more context

README.md

@@ -11,26 +11,46 @@ pinned: false
 
 This demo showcases [Latent Consistency Model (LCM)](https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7) using [Diffusers](https://github.com/huggingface/diffusers/tree/main/examples/community#latent-consistency-pipeline) with a MJPEG stream server.
 
+You need a webcam to run this demo. 🤗
+
 ## Running Locally
 
 You need CUDA and Python  
 `TIMEOUT`: limit user session timeout
 `SAFETY_CHECKER`:  disabled if you want NSFW filter off  
+`MAX_QUEUE_SIZE`: limit number of users on current app instance
 
 ```bash
 python -m venv venv 
 source venv/bin/activate 
 pip install -r requirements.txt
-TIMEOUT=0 SAFETY_CHECKER=False uvicorn "app:app" --host 0.0.0.0 --port 7860 --reload
+uvicorn "app:app" --host 0.0.0.0 --port 7860 --reload
+```
+or with environment variables
+```bash
+TIMEOUT=120 SAFETY_CHECKER=True MAX_QUEUE_SIZE=4 uvicorn "app:app" --host 0.0.0.0 --port 7860 --reload
 ```
 
+If you're running locally and want to test it on Mobile Safari, the webserver needs to be served over HTTPS. 
+
+```bash
+openssl req -newkey rsa:4096 -nodes -keyout key.pem -x509 -days 365 -out certificate.pem
+uvicorn "app:app" --host 0.0.0.0 --port 7860 --reload --log-level info --ssl-certfile=certificate.pem --ssl-keyfile=key.pem
+```
 ## Docker
 You need NVIDIA Container Toolkit for Docker
 
 ```bash
 docker build -t lcm-live .
+docker run -ti -p 7860:7860 --gpus all lcm-live
+```
+
+or with environment variables
+
+```bash
 docker run -ti -e TIMEOUT=0 -e SAFETY_CHECKER=False -p 7860:7860 --gpus all lcm-live
 ```
+
 # Demo on Hugging Face
 https://huggingface.co/spaces/radames/Real-Time-Latent-Consistency-Model
 

app.py

@@ -9,7 +9,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import StreamingResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 
-from diffusers import DiffusionPipeline
+from diffusers import DiffusionPipeline, AutoencoderTiny
 import torch
 from PIL import Image
 import numpy as np
@@ -19,7 +19,7 @@ import uuid
 import os
 import time
 
-MAX_QUEUE_SIZE = 4
+MAX_QUEUE_SIZE = int(os.environ.get("MAX_QUEUE_SIZE", 0))
 TIMEOUT = float(os.environ.get("TIMEOUT", 0))
 SAFETY_CHECKER = os.environ.get("SAFETY_CHECKER", None)
 
@@ -40,7 +40,12 @@ else:
         custom_pipeline="latent_consistency_img2img.py",
         custom_revision="main",
     )
+#TODO try to use tiny VAE
+# pipe.vae = AutoencoderTiny.from_pretrained(
+#     "madebyollin/taesd", torch_dtype=torch.float16, use_safetensors=True
+# )
 pipe.to(torch_device="cuda", torch_dtype=torch.float16)
+pipe.set_progress_bar_config(disable=True)
 user_queue_map = {}
 
 
@@ -88,7 +93,7 @@ class InputParams(BaseModel):
 @app.websocket("/ws")
 async def websocket_endpoint(websocket: WebSocket):
     await websocket.accept()
-    if len(user_queue_map) >= MAX_QUEUE_SIZE:
+    if MAX_QUEUE_SIZE > 0 and len(user_queue_map) >= MAX_QUEUE_SIZE:
         print("Server is full")
         await websocket.send_json({"status": "error", "message": "Server is full"})
         await websocket.close()

public/index.html

@@ -187,9 +187,14 @@
             </p>
         </article>
         <div>
+            <h2 class="font-medium">Prompt</h2>
+            <p class="text-sm text-gray-500">
+                Change the prompt to generate different images.
+            </p>
             <div class="flex text-normal px-1 py-1 border border-gray-700 rounded-md items-center">
                 <textarea type="text" id="prompt" class="font-light w-full px-3 py-2 mx-1 resize-none outline-none"
-                    title="Prompt" oninput="this.style.height = 0;this.style.height = this.scrollHeight + 'px'"
+                    title="Prompt, this is an example, feel free to modify"
+                    oninput="this.style.height = 0;this.style.height = this.scrollHeight + 'px'"
                     placeholder="Add your prompt here...">Portrait of The Terminator with , glare pose, detailed, intricate, full of colour, cinematic lighting, trending on artstation, 8k, hyperrealistic, focused, extreme details, unreal engine 5, cinematic, masterpiece</textarea>
             </div>