diff --git a/ldm/dream/args.py b/ldm/dream/args.py
new file mode 100644
index 0000000000..9201f46dfa
--- /dev/null
+++ b/ldm/dream/args.py
@@ -0,0 +1,619 @@
+"""Helper class for dealing with image generation arguments.
+
+The Args class parses both the command line (shell) arguments, as well as the
+command string passed at the dream> prompt. It serves as the definitive repository
+of all the arguments used by Generate and their default values.
+
+To use:
+  opt = Args()
+
+  # Read in the command line options:
+  # this returns a namespace object like the underlying argparse library)
+  # You do not have to use the return value, but you can check it against None
+  # to detect illegal arguments on the command line.
+  args = opt.parse_args()
+  if not args:
+     print('oops')
+     sys.exit(-1)
+
+  # read in a command passed to the dream> prompt:
+  opts = opt.parse_cmd('do androids dream of electric sheep? -H256 -W1024 -n4')
+
+  # The Args object acts like a namespace object
+  print(opt.model)
+
+You can set attributes in the usual way, use vars(), etc.:
+
+  opt.model = 'something-else'
+  do_something(**vars(a))
+
+It is helpful in saving metadata:
+
+  # To get a json representation of all the values, allowing
+  # you to override any values dynamically
+  j = opt.json(seed=42)
+
+  # To get the prompt string with the switches, allowing you
+  # to override any values dynamically
+  j = opt.dream_prompt_str(seed=42)
+
+If you want to access the namespace objects from the shell args or the
+parsed command directly, you may use the values returned from the
+original calls to parse_args() and parse_cmd(), or get them later
+using the _arg_switches and _cmd_switches attributes. This can be
+useful if both the args and the command contain the same attribute and
+you wish to apply logic as to which one to use. For example:
+
+  a = Args()
+  args    = a.parse_args()
+  opts    = a.parse_cmd(string)
+  do_grid = args.grid or opts.grid
+
+To add new attributes, edit the _create_arg_parser() and
+_create_dream_cmd_parser() methods.
+
+We also export the function build_metadata
+"""
+
+import argparse
+import shlex
+import json
+import hashlib
+import os
+import copy
+from ldm.dream.conditioning import split_weighted_subprompts
+
+SAMPLER_CHOICES = [
+    'ddim',
+    'k_dpm_2_a',
+    'k_dpm_2',
+    'k_euler_a',
+    'k_euler',
+    'k_heun',
+    'k_lms',
+    'plms',
+]
+
+# is there a way to pick this up during git commits?
+APP_ID      = 'lstein/stable-diffusion'
+APP_VERSION = 'v1.15'
+
+class Args(object):
+    def __init__(self,arg_parser=None,cmd_parser=None):
+        '''
+        Initialize new Args class. It takes two optional arguments, an argparse
+        parser for switches given on the shell command line, and an argparse
+        parser for switches given on the dream> CLI line. If one or both are
+        missing, it creates appropriate parsers internally.
+        '''
+        self._arg_parser   = arg_parser or self._create_arg_parser()
+        self._cmd_parser   = cmd_parser or self._create_dream_cmd_parser()
+        self._arg_switches = self.parse_cmd('')   # fill in defaults
+        self._cmd_switches = self.parse_cmd('')   # fill in defaults
+
+    def parse_args(self):
+        '''Parse the shell switches and store.'''
+        try:
+            self._arg_switches = self._arg_parser.parse_args()
+            return self._arg_switches
+        except:
+            return None
+
+    def parse_cmd(self,cmd_string):
+        '''Parse a dream>-style command string '''
+        command = cmd_string.replace("'", "\\'")
+        try:
+            elements = shlex.split(command)
+        except ValueError:
+            print(traceback.format_exc(), file=sys.stderr)
+            return
+        switches = ['']
+        switches_started = False
+
+        for element in elements:
+            if element[0] == '-' and not switches_started:
+                switches_started = True
+            if switches_started:
+                switches.append(element)
+            else:
+                switches[0] += element
+                switches[0] += ' '
+        switches[0] = switches[0][: len(switches[0]) - 1]
+        try:
+            self._cmd_switches = self._cmd_parser.parse_args(switches)
+            return self._cmd_switches
+        except:
+            return None
+
+    def json(self,**kwargs):
+        return json.dumps(self.to_dict(**kwargs))
+
+    def to_dict(self,**kwargs):
+        a = vars(self)
+        a.update(kwargs)
+        return a
+
+    # Isn't there a more automated way of doing this?
+    # Ideally we get the switch strings out of the argparse objects,
+    # but I don't see a documented API for this.
+    def dream_prompt_str(self,**kwargs):
+        """Normalized dream_prompt."""
+        a = vars(self)
+        a.update(kwargs)
+        switches = list()
+        switches.append(f'"{a["prompt"]}')
+        switches.append(f'-s {a["steps"]}')
+        switches.append(f'-W {a["width"]}')
+        switches.append(f'-H {a["height"]}')
+        switches.append(f'-C {a["cfg_scale"]}')
+        switches.append(f'-A {a["sampler_name"]}')
+        switches.append(f'-S {a["seed"]}')
+        if a['grid']:
+            switches.append('--grid')
+        if a['iterations'] and a['iterations']>0:
+            switches.append(f'-n {a["iterations"]}')
+        if a['seamless']:
+            switches.append('--seamless')
+        if a['init_img'] and len(a['init_img'])>0:
+            switches.append(f'-I {a["init_img"]}')
+        if a['fit']:
+            switches.append(f'--fit')
+        if a['strength'] and a['strength']>0:
+            switches.append(f'-f {a["strength"]}')
+        if a['gfpgan_strength']:
+            switches.append(f'-G {a["gfpgan_strength"]}')
+        if a['upscale']:
+            switches.append(f'-U {" ".join([str(u) for u in a["upscale"]])}')
+        if a['embiggen']:
+            switches.append(f'--embiggen {" ".join([str(u) for u in a["embiggen"]])}')
+        if a['embiggen_tiles']:
+            switches.append(f'--embiggen_tiles {" ".join([str(u) for u in a["embiggen_tiles"]])}')
+        if a['variation_amount'] > 0:
+            switches.append(f'-v {a["variation_amount"]}')
+        if a['with_variations']:
+            formatted_variations = ','.join(f'{seed}:{weight}' for seed, weight in (a["with_variations"]))
+            switches.append(f'-V {formatted_variations}')
+        return ' '.join(switches)
+
+    def __getattribute__(self,name):
+        '''
+        Returns union of command-line arguments and dream_prompt arguments,
+        with the latter superseding the former.
+        '''
+        cmd_switches = None
+        arg_switches = None
+        try:
+            cmd_switches = object.__getattribute__(self,'_cmd_switches')
+            arg_switches = object.__getattribute__(self,'_arg_switches')
+        except AttributeError:
+            pass
+
+        if cmd_switches and arg_switches and name=='__dict__':
+            a = arg_switches.__dict__
+            a.update(cmd_switches.__dict__)
+            return a
+
+        try:
+            return object.__getattribute__(self,name)
+        except AttributeError:
+            pass
+
+        if not hasattr(cmd_switches,name) and not hasattr(arg_switches,name):
+            raise AttributeError
+        
+        value_arg,value_cmd = (None,None)
+        try:
+            value_cmd = getattr(cmd_switches,name)
+        except AttributeError:
+            pass
+        try:
+            value_arg = getattr(arg_switches,name)
+        except AttributeError:
+            pass
+
+        # here is where we can pick and choose which to use
+        # default behavior is to choose the dream_command value over
+        # the arg value. For example, the --grid and --individual options are a little
+        # funny because of their push/pull relationship. This is how to handle it.
+        if name=='grid':
+            return value_arg or value_cmd  # arg supersedes cmd
+        if name=='individual':
+            return value_cmd or value_arg  # cmd supersedes arg
+        if value_cmd is not None:
+            return value_cmd
+        else:
+            return value_arg
+
+    def __setattr__(self,name,value):
+        if name.startswith('_'):
+            object.__setattr__(self,name,value)
+        else:
+            self._cmd_switches.__dict__[name] = value
+
+    def _create_arg_parser(self):
+        '''
+        This defines all the arguments used on the command line when you launch
+        the CLI or web backend.
+        '''
+        parser = argparse.ArgumentParser(
+            description=
+            """
+            Generate images using Stable Diffusion.
+            Use --web to launch the web interface. 
+            Use --from_file to load prompts from a file path or standard input ("-").
+            Otherwise you will be dropped into an interactive command prompt (type -h for help.)
+            Other command-line arguments are defaults that can usually be overridden
+            prompt the command prompt.
+            """,
+        )
+        model_group      = parser.add_argument_group('Model selection')
+        file_group       = parser.add_argument_group('Input/output')
+        web_server_group = parser.add_argument_group('Web server')
+        render_group     = parser.add_argument_group('Rendering')
+        postprocessing_group     = parser.add_argument_group('Postprocessing')
+        deprecated_group = parser.add_argument_group('Deprecated options')
+
+        deprecated_group.add_argument('--laion400m')
+        deprecated_group.add_argument('--weights') # deprecated
+        model_group.add_argument(
+            '--conf',
+            '-c',
+            '-conf',
+            dest='conf',
+            default='./configs/models.yaml',
+            help='Path to configuration file for alternate models.',
+        )
+        model_group.add_argument(
+            '--model',
+            default='stable-diffusion-1.4',
+            help='Indicates which diffusion model to load. (currently "stable-diffusion-1.4" (default) or "laion400m")',
+        )
+        model_group.add_argument(
+            '-F',
+            '--full_precision',
+            dest='full_precision',
+            action='store_true',
+            help='Use more memory-intensive full precision math for calculations',
+        )
+        file_group.add_argument(
+            '--from_file',
+            dest='infile',
+            type=str,
+            help='If specified, load prompts from this file',
+        )
+        file_group.add_argument(
+            '--outdir',
+            '-o',
+            type=str,
+            help='Directory to save generated images and a log of prompts and seeds. Default: outputs/img-samples',
+            default='outputs/img-samples',
+        )
+        file_group.add_argument(
+            '--prompt_as_dir',
+            '-p',
+            action='store_true',
+            help='Place images in subdirectories named after the prompt.',
+        )
+        render_group.add_argument(
+            '--seamless',
+            action='store_true',
+            help='Change the model to seamless tiling (circular) mode',
+        )
+        render_group.add_argument(
+            '--grid',
+            '-g',
+            action='store_true',
+            help='generate a grid'
+        )
+        render_group.add_argument(
+            '--embedding_path',
+            type=str,
+            help='Path to a pre-trained embedding manager checkpoint - can only be set on command line',
+        )
+        # GFPGAN related args
+        postprocessing_group.add_argument(
+            '--gfpgan_bg_upsampler',
+            type=str,
+            default='realesrgan',
+            help='Background upsampler. Default: realesrgan. Options: realesrgan, none.',
+
+        )
+        postprocessing_group.add_argument(
+            '--gfpgan_bg_tile',
+            type=int,
+            default=400,
+            help='Tile size for background sampler, 0 for no tile during testing. Default: 400.',
+        )
+        postprocessing_group.add_argument(
+            '--gfpgan_model_path',
+            type=str,
+            default='experiments/pretrained_models/GFPGANv1.3.pth',
+            help='Indicates the path to the GFPGAN model, relative to --gfpgan_dir.',
+        )
+        postprocessing_group.add_argument(
+            '--gfpgan_dir',
+            type=str,
+            default='./src/gfpgan',
+            help='Indicates the directory containing the GFPGAN code.',
+        )
+        web_server_group.add_argument(
+            '--web',
+            dest='web',
+            action='store_true',
+            help='Start in web server mode.',
+        )
+        web_server_group.add_argument(
+            '--host',
+            type=str,
+            default='127.0.0.1',
+            help='Web server: Host or IP to listen on. Set to 0.0.0.0 to accept traffic from other devices on your network.'
+        )
+        web_server_group.add_argument(
+            '--port',
+            type=int,
+            default='9090',
+            help='Web server: Port to listen on'
+        )
+        return parser
+
+    # This creates the parser that processes commands on the dream> command line
+    def _create_dream_cmd_parser(self):
+        parser = argparse.ArgumentParser(
+            description='Example: dream> a fantastic alien landscape -W1024 -H960 -s100 -n12'
+        )
+        render_group     = parser.add_argument_group('General rendering')
+        img2img_group    = parser.add_argument_group('Image-to-image and inpainting')
+        variation_group  = parser.add_argument_group('Creating and combining variations')
+        postprocessing_group   = parser.add_argument_group('Post-processing')
+        special_effects_group  = parser.add_argument_group('Special effects')
+        render_group.add_argument('prompt')
+        render_group.add_argument(
+            '-s',
+            '--steps',
+            type=int,
+            default=50,
+            help='Number of steps'
+        )
+        render_group.add_argument(
+            '-S',
+            '--seed',
+            type=int,
+            default=None,
+            help='Image seed; a +ve integer, or use -1 for the previous seed, -2 for the one before that, etc',
+        )
+        render_group.add_argument(
+            '-n',
+            '--iterations',
+            type=int,
+            default=1,
+            help='Number of samplings to perform (slower, but will provide seeds for individual images)',
+        )
+        render_group.add_argument(
+            '-W',
+            '--width',
+            type=int,
+            help='Image width, multiple of 64',
+            default=512
+        )
+        render_group.add_argument(
+            '-H',
+            '--height',
+            type=int,
+            help='Image height, multiple of 64',
+            default=512,
+        )
+        render_group.add_argument(
+            '-C',
+            '--cfg_scale',
+            default=7.5,
+            type=float,
+            help='Classifier free guidance (CFG) scale - higher numbers cause generator to "try" harder.',
+        )
+        render_group.add_argument(
+            '--grid',
+            '-g',
+            action='store_true',
+            help='generate a grid'
+        )
+        render_group.add_argument(
+            '--individual',
+            '-i',
+            action='store_true',
+            help='override command-line --grid setting and generate individual images'
+        )
+        render_group.add_argument(
+            '-x',
+            '--skip_normalize',
+            action='store_true',
+            help='Skip subprompt weight normalization',
+        )
+        render_group.add_argument(
+            '-A',
+            '-m',
+            '--sampler',
+            dest='sampler_name',
+            type=str,
+            choices=SAMPLER_CHOICES,
+            metavar='SAMPLER_NAME',
+            help=f'Switch to a different sampler. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
+            default='k_lms',
+        )
+        render_group.add_argument(
+            '-t',
+            '--log_tokenization',
+            action='store_true',
+            help='shows how the prompt is split into tokens'
+        )
+        render_group.add_argument(
+            '--outdir',
+            '-o',
+            type=str,
+            default='outputs/img-samples',
+            help='Directory to save generated images and a log of prompts and seeds',
+        )
+        img2img_group.add_argument(
+            '-I',
+            '--init_img',
+            type=str,
+            help='Path to input image for img2img mode (supersedes width and height)',
+        )
+        img2img_group.add_argument(
+            '-M',
+            '--init_mask',
+            type=str,
+            help='Path to input mask for inpainting mode (supersedes width and height)',
+        )
+        img2img_group.add_argument(
+            '-T',
+            '-fit',
+            '--fit',
+            action='store_true',
+            help='If specified, will resize the input image to fit within the dimensions of width x height (512x512 default)',
+        )
+        img2img_group.add_argument(
+            '-f',
+            '--strength',
+            type=float,
+            help='Strength for noising/unnoising. 0.0 preserves image exactly, 1.0 replaces it completely',
+            default=0.75,
+        )
+        postprocessing_group.add_argument(
+            '-G',
+            '--gfpgan_strength',
+            type=float,
+            help='The strength at which to apply the GFPGAN model to the result, in order to improve faces.',
+            default=0,
+        )
+        postprocessing_group.add_argument(
+            '-U',
+            '--upscale',
+            nargs='+',
+            type=float,
+            help='Scale factor (2, 4) for upscaling final output followed by upscaling strength (0-1.0). If strength not specified, defaults to 0.75',
+            default=None,
+        )
+        postprocessing_group.add_argument(
+            '--save_original',
+            '-save_orig',
+            action='store_true',
+            help='Save original. Use it when upscaling to save both versions.',
+        )
+        postprocessing_group.add_argument(
+            '--embiggen',
+            '-embiggen',
+            nargs='+',
+            type=float,
+            help='Embiggen tiled img2img for higher resolution and detail without extra VRAM usage. Takes scale factor relative to the size of the --init_img (-I), followed by ESRGAN upscaling strength (0-1.0), followed by minimum amount of overlap between tiles as a decimal ratio (0 - 1.0) or number of pixels. ESRGAN strength defaults to 0.75, and overlap defaults to 0.25 . ESRGAN is used to upscale the init prior to cutting it into tiles/pieces to run through img2img and then stitch back togeather.',
+            default=None,
+        )
+        postprocessing_group.add_argument(
+            '--embiggen_tiles',
+            '-embiggen_tiles',
+            nargs='+',
+            type=int,
+            help='If while doing Embiggen we are altering only parts of the image, takes a list of tiles by number to process and replace onto the image e.g. `1 3 5`, useful for redoing problematic spots from a prior Embiggen run',
+            default=None,
+        )
+        special_effects_group.add_argument(
+            '--seamless',
+            action='store_true',
+            help='Change the model to seamless tiling (circular) mode',
+        )
+        variation_group.add_argument(
+            '-v',
+            '--variation_amount',
+            default=0.0,
+            type=float,
+            help='If > 0, generates variations on the initial seed instead of random seeds per iteration. Must be between 0 and 1. Higher values will be more different.'
+        )
+        variation_group.add_argument(
+            '-V',
+            '--with_variations',
+            default=None,
+            type=str,
+            help='list of variations to apply, in the format `seed:weight,seed:weight,...'
+        )
+        return parser
+
+# very partial implementation of https://github.com/lstein/stable-diffusion/issues/266
+# it does not write all the required top-level metadata, writes too much image
+# data, and doesn't support grids yet. But you gotta start somewhere, no?
+def format_metadata(opt,
+                    seeds=[],
+                    weights=None,
+                    model_hash=None,
+                    postprocessing=None):
+    '''
+    Given an Args object, returns a partial implementation of
+    the stable diffusion metadata standard
+    '''
+    # add some RFC266 fields that are generated internally, and not as
+    # user args
+    image_dict = opt.to_dict(
+        postprocessing=postprocessing
+    )
+
+    # TODO: This is just a hack until postprocessing pipeline work completed
+    image_dict['postprocessing'] = []
+    if image_dict['gfpgan_strength'] and image_dict['gfpgan_strength'] > 0:
+        image_dict['postprocessing'].append('GFPGAN (not RFC compliant)')
+    if image_dict['upscale'] and image_dict['upscale'][0] > 0:
+        image_dict['postprocessing'].append('ESRGAN  (not RFC compliant)')
+
+    # remove any image keys not mentioned in RFC #266
+    rfc266_img_fields = ['type','postprocessing','sampler','prompt','seed','variations','steps',
+                         'cfg_scale','step_number','width','height','extra','strength']
+
+    rfc_dict ={}
+    for item in image_dict.items():
+        key,value = item
+        if key in rfc266_img_fields:
+            rfc_dict[key] = value
+
+    # semantic drift
+    rfc_dict['sampler']  = image_dict.get('sampler_name',None)
+        
+    # display weighted subprompts (liable to change)
+    if opt.prompt:
+        subprompts = split_weighted_subprompts(opt.prompt)
+        subprompts = [{'prompt':x[0],'weight':x[1]} for x in subprompts]
+        rfc_dict['prompt'] = subprompts
+
+    # variations
+    if opt.with_variations:
+        variations = [{'seed':x[0],'weight':x[1]} for x in opt.with_variations]
+        rfc_dict['variations'] = variations
+
+    if opt.init_img:
+        rfc_dict['type']           = 'img2img'
+        rfc_dict['strength_steps'] = rfc_dict.pop('strength')
+        rfc_dict['orig_hash']      = sha256(image_dict['init_img'])
+        rfc_dict['sampler']        = 'ddim'  # FIX ME WHEN IMG2IMG SUPPORTS ALL SAMPLERS
+    else:
+        rfc_dict['type']  = 'txt2img'
+
+    images = []
+    for seed in seeds:
+        rfc_dict['seed'] = seed
+        images.append(copy.copy(rfc_dict))
+
+    return {
+        'model'       : 'stable diffusion',
+        'model_id'    : opt.model,
+        'model_hash'  : model_hash,
+        'app_id'      : APP_ID,
+        'app_version' : APP_VERSION,
+        'images'      : images,
+    }
+
+# Bah. This should be moved somewhere else...
+def sha256(path):
+    sha = hashlib.sha256()
+    with open(path,'rb') as f:
+        while True:
+            data = f.read(65536)
+            if not data:
+                break
+            sha.update(data)
+    return sha.hexdigest()
+
diff --git a/ldm/dream/pngwriter.py b/ldm/dream/pngwriter.py
index 9ac8a3160f..9bf8da3b36 100644
--- a/ldm/dream/pngwriter.py
+++ b/ldm/dream/pngwriter.py
@@ -3,12 +3,13 @@ Two helper classes for dealing with PNG images and their path names.
 PngWriter -- Converts Images generated by T2I into PNGs, finds
              appropriate names for them, and writes prompt metadata
              into the PNG.
-PromptFormatter -- Utility for converting a Namespace of prompt parameters
-             back into a formatted prompt string with command-line switches.
+
+Exports function retrieve_metadata(path)
 """
 import os
 import re
-from PIL import PngImagePlugin
+import json
+from PIL import PngImagePlugin, Image
 
 # -------------------image generation utils-----
 
@@ -32,54 +33,31 @@ class PngWriter:
 
     # saves image named _image_ to outdir/name, writing metadata from prompt
     # returns full path of output
-    def save_image_and_prompt_to_png(self, image, prompt, name):
+    def save_image_and_prompt_to_png(self, image, dream_prompt, metadata, name):
         path = os.path.join(self.outdir, name)
         info = PngImagePlugin.PngInfo()
-        info.add_text('Dream', prompt)
+        info.add_text('Dream', dream_prompt)
+        info.add_text('sd-metadata', json.dumps(metadata))
         image.save(path, 'PNG', pnginfo=info)
         return path
 
+    def retrieve_metadata(self,img_basename):
+        '''
+        Given a PNG filename stored in outdir, returns the "sd-metadata"
+        metadata stored there, as a dict
+        '''
+        path = os.path.join(self.outdir,img_basename)
+        return retrieve_metadata(path)
 
-class PromptFormatter:
-    def __init__(self, t2i, opt):
-        self.t2i = t2i
-        self.opt = opt
+def retrieve_metadata(img_path):
+    '''
+    Given a path to a PNG image, returns the "sd-metadata"
+    metadata stored there, as a dict
+    '''
+    im = Image.open(img_path)
+    md = im.text.get('sd-metadata',{})
+    return json.loads(md)
 
-    # note: the t2i object should provide all these values.
-    # there should be no need to or against opt values
-    def normalize_prompt(self):
-        """Normalize the prompt and switches"""
-        t2i = self.t2i
-        opt = self.opt
 
-        switches = list()
-        switches.append(f'"{opt.prompt}"')
-        switches.append(f'-s{opt.steps        or t2i.steps}')
-        switches.append(f'-W{opt.width        or t2i.width}')
-        switches.append(f'-H{opt.height       or t2i.height}')
-        switches.append(f'-C{opt.cfg_scale    or t2i.cfg_scale}')
-        switches.append(f'-A{opt.sampler_name or t2i.sampler_name}')
-# to do: put model name into the t2i object
-#        switches.append(f'--model{t2i.model_name}')
-        if opt.seamless or t2i.seamless:
-            switches.append(f'--seamless')
-        if opt.init_img:
-            switches.append(f'-I{opt.init_img}')
-        if opt.fit:
-            switches.append(f'--fit')
-        if opt.strength and opt.init_img is not None:
-            switches.append(f'-f{opt.strength or t2i.strength}')
-        if opt.gfpgan_strength:
-            switches.append(f'-G{opt.gfpgan_strength}')
-        if opt.upscale:
-            switches.append(f'-U {" ".join([str(u) for u in opt.upscale])}')
-        if hasattr(opt, 'embiggen') and opt.embiggen:
-            switches.append(f'-embiggen {" ".join([str(u) for u in opt.embiggen])}')
-        if hasattr(opt, 'embiggen_tiles') and opt.embiggen_tiles:
-            switches.append(f'-embiggen_tiles {" ".join([str(u) for u in opt.embiggen_tiles])}')
-        if opt.variation_amount > 0:
-            switches.append(f'-v{opt.variation_amount}')
-        if opt.with_variations:
-            formatted_variations = ','.join(f'{seed}:{weight}' for seed, weight in opt.with_variations)
-            switches.append(f'-V{formatted_variations}')
-        return ' '.join(switches)
+
+    
diff --git a/ldm/dream/server.py b/ldm/dream/server.py
index 002d630326..003ec70533 100644
--- a/ldm/dream/server.py
+++ b/ldm/dream/server.py
@@ -1,14 +1,17 @@
 import argparse
 import json
+import copy
 import base64
 import mimetypes
 import os
+from ldm.dream.args import Args, format_metadata
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
-from ldm.dream.pngwriter import PngWriter, PromptFormatter
+from ldm.dream.pngwriter import PngWriter
 from threading import Event
 
 def build_opt(post_data, seed, gfpgan_model_exists):
-    opt = argparse.Namespace()
+    opt = Args()
+    opt.parse_args()  # initialize defaults
     setattr(opt, 'prompt', post_data['prompt'])
     setattr(opt, 'init_img', post_data['initimg'])
     setattr(opt, 'strength', float(post_data['strength']))
@@ -40,7 +43,7 @@ def build_opt(post_data, seed, gfpgan_model_exists):
         for part in post_data['with_variations'].split(','):
             seed_and_weight = part.split(':')
             if len(seed_and_weight) != 2:
-                print(f'could not parse with_variation part "{part}"')
+                print(f'could not parse WITH_variation part "{part}"')
                 broken = True
                 break
             try:
@@ -158,10 +161,10 @@ class DreamServer(BaseHTTPRequestHandler):
         # the images are first generated, and then again when after upscaling
         # is complete. The upscaling replaces the original file, so the second
         # entry should not be inserted into the image list.
+        # LS: This repeats code in dream.py
         def image_done(image, seed, upscaled=False):
             name = f'{prefix}.{seed}.png'
-            iter_opt = argparse.Namespace(**vars(opt)) # copy
-            print(f'iter_opt = {iter_opt}')
+            iter_opt  = copy.copy(opt)
             if opt.variation_amount > 0:
                 this_variation = [[seed, opt.variation_amount]]
                 if opt.with_variations is None:
@@ -169,10 +172,17 @@ class DreamServer(BaseHTTPRequestHandler):
                 else:
                     iter_opt.with_variations = opt.with_variations + this_variation
                 iter_opt.variation_amount = 0
-            elif opt.with_variations is None:
-                iter_opt.seed = seed
-            normalized_prompt = PromptFormatter(self.model, iter_opt).normalize_prompt()
-            path = pngwriter.save_image_and_prompt_to_png(image, f'{normalized_prompt} -S{iter_opt.seed}', name)
+            formatted_prompt  = opt.dream_prompt_str(seed=seed)
+            path = pngwriter.save_image_and_prompt_to_png(
+                image,
+                dream_prompt   = formatted_prompt,
+                metadata = format_metadata(iter_opt,
+                                           seeds      = [seed],
+                                           weights    = self.model.weights,
+                                           model_hash = self.model.model_hash
+                ),
+                name     = name,
+            )
 
             if int(config['seed']) == -1:
                 config['seed'] = seed
diff --git a/ldm/generate.py b/ldm/generate.py
index fc622c7cad..6b5cb3d794 100644
--- a/ldm/generate.py
+++ b/ldm/generate.py
@@ -13,6 +13,8 @@ import re
 import sys
 import traceback
 import transformers
+import io
+import hashlib
 
 from omegaconf import OmegaConf
 from PIL import Image, ImageOps
@@ -567,7 +569,11 @@ class Generate:
 
         # this does the work
         c     = OmegaConf.load(config)
-        pl_sd = torch.load(weights, map_location='cpu')
+        with open(weights,'rb') as f:
+            weight_bytes = f.read()
+        self.model_hash  = self._cached_sha256(weights,weight_bytes)
+        pl_sd = torch.load(io.BytesIO(weight_bytes), map_location='cpu')
+        del weight_bytes
         sd    = pl_sd['state_dict']
         model = instantiate_from_config(c.model)
         m, u  = model.load_state_dict(sd, strict=False)
@@ -728,3 +734,24 @@ class Generate:
 
     def _has_cuda(self):
         return self.device.type == 'cuda'
+
+    def _cached_sha256(self,path,data):
+        dirname    = os.path.dirname(path)
+        basename   = os.path.basename(path)
+        base, _    = os.path.splitext(basename)
+        hashpath   = os.path.join(dirname,base+'.sha256')
+        if os.path.exists(hashpath) and os.path.getmtime(path) <= os.path.getmtime(hashpath):
+            with open(hashpath) as f:
+                hash = f.read()
+            return hash
+        print(f'>> Calculating sha256 hash of weights file')
+        tic = time.time()
+        sha = hashlib.sha256()
+        sha.update(data)
+        hash = sha.hexdigest()
+        toc = time.time()
+        print(f'>> sha256 = {hash}','(%4.2fs)' % (toc - tic))
+        with open(hashpath,'w') as f:
+            f.write(hash)
+        return hash
+
diff --git a/ldm/gfpgan/gfpgan_tools.py b/ldm/gfpgan/gfpgan_tools.py
index f76790fc08..3adfc907a4 100644
--- a/ldm/gfpgan/gfpgan_tools.py
+++ b/ldm/gfpgan/gfpgan_tools.py
@@ -5,10 +5,11 @@ import sys
 import numpy as np
 
 from PIL import Image
-from scripts.dream import create_argv_parser
+#from scripts.dream import create_argv_parser
+from ldm.dream.args import Args
 
-arg_parser = create_argv_parser()
-opt        = arg_parser.parse_args()
+opt                 = Args()
+opt.parse_args()
 model_path          = os.path.join(opt.gfpgan_dir, opt.gfpgan_model_path)
 gfpgan_model_exists = os.path.isfile(model_path)
 
diff --git a/scripts/dream.py b/scripts/dream.py
old mode 100755
new mode 100644
index e5a48f38a6..35de70d650
--- a/scripts/dream.py
+++ b/scripts/dream.py
@@ -1,8 +1,6 @@
 #!/usr/bin/env python3
 # Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
 
-import argparse
-import shlex
 import os
 import re
 import sys
@@ -10,7 +8,8 @@ import copy
 import warnings
 import time
 import ldm.dream.readline
-from ldm.dream.pngwriter import PngWriter, PromptFormatter
+from ldm.dream.args import Args, format_metadata
+from ldm.dream.pngwriter import PngWriter
 from ldm.dream.server import DreamServer, ThreadingDreamServer
 from ldm.dream.image_util import make_grid
 from omegaconf import OmegaConf
@@ -22,14 +21,16 @@ output_cntr = 0
 
 def main():
     """Initialize command-line parsers and the diffusion model"""
-    arg_parser = create_argv_parser()
-    opt = arg_parser.parse_args()
+    opt  = Args()
+    args = opt.parse_args()
+    if not args:
+        sys.exit(-1)
 
-    if opt.laion400m:
+    if args.laion400m:
         print('--laion400m flag has been deprecated. Please use --model laion400m instead.')
         sys.exit(-1)
-    if opt.weights != 'model':
-        print('--weights argument has been deprecated. Please configure ./configs/models.yaml, and call it using --model instead.')
+    if args.weights:
+        print('--weights argument has been deprecated. Please edit ./configs/models.yaml, and select the weights using --model instead.')
         sys.exit(-1)
 
     print('* Initializing, be patient...\n')
@@ -47,7 +48,7 @@ def main():
     # the user input loop
     try:
         gen = Generate(
-            conf           = opt.config,
+            conf           = opt.conf,
             model          = opt.model,
             sampler_name   = opt.sampler_name,
             embedding_path = opt.embedding_path,
@@ -91,11 +92,10 @@ def main():
         dream_server_loop(gen, opt.host, opt.port, opt.outdir)
         sys.exit(0)
 
-    cmd_parser = create_cmd_parser()
-    main_loop(gen, opt.outdir, opt.prompt_as_dir, cmd_parser, infile)
+    main_loop(gen, opt, infile)
 
 # TODO: main_loop() has gotten busy. Needs to be refactored.
-def main_loop(gen, outdir, prompt_as_dir, parser, infile):
+def main_loop(gen, opt, infile):
     """prompt/read/execute loop"""
     done = False
     path_filter = re.compile(r'[<>:"/\\|?*]')
@@ -103,8 +103,8 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
 
     # os.pathconf is not available on Windows
     if hasattr(os, 'pathconf'):
-        path_max = os.pathconf(outdir, 'PC_PATH_MAX')
-        name_max = os.pathconf(outdir, 'PC_NAME_MAX')
+        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
@@ -123,41 +123,17 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
         if command.startswith(('#', '//')):
             continue
 
-        # before splitting, escape single quotes so as not to mess
-        # up the parser
-        command = command.replace("'", "\\'")
-
-        try:
-            elements = shlex.split(command)
-        except ValueError as e:
-            print(str(e))
-            continue
-
-        if elements[0] == 'q':
+        if command.startswith('q '):
             done = True
             break
 
-        if elements[0].startswith(
+        if command.startswith(
             '!dream'
         ):   # in case a stored prompt still contains the !dream command
-            elements.pop(0)
-
-        # rearrange the arguments to mimic how it works in the Dream bot.
-        switches = ['']
-        switches_started = False
-
-        for el in elements:
-            if el[0] == '-' and not switches_started:
-                switches_started = True
-            if switches_started:
-                switches.append(el)
-            else:
-                switches[0] += el
-                switches[0] += ' '
-        switches[0] = switches[0][: len(switches[0]) - 1]
+            command.replace('!dream','',1)
 
         try:
-            opt = parser.parse_args(switches)
+            parser = opt.parse_cmd(command)
         except SystemExit:
             parser.print_help()
             continue
@@ -185,6 +161,7 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
                 opt.seed = None
                 continue
 
+        # TODO - move this into a module
         if opt.with_variations is not None:
             # shotgun parsing, woo
             parts = []
@@ -220,7 +197,7 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
 
             # truncate path to maximum allowed length
             # 27 is the length of '######.##########.##.png', plus two separators and a NUL
-            subdir = subdir[:(path_max - 27 - len(os.path.abspath(outdir)))]
+            subdir = subdir[:(path_max - 27 - len(os.path.abspath(opt.outdir)))]
             current_outdir = os.path.join(outdir, subdir)
 
             print('Writing files to directory: "' + current_outdir + '"')
@@ -248,31 +225,36 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
                         filename = f'{prefix}.{seed}.postprocessed.png'
                     else:
                         filename = f'{prefix}.{seed}.png'
+                    # the handling of variations is probably broken
+                    # Also, given the ability to add stuff to the dream_prompt_str, it isn't
+                    # necessary to make a copy of the opt option just to change its attributes
                     if opt.variation_amount > 0:
-                        iter_opt = argparse.Namespace(**vars(opt))  # copy
+                        iter_opt       = copy.copy(opt)
                         this_variation = [[seed, opt.variation_amount]]
                         if opt.with_variations is None:
                             iter_opt.with_variations = this_variation
                         else:
                             iter_opt.with_variations = opt.with_variations + this_variation
                         iter_opt.variation_amount = 0
-                        normalized_prompt = PromptFormatter(
-                            gen, iter_opt).normalize_prompt()
-                        metadata_prompt = f'{normalized_prompt} -S{iter_opt.seed}'
+                        formatted_dream_prompt = iter_opt.dream_prompt_str(seed=seed)
                     elif opt.with_variations is not None:
-                        normalized_prompt = PromptFormatter(
-                            gen, opt).normalize_prompt()
-                        # use the original seed - the per-iteration value is the last variation-seed
-                        metadata_prompt = f'{normalized_prompt} -S{opt.seed}'
+                        formatted_dream_prompt = opt.dream_prompt_str(seed=seed)
                     else:
-                        normalized_prompt = PromptFormatter(
-                            gen, opt).normalize_prompt()
-                        metadata_prompt = f'{normalized_prompt} -S{seed}'
+                        formatted_dream_prompt = opt.dream_prompt_str(seed=seed)
                     path = file_writer.save_image_and_prompt_to_png(
-                        image, metadata_prompt, filename)
+                        image           = image,
+                        dream_prompt    = formatted_dream_prompt,
+                        metadata        = format_metadata(
+                            opt,
+                            seeds      = [seed],
+                            weights    = gen.weights,
+                            model_hash = gen.model_hash,
+                        ),
+                        name      = filename,
+                    )
                     if (not upscaled) or opt.save_original:
                         # only append to results if we didn't overwrite an earlier output
-                        results.append([path, metadata_prompt])
+                        results.append([path, formatted_dream_prompt])
                 last_results.append([path, seed])
 
             catch_ctrl_c = infile is None # if running interactively, we catch keyboard interrupts
@@ -286,15 +268,22 @@ def main_loop(gen, outdir, prompt_as_dir, parser, infile):
                 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'
-                # TODO better metadata for grid images
-                normalized_prompt = PromptFormatter(
-                    gen, opt).normalize_prompt()
-                metadata_prompt = f'{normalized_prompt} -S{first_seed} --grid -n{len(grid_images)} # {grid_seeds}'
+                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 = format_metadata(
+                    opt,
+                    seeds      = grid_seeds,
+                    weights    = gen.weights,
+                    model_hash = gen.model_hash
+                    )
                 path = file_writer.save_image_and_prompt_to_png(
-                    grid_img, metadata_prompt, filename
+                    image        = grid_img,
+                    dream_prompt = formatted_dream_prompt,
+                    metadata     = metadata,
+                    name         = filename
                 )
-                results = [[path, metadata_prompt]]
+                results = [[path, formatted_dream_prompt]]
 
         except AssertionError as e:
             print(e)
@@ -325,7 +314,6 @@ def get_next_command(infile=None) -> str:  # command string
             print(f'#{command}')
     return command
 
-
 def dream_server_loop(gen, host, port, outdir):
     print('\n* --web was specified, starting web server...')
     # Change working directory to the stable-diffusion directory
@@ -365,315 +353,5 @@ def write_log_message(results, log_path):
     with open(log_path, 'a', encoding='utf-8') as file:
         file.writelines(log_lines)
 
-
-SAMPLER_CHOICES = [
-    'ddim',
-    'k_dpm_2_a',
-    'k_dpm_2',
-    'k_euler_a',
-    'k_euler',
-    'k_heun',
-    'k_lms',
-    'plms',
-]
-
-
-def create_argv_parser():
-    parser = argparse.ArgumentParser(
-        description="""Generate images using Stable Diffusion.
-        Use --web to launch the web interface. 
-        Use --from_file to load prompts from a file path or standard input ("-").
-        Otherwise you will be dropped into an interactive command prompt (type -h for help.)
-        Other command-line arguments are defaults that can usually be overridden
-        prompt the command prompt.
-"""
-    )
-    parser.add_argument(
-        '--laion400m',
-        '--latent_diffusion',
-        '-l',
-        dest='laion400m',
-        action='store_true',
-        help='Fallback to the latent diffusion (laion400m) weights and config',
-    )
-    parser.add_argument(
-        '--from_file',
-        dest='infile',
-        type=str,
-        help='If specified, load prompts from this file',
-    )
-    parser.add_argument(
-        '-n',
-        '--iterations',
-        type=int,
-        default=1,
-        help='Number of images to generate',
-    )
-    parser.add_argument(
-        '-F',
-        '--full_precision',
-        dest='full_precision',
-        action='store_true',
-        help='Use more memory-intensive full precision math for calculations',
-    )
-    parser.add_argument(
-        '-g',
-        '--grid',
-        action='store_true',
-        help='Generate a grid instead of individual images',
-    )
-    parser.add_argument(
-        '-A',
-        '-m',
-        '--sampler',
-        dest='sampler_name',
-        choices=SAMPLER_CHOICES,
-        metavar='SAMPLER_NAME',
-        default='k_lms',
-        help=f'Set the initial sampler. Default: k_lms. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
-    )
-    parser.add_argument(
-        '--outdir',
-        '-o',
-        type=str,
-        default='outputs/img-samples',
-        help='Directory to save generated images and a log of prompts and seeds. Default: outputs/img-samples',
-    )
-    parser.add_argument(
-        '--seamless',
-        action='store_true',
-        help='Change the model to seamless tiling (circular) mode',
-    )
-    parser.add_argument(
-        '--embedding_path',
-        type=str,
-        help='Path to a pre-trained embedding manager checkpoint - can only be set on command line',
-    )
-    parser.add_argument(
-        '--prompt_as_dir',
-        '-p',
-        action='store_true',
-        help='Place images in subdirectories named after the prompt.',
-    )
-    # GFPGAN related args
-    parser.add_argument(
-        '--gfpgan_bg_upsampler',
-        type=str,
-        default='realesrgan',
-        help='Background upsampler. Default: realesrgan. Options: realesrgan, none.',
-
-    )
-    parser.add_argument(
-        '--gfpgan_bg_tile',
-        type=int,
-        default=400,
-        help='Tile size for background sampler, 0 for no tile during testing. Default: 400.',
-    )
-    parser.add_argument(
-        '--gfpgan_model_path',
-        type=str,
-        default='experiments/pretrained_models/GFPGANv1.3.pth',
-        help='Indicates the path to the GFPGAN model, relative to --gfpgan_dir.',
-    )
-    parser.add_argument(
-        '--gfpgan_dir',
-        type=str,
-        default='./src/gfpgan',
-        help='Indicates the directory containing the GFPGAN code.',
-    )
-    parser.add_argument(
-        '--web',
-        dest='web',
-        action='store_true',
-        help='Start in web server mode.',
-    )
-    parser.add_argument(
-        '--host',
-        type=str,
-        default='127.0.0.1',
-        help='Web server: Host or IP to listen on. Set to 0.0.0.0 to accept traffic from other devices on your network.'
-    )
-    parser.add_argument(
-        '--port',
-        type=int,
-        default='9090',
-        help='Web server: Port to listen on'
-    )
-    parser.add_argument(
-        '--weights',
-        default='model',
-        help='Indicates the Stable Diffusion model to use.',
-    )
-    parser.add_argument(
-        '--model',
-        default='stable-diffusion-1.4',
-        help='Indicates which diffusion model to load. (currently "stable-diffusion-1.4" (default) or "laion400m")',
-    )
-    parser.add_argument(
-        '--config',
-        default='configs/models.yaml',
-        help='Path to configuration file for alternate models.',
-    )
-    return parser
-
-
-def create_cmd_parser():
-    parser = argparse.ArgumentParser(
-        description='Example: dream> a fantastic alien landscape -W1024 -H960 -s100 -n12'
-    )
-    parser.add_argument('prompt')
-    parser.add_argument('-s', '--steps', type=int, help='Number of steps')
-    parser.add_argument(
-        '-S',
-        '--seed',
-        type=int,
-        help='Image seed; a +ve integer, or use -1 for the previous seed, -2 for the one before that, etc',
-    )
-    parser.add_argument(
-        '-n',
-        '--iterations',
-        type=int,
-        default=1,
-        help='Number of samplings to perform (slower, but will provide seeds for individual images)',
-    )
-    parser.add_argument(
-        '-W', '--width', type=int, help='Image width, multiple of 64'
-    )
-    parser.add_argument(
-        '-H', '--height', type=int, help='Image height, multiple of 64'
-    )
-    parser.add_argument(
-        '-C',
-        '--cfg_scale',
-        default=7.5,
-        type=float,
-        help='Classifier free guidance (CFG) scale - higher numbers cause generator to "try" harder.',
-    )
-    parser.add_argument(
-        '-g', '--grid', action='store_true', help='generate a grid'
-    )
-    parser.add_argument(
-        '--outdir',
-        '-o',
-        type=str,
-        default=None,
-        help='Directory to save generated images and a log of prompts and seeds',
-    )
-    parser.add_argument(
-        '--seamless',
-        action='store_true',
-        help='Change the model to seamless tiling (circular) mode',
-    )
-    parser.add_argument(
-        '-i',
-        '--individual',
-        action='store_true',
-        help='Generate individual files (default)',
-    )
-    parser.add_argument(
-        '-I',
-        '--init_img',
-        type=str,
-        help='Path to input image for img2img mode (supersedes width and height)',
-    )
-    parser.add_argument(
-        '-M',
-        '--init_mask',
-        type=str,
-        help='Path to input mask for inpainting mode (supersedes width and height)',
-    )
-    parser.add_argument(
-        '-T',
-        '-fit',
-        '--fit',
-        action='store_true',
-        help='If specified, will resize the input image to fit within the dimensions of width x height (512x512 default)',
-    )
-    parser.add_argument(
-        '-f',
-        '--strength',
-        default=0.75,
-        type=float,
-        help='Strength for noising/unnoising. 0.0 preserves image exactly, 1.0 replaces it completely',
-    )
-    parser.add_argument(
-        '-G',
-        '--gfpgan_strength',
-        default=0,
-        type=float,
-        help='The strength at which to apply the GFPGAN model to the result, in order to improve faces.',
-    )
-    parser.add_argument(
-        '-U',
-        '--upscale',
-        nargs='+',
-        default=None,
-        type=float,
-        help='Scale factor (2, 4) for upscaling final output followed by upscaling strength (0-1.0). If strength not specified, defaults to 0.75'
-    )
-    parser.add_argument(
-        '-save_orig',
-        '--save_original',
-        action='store_true',
-        help='Save original. Use it when upscaling to save both versions.',
-    )
-    parser.add_argument(
-        '-embiggen',
-        '--embiggen',
-        nargs='+',
-        default=None,
-        type=float,
-        help='Embiggen tiled img2img for higher resolution and detail without extra VRAM usage. Takes scale factor relative to the size of the --init_img (-I), followed by ESRGAN upscaling strength (0-1.0), followed by minimum amount of overlap between tiles as a decimal ratio (0 - 1.0) or number of pixels. ESRGAN strength defaults to 0.75, and overlap defaults to 0.25 . ESRGAN is used to upscale the init prior to cutting it into tiles/pieces to run through img2img and then stitch back togeather.',
-    )
-    parser.add_argument(
-        '-embiggen_tiles',
-        '--embiggen_tiles',
-        nargs='+',
-        default=None,
-        type=int,
-        help='If while doing Embiggen we are altering only parts of the image, takes a list of tiles by number to process and replace onto the image e.g. `1 3 5`, useful for redoing problematic spots from a prior Embiggen run',
-    )
-    # variants is going to be superseded by a generalized "prompt-morph" function
-    #    parser.add_argument('-v','--variants',type=int,help="in img2img mode, the first generated image will get passed back to img2img to generate the requested number of variants")
-    parser.add_argument(
-        '-x',
-        '--skip_normalize',
-        action='store_true',
-        help='Skip subprompt weight normalization',
-    )
-    parser.add_argument(
-        '-A',
-        '-m',
-        '--sampler',
-        dest='sampler_name',
-        default=None,
-        type=str,
-        choices=SAMPLER_CHOICES,
-        metavar='SAMPLER_NAME',
-        help=f'Switch to a different sampler. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
-    )
-    parser.add_argument(
-        '-t',
-        '--log_tokenization',
-        action='store_true',
-        help='shows how the prompt is split into tokens'
-    )
-    parser.add_argument(
-        '-v',
-        '--variation_amount',
-        default=0.0,
-        type=float,
-        help='If > 0, generates variations on the initial seed instead of random seeds per iteration. Must be between 0 and 1. Higher values will be more different.'
-    )
-    parser.add_argument(
-        '-V',
-        '--with_variations',
-        default=None,
-        type=str,
-        help='list of variations to apply, in the format `seed:weight,seed:weight,...'
-    )
-    return parser
-
-
 if __name__ == '__main__':
     main()
diff --git a/scripts/sd-metadata.py b/scripts/sd-metadata.py
new file mode 100644
index 0000000000..a3438fa078
--- /dev/null
+++ b/scripts/sd-metadata.py
@@ -0,0 +1,22 @@
+#!/usr/bin/env python
+
+import sys
+import json
+from ldm.dream.pngwriter import retrieve_metadata
+
+if len(sys.argv) < 2:
+    print("Usage: file2prompt.py <file1.png> <file2.png> <file3.png>...")
+    print("This script opens up the indicated dream.py-generated PNG file(s) and prints out their metadata.")
+    exit(-1)
+
+filenames = sys.argv[1:]
+for f in filenames:
+    try:
+        metadata = retrieve_metadata(f)
+        print(f'{f}:\n',json.dumps(metadata, indent=4))
+    except FileNotFoundError:
+        sys.stderr.write(f'{f} not found\n')
+        continue
+    except PermissionError:
+        sys.stderr.write(f'{f} could not be opened due to inadequate permissions\n')
+        continue