diff --git a/ldm/invoke/CLI.py b/ldm/invoke/CLI.py
new file mode 100644
index 0000000000..d64d72059d
--- /dev/null
+++ b/ldm/invoke/CLI.py
@@ -0,0 +1,943 @@
+import os
+import re
+import sys
+import shlex
+import copy
+import warnings
+import time
+import traceback
+import yaml
+
+from ldm.invoke.globals import Globals
+from ldm.invoke.prompt_parser import PromptParser
+from ldm.invoke.readline import get_completer, Completer
+from ldm.invoke.args import Args, metadata_dumps, metadata_from_png, dream_cmd_from_png
+from ldm.invoke.pngwriter import PngWriter, retrieve_metadata, write_metadata
+from ldm.invoke.image_util import make_grid
+from ldm.invoke.log import write_log
+from omegaconf import OmegaConf
+from pathlib import Path
+import pyparsing
+
+# global used in multiple functions (fix)
+infile = None
+
+def main():
+    """Initialize command-line parsers and the diffusion model"""
+    global infile
+    print('* Initializing, be patient...')
+    
+    opt  = Args()
+    args = opt.parse_args()
+    if not args:
+        sys.exit(-1)
+
+    if args.laion400m:
+        print('--laion400m flag has been deprecated. Please use --model laion400m instead.')
+        sys.exit(-1)
+    if args.weights:
+        print('--weights argument has been deprecated. Please edit ./configs/models.yaml, and select the weights using --model instead.')
+        sys.exit(-1)
+    if args.max_loaded_models is not None:
+        if args.max_loaded_models <= 0:
+            print('--max_loaded_models must be >= 1; using 1')
+            args.max_loaded_models = 1
+
+    # alert - setting a global here
+    Globals.root = os.path.expanduser(args.root_dir or os.environ.get('INVOKEAI_ROOT') or '.')
+    print(f'>> InvokeAI runtime directory is "{Globals.root}"')
+
+    # loading here to avoid long delays on startup
+    from ldm.generate import Generate
+
+    # these two lines prevent a horrible warning message from appearing
+    # when the frozen CLIP tokenizer is imported
+    import transformers
+    transformers.logging.set_verbosity_error()
+
+    # Loading Face Restoration and ESRGAN Modules
+    gfpgan,codeformer,esrgan = load_face_restoration(opt)
+
+    # normalize the config directory relative to root
+    if not os.path.isabs(opt.conf):
+        opt.conf=os.path.normpath(os.path.join(Globals.root,opt.conf))
+
+    # load the infile as a list of lines
+    if opt.infile:
+        try:
+            if os.path.isfile(opt.infile):
+                infile = open(opt.infile, 'r', encoding='utf-8')
+            elif opt.infile == '-':  # stdin
+                infile = sys.stdin
+            else:
+                raise FileNotFoundError(f'{opt.infile} not found.')
+        except (FileNotFoundError, IOError) as e:
+            print(f'{e}. Aborting.')
+            sys.exit(-1)
+
+    # creating a Generate object:
+    try:
+        gen = Generate(
+            conf = os.path.join(Globals.root,opt.conf),
+            model = opt.model,
+            sampler_name = opt.sampler_name,
+            embedding_path = opt.embedding_path,
+            full_precision = opt.full_precision,
+            precision = opt.precision,
+            gfpgan=gfpgan,
+            codeformer=codeformer,
+            esrgan=esrgan,
+            free_gpu_mem=opt.free_gpu_mem,
+            safety_checker=opt.safety_checker,
+            max_loaded_models=opt.max_loaded_models,
+            )
+    except FileNotFoundError:
+        print('** You appear to be missing configs/models.yaml')
+        print('** You can either exit this script and run scripts/preload_models.py, or fix the problem now.')
+        emergency_model_create(opt)
+        sys.exit(-1)
+    except (IOError, KeyError) as e:
+        print(f'{e}. Aborting.')
+        sys.exit(-1)
+
+    if opt.seamless:
+        print(">> changed to seamless tiling mode")
+
+    # preload the model
+    gen.load_model()
+
+    # web server loops forever
+    if opt.web or opt.gui:
+        invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan)
+        sys.exit(0)
+
+    if not infile:
+        print(
+            "\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)"
+        )
+
+    try:
+        main_loop(gen, opt)
+    except KeyboardInterrupt:
+        print("\ngoodbye!")
+
+# TODO: main_loop() has gotten busy. Needs to be refactored.
+def main_loop(gen, opt):
+    """prompt/read/execute loop"""
+    global infile
+    done = False
+    doneAfterInFile = infile is not None
+    path_filter = re.compile(r'[<>:"/\\|?*]')
+    last_results = list()
+    if not os.path.isabs(opt.conf):
+        opt.conf = os.path.join(Globals.root,opt.conf)
+    model_config = OmegaConf.load(opt.conf)
+
+    # The readline completer reads history from the .dream_history file located in the
+    # output directory specified at the time of script launch. We do not currently support
+    # changing the history file midstream when the output directory is changed.
+    completer   = get_completer(opt, models=list(model_config.keys()))
+    set_default_output_dir(opt, completer)
+    output_cntr = completer.get_current_history_length()+1
+
+    # os.pathconf is not available on Windows
+    if hasattr(os, 'pathconf'):
+        path_max = os.pathconf(opt.outdir, 'PC_PATH_MAX')
+        name_max = os.pathconf(opt.outdir, 'PC_NAME_MAX')
+    else:
+        path_max = 260
+        name_max = 255
+
+    while not done:
+
+        operation = 'generate'
+
+        try:
+            command = get_next_command(infile)
+        except EOFError:
+            done = infile is None or doneAfterInFile
+            infile = None
+            continue
+
+        # skip empty lines
+        if not command.strip():
+            continue
+
+        if command.startswith(('#', '//')):
+            continue
+
+        if len(command.strip()) == 1 and command.startswith('q'):
+            done = True
+            break
+
+        if not command.startswith('!history'):
+            completer.add_history(command)
+
+        if command.startswith('!'):
+            command, operation = do_command(command, gen, opt, completer)
+
+        if operation is None:
+            continue
+
+        if opt.parse_cmd(command) is None:
+            continue
+
+        if opt.init_img:
+            try:
+                if not opt.prompt:
+                    oldargs    = metadata_from_png(opt.init_img)
+                    opt.prompt = oldargs.prompt
+                    print(f'>> Retrieved old prompt "{opt.prompt}" from {opt.init_img}')
+            except (OSError, AttributeError, KeyError):
+                pass
+
+        if len(opt.prompt) == 0:
+            opt.prompt = ''
+
+        # width and height are set by model if not specified
+        if not opt.width:
+            opt.width = gen.width
+        if not opt.height:
+            opt.height = gen.height
+
+        # retrieve previous value of init image if requested
+        if opt.init_img is not None and re.match('^-\\d+$', opt.init_img):
+            try:
+                opt.init_img = last_results[int(opt.init_img)][0]
+                print(f'>> Reusing previous image {opt.init_img}')
+            except IndexError:
+                print(
+                    f'>> No previous initial image at position {opt.init_img} found')
+                opt.init_img = None
+                continue
+
+        # the outdir can change with each command, so we adjust it here
+        set_default_output_dir(opt,completer)
+
+        # try to relativize pathnames
+        for attr in ('init_img','init_mask','init_color','embedding_path'):
+            if getattr(opt,attr) and not os.path.exists(getattr(opt,attr)):
+                basename = getattr(opt,attr)
+                path     = os.path.join(opt.outdir,basename)
+                setattr(opt,attr,path)
+
+        # retrieve previous value of seed if requested
+        # Exception: for postprocess operations negative seed values
+        # mean "discard the original seed and generate a new one"
+        # (this is a non-obvious hack and needs to be reworked)
+        if opt.seed is not None and opt.seed < 0 and operation != 'postprocess':
+            try:
+                opt.seed = last_results[opt.seed][1]
+                print(f'>> Reusing previous seed {opt.seed}')
+            except IndexError:
+                print(f'>> No previous seed at position {opt.seed} found')
+                opt.seed = None
+                continue
+
+        if opt.strength is None:
+            opt.strength = 0.75 if opt.out_direction is None else 0.83
+
+        if opt.with_variations is not None:
+            opt.with_variations = split_variations(opt.with_variations)
+
+        if opt.prompt_as_dir and operation == 'generate':
+            # sanitize the prompt to a valid folder name
+            subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .')
+
+            # truncate path to maximum allowed length
+            # 39 is the length of '######.##########.##########-##.png', plus two separators and a NUL
+            subdir = subdir[:(path_max - 39 - len(os.path.abspath(opt.outdir)))]
+            current_outdir = os.path.join(opt.outdir, subdir)
+
+            print('Writing files to directory: "' + current_outdir + '"')
+
+            # make sure the output directory exists
+            if not os.path.exists(current_outdir):
+                os.makedirs(current_outdir)
+        else:
+            if not os.path.exists(opt.outdir):
+                os.makedirs(opt.outdir)
+            current_outdir = opt.outdir
+
+        # Here is where the images are actually generated!
+        last_results = []
+        try:
+            file_writer      = PngWriter(current_outdir)
+            results          = []  # list of filename, prompt pairs
+            grid_images      = dict()  # seed -> Image, only used if `opt.grid`
+            prior_variations = opt.with_variations or []
+            prefix = file_writer.unique_prefix()
+            step_callback = make_step_callback(gen, opt, prefix) if opt.save_intermediates > 0 else None
+
+            def image_writer(image, seed, upscaled=False, first_seed=None, use_prefix=None):
+                # note the seed is the seed of the current image
+                # the first_seed is the original seed that noise is added to
+                # when the -v switch is used to generate variations
+                nonlocal prior_variations
+                nonlocal prefix
+
+                path = None
+                if opt.grid:
+                    grid_images[seed] = image
+
+                elif operation == 'mask':
+                    filename = f'{prefix}.{use_prefix}.{seed}.png'
+                    tm = opt.text_mask[0]
+                    th = opt.text_mask[1] if len(opt.text_mask)>1 else 0.5
+                    formatted_dream_prompt = f'!mask {opt.input_file_path} -tm {tm} {th}'
+                    path = file_writer.save_image_and_prompt_to_png(
+                        image           = image,
+                        dream_prompt    = formatted_dream_prompt,
+                        metadata        = {},
+                        name      = filename,
+                        compress_level = opt.png_compression,
+                    )
+                    results.append([path, formatted_dream_prompt])
+
+                else:
+                    if use_prefix is not None:
+                        prefix = use_prefix
+                    postprocessed = upscaled if upscaled else operation=='postprocess'
+                    filename, formatted_dream_prompt = prepare_image_metadata(
+                        opt,
+                        prefix,
+                        seed,
+                        operation,
+                        prior_variations,
+                        postprocessed,
+                        first_seed
+                    )
+                    path = file_writer.save_image_and_prompt_to_png(
+                        image           = image,
+                        dream_prompt    = formatted_dream_prompt,
+                        metadata        = metadata_dumps(
+                            opt,
+                            seeds      = [seed if opt.variation_amount==0 and len(prior_variations)==0 else first_seed],
+                            model_hash = gen.model_hash,
+                        ),
+                        name      = filename,
+                        compress_level = opt.png_compression,
+                    )
+
+                    # update rfc metadata
+                    if operation == 'postprocess':
+                        tool = re.match('postprocess:(\w+)',opt.last_operation).groups()[0]
+                        add_postprocessing_to_metadata(
+                            opt,
+                            opt.input_file_path,
+                            filename,
+                            tool,
+                            formatted_dream_prompt,
+                        )                           
+                        
+                    if (not postprocessed) or opt.save_original:
+                        # only append to results if we didn't overwrite an earlier output
+                        results.append([path, formatted_dream_prompt])
+
+                # so that the seed autocompletes (on linux|mac when -S or --seed specified
+                if completer and operation == 'generate':
+                    completer.add_seed(seed)
+                    completer.add_seed(first_seed)
+                last_results.append([path, seed])
+
+            if operation == 'generate':
+                catch_ctrl_c = infile is None # if running interactively, we catch keyboard interrupts
+                opt.last_operation='generate'
+                try:
+                    gen.prompt2image(
+                        image_callback=image_writer,
+                        step_callback=step_callback,
+                        catch_interrupts=catch_ctrl_c,
+                        **vars(opt)
+                    )
+                except (PromptParser.ParsingException, pyparsing.ParseException) as e:
+                    print('** An error occurred while processing your prompt **')
+                    print(f'** {str(e)} **')
+            elif operation == 'postprocess':
+                print(f'>> fixing {opt.prompt}')
+                opt.last_operation = do_postprocess(gen,opt,image_writer)
+
+            elif operation == 'mask':
+                print(f'>> generating masks from {opt.prompt}')
+                do_textmask(gen, opt, image_writer)
+
+            if opt.grid and len(grid_images) > 0:
+                grid_img   = make_grid(list(grid_images.values()))
+                grid_seeds = list(grid_images.keys())
+                first_seed = last_results[0][1]
+                filename   = f'{prefix}.{first_seed}.png'
+                formatted_dream_prompt  = opt.dream_prompt_str(seed=first_seed,grid=True,iterations=len(grid_images))
+                formatted_dream_prompt += f' # {grid_seeds}'
+                metadata = metadata_dumps(
+                    opt,
+                    seeds      = grid_seeds,
+                    model_hash = gen.model_hash
+                    )
+                path = file_writer.save_image_and_prompt_to_png(
+                    image        = grid_img,
+                    dream_prompt = formatted_dream_prompt,
+                    metadata     = metadata,
+                    name         = filename
+                )
+                results = [[path, formatted_dream_prompt]]
+
+        except AssertionError as e:
+            print(e)
+            continue
+
+        except OSError as e:
+            print(e)
+            continue
+
+        print('Outputs:')
+        log_path = os.path.join(current_outdir, 'invoke_log')
+        output_cntr = write_log(results, log_path ,('txt', 'md'), output_cntr)
+        print()
+
+    print('goodbye!')
+
+# TO DO: remove repetitive code and the awkward command.replace() trope
+# Just do a simple parse of the command!
+def do_command(command:str, gen, opt:Args, completer) -> tuple:
+    global infile
+    operation = 'generate'   # default operation, alternative is 'postprocess'
+
+    if command.startswith('!dream'):   # in case a stored prompt still contains the !dream command
+        command = command.replace('!dream ','',1)
+
+    elif command.startswith('!fix'):
+        command = command.replace('!fix ','',1)
+        operation = 'postprocess'
+
+    elif command.startswith('!mask'):
+        command = command.replace('!mask ','',1)
+        operation = 'mask'
+
+    elif command.startswith('!switch'):
+        model_name = command.replace('!switch ','',1)
+        gen.set_model(model_name)
+        completer.add_history(command)
+        operation = None
+        
+    elif command.startswith('!models'):
+        gen.model_cache.print_models()
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!import'):
+        path = shlex.split(command)
+        if len(path) < 2:
+            print('** please provide a path to a .ckpt or .vae model file')
+        elif not os.path.exists(path[1]):
+            print(f'** {path[1]}: file not found')
+        else:
+            add_weights_to_config(path[1], gen, opt, completer)
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!edit'):
+        path = shlex.split(command)
+        if len(path) < 2:
+            print('** please provide the name of a model')
+        else:
+            edit_config(path[1], gen, opt, completer)
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!del'):
+        path = shlex.split(command)
+        if len(path) < 2:
+            print('** please provide the name of a model')
+        else:
+            del_config(path[1], gen, opt, completer)
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!fetch'):
+        file_path = command.replace('!fetch','',1).strip()
+        retrieve_dream_command(opt,file_path,completer)
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!replay'):
+        file_path = command.replace('!replay','',1).strip()
+        if infile is None and os.path.isfile(file_path):
+            infile = open(file_path, 'r', encoding='utf-8')
+        completer.add_history(command)
+        operation = None
+
+    elif command.startswith('!history'):
+        completer.show_history()
+        operation = None
+
+    elif command.startswith('!search'):
+        search_str = command.replace('!search','',1).strip()
+        completer.show_history(search_str)
+        operation = None
+
+    elif command.startswith('!clear'):
+        completer.clear_history()
+        operation = None
+
+    elif re.match('^!(\d+)',command):
+        command_no = re.match('^!(\d+)',command).groups()[0]
+        command    = completer.get_line(int(command_no))
+        completer.set_line(command)
+        operation = None
+
+    else:  # not a recognized command, so give the --help text
+        command = '-h'
+    return command, operation
+
+def set_default_output_dir(opt:Args, completer:Completer):
+    '''
+    If opt.outdir is relative, we add the root directory to it
+    normalize the outdir relative to root and make sure it exists.
+    '''
+    if not os.path.isabs(opt.outdir):
+        opt.outdir=os.path.normpath(os.path.join(Globals.root,opt.outdir))
+    if not os.path.exists(opt.outdir):
+        os.makedirs(opt.outdir)
+    completer.set_default_dir(opt.outdir)
+
+
+def add_weights_to_config(model_path:str, gen, opt, completer):
+    print(f'>> Model import in process. Please enter the values needed to configure this model:')
+    print()
+
+    new_config = {}
+    new_config['weights'] = model_path
+
+    done = False
+    while not done:
+        model_name = input('Short name for this model: ')
+        if not re.match('^[\w._-]+$',model_name):
+            print('** model name must contain only words, digits and the characters [._-] **')
+        else:
+            done = True
+    new_config['description'] = input('Description of this model: ')
+
+    completer.complete_extensions(('.yaml','.yml'))
+    completer.linebuffer = 'configs/stable-diffusion/v1-inference.yaml'
+    
+    done = False
+    while not done:
+        new_config['config'] = input('Configuration file for this model: ')
+        done = os.path.exists(new_config['config'])
+
+    done = False
+    completer.complete_extensions(('.vae.pt','.vae','.ckpt'))
+    while not done:
+        vae = input('VAE autoencoder file for this model [None]: ')
+        if os.path.exists(vae):
+            new_config['vae'] = vae
+            done = True
+        else:
+            done = len(vae)==0
+
+    completer.complete_extensions(None)
+
+    for field in ('width','height'):
+        done = False
+        while not done:
+            try:
+                completer.linebuffer = '512'
+                value = int(input(f'Default image {field}: '))
+                assert value >= 64 and value <= 2048
+                new_config[field] = value
+                done = True
+            except:
+                print('** Please enter a valid integer between 64 and 2048')
+
+    make_default = input('Make this the default model? [n] ') in ('y','Y')
+    
+    if write_config_file(opt.conf, gen, model_name, new_config, make_default=make_default):
+        completer.add_model(model_name)
+
+def del_config(model_name:str, gen, opt, completer):
+    current_model = gen.model_name
+    if model_name == current_model:
+        print("** Can't delete active model. !switch to another model first. **")
+        return
+    if gen.model_cache.del_model(model_name):
+        gen.model_cache.commit(opt.conf)
+    print(f'** {model_name} deleted')
+    completer.del_model(model_name)
+    
+def edit_config(model_name:str, gen, opt, completer):
+    config = gen.model_cache.config
+    
+    if model_name not in config:
+        print(f'** Unknown model {model_name}')
+        return
+    
+    print(f'\n>> Editing model {model_name} from configuration file {opt.conf}')
+
+    conf = config[model_name]
+    new_config = {}
+    completer.complete_extensions(('.yaml','.yml','.ckpt','.vae.pt'))
+    for field in ('description', 'weights', 'vae', 'config', 'width','height'):
+        completer.linebuffer = str(conf[field]) if field in conf else ''
+        new_value = input(f'{field}: ')
+        new_config[field] = int(new_value) if field in ('width','height') else new_value
+    make_default = input('Make this the default model? [n] ') in ('y','Y')
+    completer.complete_extensions(None)
+    write_config_file(opt.conf, gen, model_name, new_config, clobber=True, make_default=make_default)
+    
+def write_config_file(conf_path, gen, model_name, new_config, clobber=False, make_default=False):
+    current_model = gen.model_name
+    
+    op = 'modify' if clobber else 'import'
+    print('\n>> New configuration:')
+    if make_default:
+        new_config['default'] = True
+    print(yaml.dump({model_name:new_config}))
+    if input(f'OK to {op} [n]? ') not in ('y','Y'):
+        return False
+
+    try:
+        print('>> Verifying that new model loads...')
+        gen.model_cache.add_model(model_name, new_config, clobber)
+        assert gen.set_model(model_name) is not None, 'model failed to load'
+    except AssertionError as e:
+        print(f'** aborting **')
+        gen.model_cache.del_model(model_name)
+        return False
+
+    if make_default:
+        print('making this default')
+        gen.model_cache.set_default_model(model_name)
+
+    gen.model_cache.commit(conf_path)
+    
+    do_switch = input(f'Keep model loaded? [y]')
+    if len(do_switch)==0 or do_switch[0] in ('y','Y'):
+        pass
+    else:
+        gen.set_model(current_model)
+    return True
+
+def do_textmask(gen, opt, callback):
+    image_path = opt.prompt
+    if not os.path.exists(image_path):
+        image_path = os.path.join(opt.outdir,image_path)
+    assert os.path.exists(image_path), '** "{opt.prompt}" not found. Please enter the name of an existing image file to mask **'
+    assert opt.text_mask is not None and len(opt.text_mask) >= 1, '** Please provide a text mask with -tm **'
+    opt.input_file_path = image_path
+    tm = opt.text_mask[0]
+    threshold = float(opt.text_mask[1]) if len(opt.text_mask) > 1  else 0.5
+    gen.apply_textmask(
+        image_path = image_path,
+        prompt = tm,
+        threshold = threshold,
+        callback = callback,
+    )
+
+def do_postprocess (gen, opt, callback):
+    file_path = opt.prompt      # treat the prompt as the file pathname
+    if opt.new_prompt is not None:
+        opt.prompt = opt.new_prompt
+    else:
+        opt.prompt = None
+        
+    if os.path.dirname(file_path) == '': #basename given
+        file_path = os.path.join(opt.outdir,file_path)
+
+    opt.input_file_path = file_path
+
+    tool=None
+    if opt.facetool_strength > 0:
+        tool = opt.facetool
+    elif opt.embiggen:
+        tool = 'embiggen'
+    elif opt.upscale:
+        tool = 'upscale'
+    elif opt.out_direction:
+        tool = 'outpaint'
+    elif opt.outcrop:
+        tool = 'outcrop'
+    opt.save_original  = True # do not overwrite old image!
+    opt.last_operation = f'postprocess:{tool}'
+    try:
+        gen.apply_postprocessor(
+            image_path      = file_path,
+            tool            = tool,
+            facetool_strength = opt.facetool_strength,
+            codeformer_fidelity = opt.codeformer_fidelity,
+            save_original       = opt.save_original,
+            upscale             = opt.upscale,
+            out_direction       = opt.out_direction,
+            outcrop             = opt.outcrop,
+            callback            = callback,
+            opt                 = opt,
+        )
+    except OSError:
+        print(traceback.format_exc(), file=sys.stderr)
+        print(f'** {file_path}: file could not be read')
+        return
+    except (KeyError, AttributeError):
+        print(traceback.format_exc(), file=sys.stderr)
+        return
+    return opt.last_operation
+
+def add_postprocessing_to_metadata(opt,original_file,new_file,tool,command):
+    original_file = original_file if os.path.exists(original_file) else os.path.join(opt.outdir,original_file)
+    new_file       = new_file     if os.path.exists(new_file)      else os.path.join(opt.outdir,new_file)
+    try:
+        meta = retrieve_metadata(original_file)['sd-metadata']
+    except AttributeError:
+        try:
+            meta = retrieve_metadata(new_file)['sd-metadata']
+        except AttributeError:
+            meta = {}
+
+    if 'image' not in meta:
+        meta = metadata_dumps(opt,seeds=[opt.seed])['image']
+        meta['image'] = {}
+    img_data = meta.get('image')
+    pp = img_data.get('postprocessing',[]) or []
+    pp.append(
+        {
+            'tool':tool,
+            'dream_command':command,
+        }
+    )
+    meta['image']['postprocessing'] = pp
+    write_metadata(new_file,meta)
+    
+def prepare_image_metadata(
+        opt,
+        prefix,
+        seed,
+        operation='generate',
+        prior_variations=[],
+        postprocessed=False,
+        first_seed=None
+):
+
+    if postprocessed and opt.save_original:
+        filename = choose_postprocess_name(opt,prefix,seed)
+    else:
+        wildcards = dict(opt.__dict__)
+        wildcards['prefix'] = prefix
+        wildcards['seed'] = seed
+        try:
+            filename = opt.fnformat.format(**wildcards)
+        except KeyError as e:
+            print(f'** The filename format contains an unknown key \'{e.args[0]}\'. Will use \'{{prefix}}.{{seed}}.png\' instead')
+            filename = f'{prefix}.{seed}.png'
+        except IndexError as e:
+            print(f'** The filename format is broken or complete. Will use \'{{prefix}}.{{seed}}.png\' instead')
+            filename = f'{prefix}.{seed}.png'
+
+    if opt.variation_amount > 0:
+        first_seed             = first_seed or seed
+        this_variation         = [[seed, opt.variation_amount]]
+        opt.with_variations    = prior_variations + this_variation
+        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
+    elif len(prior_variations) > 0:
+        formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
+    elif operation == 'postprocess':
+        formatted_dream_prompt = '!fix '+opt.dream_prompt_str(seed=seed,prompt=opt.input_file_path)
+    else:
+        formatted_dream_prompt = opt.dream_prompt_str(seed=seed)
+    return filename,formatted_dream_prompt
+
+def choose_postprocess_name(opt,prefix,seed) -> str:
+    match      = re.search('postprocess:(\w+)',opt.last_operation)
+    if match:
+        modifier = match.group(1)   # will look like "gfpgan", "upscale", "outpaint" or "embiggen"
+    else:
+        modifier = 'postprocessed'
+
+    counter   = 0
+    filename  = None
+    available = False
+    while not available:
+        if counter == 0:
+            filename = f'{prefix}.{seed}.{modifier}.png'
+        else:
+            filename = f'{prefix}.{seed}.{modifier}-{counter:02d}.png'
+        available = not os.path.exists(os.path.join(opt.outdir,filename))
+        counter += 1
+    return filename
+
+def get_next_command(infile=None) -> str:  # command string
+    if infile is None:
+        command = input('invoke> ')
+    else:
+        command = infile.readline()
+        if not command:
+            raise EOFError
+        else:
+            command = command.strip()
+        if len(command)>0:
+            print(f'#{command}')
+    return command
+
+def invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan):
+    print('\n* --web was specified, starting web server...')
+    from backend.invoke_ai_web_server import InvokeAIWebServer
+    # Change working directory to the stable-diffusion directory
+    os.chdir(
+        os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
+    )
+    
+    invoke_ai_web_server = InvokeAIWebServer(generate=gen, gfpgan=gfpgan, codeformer=codeformer, esrgan=esrgan)
+
+    try:
+        invoke_ai_web_server.run()
+    except KeyboardInterrupt:
+        pass
+    
+
+def split_variations(variations_string) -> list:
+    # shotgun parsing, woo
+    parts = []
+    broken = False  # python doesn't have labeled loops...
+    for part in variations_string.split(','):
+        seed_and_weight = part.split(':')
+        if len(seed_and_weight) != 2:
+            print(f'** Could not parse with_variation part "{part}"')
+            broken = True
+            break
+        try:
+            seed   = int(seed_and_weight[0])
+            weight = float(seed_and_weight[1])
+        except ValueError:
+            print(f'** Could not parse with_variation part "{part}"')
+            broken = True
+            break
+        parts.append([seed, weight])
+    if broken:
+        return None
+    elif len(parts) == 0:
+        return None
+    else:
+        return parts
+
+def load_face_restoration(opt):
+    try:
+        gfpgan, codeformer, esrgan = None, None, None
+        if opt.restore or opt.esrgan:
+            from ldm.invoke.restoration import Restoration
+            restoration = Restoration()
+            if opt.restore:
+                gfpgan, codeformer = restoration.load_face_restore_models(opt.gfpgan_model_path)
+            else:
+                print('>> Face restoration disabled')
+            if opt.esrgan:
+                esrgan = restoration.load_esrgan(opt.esrgan_bg_tile)
+            else:
+                print('>> Upscaling disabled')
+        else:
+            print('>> Face restoration and upscaling disabled')
+    except (ModuleNotFoundError, ImportError):
+        print(traceback.format_exc(), file=sys.stderr)
+        print('>> You may need to install the ESRGAN and/or GFPGAN modules')
+    return gfpgan,codeformer,esrgan
+
+def make_step_callback(gen, opt, prefix):
+    destination = os.path.join(opt.outdir,'intermediates',prefix)
+    os.makedirs(destination,exist_ok=True)
+    print(f'>> Intermediate images will be written into {destination}')
+    def callback(img, step):
+        if step % opt.save_intermediates == 0 or step == opt.steps-1:
+            filename = os.path.join(destination,f'{step:04}.png')
+            image = gen.sample_to_image(img)
+            image.save(filename,'PNG')
+    return callback
+    
+def retrieve_dream_command(opt,command,completer):
+    '''
+    Given a full or partial path to a previously-generated image file,
+    will retrieve and format the dream command used to generate the image,
+    and pop it into the readline buffer (linux, Mac), or print out a comment
+    for cut-and-paste (windows)
+
+    Given a wildcard path to a folder with image png files, 
+    will retrieve and format the dream command used to generate the images,
+    and save them to a file commands.txt for further processing
+    '''
+    if len(command) == 0:
+        return
+
+    tokens = command.split()
+    dir,basename = os.path.split(tokens[0])
+    if len(dir) == 0:
+        path = os.path.join(opt.outdir,basename)
+    else:
+        path = tokens[0]
+
+    if len(tokens) > 1:
+        return write_commands(opt, path, tokens[1])
+
+    cmd = ''
+    try:
+        cmd = dream_cmd_from_png(path)
+    except OSError:
+        print(f'## {tokens[0]}: file could not be read')
+    except (KeyError, AttributeError, IndexError):
+        print(f'## {tokens[0]}: file has no metadata')
+    except:
+        print(f'## {tokens[0]}: file could not be processed')
+    if len(cmd)>0:
+        completer.set_line(cmd)
+
+def write_commands(opt, file_path:str, outfilepath:str):
+    dir,basename = os.path.split(file_path)
+    try:
+        paths = sorted(list(Path(dir).glob(basename)))
+    except ValueError:
+        print(f'## "{basename}": unacceptable pattern')
+        return
+ 
+    commands = []
+    cmd = None
+    for path in paths:
+        try:
+            cmd = dream_cmd_from_png(path)
+        except (KeyError, AttributeError, IndexError):
+            print(f'## {path}: file has no metadata')
+        except:
+            print(f'## {path}: file could not be processed')
+        if cmd:
+            commands.append(f'# {path}')
+            commands.append(cmd)
+    if len(commands)>0:
+        dir,basename = os.path.split(outfilepath)
+        if len(dir)==0:
+            outfilepath = os.path.join(opt.outdir,basename)
+        with open(outfilepath, 'w', encoding='utf-8') as f:
+            f.write('\n'.join(commands))
+        print(f'>> File {outfilepath} with commands created')
+
+def emergency_model_create(opt:Args):
+    completer   = get_completer(opt)
+    completer.complete_extensions(('.yaml','.yml','.ckpt','.vae.pt'))
+    completer.set_default_dir('.')
+    valid_path = False
+    while not valid_path:
+        weights_file = input('Enter the path to a downloaded models file, or ^C to exit: ')
+        valid_path = os.path.exists(weights_file)
+    dir,basename = os.path.split(weights_file)
+
+    valid_name = False
+    while not valid_name:
+        name = input('Enter a short name for this model (no spaces): ')
+        name = 'unnamed model' if len(name)==0 else name
+        valid_name = ' ' not in name
+
+    description = input('Enter a description for this model: ')
+    description = 'no description' if len(description)==0 else description
+
+    with open(opt.conf, 'w', encoding='utf-8') as f:
+        f.write(f'{name}:\n')
+        f.write(f'  description: {description}\n')
+        f.write(f'  weights: {weights_file}\n')
+        f.write(f'  config: ./configs/stable-diffusion/v1-inference.yaml\n')
+        f.write(f'  width: 512\n')
+        f.write(f'  height: 512\n')
+        f.write(f'  default: true\n')
+    print(f'Config file {opt.conf} is created. This script will now exit.')
+    print(f'After restarting you may examine the entry with !models and edit it with !edit.')