"""server.py: FastAPI SD-UI Web Host. Notes: async endpoints always run on the main thread. Without they run on the thread pool. """ import json import traceback import sys import os SD_DIR = os.getcwd() print('started in ', SD_DIR) SD_UI_DIR = os.getenv('SD_UI_PATH', None) sys.path.append(os.path.dirname(SD_UI_DIR)) CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts')) MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'models')) UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui')) OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder TASK_TTL = 15 * 60 # Discard last session's task timeout APP_CONFIG_DEFAULTS = { # auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device. 'render_devices': ['auto'], # ['cuda'] or ['CPU', 'GPU:0', 'GPU:1', ...] or ['cpu'] 'update_branch': 'main', } APP_CONFIG_DEFAULT_MODELS = [ # needed to support the legacy installations 'custom-model', # Check if user has a custom model, use it first. 'sd-v1-4', # Default fallback. ] from fastapi import FastAPI, HTTPException from fastapi.staticfiles import StaticFiles from starlette.responses import FileResponse, JSONResponse, StreamingResponse from pydantic import BaseModel import logging #import queue, threading, time from typing import Any, Generator, Hashable, List, Optional, Union from sd_internal import Request, Response, task_manager app = FastAPI() modifiers_cache = None outpath = os.path.join(os.path.expanduser("~"), OUTPUT_DIRNAME) os.makedirs(UI_PLUGINS_DIR, exist_ok=True) # don't show access log entries for URLs that start with the given prefix ACCESS_LOG_SUPPRESS_PATH_PREFIXES = ['/ping', '/image', '/modifier-thumbnails'] NOCACHE_HEADERS={"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"} app.mount('/media', StaticFiles(directory=os.path.join(SD_UI_DIR, 'media')), name="media") app.mount('/plugins', StaticFiles(directory=UI_PLUGINS_DIR), name="plugins") config_cached = None config_last_mod_time = 0 def getConfig(default_val=APP_CONFIG_DEFAULTS): global config_cached, config_last_mod_time try: config_json_path = os.path.join(CONFIG_DIR, 'config.json') if not os.path.exists(config_json_path): return default_val if config_last_mod_time > 0 and config_cached is not None: # Don't read if file was not modified mtime = os.path.getmtime(config_json_path) if mtime <= config_last_mod_time: return config_cached with open(config_json_path, 'r', encoding='utf-8') as f: config_cached = json.load(f) config_last_mod_time = os.path.getmtime(config_json_path) return config_cached except Exception as e: print(str(e)) print(traceback.format_exc()) return default_val def setConfig(config): try: # config.json config_json_path = os.path.join(CONFIG_DIR, 'config.json') with open(config_json_path, 'w', encoding='utf-8') as f: return json.dump(config, f) except: print(traceback.format_exc()) if 'render_devices' in config: gpu_devices = filter(lambda dev: dev.lower().startswith('gpu') or dev.lower().startswith('cuda'), config['render_devices']) else: gpu_devices = [] has_first_cuda_device = False for device in gpu_devices: if not task_manager.is_first_cuda_device(device): continue has_first_cuda_device = True break if len(gpu_devices) > 0 and not has_first_cuda_device: print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer') try: # config.bat config_bat = [ f"@set update_branch={config['update_branch']}" ] if len(gpu_devices) > 0 and not has_first_cuda_device: config_bat.append('::Set the devices visible inside SD-UI here') config_bat.append(f"::@set CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now. print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat') config_bat_path = os.path.join(CONFIG_DIR, 'config.bat') with open(config_bat_path, 'w', encoding='utf-8') as f: f.write(f.write('\r\n'.join(config_bat))) except Exception as e: print(traceback.format_exc()) try: # config.sh config_sh = [ '#!/bin/bash' f"export update_branch={config['update_branch']}" ] if len(gpu_devices) > 0 and not has_first_cuda_device: config_sh.append('#Set the devices visible inside SD-UI here') config_sh.append(f"#CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now. print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh') config_sh_path = os.path.join(CONFIG_DIR, 'config.sh') with open(config_sh_path, 'w', encoding='utf-8') as f: f.write('\n'.join(config_sh)) except Exception as e: print(traceback.format_exc()) def resolve_model_to_use(model_name:str=None): if not model_name: # When None try user configured model. config = getConfig() if 'model' in config and 'stable-diffusion' in config['model']: model_name = config['model']['stable-diffusion'] if model_name: # Check models directory models_dir_path = os.path.join(MODELS_DIR, 'stable-diffusion', model_name) if os.path.exists(models_dir_path + '.ckpt'): return models_dir_path if os.path.exists(model_name + '.ckpt'): # Direct Path to file model_name = os.path.abspath(model_name) return model_name # Default locations if model_name in APP_CONFIG_DEFAULT_MODELS: default_model_path = os.path.join(SD_DIR, model_name) if os.path.exists(default_model_path + '.ckpt'): return default_model_path # Can't find requested model, check the default paths. for default_model in APP_CONFIG_DEFAULT_MODELS: default_model_path = os.path.join(SD_DIR, default_model) if os.path.exists(default_model_path + '.ckpt'): if model_name is not None: print(f'Could not find the configured custom model {model_name}.ckpt. Using the default one: {default_model_path}.ckpt') return default_model_path raise Exception('No valid models found.') class SetAppConfigRequest(BaseModel): update_branch: str = None render_devices: Union[List[str], List[int], str, int] = None @app.post('/app_config') async def setAppConfig(req : SetAppConfigRequest): config = getConfig() if req.update_branch: config['update_branch'] = req.update_branch if req.render_devices and hasattr(req.render_devices, "__len__"): # strings, array of strings or numbers. render_devices = [] if isinstance(req.render_devices, str): req.render_devices = req.render_devices.split(',') if isinstance(req.render_devices, list): for gpu in req.render_devices: if isinstance(req.render_devices, int): render_devices.append('GPU:' + gpu) else: render_devices.append(gpu) if isinstance(req.render_devices, int): render_devices.append('GPU:' + req.render_devices) if len(render_devices) > 0: config['render_devices'] = render_devices try: setConfig(config) return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS) except Exception as e: print(traceback.format_exc()) raise HTTPException(status_code=500, detail=str(e)) def getModels(): models = { 'active': { 'stable-diffusion': 'sd-v1-4', }, 'options': { 'stable-diffusion': ['sd-v1-4'], }, } # custom models sd_models_dir = os.path.join(MODELS_DIR, 'stable-diffusion') for file in os.listdir(sd_models_dir): if file.endswith('.ckpt'): model_name = os.path.splitext(file)[0] models['options']['stable-diffusion'].append(model_name) # legacy custom_weight_path = os.path.join(SD_DIR, 'custom-model.ckpt') if os.path.exists(custom_weight_path): models['active']['stable-diffusion'] = 'custom-model' models['options']['stable-diffusion'].append('custom-model') config = getConfig() if 'model' in config and 'stable-diffusion' in config['model']: models['active']['stable-diffusion'] = config['model']['stable-diffusion'] return models def getUIPlugins(): plugins = [] for file in os.listdir(UI_PLUGINS_DIR): if file.endswith('.plugin.js'): plugins.append(f'/plugins/{file}') return plugins @app.get('/get/{key:path}') def read_web_data(key:str=None): if not key: # /get without parameters, stable-diffusion easter egg. raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot elif key == 'app_config': config = getConfig(default_val=None) if config is None: raise HTTPException(status_code=500, detail="Config file is missing or unreadable") return JSONResponse(config, headers=NOCACHE_HEADERS) elif key == 'models': return JSONResponse(getModels(), headers=NOCACHE_HEADERS) elif key == 'modifiers': return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS) elif key == 'output_dir': return JSONResponse({ 'output_dir': outpath }, headers=NOCACHE_HEADERS) elif key == 'ui_plugins': return JSONResponse(getUIPlugins(), headers=NOCACHE_HEADERS) else: raise HTTPException(status_code=404, detail=f'Request for unknown {key}') # HTTP404 Not Found @app.get('/ping') # Get server and optionally session status. def ping(session_id:str=None): if task_manager.is_alive() <= 0: # Check that render threads are alive. if task_manager.current_state_error: raise HTTPException(status_code=500, detail=str(task_manager.current_state_error)) raise HTTPException(status_code=500, detail='Render thread is dead.') if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration): raise HTTPException(status_code=500, detail=str(task_manager.current_state_error)) # Alive response = {'status': str(task_manager.current_state)} if session_id: task = task_manager.get_cached_task(session_id, update_ttl=True) if task: response['task'] = id(task) if task.lock.locked(): response['session'] = 'running' elif isinstance(task.error, StopAsyncIteration): response['session'] = 'stopped' elif task.error: response['session'] = 'error' elif not task.buffer_queue.empty(): response['session'] = 'buffer' elif task.response: response['session'] = 'completed' else: response['session'] = 'pending' return JSONResponse(response, headers=NOCACHE_HEADERS) def save_model_to_config(model_name): config = getConfig() if 'model' not in config: config['model'] = {} config['model']['stable-diffusion'] = model_name setConfig(config) @app.post('/render') def render(req : task_manager.ImageRequest): if req.use_cpu and task_manager.is_alive('cpu') <= 0: raise HTTPException(status_code=403, detail=f'CPU rendering is not enabled in config.json or the thread has died...') # HTTP403 Forbidden if req.use_face_correction and task_manager.is_alive(0) <= 0: #TODO Remove when GFPGANer is fixed upstream. raise HTTPException(status_code=412, detail=f'GFPGANer only works GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') # HTTP412 Precondition Failed try: save_model_to_config(req.use_stable_diffusion_model) req.use_stable_diffusion_model = resolve_model_to_use(req.use_stable_diffusion_model) new_task = task_manager.render(req) response = { 'status': str(task_manager.current_state), 'queue': len(task_manager.tasks_queue), 'stream': f'/image/stream/{req.session_id}/{id(new_task)}', 'task': id(new_task) } return JSONResponse(response, headers=NOCACHE_HEADERS) except ChildProcessError as e: # Render thread is dead raise HTTPException(status_code=500, detail=f'Rendering thread has died.') # HTTP500 Internal Server Error except ConnectionRefusedError as e: # Unstarted task pending, deny queueing more than one. raise HTTPException(status_code=503, detail=f'Session {req.session_id} has an already pending task.') # HTTP503 Service Unavailable except Exception as e: raise HTTPException(status_code=500, detail=str(e)) @app.get('/image/stream/{session_id:str}/{task_id:int}') def stream(session_id:str, task_id:int): #TODO Move to WebSockets ?? task = task_manager.get_cached_task(session_id, update_ttl=True) if not task: raise HTTPException(status_code=410, detail='No request received.') # HTTP410 Gone if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict if task.buffer_queue.empty() and not task.lock.locked(): if task.response: #print(f'Session {session_id} sending cached response') return JSONResponse(task.response, headers=NOCACHE_HEADERS) raise HTTPException(status_code=425, detail='Too Early, task not started yet.') # HTTP425 Too Early #print(f'Session {session_id} opened live render stream {id(task.buffer_queue)}') return StreamingResponse(task.read_buffer_generator(), media_type='application/json') @app.get('/image/stop') def stop(session_id:str=None): if not session_id: if task_manager.current_state == task_manager.ServerStates.Online or task_manager.current_state == task_manager.ServerStates.Unavailable: raise HTTPException(status_code=409, detail='Not currently running any tasks.') # HTTP409 Conflict task_manager.current_state_error = StopAsyncIteration('') return {'OK'} task = task_manager.get_cached_task(session_id, update_ttl=False) if not task: raise HTTPException(status_code=404, detail=f'Session {session_id} has no active task.') # HTTP404 Not Found if isinstance(task.error, StopAsyncIteration): raise HTTPException(status_code=409, detail=f'Session {session_id} task is already stopped.') # HTTP409 Conflict task.error = StopAsyncIteration('') return {'OK'} @app.get('/image/tmp/{session_id}/{img_id:int}') def get_image(session_id, img_id): task = task_manager.get_cached_task(session_id, update_ttl=True) if not task: raise HTTPException(status_code=410, detail=f'Session {session_id} has not submitted a task.') # HTTP410 Gone if not task.temp_images[img_id]: raise HTTPException(status_code=425, detail='Too Early, task data is not available yet.') # HTTP425 Too Early try: img_data = task.temp_images[img_id] if isinstance(img_data, str): return img_data img_data.seek(0) return StreamingResponse(img_data, media_type='image/jpeg') except KeyError as e: raise HTTPException(status_code=500, detail=str(e)) @app.get('/') def read_root(): return FileResponse(os.path.join(SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS) @app.on_event("shutdown") def shutdown_event(): # Signal render thread to close on shutdown task_manager.current_state_error = SystemExit('Application shutting down.') # don't log certain requests class LogSuppressFilter(logging.Filter): def filter(self, record: logging.LogRecord) -> bool: path = record.getMessage() for prefix in ACCESS_LOG_SUPPRESS_PATH_PREFIXES: if path.find(prefix) != -1: return False return True logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter()) config = getConfig() # Start the task_manager task_manager.default_model_to_load = resolve_model_to_use() # Check that the loaded config.json yielded a server in a known valid state. # When issues are found, try to fix them when possible and warn the user. if 'render_devices' in config: # Start a new thread for each device. if isinstance(config['render_devices'], str): config['render_devices'] = config['render_devices'].split(',') if not isinstance(config['render_devices'], list): raise Exception('Invalid render_devices value in config.') for device in config['render_devices']: task_manager.start_render_thread(device) if task_manager.is_alive() <= 0: # No running devices, probably invalid user config. print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json') print('Loading default render devices to replace invalid render_devices field from config', config['render_devices']) display_warning = False if task_manager.is_alive() <= 0: # Either no defauls or no devices after loading config. # Select best GPU device using free memory, if more than one device. task_manager.start_render_thread('auto') # Detect best device for renders if task_manager.is_alive(0) <= 0: # without cuda:0 task_manager.start_render_thread('cuda') # An other cuda device is better and cuda:0 is missing, start it... display_warning = True # And warn user to update settings... if task_manager.is_alive('cpu') <= 0: # Allow CPU to be used for renders task_manager.start_render_thread('cpu') if display_warning or task_manager.is_alive(0) <= 0: print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer') print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat') print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh') del display_warning # start the browser ui import webbrowser; webbrowser.open('http://localhost:9000')