaudio
-from folder_paths import get_annotated_filepath
-
-class ComfyUIDeployExternalAudio:
-    RETURN_TYPES = ("AUDIO",)
-    RETURN_NAMES = ("audio",)
-    FUNCTION = "load_audio"
-    
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "input_id": (
-                    "STRING",
-                    {"multiline": False, "default": "input_audio"},
-                ),
-                "audio_file": ("STRING", {"default": ""}),
-            },
-            "optional": {
-                "default_value": ("AUDIO",),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-            }
-        }
-    
-    @classmethod
-    def VALIDATE_INPUTS(s, audio_file, **kwargs):
-        return True
-
-    def load_audio(self, input_id, audio_file, default_value=None, display_name=None, description=None):
-        if audio_file and audio_file != "":
-            if audio_file.startswith(('http://', 'https://')):
-                # Handle URL input
-                import requests
-                response = requests.get(audio_file)
-                audio_data = io.BytesIO(response.content)
-                waveform, sample_rate = torchaudio.load(audio_data)
-            else:
-                # Handle local file
-                audio_path = get_annotated_filepath(audio_file)
-                waveform, sample_rate = torchaudio.load(audio_path)
-            
-            audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
-            return (audio,)
-        else:
-            return (default_value,)
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"}

comfy-nodes/external_boolean.py

@@ -8,16 +8,6 @@ class ComfyUIDeployExternalBoolean:
                     {"multiline": False, "default": "input_bool"},
                 ),
                 "default_value": ("BOOLEAN", {"default": False})
-            },
-            "optional": {
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
             }
         }
 
@@ -26,7 +16,7 @@ class ComfyUIDeployExternalBoolean:
     
     FUNCTION = "run"
     
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         print(f"Node '{input_id}' processing with switch set to {default_value}")
         return [default_value]
     

comfy-nodes/external_checkpoints.py

@@ -5,12 +5,6 @@ import torch
 import folder_paths
 from tqdm import tqdm
 
-class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-        
-WILDCARD = AnyType("*")
-
 class ComfyUIDeployExternalCheckpoint:
     @classmethod
     def INPUT_TYPES(s):
@@ -23,25 +17,17 @@ class ComfyUIDeployExternalCheckpoint:
             },
             "optional": {
                 "default_value": (folder_paths.get_filename_list("checkpoints"), ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
             }
         }
 
-    RETURN_TYPES = (WILDCARD,)
+    RETURN_TYPES = (folder_paths.get_filename_list("checkpoints"),)
     RETURN_NAMES = ("path",)
 
     FUNCTION = "run"
 
     CATEGORY = "deploy"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         import requests
         import os
         import uuid

comfy-nodes/external_face_model.py

@@ -1,108 +0,0 @@
-from PIL import Image, ImageOps
-import numpy as np
-import torch
-import folder_paths
-
-
-class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-
-
-WILDCARD = AnyType("*")
-
-
-class ComfyUIDeployExternalFaceModel:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "input_id": (
-                    "STRING",
-                    {"multiline": False, "default": "input_reactor_face_model"},
-                ),
-            },
-            "optional": {
-                "default_face_model_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "face_model_save_name": (  # if `default_face_model_name` is a link to download a file, we will attempt to save it with this name
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
-                "face_model_url": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-            },
-        }
-
-    RETURN_TYPES = (WILDCARD,)
-    RETURN_NAMES = ("path",)
-
-    FUNCTION = "run"
-
-    CATEGORY = "deploy"
-
-    def run(
-        self,
-        input_id,
-        default_face_model_name=None,
-        face_model_save_name=None,
-        display_name=None,
-        description=None,
-        face_model_url=None,
-    ):
-        import requests
-        import os
-        import uuid
-
-        if face_model_url and face_model_url.startswith("http"):
-            if face_model_save_name:
-                existing_face_models = folder_paths.get_filename_list("reactor/faces")
-                # Check if face_model_save_name exists in the list
-                if face_model_save_name in existing_face_models:
-                    print(f"using face model: {face_model_save_name}")
-                    return (face_model_save_name,)
-            else:
-                face_model_save_name = str(uuid.uuid4()) + ".safetensors"
-            print(face_model_save_name)
-            print(folder_paths.folder_names_and_paths["reactor/faces"][0][0])
-            destination_path = os.path.join(
-                folder_paths.folder_names_and_paths["reactor/faces"][0][0],
-                face_model_save_name,
-            )
-
-            print(destination_path)
-            print(
-                "Downloading external face model - "
-                + face_model_url
-                + " to "
-                + destination_path
-            )
-            response = requests.get(
-                face_model_url,
-                headers={"User-Agent": "Mozilla/5.0"},
-                allow_redirects=True,
-            )
-            with open(destination_path, "wb") as out_file:
-                out_file.write(response.content)
-            return (face_model_save_name,)
-        else:
-            print(f"using face model: {default_face_model_name}")
-            return (default_face_model_name,)
-
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalFaceModel": ComfyUIDeployExternalFaceModel}
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ComfyUIDeployExternalFaceModel": "External Face Model (ComfyUI Deploy)"
-}

comfy-nodes/external_image.py

@@ -15,15 +15,6 @@ class ComfyUIDeployExternalImage:
             },
             "optional": {
                 "default_value": ("IMAGE",),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "default_value_url": ("STRING", {"image_preview": True, "default": ""}),
             }
         }
 
@@ -34,43 +25,31 @@ class ComfyUIDeployExternalImage:
 
     CATEGORY = "image"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None, default_value_url=None):
+    def run(self, input_id, default_value=None):
         image = default_value
-        
-        # Try both input_id and default_value_url
-        urls_to_try = [url for url in [input_id, default_value_url] if url]
-        
-        print(default_value_url)
-        
-        for url in urls_to_try:
         try:
-                if url.startswith('http'):
+            if input_id.startswith('http'):
                 import requests
                 from io import BytesIO
-                    print(f"Fetching image from url: {url}")
+                print("Fetching image from url: ", input_id)
-                    response = requests.get(url)
+                response = requests.get(input_id)
                 image = Image.open(BytesIO(response.content))
-                    break
+            elif input_id.startswith('data:image/png;base64,') or input_id.startswith('data:image/jpeg;base64,') or input_id.startswith('data:image/jpg;base64,'):
-                elif url.startswith(('data:image/png;base64,', 'data:image/jpeg;base64,', 'data:image/jpg;base64,')):
                 import base64
                 from io import BytesIO
                 print("Decoding base64 image")
-                    base64_image = url[url.find(",")+1:]
+                base64_image = input_id[input_id.find(",")+1:]
                 decoded_image = base64.b64decode(base64_image)
                 image = Image.open(BytesIO(decoded_image))
-                    break
+            else:
-            except:
+                raise ValueError("Invalid image url provided.")
-                continue
 
-        if image is not None:
-            try:
             image = ImageOps.exif_transpose(image)
             image = image.convert("RGB")
             image = np.array(image).astype(np.float32) / 255.0
             image = torch.from_numpy(image)[None,]
+            return [image]
         except:
-                pass
-                
             return [image]
 
 

comfy-nodes/external_image_alpha.py

@@ -15,14 +15,6 @@ class ComfyUIDeployExternalImageAlpha:
             },
             "optional": {
                 "default_value": ("IMAGE",),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
             }
         }
 
@@ -33,7 +25,7 @@ class ComfyUIDeployExternalImageAlpha:
 
     CATEGORY = "image"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         image = default_value
         try:
             if input_id.startswith('http'):

comfy-nodes/external_image_batch.py

@@ -21,14 +21,6 @@ class ComfyUIDeployExternalImageBatch:
             },
             "optional": {
                 "default_value": ("IMAGE",),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
             }
         }
 
@@ -39,34 +31,14 @@ class ComfyUIDeployExternalImageBatch:
 
     CATEGORY = "image"
     
-    def process_image(self, image):
+    def run(self, input_id, images=None, default_value=None):
-        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,]
-        return image_tensor
-    
-    def run(self, input_id, images=None, default_value=None, display_name=None, description=None):
-        import requests
-        import zipfile
-        import io
-        
         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') and img_input.endswith('.zip'):
+                if img_input.startswith('http'):
-                    print("Fetching zip file from url: ", img_input)
+                    import requests
-                    response = requests.get(img_input)
-                    zip_file = zipfile.ZipFile(io.BytesIO(response.content))
-                    for file_name in zip_file.namelist():
-                        if file_name.lower().endswith(('.png', '.jpg', '.jpeg')):
-                            with zip_file.open(file_name) as file:
-                                image = Image.open(file)
-                                image = self.process_image(image)
-                                processed_images.append(image)
-                elif  img_input.startswith('http'):
                     from io import BytesIO
                     print("Fetching image from url: ", img_input)
                     response = requests.get(img_input)

comfy-nodes/external_lora.py

@@ -5,14 +5,6 @@ import torch
 import folder_paths
 
 
-class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-
-
-WILDCARD = AnyType("*")
-
-
 class ComfyUIDeployExternalLora:
     @classmethod
     def INPUT_TYPES(s):
@@ -25,81 +17,40 @@ class ComfyUIDeployExternalLora:
             },
             "optional": {
                 "default_lora_name": (folder_paths.get_filename_list("loras"),),
-                "lora_save_name": (  # if `default_lora_name` is a link to download a file, we will attempt to save it with this name
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
-                "lora_url": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
             },
         }
 
-    RETURN_TYPES = (WILDCARD,)
+    RETURN_TYPES = (folder_paths.get_filename_list("loras"),)
     RETURN_NAMES = ("path",)
 
     FUNCTION = "run"
 
     CATEGORY = "deploy"
 
-    def run(
+    def run(self, input_id, default_lora_name=None):
-        self,
-        input_id,
-        default_lora_name=None,
-        lora_save_name=None,
-        display_name=None,
-        description=None,
-        lora_url=None,
-    ):
         import requests
         import os
         import uuid
 
-        if lora_url:
+        if default_lora_name.startswith("http"):
-            if lora_url.startswith("http"):
+            unique_filename = str(uuid.uuid4()) + ".safetensors"
-                if lora_save_name:
+            print(unique_filename)
-                    existing_loras = folder_paths.get_filename_list("loras")
-                    # Check if lora_save_name exists in the list
-                    if lora_save_name in existing_loras:
-                        print(f"using lora: {lora_save_name}")
-                        return (lora_save_name,)
-                else:
-                    lora_save_name = str(uuid.uuid4()) + ".safetensors"
-                print(lora_save_name)
             print(folder_paths.folder_names_and_paths["loras"][0][0])
             destination_path = os.path.join(
-                    folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
+                folder_paths.folder_names_and_paths["loras"][0][0], unique_filename
             )
             print(destination_path)
-                print(
+            print("Downloading external lora - " + input_id + " to " + destination_path)
-                    "Downloading external lora - "
-                    + lora_url
-                    + " to "
-                    + destination_path
-                )
             response = requests.get(
-                    lora_url,
+                input_id,
                 headers={"User-Agent": "Mozilla/5.0"},
                 allow_redirects=True,
             )
             with open(destination_path, "wb") as out_file:
                 out_file.write(response.content)
-                print(f"Ext Lora loading: {lora_url} to {lora_save_name}")
+            return (unique_filename,)
-                return (lora_save_name,)
         else:
-                print(f"Ext Lora loading: {lora_url}")
+            print(f"using lora: {default_lora_name}")
-                return (lora_url,)
-        else:
-            print(f"Ext Lora loading: {default_lora_name}")
             return (default_lora_name,)
 
 

comfy-nodes/external_number.py

@@ -16,15 +16,7 @@ class ComfyUIDeployExternalNumber:
             "optional": {
                 "default_value": (
                     "FLOAT",
-                    {"multiline": True, "display": "number", "default": 0, "min": -2147483647, "max": 2147483647, "step": 0.01},
+                    {"multiline": True, "display": "number", "default": 0, "step": 0.01},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
                 ),
             }
         }
@@ -36,7 +28,7 @@ class ComfyUIDeployExternalNumber:
 
     CATEGORY = "number"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         try:
             float_value = float(input_id)
             print("my number", float_value)

comfy-nodes/external_number_int.py

@@ -16,15 +16,7 @@ class ComfyUIDeployExternalNumberInt:
             "optional": {
                 "default_value": (
                     "INT",
-                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0},
+                    {"multiline": True, "display": "number", "default": 0},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
                 ),
             }
         }
@@ -36,7 +28,7 @@ class ComfyUIDeployExternalNumberInt:
 
     CATEGORY = "number"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         if not input_id or (isinstance(input_id, str) and not input_id.strip().isdigit()):
             return [default_value]
         return [int(input_id)]

comfy-nodes/external_number_slider.py

@@ -11,23 +11,15 @@ class ComfyUIDeployExternalNumberSlider:
             "optional": {
                 "default_value": (
                     "FLOAT",
-                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0.5, "step": 0.01},
+                    {"multiline": True, "display": "number", "default": 0.5, "step": 0.01},
                 ),
                 "min_value": (
                     "FLOAT",
-                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0, "step": 0.01},
+                    {"multiline": True, "display": "number", "default": 0, "step": 0.01},
                 ),
                 "max_value": (
                     "FLOAT",
-                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 1, "step": 0.01},
+                    {"multiline": True, "display": "number", "default": 1, "step": 0.01},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
                 ),
             }
         }
@@ -39,7 +31,7 @@ class ComfyUIDeployExternalNumberSlider:
 
     CATEGORY = "number"
 
-    def run(self, input_id, default_value=None, min_value=0, max_value=1, display_name=None, description=None):
+    def run(self, input_id, default_value=None, min_value=0, max_value=1):
         try:
             float_value = float(input_id)
             if min_value <= float_value <= max_value:

comfy-nodes/external_string_combine.py

@@ -1,53 +0,0 @@
-import re
-
-
-class StringFunction:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "action": (["append", "replace"], {}),
-                "tidy_tags": (["yes", "no"], {}),
-            },
-            "optional": {
-                "text_a": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                "text_b": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-                "text_c": ("STRING", {"multiline": True, "dynamicPrompts": False}),
-            },
-        }
-
-    RETURN_TYPES = ("STRING",)
-    FUNCTION = "exec"
-    CATEGORY = "utils"
-    OUTPUT_NODE = True
-
-    def exec(self, action, tidy_tags, text_a="", text_b="", text_c=""):
-        tidy_tags = tidy_tags == "yes"
-        out = ""
-        if action == "append":
-            out = (", " if tidy_tags else "").join(
-                filter(None, [text_a, text_b, text_c])
-            )
-        else:
-            if text_c is None:
-                text_c = ""
-            if text_b.startswith("/") and text_b.endswith("/"):
-                regex = text_b[1:-1]
-                out = re.sub(regex, text_c, text_a)
-            else:
-                out = text_a.replace(text_b, text_c)
-        if tidy_tags:
-            out = re.sub(r"\s{2,}", " ", out)
-            out = out.replace(" ,", ",")
-            out = re.sub(r",{2,}", ",", out)
-            out = out.strip()
-        return {"ui": {"text": (out,)}, "result": (out,)}
-
-
-NODE_CLASS_MAPPINGS = {
-    "ComfyUIDeployStringCombine": StringFunction,
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ComfyUIDeployStringCombine": "String Combine (ComfyUI Deploy)",
-}

comfy-nodes/external_text.py

@@ -18,14 +18,6 @@ class ComfyUIDeployExternalText:
                     "STRING",
                     {"multiline": True, "default": ""},
                 ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
             }
         }
 
@@ -36,7 +28,7 @@ class ComfyUIDeployExternalText:
 
     CATEGORY = "text"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None):
         return [default_value]
 
 

comfy-nodes/external_text_any.py

@@ -1,46 +0,0 @@
-class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-
-
-WILDCARD = AnyType("*")
-
-class ComfyUIDeployExternalTextAny:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "input_id": (
-                    "STRING",
-                    {"multiline": False, "default": "input_text"},
-                ),
-            },
-            "optional": {
-                "default_value": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
-            }
-        }
-
-    RETURN_TYPES = (WILDCARD,)
-    RETURN_NAMES = ("text",)
-
-    FUNCTION = "run"
-
-    CATEGORY = "text"
-
-    def run(self, input_id, default_value=None, display_name=None, description=None):
-        return [default_value]
-
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextAny": ComfyUIDeployExternalTextAny}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextAny": "External Text Any (ComfyUI Deploy)"}

comfy-nodes/external_video.py

@@ -1,15 +1,10 @@
-# credit goes to https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite
+# credit goes to https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite and is meant to work with
-# Intended to work with https://github.com/NicholasKao1029/ComfyUI-VideoHelperSuite/tree/main
 import os
 import itertools
 import numpy as np
 import torch
-from typing import Union
-from torch import Tensor
 import cv2
-import psutil
 
-from collections.abc import Mapping
 import folder_paths
 from comfy.utils import common_upscale
 
@@ -95,25 +90,13 @@ if gifski_path is None:
         gifski_path = shutil.which("gifski")
 
 
-def is_safe_path(path):
-    if "VHS_STRICT_PATHS" not in os.environ:
-        return True
-    basedir = os.path.abspath(".")
-    try:
-        common_path = os.path.commonpath([basedir, path])
-    except:
-        # Different drive on windows
-        return False
-    return common_path == basedir
-
-
 def get_sorted_dir_files_from_directory(
     directory: str,
     skip_first_images: int = 0,
     select_every_nth: int = 1,
     extensions: Iterable = None,
 ):
-    directory = strip_path(directory)
+    directory = directory.strip()
     dir_files = os.listdir(directory)
     dir_files = sorted(dir_files)
     dir_files = [os.path.join(directory, x) for x in dir_files]
@@ -194,59 +177,18 @@ def requeue_workflow(requeue_required=(-1, True)):
 
 
 def get_audio(file, start_time=0, duration=0):
-    args = [ffmpeg_path, "-i", file]
+    args = [ffmpeg_path, "-v", "error", "-i", file]
     if start_time > 0:
         args += ["-ss", str(start_time)]
     if duration > 0:
         args += ["-t", str(duration)]
     try:
-        # TODO: scan for sample rate and maintain
         res = subprocess.run(
-            args + ["-f", "f32le", "-"], capture_output=True, check=True
+            args + ["-f", "wav", "-"], stdout=subprocess.PIPE, check=True
-        )
+        ).stdout
-        audio = torch.frombuffer(bytearray(res.stdout), dtype=torch.float32)
-        match = re.search(", (\\d+) Hz, (\\w+), ", res.stderr.decode("utf-8"))
     except subprocess.CalledProcessError as e:
-        raise Exception(
+        return False
-            f"VHS failed to extract audio from {file}:\n" + e.stderr.decode("utf-8")
+    return res
-        )
-    if match:
-        ar = int(match.group(1))
-        # NOTE: Just throwing an error for other channel types right now
-        # Will deal with issues if they come
-        ac = {"mono": 1, "stereo": 2}[match.group(2)]
-    else:
-        ar = 44100
-        ac = 2
-    audio = audio.reshape((-1, ac)).transpose(0, 1).unsqueeze(0)
-    return {"waveform": audio, "sample_rate": ar}
-
-
-class LazyAudioMap(Mapping):
-    def __init__(self, file, start_time, duration):
-        self.file = file
-        self.start_time = start_time
-        self.duration = duration
-        self._dict = None
-
-    def __getitem__(self, key):
-        if self._dict is None:
-            self._dict = get_audio(self.file, self.start_time, self.duration)
-        return self._dict[key]
-
-    def __iter__(self):
-        if self._dict is None:
-            self._dict = get_audio(self.file, self.start_time, self.duration)
-        return iter(self._dict)
-
-    def __len__(self):
-        if self._dict is None:
-            self._dict = get_audio(self.file, self.start_time, self.duration)
-        return len(self._dict)
-
-
-def lazy_get_audio(file, start_time=0, duration=0):
-    return LazyAudioMap(file, start_time, duration)
 
 
 def lazy_eval(func):
@@ -288,19 +230,6 @@ def validate_sequence(path):
     return False
 
 
-def strip_path(path):
-    # This leaves whitespace inside quotes and only a single "
-    # thus ' ""test"' -> '"test'
-    # consider path.strip(string.whitespace+"\"")
-    # or weightier re.fullmatch("[\\s\"]*(.+?)[\\s\"]*", path).group(1)
-    path = path.strip()
-    if path.startswith('"'):
-        path = path[1:]
-    if path.endswith('"'):
-        path = path[:-1]
-    return path
-
-
 def hash_path(path):
     if path is None:
         return "input"
@@ -357,145 +286,6 @@ def target_size(
     return (width, height)
 
 
-def validate_index(
-    index: int,
-    length: int = 0,
-    is_range: bool = False,
-    allow_negative=False,
-    allow_missing=False,
-) -> int:
-    # if part of range, do nothing
-    if is_range:
-        return index
-    # otherwise, validate index
-    # validate not out of range - only when latent_count is passed in
-    if length > 0 and index > length - 1 and not allow_missing:
-        raise IndexError(f"Index '{index}' out of range for {length} item(s).")
-    # if negative, validate not out of range
-    if index < 0:
-        if not allow_negative:
-            raise IndexError(f"Negative indeces not allowed, but was '{index}'.")
-        conv_index = length + index
-        if conv_index < 0 and not allow_missing:
-            raise IndexError(
-                f"Index '{index}', converted to '{conv_index}' out of range for {length} item(s)."
-            )
-        index = conv_index
-    return index
-
-
-def convert_to_index_int(
-    raw_index: str,
-    length: int = 0,
-    is_range: bool = False,
-    allow_negative=False,
-    allow_missing=False,
-) -> int:
-    try:
-        return validate_index(
-            int(raw_index),
-            length=length,
-            is_range=is_range,
-            allow_negative=allow_negative,
-            allow_missing=allow_missing,
-        )
-    except ValueError as e:
-        raise ValueError(f"Index '{raw_index}' must be an integer.", e)
-
-
-def convert_str_to_indexes(
-    indexes_str: str, length: int = 0, allow_missing=False
-) -> list[int]:
-    if not indexes_str:
-        return []
-    int_indexes = list(range(0, length))
-    allow_negative = length > 0
-    chosen_indexes = []
-    # parse string - allow positive ints, negative ints, and ranges separated by ':'
-    groups = indexes_str.split(",")
-    groups = [g.strip() for g in groups]
-    for g in groups:
-        # parse range of indeces (e.g. 2:16)
-        if ":" in g:
-            index_range = g.split(":", 2)
-            index_range = [r.strip() for r in index_range]
-
-            start_index = index_range[0]
-            if len(start_index) > 0:
-                start_index = convert_to_index_int(
-                    start_index,
-                    length=length,
-                    is_range=True,
-                    allow_negative=allow_negative,
-                    allow_missing=allow_missing,
-                )
-            else:
-                start_index = 0
-            end_index = index_range[1]
-            if len(end_index) > 0:
-                end_index = convert_to_index_int(
-                    end_index,
-                    length=length,
-                    is_range=True,
-                    allow_negative=allow_negative,
-                    allow_missing=allow_missing,
-                )
-            else:
-                end_index = length
-            # support step as well, to allow things like reversing, every-other, etc.
-            step = 1
-            if len(index_range) > 2:
-                step = index_range[2]
-                if len(step) > 0:
-                    step = convert_to_index_int(
-                        step,
-                        length=length,
-                        is_range=True,
-                        allow_negative=True,
-                        allow_missing=True,
-                    )
-                else:
-                    step = 1
-            # if latents were passed in, base indeces on known latent count
-            if len(int_indexes) > 0:
-                chosen_indexes.extend(int_indexes[start_index:end_index][::step])
-            # otherwise, assume indeces are valid
-            else:
-                chosen_indexes.extend(list(range(start_index, end_index, step)))
-        # parse individual indeces
-        else:
-            chosen_indexes.append(
-                convert_to_index_int(
-                    g,
-                    length=length,
-                    allow_negative=allow_negative,
-                    allow_missing=allow_missing,
-                )
-            )
-    return chosen_indexes
-
-
-def select_indexes(input_obj: Union[Tensor, list], idxs: list):
-    if type(input_obj) == Tensor:
-        return input_obj[idxs]
-    else:
-        return [input_obj[i] for i in idxs]
-
-
-def select_indexes_from_str(
-    input_obj: Union[Tensor, list], indexes: str, err_if_missing=True, err_if_empty=True
-):
-    real_idxs = convert_str_to_indexes(
-        indexes, len(input_obj), allow_missing=not err_if_missing
-    )
-    if err_if_empty and len(real_idxs) == 0:
-        raise Exception(f"Nothing was selected based on indexes found in '{indexes}'.")
-    return select_indexes(input_obj, real_idxs)
-
-
-###
-
-
 def cv_frame_generator(
     video,
     force_rate,
@@ -505,10 +295,9 @@ def cv_frame_generator(
     meta_batch=None,
     unique_id=None,
 ):
-    video_cap = cv2.VideoCapture(strip_path(video))
+    video_cap = cv2.VideoCapture(video)
     if not video_cap.isOpened():
         raise ValueError(f"{video} could not be loaded with cv.")
-    pbar = None
 
     # extract video metadata
     fps = video_cap.get(cv2.CAP_PROP_FPS)
@@ -530,8 +319,6 @@ def cv_frame_generator(
         target_frame_time = 1 / force_rate
 
     yield (width, height, fps, duration, total_frames, target_frame_time)
-    if meta_batch is not None:
-        yield min(frame_load_cap, total_frames)
 
     time_offset = target_frame_time - base_frame_time
     while video_cap.isOpened():
@@ -562,8 +349,7 @@ def cv_frame_generator(
         frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
         # convert frame to comfyui's expected format
         # TODO: frame contains no exif information. Check if opencv2 has already applied
-        frame = np.array(frame, dtype=np.float32)
+        frame = np.array(frame, dtype=np.float32) / 255.0
-        torch.from_numpy(frame).div_(255)
         if prev_frame is not None:
             inp = yield prev_frame
             if inp is not None:
@@ -571,8 +357,6 @@ def cv_frame_generator(
                 return
         prev_frame = frame
         frames_added += 1
-        if pbar is not None:
-            pbar.update_absolute(frames_added, frame_load_cap)
         # if cap exists and we've reached it, stop processing frames
         if frame_load_cap > 0 and frames_added >= frame_load_cap:
             break
@@ -583,17 +367,6 @@ def cv_frame_generator(
         yield prev_frame
 
 
-def batched(it, n):
-    while batch := tuple(itertools.islice(it, n)):
-        yield batch
-
-
-def batched_vae_encode(images, vae, frames_per_batch):
-    for batch in batched(images, frames_per_batch):
-        image_batch = torch.from_numpy(np.array(batch))
-        yield from vae.encode(image_batch).numpy()
-
-
 def load_video_cv(
     video: str,
     force_rate: int,
@@ -605,8 +378,6 @@ def load_video_cv(
     select_every_nth: int,
     meta_batch=None,
     unique_id=None,
-    memory_limit_mb=None,
-    vae=None,
 ):
     if meta_batch is None or unique_id not in meta_batch.inputs:
         gen = cv_frame_generator(
@@ -630,89 +401,30 @@ def load_video_cv(
                 total_frames,
                 target_frame_time,
             )
-            meta_batch.total_frames = min(meta_batch.total_frames, next(gen))
 
     else:
         (gen, width, height, fps, duration, total_frames, target_frame_time) = (
             meta_batch.inputs[unique_id]
         )
 
-    memory_limit = None
-    if memory_limit_mb is not None:
-        memory_limit *= 2**20
-    else:
-        # TODO: verify if garbage collection should be performed here.
-        # leaves ~128 MB unreserved for safety
-        try:
-            memory_limit = (
-                psutil.virtual_memory().available + psutil.swap_memory().free
-            ) - 2**27
-        except:
-            print(
-                "Failed to calculate available memory. Memory load limit has been disabled"
-            )
-    if memory_limit is not None:
-        if vae is not None:
-            # space required to load as f32, exist as latent with wiggle room, decode to f32
-            max_loadable_frames = int(
-                memory_limit // (width * height * 3 * (4 + 4 + 1 / 10))
-            )
-        else:
-            # TODO: use better estimate for when vae is not None
-            # Consider completely ignoring for load_latent case?
-            max_loadable_frames = int(memory_limit // (width * height * 3 * (0.1)))
     if meta_batch is not None:
-            if meta_batch.frames_per_batch > max_loadable_frames:
-                raise RuntimeError(
-                    f"Meta Batch set to {meta_batch.frames_per_batch} frames but only {max_loadable_frames} can fit in memory"
-                )
         gen = itertools.islice(gen, meta_batch.frames_per_batch)
-        else:
-            original_gen = gen
-            gen = itertools.islice(gen, max_loadable_frames)
-    downscale_ratio = getattr(vae, "downscale_ratio", 8)
-    frames_per_batch = (1920 * 1080 * 16) // (width * height) or 1
-    if force_size != "Disabled" or vae is not None:
-        new_size = target_size(
-            width, height, force_size, custom_width, custom_height, downscale_ratio
-        )
-        if new_size[0] != width or new_size[1] != height:
 
-            def rescale(frame):
-                s = torch.from_numpy(
-                    np.fromiter(frame, np.dtype((np.float32, (height, width, 3))))
-                )
-                s = s.movedim(-1, 1)
-                s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
-                return s.movedim(1, -1).numpy()
-
-            gen = itertools.chain.from_iterable(
-                map(rescale, batched(gen, frames_per_batch))
-            )
-    else:
-        new_size = width, height
-    if vae is not None:
-        gen = batched_vae_encode(gen, vae, frames_per_batch)
-        vw, vh = new_size[0] // downscale_ratio, new_size[1] // downscale_ratio
-        images = torch.from_numpy(np.fromiter(gen, np.dtype((np.float32, (4, vh, vw)))))
-    else:
     # Some minor wizardry to eliminate a copy and reduce max memory by a factor of ~2
     images = torch.from_numpy(
-            np.fromiter(gen, np.dtype((np.float32, (new_size[1], new_size[0], 3))))
+        np.fromiter(gen, np.dtype((np.float32, (height, width, 3))))
     )
-    if meta_batch is None and memory_limit is not None:
-        try:
-            next(original_gen)
-            raise RuntimeError(
-                f"Memory limit hit after loading {len(images)} frames. Stopping execution."
-            )
-        except StopIteration:
-            pass
     if len(images) == 0:
         raise RuntimeError("No frames generated")
+    if force_size != "Disabled":
+        new_size = target_size(width, height, force_size, custom_width, custom_height)
+        if new_size[0] != width or new_size[1] != height:
+            s = images.movedim(-1, 1)
+            s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
+            images = s.movedim(1, -1)
 
     # Setup lambda for lazy audio capture
-    audio = lazy_get_audio(
+    audio = lambda: get_audio(
         video,
         skip_first_frames * target_frame_time,
         frame_load_cap * target_frame_time * select_every_nth,
@@ -728,16 +440,13 @@ def load_video_cv(
         "loaded_fps": 1 / target_frame_time,
         "loaded_frame_count": len(images),
         "loaded_duration": len(images) * target_frame_time,
-        "loaded_width": new_size[0],
+        "loaded_width": images.shape[2],
-        "loaded_height": new_size[1],
+        "loaded_height": images.shape[1],
     }
-    if vae is None:
+
-        return (images, len(images), audio, video_info, None)
+    return (images, len(images), lazy_eval(audio), video_info)
-    else:
-        return (None, len(images), audio, video_info, {"samples": images})
 
 
-# modeled after Video upload node
 class ComfyUIDeployExternalVideo:
     @classmethod
     def INPUT_TYPES(s):
@@ -748,46 +457,68 @@ class ComfyUIDeployExternalVideo:
                 file_parts = f.split(".")
                 if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
                     files.append(f)
-        return {"required": {
+        return {
+            "required": {
                 "input_id": (
                     "STRING",
                     {"multiline": False, "default": "input_video"},
                 ),
                 "force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
-                     "force_size": (["Disabled", "Custom Height", "Custom Width", "Custom", "256x?", "?x256", "256x256", "512x?", "?x512", "512x512"],),
+                "force_size": (
-                     "custom_width": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
+                    [
-                     "custom_height": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
+                        "Disabled",
-                     "frame_load_cap": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
+                        "Custom Height",
-                     "skip_first_frames": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
+                        "Custom Width",
-                     "select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
+                        "Custom",
+                        "256x?",
+                        "?x256",
+                        "256x256",
+                        "512x?",
+                        "?x512",
+                        "512x512",
+                    ],
+                ),
+                "custom_width": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "custom_height": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "frame_load_cap": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "skip_first_frames": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "select_every_nth": (
+                    "INT",
+                    {"default": 1, "min": 1, "max": BIGMAX, "step": 1},
+                ),
             },
             "optional": {
                 "meta_batch": ("VHS_BatchManager",),
-                    "vae": ("VAE",),
+                "default_value": (sorted(files),),
-                    "default_video": (sorted(files),),
-                    "display_name": (
-                        "STRING",
-                        {"multiline": False, "default": ""},
-                    ),
-                    "description": (
-                        "STRING",
-                        {"multiline": True, "default": ""},
-                    ),
-                },
-                "hidden": {
-                    "unique_id": "UNIQUE_ID"
             },
+            "hidden": {"unique_id": "UNIQUE_ID"},
         }
 
     CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
 
-    RETURN_TYPES = ("IMAGE", "INT", "AUDIO", "VHS_VIDEOINFO", "LATENT")
+    RETURN_TYPES = (
+        "IMAGE",
+        "INT",
+        "VHS_AUDIO",
+        "VHS_VIDEOINFO",
+    )
     RETURN_NAMES = (
         "IMAGE",
         "frame_count",
         "audio",
         "video_info",
-        "LATENT",
     )
 
     FUNCTION = "load_video"
@@ -804,6 +535,8 @@ class ComfyUIDeployExternalVideo:
         meta_batch = kwargs.get("meta_batch")
         unique_id = kwargs.get("unique_id")
 
+        video = kwargs.get("default_value")
+        video_path = folder_paths.get_annotated_filepath(video.strip('"'))
 
         input_dir = folder_paths.get_input_directory()
         if input_id.startswith("http"):
@@ -833,11 +566,8 @@ class ComfyUIDeployExternalVideo:
                     leave=True,
                 ):
                     out_file.write(chunk)
-        else:
+
-            video = kwargs.get("default_video", None)
+        print("video path: ", video_path)
-            if video is None:
-                raise "No default video given and no external video provided"
-            video_path = folder_paths.get_annotated_filepath(video.strip('"'))
 
         return load_video_cv(
             video=video_path,

comfy-nodes/model_list.py

@@ -1,60 +0,0 @@
-import folder_paths
-class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-
-from os import walk
-
-WILDCARD = AnyType("*")
-
-MODEL_EXTENSIONS = {
-    "safetensors": "SafeTensors file format",
-    "ckpt": "Checkpoint file",
-    "pth": "PyTorch serialized file",
-    "pkl": "Pickle file",
-    "onnx": "ONNX file",
-}
-
-def fetch_files(path):
-    for (dirpath, dirnames, filenames) in walk(path):
-        fs = []
-        if len(dirnames) > 0:
-            for dirname in dirnames:
-                fs.extend(fetch_files(f"{dirpath}/{dirname}"))
-        for filename in filenames:
-            # Remove "./models/" from the beginning of dirpath
-            relative_dirpath = dirpath.replace("./models/", "", 1)
-            file_path = f"{relative_dirpath}/{filename}"
-            
-            # Only add files that are known model extensions
-            file_extension = filename.split('.')[-1].lower()
-            if file_extension in MODEL_EXTENSIONS:
-                fs.append(file_path)
-
-        return fs
-allModels = fetch_files("./models")
-
-class ComfyUIDeployModalList:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "model": (allModels, ),
-            }
-        }
-
-    RETURN_TYPES = (WILDCARD,)
-    RETURN_NAMES = ("model",)
-
-    FUNCTION = "run"
-
-    CATEGORY = "model"
-
-    def run(self, model=""):
-        # Split the model path by '/' and select the last item
-        model_name = model.split('/')[-1]
-        return [model_name]
-
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployModelList": ComfyUIDeployModalList}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployModelList": "Model List (ComfyUI Deploy)"}

comfy-nodes/output_image.py

@@ -1,92 +0,0 @@
-import os
-import json
-import numpy as np
-from PIL import Image
-from PIL.PngImagePlugin import PngInfo
-import folder_paths
-
-
-class ComfyDeployOutputImage:
-    def __init__(self):
-        self.output_dir = folder_paths.get_output_directory()
-        self.type = "output"
-        self.prefix_append = ""
-        self.compress_level = 4
-
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "images": ("IMAGE", {"tooltip": "The images to save."}),
-                "filename_prefix": (
-                    "STRING",
-                    {
-                        "default": "ComfyUI",
-                        "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
-                    },
-                ),
-                "file_type": (["png", "jpg", "webp"], {"default": "webp"}),
-                "quality": ("INT", {"default": 80, "min": 1, "max": 100, "step": 1}),
-            },
-            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-
-    OUTPUT_NODE = True
-
-    CATEGORY = "output"
-    DESCRIPTION = "Saves the input images to your ComfyUI output directory."
-
-    def run(
-        self,
-        images,
-        filename_prefix="ComfyUI",
-        file_type="png",
-        quality=80,
-        prompt=None,
-        extra_pnginfo=None,
-    ):
-        filename_prefix += self.prefix_append
-        full_output_folder, filename, counter, subfolder, filename_prefix = (
-            folder_paths.get_save_image_path(
-                filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
-            )
-        )
-        results = list()
-        for batch_number, image in enumerate(images):
-            i = 255.0 * image.cpu().numpy()
-            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
-            metadata = PngInfo()
-            if prompt is not None:
-                metadata.add_text("prompt", json.dumps(prompt))
-            if extra_pnginfo is not None:
-                for x in extra_pnginfo:
-                    metadata.add_text(x, json.dumps(extra_pnginfo[x]))
-
-            filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
-            file = f"{filename_with_batch_num}_{counter:05}_.{file_type}"
-            file_path = os.path.join(full_output_folder, file)
-
-            if file_type == "png":
-                img.save(
-                    file_path, pnginfo=metadata, compress_level=self.compress_level
-                )
-            elif file_type == "jpg":
-                img.save(file_path, quality=quality, optimize=True)
-            elif file_type == "webp":
-                img.save(file_path, quality=quality)
-
-            results.append(
-                {"filename": file, "subfolder": subfolder, "type": self.type}
-            )
-            counter += 1
-
-        return {"ui": {"images": results}}
-
-
-NODE_CLASS_MAPPINGS = {"ComfyDeployOutputImage": ComfyDeployOutputImage}
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ComfyDeployOutputImage": "Image Output (ComfyDeploy)"
-}

globals.py

@@ -6,12 +6,10 @@ 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"
@@ -19,60 +17,48 @@ class Status(Enum):
     FAILED = "failed"
     UPLOADING = "uploading"
 
-
 class StreamingPrompt(BaseModel):
     workflow_api: Any
     auth_token: str
     inputs: dict[str, Union[str, bytes, Image.Image]]
     running_prompt_ids: set[str] = set()
-    status_endpoint: Optional[str]
+    status_endpoint: str
-    file_upload_endpoint: Optional[str]
+    file_upload_endpoint: str
-    workflow: Any
-    gpu_event_id: Optional[str] = None
-
     
 class SimplePrompt(BaseModel):
-    status_endpoint: Optional[str]
+    status_endpoint: str
-    file_upload_endpoint: Optional[str]
+    file_upload_endpoint: str
-
-    token: Optional[str]
-
     workflow_api: dict
     status: Status = Status.NOT_STARTED
     progress: set = set()
-    last_updated_node: Optional[str] = None
+    last_updated_node: Optional[str] = None,
     uploading_nodes: set = set()
     done: bool = False
-    is_realtime: bool = False
+    is_realtime: bool = False,
-    start_time: Optional[float] = None
+    start_time: Optional[float] = None,
-    gpu_event_id: Optional[str] = None
-
 
 sockets = dict()
 prompt_metadata: dict[str, SimplePrompt] = {}
 streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
 
-
 class BinaryEventTypes:
     PREVIEW_IMAGE = 1
     UNENCODED_PREVIEW_IMAGE = 2
     
-
 max_output_id_length = 24
 
-
+async def send_image(image_data, sid=None, output_id:str = None):
-async def send_image(image_data, sid=None, output_id: str = None):
     max_length = max_output_id_length
     output_id = output_id[:max_length]
-    padded_output_id = output_id.ljust(max_length, "\x00")
+    padded_output_id = output_id.ljust(max_length, '\x00')
-    encoded_output_id = padded_output_id.encode("ascii", "replace")
+    encoded_output_id = padded_output_id.encode('ascii', 'replace')
     
     image_type = image_data[0]
     image = image_data[1]
     max_size = image_data[2]
     quality = image_data[3]
     if max_size is not None:
-        if hasattr(Image, "Resampling"):
+        if hasattr(Image, 'Resampling'):
             resampling = Image.Resampling.BILINEAR
         else:
             resampling = Image.ANTIALIAS
@@ -101,18 +87,12 @@ async def send_image(image_data, sid=None, output_id: str = None):
     preview_bytes = bytesIO.getvalue()
     await send_bytes(BinaryEventTypes.PREVIEW_IMAGE, preview_bytes, sid=sid)
         
-
 async def send_socket_catch_exception(function, message):
     try:
         await function(message)
-    except (
+    except (aiohttp.ClientError, aiohttp.ClientPayloadError, ConnectionResetError) as err:
-        aiohttp.ClientError,
-        aiohttp.ClientPayloadError,
-        ConnectionResetError,
-    ) as err:
         print("send error:", err)
 
-
 def encode_bytes(event, data):
     if not isinstance(event, int):
         raise RuntimeError(f"Binary event types must be integers, got {event}")
@@ -122,7 +102,6 @@ def encode_bytes(event, data):
     message.extend(data)
     return message
 
-
 async def send_bytes(event, data, sid=None):
     message = encode_bytes(event, data)
     

pyproject.toml

@@ -1,8 +1,8 @@
 [project]
 name = "comfyui-deploy"
 description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
-version = "1.1.0"
+version = "1.0.0"
-license = { file = "LICENSE" }
+license = "LICENSE"
 dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
 
 [project.urls]

requirements.txt

@@ -2,6 +2,3 @@ aiofiles
 pydantic
 opencv-python
 imageio-ffmpeg
-brotli
-tabulate
-# logfire

web-plugin/api.js

@@ -0,0 +1,4 @@
+/** @typedef {import('../../../web/scripts/api.js').api} API*/
+import { api as _api } from '../../scripts/api.js';
+/** @type {API} */
+export const api = _api;

web-plugin/app.js

@@ -0,0 +1,4 @@
+/** @typedef {import('../../../web/scripts/app.js').ComfyApp} ComfyApp*/
+import { app as _app } from '../../scripts/app.js';
+/** @type {ComfyApp} */
+export const app = _app;

web-plugin/widgets.js

@@ -0,0 +1,18 @@
+// /** @typedef {import('../../../web/scripts/api.js').api} API*/
+// import { api as _api } from "../../scripts/api.js";
+// /** @type {API} */
+// export const api = _api;
+
+/** @typedef {typeof import('../../../web/scripts/widgets.js').ComfyWidgets} Widgets*/
+import { ComfyWidgets as _ComfyWidgets } from "../../scripts/widgets.js";
+
+/**
+ * @type {Widgets}
+ */
+export const ComfyWidgets = _ComfyWidgets;
+
+// import { LGraphNode as _LGraphNode } from "../../types/litegraph.js";
+
+/** @typedef {typeof import('../../../web/types/litegraph.js').LGraphNode} LGraphNode*/
+/** @type {LGraphNode}*/
+export const LGraphNode = LiteGraph.LGraphNode;

web/package.json

@@ -74,7 +74,7 @@
     "mitata": "^0.1.6",
     "ms": "^2.1.3",
     "nanoid": "^5.0.4",
-    "next": "14.2",
+    "next": "14.1",
     "next-plausible": "^3.12.0",
     "next-themes": "^0.2.1",
     "next-usequerystate": "^1.13.2",

web/src/components/customInputNodes.tsx

@@ -6,5 +6,4 @@ export const customInputNodes: Record<string, string> = {
   ComfyUIDeployExternalNumberInt: "integer",
   ComfyUIDeployExternalLora: "string - (public lora download url)",
   ComfyUIDeployExternalCheckpoint: "string - (public checkpoints download url)",
-  ComfyUIDeployExternalFaceModel: "string - (public face model download url)",
 };

web/src/routes/registerCreateRunRoute.ts

@@ -51,9 +51,7 @@ const createRunRoute = createRoute({
 export const registerCreateRunRoute = (app: App) => {
   app.openapi(createRunRoute, async (c) => {
     const data = c.req.valid("json");
-    const proto = c.req.headers.get('x-forwarded-proto')  || "http";
+    const origin = new URL(c.req.url).origin;
-    const host = c.req.headers.get('x-forwarded-host') || c.req.headers.get('host');
-    const origin = `${proto}://${host}` || new URL(c.req.url).origin;
     const apiKeyTokenData = c.get("apiKeyTokenData")!;
 
     const { deployment_id, inputs } = data;

web/src/server/createRun.ts

@@ -102,7 +102,7 @@ export const createRun = withServerPromise(
 
     let prompt_id: string | undefined = undefined;
     const shareData = {
-      workflow_api_raw: workflow_api,
+      workflow_api: workflow_api,
       status_endpoint: `${origin}/api/update-run`,
       file_upload_endpoint: `${origin}/api/file-upload`,
     };