complete several steps needed to make 3.0 installable

- invokeai-configure updated to work with new config system
- migrate invokeai.init to invokeai.yaml during configure
- replace legacy invokeai with invokeai-node-cli
- add ability to run an invocation directly from invokeai-node-cli command line
- update CI tests to work with new invokeai syntax

.github/workflows/test-invoke-pip.yml

@@ -133,8 +133,10 @@ jobs:
           invokeai
           --no-patchmatch
           --no-nsfw_checker
-          --from_file ${{ env.TEST_PROMPTS }}
+	  --precision=float32
+	  --always_use_cpu
           --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
+	  < ${{ env.TEST_PROMPTS }}
 
       - name: Archive results
         id: archive-results

invokeai/app/cli_app.py

@@ -10,7 +10,7 @@ from typing import (
     get_type_hints,
 )
 
-from pydantic import BaseModel
+from pydantic import BaseModel, ValidationError
 from pydantic.fields import Field
 
 
@@ -188,7 +188,14 @@ def invoke_all(context: CliContext):
 
 
 def invoke_cli():
+    # this gets the basic configuration
     config = get_invokeai_config()
+
+    # get the optional list of invocations to execute on the command line
+    parser = config.get_parser()
+    parser.add_argument('commands',nargs='*')
+    invocation_commands = parser.parse_args().commands
+    
     model_manager = get_model_manager(config,logger=logger)
     
     events = EventServiceBase()
@@ -232,8 +239,15 @@ def invoke_cli():
     context = CliContext(invoker, session, parser)
     set_autocompleter(services)
 
-    while True:
+    command_line_args_exist = len(invocation_commands) > 0
+    done = False
+    
+    while not done:
         try:
+            if command_line_args_exist:
+                cmd_input = invocation_commands.pop(0)
+                done = len(invocation_commands) == 0
+            else:
                 cmd_input = input("invoke> ")
         except (KeyboardInterrupt, EOFError):
             # Ctrl-c exits
@@ -358,6 +372,9 @@ def invoke_cli():
             invoker.services.logger.warning('Invalid command, use "help" to list commands')
             continue
 
+        except ValidationError:
+            invoker.services.logger.warning('Invalid command arguments, run "<command> --help" for summary')
+
         except SessionError:
             # Start a new session
             invoker.services.logger.warning("Session error: creating a new session")

invokeai/backend/config/invokeai_configure.py

@@ -472,19 +472,30 @@ class editOptsForm(npyscreen.FormMultiPage):
         self.nextrely += 1
         self.add_widget_intelligent(
             npyscreen.FixedText,
-            value="Directory containing embedding/textual inversion files:",
+            value="Directories containing textual inversion and LoRA models (<tab> autocompletes, ctrl-N advances):",
             editable=False,
             color="CONTROL",
         )
-        self.embedding_path = self.add_widget_intelligent(
+        self.embedding_dir = self.add_widget_intelligent(
             npyscreen.TitleFilename,
-            name="(<tab> autocompletes, ctrl-N advances):",
+            name=" Textual Inversion Embeddings:",
             value=str(default_embedding_dir()),
             select_dir=True,
             must_exist=False,
             use_two_lines=False,
             labelColor="GOOD",
-            begin_entry_at=40,
+            begin_entry_at=32,
+            scroll_exit=True,
+        )
+        self.lora_dir = self.add_widget_intelligent(
+            npyscreen.TitleFilename,
+            name="             LoRA and LyCORIS:",
+            value=str(default_lora_dir()),
+            select_dir=True,
+            must_exist=False,
+            use_two_lines=False,
+            labelColor="GOOD",
+            begin_entry_at=32,
             scroll_exit=True,
         )
         self.nextrely += 1
@@ -551,9 +562,9 @@ class editOptsForm(npyscreen.FormMultiPage):
             bad_fields.append(
                 f"The output directory does not seem to be valid. Please check that {str(Path(opt.outdir).parent)} is an existing directory."
             )
-        if not Path(opt.embedding_path).parent.exists():
+        if not Path(opt.embedding_dir).parent.exists():
             bad_fields.append(
-                f"The embedding directory does not seem to be valid. Please check that {str(Path(opt.embedding_path).parent)} is an existing directory."
+                f"The embedding directory does not seem to be valid. Please check that {str(Path(opt.embedding_dir).parent)} is an existing directory."
             )
         if len(bad_fields) > 0:
             message = "The following problems were detected and must be corrected:\n"
@@ -574,7 +585,8 @@ class editOptsForm(npyscreen.FormMultiPage):
                 "max_loaded_models",
                 "xformers_enabled",
                 "always_use_cpu",
-            "embedding_path",
+                "embedding_dir",
+                "lora_dir",
         ]:
             setattr(new_opts, attr, getattr(self, attr).value)
 
@@ -680,31 +692,21 @@ def run_console_ui(
 # -------------------------------------
 def write_opts(opts: Namespace, init_file: Path):
     """
-    Update the invokeai.init file with values from current settings.
+    Update the invokeai.yaml file with values from current settings.
     """
 
-    if Path(init_file).exists():
-        config = OmegaConf.load(init_file)
-    else:
-        config = OmegaConf.create()
-
-    if not config.globals:
-        config.globals = dict()
-        
-    globals = config.globals
-    fields = list(get_type_hints(InvokeAIAppConfig).keys())
-    for attr in fields:
-        if hasattr(opts,attr):
-            setattr(globals,attr,getattr(opts,attr))
+    # this will load current settings
+    config = InvokeAIAppConfig()
+    for key,value in opts.__dict__.items():
+        if hasattr(config,key):
+            setattr(config,key,value)
             
     with open(init_file,'w', encoding='utf-8') as file:
-        file.write(OmegaConf.to_yaml(config))
+        file.write(config.to_yaml())
         
     if opts.hf_token:
         HfLogin(opts.hf_token)
 
-
-
 # -------------------------------------
 def default_output_dir() -> Path:
     return config.root / "outputs"
@@ -713,6 +715,10 @@ def default_output_dir() -> Path:
 def default_embedding_dir() -> Path:
     return config.root / "embeddings"
 
+# -------------------------------------
+def default_lora_dir() -> Path:
+    return config.root / "loras"
+
 # -------------------------------------
 def write_default_options(program_opts: Namespace, initfile: Path):
     opt = default_startup_options(initfile)
@@ -725,35 +731,26 @@ def write_default_options(program_opts: Namespace, initfile: Path):
 # the old init file and write out the new
 # yaml format.
 def migrate_init_file(legacy_format:Path):
-    
     old = legacy_parser.parse_args([f'@{str(legacy_format)}'])
-    new = 
-    new = OmegaConf.create()
-    
-    new.globals = dict()
-    globals = new.globals
-    for attr in ['host','port']:
-        if hasattr(old,attr):
-            setattr(globals,attr,getattr(old,attr))
-    # change of name
-    globals.allow_origins = old.cors or []
+    new = InvokeAIAppConfig(conf={})
     
     fields = list(get_type_hints(InvokeAIAppConfig).keys())
     for attr in fields:
         if hasattr(old,attr):
-            setattr(globals,attr,getattr(old,attr))
+            setattr(new,attr,getattr(old,attr))
 
-    # a few places where the names have changed
-    globals.nsfw_checker = old.nsfw_checker
-    globals.xformers_enabled = old.xformers
-    globals.conf_path = old.conf
-    globals.embedding_dir = old.embedding_path
-
-    new.globals = {key: globals[key] for key in sorted(globals)}
+    # a few places where the field names have changed and we have to
+    # manually add in the new names/values
+    new.nsfw_checker = old.safety_checker
+    new.xformers_enabled = old.xformers
+    new.conf_path = old.conf
+    new.embedding_dir = old.embedding_path
 
     invokeai_yaml = legacy_format.parent / 'invokeai.yaml'
     with open(invokeai_yaml,"w", encoding="utf-8") as outfile:
-        outfile.write(OmegaConf.to_yaml(new))
+        outfile.write(new.to_yaml())
+
+    legacy_format.replace(legacy_format.parent / 'invokeai.init.old')
     
 # -------------------------------------
 def main():
@@ -822,10 +819,10 @@ def main():
         old_init_file = Path(config.root, 'invokeai.init')
         new_init_file = Path(config.root, 'invokeai.yaml')
         if old_init_file.exists() and not new_init_file.exists():
-            print('** MIGRATING OLD invokeai.init FILE TO NEW invokeai.yaml FORMAT')
+            print('** Migrating invokeai.init to invokeai.yaml')
             migrate_init_file(old_init_file)
-            # is it a good idea to re-read invokeai.yaml?
-            config = get_invokeai_config()            
+            config = get_invokeai_config()  # reread defaults
+            
             
         if not config.model_conf_path.exists():
             initialize_rootdir(config.root, opt.yes_to_all)

invokeai/backend/training/textual_inversion_training.py

@@ -47,8 +47,7 @@ from tqdm.auto import tqdm
 from transformers import CLIPTextModel, CLIPTokenizer
 
 # invokeai stuff
-from ..args import ArgFormatter, PagingArgumentParser
-from ..globals import Globals, global_cache_dir
+from invokeai.app.services.config import InvokeAIAppConfig
 
 if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
     PIL_INTERPOLATION = {
@@ -90,6 +89,8 @@ def save_progress(
 
 
 def parse_args():
+    config = InvokeAIAppConfig()
+    
     parser = PagingArgumentParser(
         description="Textual inversion training", formatter_class=ArgFormatter
     )
@@ -112,7 +113,7 @@ def parse_args():
         "--root_dir",
         "--root",
         type=Path,
-        default=Globals.root,
+        default=config.root,
         help="Path to the invokeai runtime directory",
     )
     general_group.add_argument(
@@ -127,7 +128,7 @@ def parse_args():
     general_group.add_argument(
         "--output_dir",
         type=Path,
-        default=f"{Globals.root}/text-inversion-model",
+        default=f"{config.root}/text-inversion-model",
         help="The output directory where the model predictions and checkpoints will be written.",
     )
     model_group.add_argument(
@@ -580,7 +581,7 @@ def do_textual_inversion_training(
 
     # setting up things the way invokeai expects them
     if not os.path.isabs(output_dir):
-        output_dir = os.path.join(Globals.root, output_dir)
+        output_dir = os.path.join(config.root, output_dir)
 
     logging_dir = output_dir / logging_dir
 
@@ -628,7 +629,7 @@ def do_textual_inversion_training(
         elif output_dir is not None:
             os.makedirs(output_dir, exist_ok=True)
 
-    models_conf = OmegaConf.load(os.path.join(Globals.root, "configs/models.yaml"))
+    models_conf = OmegaConf.load(os.path.join(config.root, "configs/models.yaml"))
     model_conf = models_conf.get(model, None)
     assert model_conf is not None, f"Unknown model: {model}"
     assert (
@@ -640,7 +641,7 @@ def do_textual_inversion_training(
     assert (
         pretrained_model_name_or_path
     ), f"models.yaml error: neither 'repo_id' nor 'path' is defined for {model}"
-    pipeline_args = dict(cache_dir=global_cache_dir("hub"))
+    pipeline_args = dict(cache_dir=config.cache_dir())
 
     # Load tokenizer
     if tokenizer_name:

tests/test_config.py

@@ -60,6 +60,7 @@ def test_env_override():
 
     conf = InvokeAIAppConfig(conf=init1,argv=['--no-nsfw_checker','--max_loaded=10'])
     assert conf.nsfw_checker==False
+    assert conf.max_loaded_models==10
 
     conf = InvokeAIAppConfig(conf=init1,argv=[],max_loaded_models=20)
     assert conf.max_loaded_models==20

tests/validate_pr_prompt.txt

@@ -1,3 +1,4 @@
-banana sushi -Ak_lms -S42 -s5
-banana sushi -Ak_heun -S42 -s5
-banana sushi -Addim -S42 -s5
+t2i --positive_prompt 'banana sushi' --seed 42
+compel --prompt 'strawberry sushi' | compel | noise | t2l --scheduler heun --steps 3 --scheduler ddim --link -3 conditioning positive_conditioning --link -2 conditioning negative_conditioning | l2i
+compel --prompt 'banana sushi' | compel | noise | t2i --scheduler heun --steps 3 --scheduler euler_a --link -3 conditioning positive_conditioning --link -2 conditioning negative_conditioning
+