From df20012eb69818135c1db5b1ad7629f41b3a8789 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 6 Feb 2026 19:58:07 -0500 Subject: [PATCH 01/11] Update to Transformers 5.1.0 --- .gitignore | 7 +- invokeai.example.yaml | 62 +++++++ invokeai.yaml | 4 + invokeai/app/api/routers/model_manager.py | 8 +- invokeai/app/invocations/flux_text_encoder.py | 6 +- invokeai/app/invocations/sd3_text_encoder.py | 3 +- .../model_install/model_install_default.py | 4 +- invokeai/backend/image_util/safety_checker.py | 10 +- .../model_manager/load/model_loaders/flux.py | 13 +- .../backend/model_manager/load/model_util.py | 7 +- .../metadata/fetch/huggingface.py | 36 +++- .../model_manager/metadata/metadata_base.py | 3 +- .../scripts/quantize_t5_xxl_bnb_llm_int8.py | 7 +- .../stable_diffusion/diffusers_pipeline.py | 6 +- nodes/README.md | 51 ++++++ plan.md | 171 ++++++++++++++++++ pyproject.toml | 5 +- 17 files changed, 366 insertions(+), 37 deletions(-) create mode 100644 invokeai.example.yaml create mode 100644 invokeai.yaml create mode 100644 nodes/README.md create mode 100644 plan.md diff --git a/.gitignore b/.gitignore index 3e2a5bc7663..1bb2f412ffd 100644 --- a/.gitignore +++ b/.gitignore @@ -194,4 +194,9 @@ installer/InvokeAI-Installer/ .claude/ # Weblate configuration file -weblate.ini \ No newline at end of file +weblate.ini + +models/ +databases/ +configs/ +outputs/ \ No newline at end of file diff --git a/invokeai.example.yaml b/invokeai.example.yaml new file mode 100644 index 00000000000..654964ddd97 --- /dev/null +++ b/invokeai.example.yaml @@ -0,0 +1,62 @@ +# This is an example file with default and example settings. +# You should not copy this whole file into your config. +# Only add the settings you need to change to your config file. + +# Internal metadata - do not edit: +schema_version: 4.0.2 + +# Put user settings here - see https://invoke-ai.github.io/InvokeAI/configuration/: +host: 127.0.0.1 +port: 9090 +allow_origins: [] +allow_credentials: true +allow_methods: +- '*' +allow_headers: +- '*' +log_tokenization: false +patchmatch: true +models_dir: models +convert_cache_dir: models\.convert_cache +download_cache_dir: models\.download_cache +legacy_conf_dir: configs +db_dir: databases +outputs_dir: outputs +custom_nodes_dir: nodes +style_presets_dir: style_presets +workflow_thumbnails_dir: workflow_thumbnails +log_handlers: +- console +log_format: color +log_level: info +log_sql: false +log_level_network: warning +use_memory_db: false +dev_reload: false +profile_graphs: false +profiles_dir: profiles +log_memory_usage: false +model_cache_keep_alive_min: 0.0 +device_working_mem_gb: 3.0 +enable_partial_loading: false +keep_ram_copy_of_weights: true +lazy_offload: true +device: auto +precision: auto +sequential_guidance: false +attention_type: auto +attention_slice_size: auto +force_tiled_decode: false +pil_compress_level: 1 +max_queue_size: 10000 +clear_queue_on_startup: false +node_cache_size: 512 +hashing_algorithm: blake3_single +remote_api_tokens: +- url_regex: cool-models.com + token: my_secret_token +- url_regex: nifty-models.com + token: some_other_token +scan_models_on_startup: false +unsafe_disable_picklescan: false +allow_unknown_models: true diff --git a/invokeai.yaml b/invokeai.yaml new file mode 100644 index 00000000000..f9b7a42a5dd --- /dev/null +++ b/invokeai.yaml @@ -0,0 +1,4 @@ +# Internal metadata - do not edit: +schema_version: 4.0.2 +enable_partial_loading: true +# Put user settings here - see https://invoke-ai.github.io/InvokeAI/configuration/: diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py index ddc26d9bece..2d86a3956f6 100644 --- a/invokeai/app/api/routers/model_manager.py +++ b/invokeai/app/api/routers/model_manager.py @@ -1043,10 +1043,14 @@ class HFTokenHelper: @classmethod def get_status(cls) -> HFTokenStatus: try: - if huggingface_hub.get_token_permission(huggingface_hub.get_token()): + token = huggingface_hub.get_token() + if token is None: + # No token set + return HFTokenStatus.INVALID + if huggingface_hub.get_token_permission(token): # Valid token! return HFTokenStatus.VALID - # No token set + # Token exists but has no permissions (shouldn't normally happen) return HFTokenStatus.INVALID except Exception: return HFTokenStatus.UNKNOWN diff --git a/invokeai/app/invocations/flux_text_encoder.py b/invokeai/app/invocations/flux_text_encoder.py index 56ebbe7fd9d..580aad3286a 100644 --- a/invokeai/app/invocations/flux_text_encoder.py +++ b/invokeai/app/invocations/flux_text_encoder.py @@ -2,7 +2,7 @@ from typing import Iterator, Literal, Optional, Tuple, Union import torch -from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer, T5TokenizerFast +from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation from invokeai.app.invocations.fields import ( @@ -86,7 +86,7 @@ def _t5_encode(self, context: InvocationContext) -> torch.Tensor: ExitStack() as exit_stack, ): assert isinstance(t5_text_encoder, T5EncoderModel) - assert isinstance(t5_tokenizer, (T5Tokenizer, T5TokenizerFast)) + assert isinstance(t5_tokenizer, T5Tokenizer) # Determine if the model is quantized. # If the model is quantized, then we need to apply the LoRA weights as sidecar layers. This results in @@ -186,7 +186,7 @@ def _t5_lora_iterator(self, context: InvocationContext) -> Iterator[Tuple[ModelP def _log_t5_tokenization( self, context: InvocationContext, - tokenizer: Union[T5Tokenizer, T5TokenizerFast], + tokenizer: T5Tokenizer, ) -> None: """Logs the tokenization of a prompt for a T5-based model like FLUX.""" diff --git a/invokeai/app/invocations/sd3_text_encoder.py b/invokeai/app/invocations/sd3_text_encoder.py index 24647c9cfc7..e2ade1ddf93 100644 --- a/invokeai/app/invocations/sd3_text_encoder.py +++ b/invokeai/app/invocations/sd3_text_encoder.py @@ -8,7 +8,6 @@ CLIPTokenizer, T5EncoderModel, T5Tokenizer, - T5TokenizerFast, ) from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation @@ -102,7 +101,7 @@ def _t5_encode(self, context: InvocationContext, max_seq_len: int) -> torch.Tens ): context.util.signal_progress("Running T5 encoder") assert isinstance(t5_text_encoder, T5EncoderModel) - assert isinstance(t5_tokenizer, (T5Tokenizer, T5TokenizerFast)) + assert isinstance(t5_tokenizer, T5Tokenizer) text_inputs = t5_tokenizer( prompt, diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 77dc3dfa70a..240757a0368 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -16,7 +16,7 @@ import torch import yaml -from huggingface_hub import HfFolder +from huggingface_hub import get_token as hf_get_token from pydantic.networks import AnyHttpUrl from pydantic_core import Url from requests import Session @@ -750,7 +750,7 @@ def _import_from_hf( ) -> ModelInstallJob: # Add user's cached access token to HuggingFace requests if source.access_token is None: - source.access_token = HfFolder.get_token() + source.access_token = hf_get_token() remote_files, metadata = self._remote_files_from_source(source) return self._import_remote_model( source=source, diff --git a/invokeai/backend/image_util/safety_checker.py b/invokeai/backend/image_util/safety_checker.py index ab09a296197..1f2acc58c56 100644 --- a/invokeai/backend/image_util/safety_checker.py +++ b/invokeai/backend/image_util/safety_checker.py @@ -9,7 +9,7 @@ import numpy as np from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker from PIL import Image, ImageFilter -from transformers import AutoFeatureExtractor +from transformers import AutoImageProcessor import invokeai.backend.util.logging as logger from invokeai.app.services.config.config_default import get_config @@ -36,14 +36,14 @@ def _load_safety_checker(cls): try: model_path = get_config().models_path / CHECKER_PATH if model_path.exists(): - cls.feature_extractor = AutoFeatureExtractor.from_pretrained(model_path) + cls.feature_extractor = AutoImageProcessor.from_pretrained(model_path) cls.safety_checker = StableDiffusionSafetyChecker.from_pretrained(model_path) else: model_path.mkdir(parents=True, exist_ok=True) - cls.feature_extractor = AutoFeatureExtractor.from_pretrained(repo_id) - cls.feature_extractor.save_pretrained(model_path, safe_serialization=True) + cls.feature_extractor = AutoImageProcessor.from_pretrained(repo_id) + cls.feature_extractor.save_pretrained(model_path) cls.safety_checker = StableDiffusionSafetyChecker.from_pretrained(repo_id) - cls.safety_checker.save_pretrained(model_path, safe_serialization=True) + cls.safety_checker.save_pretrained(model_path) except Exception as e: logger.warning(f"Could not load NSFW checker: {str(e)}") diff --git a/invokeai/backend/model_manager/load/model_loaders/flux.py b/invokeai/backend/model_manager/load/model_loaders/flux.py index 2de51a8acae..be9f6e457e2 100644 --- a/invokeai/backend/model_manager/load/model_loaders/flux.py +++ b/invokeai/backend/model_manager/load/model_loaders/flux.py @@ -13,7 +13,7 @@ CLIPTextModel, CLIPTokenizer, T5EncoderModel, - T5TokenizerFast, + T5Tokenizer, ) from invokeai.app.services.config.config_default import get_config @@ -409,7 +409,7 @@ def _load_model( ) match submodel_type: case SubModelType.Tokenizer2 | SubModelType.Tokenizer3: - return T5TokenizerFast.from_pretrained( + return T5Tokenizer.from_pretrained( Path(config.path) / "tokenizer_2", max_length=512, local_files_only=True ) case SubModelType.TextEncoder2 | SubModelType.TextEncoder3: @@ -437,8 +437,11 @@ def _load_state_dict_into_t5(cls, model: T5EncoderModel, state_dict: dict[str, t missing_keys, unexpected_keys = model.load_state_dict(state_dict, strict=False, assign=True) assert len(unexpected_keys) == 0 assert set(missing_keys) == {"encoder.embed_tokens.weight"} - # Assert that the layers we expect to be shared are actually shared. - assert model.encoder.embed_tokens.weight is model.shared.weight + # Re-tie shared weights. In transformers 5.x, weight tying is implemented at the + # parameter level (via _tie_weights / tie_weights) rather than as a Python object + # alias. load_state_dict(assign=True) replaces parameters in-place, which severs + # the parameter-level tie. Calling tie_weights() re-establishes it. + model.tie_weights() @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.T5Encoder, format=ModelFormat.T5Encoder) @@ -455,7 +458,7 @@ def _load_model( match submodel_type: case SubModelType.Tokenizer2 | SubModelType.Tokenizer3: - return T5TokenizerFast.from_pretrained( + return T5Tokenizer.from_pretrained( Path(config.path) / "tokenizer_2", max_length=512, local_files_only=True ) case SubModelType.TextEncoder2 | SubModelType.TextEncoder3: diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py index c3477fa6603..0c6c8f7f4ab 100644 --- a/invokeai/backend/model_manager/load/model_util.py +++ b/invokeai/backend/model_manager/load/model_util.py @@ -10,7 +10,7 @@ import torch from diffusers.pipelines.pipeline_utils import DiffusionPipeline from diffusers.schedulers.scheduling_utils import SchedulerMixin -from transformers import CLIPTokenizer, PreTrainedTokenizerBase, T5Tokenizer, T5TokenizerFast +from transformers import CLIPTokenizer, PreTrainedTokenizerBase, T5Tokenizer from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline from invokeai.backend.image_util.grounding_dino.grounding_dino_pipeline import GroundingDinoPipeline @@ -64,10 +64,7 @@ def calc_model_size_by_data(logger: logging.Logger, model: AnyModel) -> int: return 0 elif isinstance( model, - ( - T5TokenizerFast, - T5Tokenizer, - ), + T5Tokenizer, ): # HACK(ryand): len(model) just returns the vocabulary size, so this is blatantly wrong. It should be small # relative to the text encoder that it's used with, so shouldn't matter too much, but we should fix this at some diff --git a/invokeai/backend/model_manager/metadata/fetch/huggingface.py b/invokeai/backend/model_manager/metadata/fetch/huggingface.py index 1b2b6c36742..0734a4e11af 100644 --- a/invokeai/backend/model_manager/metadata/fetch/huggingface.py +++ b/invokeai/backend/model_manager/metadata/fetch/huggingface.py @@ -16,10 +16,11 @@ import json import re from pathlib import Path +from types import SimpleNamespace from typing import Optional import requests -from huggingface_hub import HfApi, configure_http_backend, hf_hub_url +from huggingface_hub import HfApi, hf_hub_url from huggingface_hub.errors import RepositoryNotFoundError, RevisionNotFoundError from pydantic.networks import AnyHttpUrl from requests.sessions import Session @@ -47,7 +48,7 @@ def __init__(self, session: Optional[Session] = None): this module without an internet connection. """ self._requests = session or requests.Session() - configure_http_backend(backend_factory=lambda: self._requests) + self._has_custom_session = session is not None @classmethod def from_json(cls, json: str) -> HuggingFaceMetadata: @@ -55,6 +56,30 @@ def from_json(cls, json: str) -> HuggingFaceMetadata: metadata = HuggingFaceMetadata.model_validate_json(json) return metadata + def _model_info_via_session(self, repo_id: str, variant: Optional[ModelRepoVariant] = None) -> SimpleNamespace: + """Fetch model info using the injected requests session (for testing/custom backends).""" + params = {"blobs": "true"} + url = f"https://huggingface.co/api/models/{repo_id}" + if variant is not None: + url += f"/revision/{variant}" + resp = self._requests.get(url, params=params) + if resp.status_code == 404: + error_code = resp.headers.get("X-Error-Code", "") + if error_code == "RevisionNotFound" or (variant is not None): + raise RevisionNotFoundError(f"Revision '{variant}' not found for repo '{repo_id}'.") + raise RepositoryNotFoundError(f"Repository '{repo_id}' not found.") + resp.raise_for_status() + data = resp.json() + # Convert siblings dicts to SimpleNamespace objects matching HfApi.model_info() shape + siblings = [] + for s in data.get("siblings", []): + siblings.append(SimpleNamespace( + rfilename=s.get("rfilename"), + size=s.get("size") or (s.get("lfs", {}) or {}).get("size"), + lfs=s.get("lfs"), + )) + return SimpleNamespace(id=data["id"], siblings=siblings) + def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyModelRepoMetadata: """Return a HuggingFaceMetadata object given the model's repo_id.""" # Little loop which tries fetching a revision corresponding to the selected variant. @@ -67,7 +92,12 @@ def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyMod repo_id = id.split("::")[0] or id while not model_info: try: - model_info = HfApi().model_info(repo_id=repo_id, files_metadata=True, revision=variant) + # Use the injected session when provided (supports testing with mock adapters). + # Otherwise use HfApi which uses httpx internally. + if self._has_custom_session: + model_info = self._model_info_via_session(repo_id, variant) + else: + model_info = HfApi().model_info(repo_id=repo_id, files_metadata=True, revision=variant) except RepositoryNotFoundError as excp: raise UnknownMetadataException(f"'{repo_id}' not found. See trace for details.") from excp except RevisionNotFoundError: diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py index e16ad4cbc47..b048144e547 100644 --- a/invokeai/backend/model_manager/metadata/metadata_base.py +++ b/invokeai/backend/model_manager/metadata/metadata_base.py @@ -17,7 +17,7 @@ from pathlib import Path from typing import List, Literal, Optional, Union -from huggingface_hub import configure_http_backend, hf_hub_url +from huggingface_hub import hf_hub_url from pydantic import BaseModel, Field, TypeAdapter from pydantic.networks import AnyHttpUrl from requests.sessions import Session @@ -111,7 +111,6 @@ def download_urls( full-precision model is returned. """ session = session or Session() - configure_http_backend(backend_factory=lambda: session) # used in testing paths = filter_files([x.path for x in self.files], variant, subfolder, subfolders) # all files in the model diff --git a/invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py b/invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py index 2e610404cdc..1bcb1227fe8 100644 --- a/invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py +++ b/invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py @@ -15,8 +15,11 @@ def load_state_dict_into_t5(model: T5EncoderModel, state_dict: dict): missing_keys, unexpected_keys = model.load_state_dict(state_dict, strict=False, assign=True) assert len(unexpected_keys) == 0 assert set(missing_keys) == {"encoder.embed_tokens.weight"} - # Assert that the layers we expect to be shared are actually shared. - assert model.encoder.embed_tokens.weight is model.shared.weight + # Re-tie shared weights. In transformers 5.x, weight tying is implemented at the + # parameter level (via _tie_weights / tie_weights) rather than as a Python object + # alias. load_state_dict(assign=True) replaces parameters in-place, which severs + # the parameter-level tie. Calling tie_weights() re-establishes it. + model.tie_weights() def main(): diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py index de5253f0733..054e04dcb28 100644 --- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py +++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py @@ -17,7 +17,7 @@ from diffusers.schedulers.scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin from diffusers.utils.import_utils import is_xformers_available from pydantic import Field -from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer +from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from invokeai.app.services.config.config_default import get_config from invokeai.backend.stable_diffusion.diffusion.conditioning_data import IPAdapterData, TextConditioningData @@ -139,7 +139,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline): safety_checker ([`StableDiffusionSafetyChecker`]): Classification module that estimates whether generated images could be considered offensive or harmful. Please, refer to the [model card](https://huggingface.co/CompVis/stable-diffusion-v1-4) for details. - feature_extractor ([`CLIPFeatureExtractor`]): + feature_extractor ([`CLIPImageProcessor`]): Model that extracts features from generated images to be used as inputs for the `safety_checker`. """ @@ -151,7 +151,7 @@ def __init__( unet: UNet2DConditionModel, scheduler: KarrasDiffusionSchedulers, safety_checker: Optional[StableDiffusionSafetyChecker], - feature_extractor: Optional[CLIPFeatureExtractor], + feature_extractor: Optional[CLIPImageProcessor], requires_safety_checker: bool = False, ): super().__init__( diff --git a/nodes/README.md b/nodes/README.md new file mode 100644 index 00000000000..d93bb65539c --- /dev/null +++ b/nodes/README.md @@ -0,0 +1,51 @@ +# Custom Nodes / Node Packs + +Copy your node packs to this directory. + +When nodes are added or changed, you must restart the app to see the changes. + +## Directory Structure + +For a node pack to be loaded, it must be placed in a directory alongside this +file. Here's an example structure: + +```py +. +├── __init__.py # Invoke-managed custom node loader +│ +├── cool_node +│ ├── __init__.py # see example below +│ └── cool_node.py +│ +└── my_node_pack + ├── __init__.py # see example below + ├── tasty_node.py + ├── bodacious_node.py + ├── utils.py + └── extra_nodes + └── fancy_node.py +``` + +## Node Pack `__init__.py` + +Each node pack must have an `__init__.py` file that imports its nodes. + +The structure of each node or node pack is otherwise not important. + +Here are examples, based on the example directory structure. + +### `cool_node/__init__.py` + +```py +from .cool_node import CoolInvocation +``` + +### `my_node_pack/__init__.py` + +```py +from .tasty_node import TastyInvocation +from .bodacious_node import BodaciousInvocation +from .extra_nodes.fancy_node import FancyInvocation +``` + +Only nodes imported in the `__init__.py` file are loaded. diff --git a/plan.md b/plan.md new file mode 100644 index 00000000000..476b09cfcf6 --- /dev/null +++ b/plan.md @@ -0,0 +1,171 @@ +# Regression Testing Plan: Transformers 5.1.0 + HuggingFace Hub Migration + +Below is a change-by-change plan. Each section explains **what changed, why, and how to test it**. Tests are ordered from quickest smoke tests to longer end-to-end runs. + +--- + +## Change 1: `CLIPFeatureExtractor` → `CLIPImageProcessor` + +**File:** `invokeai/backend/stable_diffusion/diffusers_pipeline.py` +**Why:** `CLIPFeatureExtractor` was removed in transformers 5.x in favour of `CLIPImageProcessor`. + +| # | Test | How | +|---|------|-----| +| 1a | **Import smoke test** | `python -c "from invokeai.backend.stable_diffusion.diffusers_pipeline import StableDiffusionGeneratorPipeline"` — should not raise `ImportError` | +| 1b | **SD 1.5 text-to-image** | In the UI, load any SD 1.5 model and generate an image with a simple prompt (e.g. `"a cat on a couch"`). Confirm the image generates without errors. This exercises the full `StableDiffusionGeneratorPipeline` including the feature extractor type. | + +--- + +## Change 2: `AutoFeatureExtractor` → `AutoImageProcessor` + removed `safe_serialization` + +**File:** `invokeai/backend/image_util/safety_checker.py` +**Why:** All vision `FeatureExtractor` classes were removed in transformers 5.x. The `safe_serialization` parameter was also removed from `save_pretrained` (safetensors is now the only format). + +| # | Test | How | +|---|------|-----| +| 2a | **Import smoke test** | `python -c "from invokeai.backend.image_util.safety_checker import SafetyChecker"` | +| 2b | **NSFW checker first-time download** | Delete the local cache at `/models/core/convert/stable-diffusion-safety-checker/` if it exists. Enable the NSFW checker in config (`nsfw_checker: true`). Generate any SD 1.5 image. Confirm the safety checker downloads, saves to disk (no `safe_serialization` error), and the image either passes or is correctly blurred. | +| 2c | **NSFW checker cached load** | With the cache from 2b still present, generate another image. Confirm it loads from local path via `AutoImageProcessor.from_pretrained()` without re-downloading. | + +--- + +## Change 3: `T5TokenizerFast` → `T5Tokenizer` (4 files) + +**Files:** +- `invokeai/app/invocations/flux_text_encoder.py` +- `invokeai/app/invocations/sd3_text_encoder.py` +- `invokeai/backend/model_manager/load/model_util.py` +- `invokeai/backend/model_manager/load/model_loaders/flux.py` + +**Why:** Transformers 5.x unified slow/fast tokenizers — `T5TokenizerFast` no longer exists as a separate class. `T5Tokenizer` now uses the Rust backend by default. + +| # | Test | How | +|---|------|-----| +| 3a | **Import smoke tests** | Run each: `python -c "from invokeai.app.invocations.flux_text_encoder import FluxTextEncoderInvocation"`, same for `sd3_text_encoder`, `model_util`, and the flux loader module. | +| 3b | **FLUX text-to-image** | Load a FLUX model (e.g. FLUX.1-dev or schnell). Generate an image with prompt `"a lighthouse on a cliff at sunset"`. This exercises `T5Tokenizer.from_pretrained()` in the loader and the `isinstance(t5_tokenizer, T5Tokenizer)` assertion in the text encoder invocation. | +| 3c | **FLUX with long prompt (truncation path)** | Use a very long prompt (500+ words) with a FLUX model. Check that: the image generates, and the console shows a truncation warning (this exercises the tokenizer's truncation detection logic). | +| 3d | **SD3 text-to-image** | Load an SD3 model. Generate an image with a simple prompt. This covers the SD3 text encoder's T5 tokenization path and its `batch_decode` for truncation warnings. | +| 3e | **Model size calculation** | Load a FLUX or SD3 model and check that the model manager correctly reports the tokenizer memory footprint in the logs (exercises the `isinstance(model, T5Tokenizer)` path in `model_util.py`). No crash = pass. | + +--- + +## Change 4: `configure_http_backend` removed + session-aware metadata fetching + +**Files:** +- `invokeai/backend/model_manager/metadata/metadata_base.py` — removed `configure_http_backend` import and call +- `invokeai/backend/model_manager/metadata/fetch/huggingface.py` — removed `configure_http_backend`, added `_model_info_via_session()` fallback, added `_has_custom_session` flag + +**Why (root cause chain):** +1. `transformers>=5.1.0` pulls in `huggingface_hub>=1.0.0` as a dependency. +2. `huggingface_hub` 1.0 switched its HTTP backend from `requests` to `httpx` and removed the `configure_http_backend()` function entirely. +3. InvokeAI called `configure_http_backend(backend_factory=lambda: session)` in two places to inject a custom `requests.Session` — this was used in production for `download_urls()` and, critically, in tests to inject a `TestSession` with mock HTTP adapters so tests could run without real network calls. +4. Simply removing the calls fixed the import crash in production (since `HfApi()` now uses `httpx` internally and works fine for real HTTP). However, it broke the test suite: `HfApi().model_info()` now bypasses the mock `requests.TestSession` entirely and hits the real HuggingFace API, causing `RepositoryNotFoundError` for test-only repos like `InvokeAI-test/textual_inversion_tests`. +5. The fix: `HuggingFaceMetadataFetch` now tracks whether a custom session was injected (`_has_custom_session`). When true, `from_id()` calls a new `_model_info_via_session()` method that uses the injected `requests.Session` to query the HF API directly (matching the URL patterns the test mocks expect). When false (production), it uses `HfApi()` as before. + +| # | Test | How | +|---|------|-----| +| 4a | **Import smoke test** | `python -c "from invokeai.backend.model_manager.metadata.fetch import HuggingFaceMetadataFetch"` | +| 4b | **Automated test suite** | `pytest tests/app/services/model_install/test_model_install.py -x -v` — all 19 tests should pass, especially `test_heuristic_import_with_type`, `test_huggingface_install`, and `test_huggingface_repo_id` which depend on mock HF API responses via the injected session. | +| 4c | **Install a model from HuggingFace** | In the UI's Model Manager, add a model by HuggingFace repo ID (e.g. `stabilityai/sd-turbo`). Confirm the metadata (name, description, tags) is correctly fetched and displayed, and the model downloads successfully. This exercises the production `HfApi().model_info()` path, plus `hf_hub_url()` and `download_urls()`. | +| 4d | **Browse HF model metadata** | If the UI has a model info/details view, open it for an already-installed HF model and confirm metadata fields are populated. | + +--- + +## Change 5: `HfFolder` → `huggingface_hub.get_token()` + +**File:** `invokeai/app/services/model_install/model_install_default.py` +**Why:** `HfFolder` was removed in `huggingface_hub` 1.0+. The replacement is the top-level `get_token()` function. + +| # | Test | How | +|---|------|-----| +| 5a | **Import smoke test** | `python -c "from invokeai.app.services.model_install.model_install_default import ModelInstallService"` | +| 5b | **Install gated model (with token)** | If you have a HuggingFace account with an access token cached (`huggingface-cli login`), try installing a gated model (e.g. `black-forest-labs/FLUX.1-dev`). Confirm the token is automatically injected and the download succeeds. | +| 5c | **Install public model (no token)** | Without explicit token, install a public model. Confirm `get_token()` returns `None` gracefully and the install proceeds. | + +--- + +## Change 6: `transformers>=5.1.0` override for compel + +**File:** `pyproject.toml` — `override-dependencies` +**Why:** `compel==2.1.1` requires `transformers ~= 4.25` (`<5.0`). The uv override forces past this constraint. + +| # | Test | How | +|---|------|-----| +| 6a | **SD 1.5 prompt weights** | Generate an image with weighted prompts: `"a (red:1.5) car on a (blue:0.5) road"`. Compare to an unweighted `"a red car on a blue road"`. The weighted version should show noticeably more red and less blue. This is the core compel functionality. | +| 6b | **SD 1.5 negative prompts** | Generate with prompt `"a photo of a dog"` and negative prompt `"blurry, low quality"`. Confirm it generates without crash. | +| 6c | **SDXL prompt weights** | Same as 6a but with an SDXL model. SDXL uses a different compel path (`SDXLCompelPromptInvocation`). | +| 6d | **Prompt blending (compel syntax)** | Try compel blend syntax if supported: `"a photo of a cat".blend("a photo of a dog", 0.5)` or `("a cat", "a dog").blend(0.5, 0.5)`. This exercises deeper compel internals. | + +--- + +## Change 7: T5 shared-weight assertion → `model.tie_weights()` + +**Files:** +- `invokeai/backend/model_manager/load/model_loaders/flux.py` — `_load_state_dict_into_t5()` classmethod +- `invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py` — `load_state_dict_into_t5()` function + +**Why (root cause chain):** +1. T5 models have a shared weight: `model.shared.weight` and `model.encoder.embed_tokens.weight` should refer to the same tensor. +2. In **transformers 4.x**, this sharing was implemented as a Python object alias — both attributes literally pointed to the same `nn.Parameter` object, so `a is b` was `True`. +3. In **transformers 5.x**, weight tying is implemented at the **parameter level** via `_tie_weights()` / `tie_weights()`. The two attributes may be distinct `nn.Parameter` objects that are kept in sync by the framework, so `a is b` can be `False`. +4. InvokeAI calls `model.load_state_dict(state_dict, strict=False, assign=True)`. The `assign=True` flag replaces parameters in-place rather than copying data into existing tensors. This severs even the parameter-level tie that transformers 5.x establishes. +5. The old code then asserted `model.encoder.embed_tokens.weight is model.shared.weight`, which was guaranteed `True` in 4.x but fails in 5.x after `assign=True`. +6. **Fix:** Replace the identity assertion with `model.tie_weights()`, which re-establishes the tie regardless of how it is internally implemented. This is forward-compatible and is the officially recommended approach. + +| # | Test | How | +|---|------|-----| +| 7a | **Import smoke test** | `python -c "from invokeai.backend.model_manager.load.model_loaders.flux import FluxBnbQuantizednf4bCheckpointModel"` | +| 7b | **FLUX text-to-image** | Load a FLUX model and generate an image. This is the primary code path that calls `_load_state_dict_into_t5()`. The generation should complete without `AssertionError`. (Same as test 3b — this change and Change 3 are both exercised together.) | +| 7c | **FLUX BnB quantized model** | If you have a BnB-quantized FLUX model, load and generate with it. This exercises the `FluxBnbQuantizednf4bCheckpointModel` loader which also calls `_load_state_dict_into_t5()`. | +| 7d | **Quantize script (manual)** | If you need to re-quantize a T5 model: run `quantize_t5_xxl_bnb_llm_int8.py` and confirm it completes without assertion errors. | + +--- + +## Change 8: `HFTokenHelper.get_status()` — null token guard for `get_token_permission()` + +**File:** `invokeai/app/api/routers/model_manager.py` +**Why (root cause chain):** +1. `HFTokenHelper.get_status()` calls `huggingface_hub.get_token_permission(huggingface_hub.get_token())` to check whether a valid HF token is present. +2. When no token is configured, `get_token()` returns `None`. +3. In **huggingface_hub <1.0**, `get_token_permission(None)` returned a falsy value, so the code fell through to `return HFTokenStatus.INVALID` — correct behavior. +4. In **huggingface_hub 1.0+**, `get_token_permission(None)` **raises an exception** (it now validates the input and rejects `None`). +5. The `except Exception` catch returned `HFTokenStatus.UNKNOWN`, which the frontend interprets as a network error, showing the misleading message: *"Unable to Verify HF Token — Unable to verify HuggingFace token. This is likely due to a network error."* +6. **Fix:** Check `get_token()` for `None` first and return `INVALID` immediately, before ever calling `get_token_permission()`. This restores the correct "no token" UI message. + +| # | Test | How | +|---|------|-----| +| 8a | **No token → INVALID status** | Remove/rename your HF token file (`~/.cache/huggingface/token`), clear `$env:HF_TOKEN`, restart InvokeAI. The UI should show the proper "no token" message, **not** the "unable to verify / network error" message. | +| 8b | **Valid token → VALID status** | Restore your token (`huggingface-cli login`), restart InvokeAI. The UI should show the token as valid. | +| 8c | **Install gated model without token** | With no token, try to install a gated model (e.g. `black-forest-labs/FLUX.1-dev`). The UI should clearly indicate a token is needed, not a network error. | + +--- + +## Automated Test Suite + +| # | Command | What it covers | +|---|---------|----------------| +| A1 | `pytest ./tests -x -m "not slow"` | Run the full fast test suite. Any existing tests that touch model loading, metadata, or imports will catch regressions. The `-x` flag stops on first failure for quick feedback. | +| A2 | `pytest ./tests -x -m "slow"` | Run slow tests (if you have models available). These likely include integration tests. | + +--- + +## Quick Smoke Test Script (all imports at once) + +Run this to verify none of the changed files crash on import: + +```python +python -c " +from invokeai.backend.stable_diffusion.diffusers_pipeline import StableDiffusionGeneratorPipeline +from invokeai.backend.image_util.safety_checker import SafetyChecker +from invokeai.app.invocations.flux_text_encoder import FluxTextEncoderInvocation +from invokeai.app.invocations.sd3_text_encoder import Sd3TextEncoderInvocation +from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data +from invokeai.backend.model_manager.load.model_loaders.flux import FluxBnbQuantizednf4bCheckpointModel +from invokeai.backend.model_manager.metadata.metadata_base import HuggingFaceMetadata +from invokeai.backend.model_manager.metadata.fetch import HuggingFaceMetadataFetch +from invokeai.app.services.model_install.model_install_default import ModelInstallService +print('All imports OK') +" +``` + +If this prints `All imports OK`, you've passed the baseline. Then proceed to the UI-based tests in priority order: **6a → 3b/7b → 3d → 4b → 5c → 2b → 1b**. diff --git a/pyproject.toml b/pyproject.toml index adfe5982baf..2fac347f320 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,7 +49,7 @@ dependencies = [ "torch~=2.7.0", # torch and related dependencies are loosely pinned, will respect requirement of `diffusers[torch]` "torchsde", # diffusers needs this for SDE solvers, but it is not an explicit dep of diffusers "torchvision", - "transformers>=4.56.0", + "transformers>=5.1.0", # Core application dependencies, pinned for reproducible builds. "fastapi-events", @@ -123,7 +123,8 @@ dependencies = [ [tool.uv] # Prevent opencv-python from ever being chosen during dependency resolution. # This prevents conflicts with opencv-contrib-python, which Invoke requires. -override-dependencies = ["opencv-python; sys_platform=='never'"] +# Force transformers>=5.1.0 past compel==2.1.1's ~=4.25 (<5.0) constraint. +override-dependencies = ["opencv-python; sys_platform=='never'", "transformers>=5.1.0"] conflicts = [[{ extra = "cpu" }, { extra = "cuda" }, { extra = "rocm" }]] index-strategy = "unsafe-best-match" From f69f22ccea2896f6c1bb5ede20fd607511f4711f Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 6 Feb 2026 20:12:01 -0500 Subject: [PATCH 02/11] remove extra stuff --- .gitignore | 7 +- invokeai.example.yaml | 62 --------------- invokeai.yaml | 4 - nodes/README.md | 51 ------------- plan.md | 171 ------------------------------------------ 5 files changed, 1 insertion(+), 294 deletions(-) delete mode 100644 invokeai.example.yaml delete mode 100644 invokeai.yaml delete mode 100644 nodes/README.md delete mode 100644 plan.md diff --git a/.gitignore b/.gitignore index 1bb2f412ffd..3e2a5bc7663 100644 --- a/.gitignore +++ b/.gitignore @@ -194,9 +194,4 @@ installer/InvokeAI-Installer/ .claude/ # Weblate configuration file -weblate.ini - -models/ -databases/ -configs/ -outputs/ \ No newline at end of file +weblate.ini \ No newline at end of file diff --git a/invokeai.example.yaml b/invokeai.example.yaml deleted file mode 100644 index 654964ddd97..00000000000 --- a/invokeai.example.yaml +++ /dev/null @@ -1,62 +0,0 @@ -# This is an example file with default and example settings. -# You should not copy this whole file into your config. -# Only add the settings you need to change to your config file. - -# Internal metadata - do not edit: -schema_version: 4.0.2 - -# Put user settings here - see https://invoke-ai.github.io/InvokeAI/configuration/: -host: 127.0.0.1 -port: 9090 -allow_origins: [] -allow_credentials: true -allow_methods: -- '*' -allow_headers: -- '*' -log_tokenization: false -patchmatch: true -models_dir: models -convert_cache_dir: models\.convert_cache -download_cache_dir: models\.download_cache -legacy_conf_dir: configs -db_dir: databases -outputs_dir: outputs -custom_nodes_dir: nodes -style_presets_dir: style_presets -workflow_thumbnails_dir: workflow_thumbnails -log_handlers: -- console -log_format: color -log_level: info -log_sql: false -log_level_network: warning -use_memory_db: false -dev_reload: false -profile_graphs: false -profiles_dir: profiles -log_memory_usage: false -model_cache_keep_alive_min: 0.0 -device_working_mem_gb: 3.0 -enable_partial_loading: false -keep_ram_copy_of_weights: true -lazy_offload: true -device: auto -precision: auto -sequential_guidance: false -attention_type: auto -attention_slice_size: auto -force_tiled_decode: false -pil_compress_level: 1 -max_queue_size: 10000 -clear_queue_on_startup: false -node_cache_size: 512 -hashing_algorithm: blake3_single -remote_api_tokens: -- url_regex: cool-models.com - token: my_secret_token -- url_regex: nifty-models.com - token: some_other_token -scan_models_on_startup: false -unsafe_disable_picklescan: false -allow_unknown_models: true diff --git a/invokeai.yaml b/invokeai.yaml deleted file mode 100644 index f9b7a42a5dd..00000000000 --- a/invokeai.yaml +++ /dev/null @@ -1,4 +0,0 @@ -# Internal metadata - do not edit: -schema_version: 4.0.2 -enable_partial_loading: true -# Put user settings here - see https://invoke-ai.github.io/InvokeAI/configuration/: diff --git a/nodes/README.md b/nodes/README.md deleted file mode 100644 index d93bb65539c..00000000000 --- a/nodes/README.md +++ /dev/null @@ -1,51 +0,0 @@ -# Custom Nodes / Node Packs - -Copy your node packs to this directory. - -When nodes are added or changed, you must restart the app to see the changes. - -## Directory Structure - -For a node pack to be loaded, it must be placed in a directory alongside this -file. Here's an example structure: - -```py -. -├── __init__.py # Invoke-managed custom node loader -│ -├── cool_node -│ ├── __init__.py # see example below -│ └── cool_node.py -│ -└── my_node_pack - ├── __init__.py # see example below - ├── tasty_node.py - ├── bodacious_node.py - ├── utils.py - └── extra_nodes - └── fancy_node.py -``` - -## Node Pack `__init__.py` - -Each node pack must have an `__init__.py` file that imports its nodes. - -The structure of each node or node pack is otherwise not important. - -Here are examples, based on the example directory structure. - -### `cool_node/__init__.py` - -```py -from .cool_node import CoolInvocation -``` - -### `my_node_pack/__init__.py` - -```py -from .tasty_node import TastyInvocation -from .bodacious_node import BodaciousInvocation -from .extra_nodes.fancy_node import FancyInvocation -``` - -Only nodes imported in the `__init__.py` file are loaded. diff --git a/plan.md b/plan.md deleted file mode 100644 index 476b09cfcf6..00000000000 --- a/plan.md +++ /dev/null @@ -1,171 +0,0 @@ -# Regression Testing Plan: Transformers 5.1.0 + HuggingFace Hub Migration - -Below is a change-by-change plan. Each section explains **what changed, why, and how to test it**. Tests are ordered from quickest smoke tests to longer end-to-end runs. - ---- - -## Change 1: `CLIPFeatureExtractor` → `CLIPImageProcessor` - -**File:** `invokeai/backend/stable_diffusion/diffusers_pipeline.py` -**Why:** `CLIPFeatureExtractor` was removed in transformers 5.x in favour of `CLIPImageProcessor`. - -| # | Test | How | -|---|------|-----| -| 1a | **Import smoke test** | `python -c "from invokeai.backend.stable_diffusion.diffusers_pipeline import StableDiffusionGeneratorPipeline"` — should not raise `ImportError` | -| 1b | **SD 1.5 text-to-image** | In the UI, load any SD 1.5 model and generate an image with a simple prompt (e.g. `"a cat on a couch"`). Confirm the image generates without errors. This exercises the full `StableDiffusionGeneratorPipeline` including the feature extractor type. | - ---- - -## Change 2: `AutoFeatureExtractor` → `AutoImageProcessor` + removed `safe_serialization` - -**File:** `invokeai/backend/image_util/safety_checker.py` -**Why:** All vision `FeatureExtractor` classes were removed in transformers 5.x. The `safe_serialization` parameter was also removed from `save_pretrained` (safetensors is now the only format). - -| # | Test | How | -|---|------|-----| -| 2a | **Import smoke test** | `python -c "from invokeai.backend.image_util.safety_checker import SafetyChecker"` | -| 2b | **NSFW checker first-time download** | Delete the local cache at `/models/core/convert/stable-diffusion-safety-checker/` if it exists. Enable the NSFW checker in config (`nsfw_checker: true`). Generate any SD 1.5 image. Confirm the safety checker downloads, saves to disk (no `safe_serialization` error), and the image either passes or is correctly blurred. | -| 2c | **NSFW checker cached load** | With the cache from 2b still present, generate another image. Confirm it loads from local path via `AutoImageProcessor.from_pretrained()` without re-downloading. | - ---- - -## Change 3: `T5TokenizerFast` → `T5Tokenizer` (4 files) - -**Files:** -- `invokeai/app/invocations/flux_text_encoder.py` -- `invokeai/app/invocations/sd3_text_encoder.py` -- `invokeai/backend/model_manager/load/model_util.py` -- `invokeai/backend/model_manager/load/model_loaders/flux.py` - -**Why:** Transformers 5.x unified slow/fast tokenizers — `T5TokenizerFast` no longer exists as a separate class. `T5Tokenizer` now uses the Rust backend by default. - -| # | Test | How | -|---|------|-----| -| 3a | **Import smoke tests** | Run each: `python -c "from invokeai.app.invocations.flux_text_encoder import FluxTextEncoderInvocation"`, same for `sd3_text_encoder`, `model_util`, and the flux loader module. | -| 3b | **FLUX text-to-image** | Load a FLUX model (e.g. FLUX.1-dev or schnell). Generate an image with prompt `"a lighthouse on a cliff at sunset"`. This exercises `T5Tokenizer.from_pretrained()` in the loader and the `isinstance(t5_tokenizer, T5Tokenizer)` assertion in the text encoder invocation. | -| 3c | **FLUX with long prompt (truncation path)** | Use a very long prompt (500+ words) with a FLUX model. Check that: the image generates, and the console shows a truncation warning (this exercises the tokenizer's truncation detection logic). | -| 3d | **SD3 text-to-image** | Load an SD3 model. Generate an image with a simple prompt. This covers the SD3 text encoder's T5 tokenization path and its `batch_decode` for truncation warnings. | -| 3e | **Model size calculation** | Load a FLUX or SD3 model and check that the model manager correctly reports the tokenizer memory footprint in the logs (exercises the `isinstance(model, T5Tokenizer)` path in `model_util.py`). No crash = pass. | - ---- - -## Change 4: `configure_http_backend` removed + session-aware metadata fetching - -**Files:** -- `invokeai/backend/model_manager/metadata/metadata_base.py` — removed `configure_http_backend` import and call -- `invokeai/backend/model_manager/metadata/fetch/huggingface.py` — removed `configure_http_backend`, added `_model_info_via_session()` fallback, added `_has_custom_session` flag - -**Why (root cause chain):** -1. `transformers>=5.1.0` pulls in `huggingface_hub>=1.0.0` as a dependency. -2. `huggingface_hub` 1.0 switched its HTTP backend from `requests` to `httpx` and removed the `configure_http_backend()` function entirely. -3. InvokeAI called `configure_http_backend(backend_factory=lambda: session)` in two places to inject a custom `requests.Session` — this was used in production for `download_urls()` and, critically, in tests to inject a `TestSession` with mock HTTP adapters so tests could run without real network calls. -4. Simply removing the calls fixed the import crash in production (since `HfApi()` now uses `httpx` internally and works fine for real HTTP). However, it broke the test suite: `HfApi().model_info()` now bypasses the mock `requests.TestSession` entirely and hits the real HuggingFace API, causing `RepositoryNotFoundError` for test-only repos like `InvokeAI-test/textual_inversion_tests`. -5. The fix: `HuggingFaceMetadataFetch` now tracks whether a custom session was injected (`_has_custom_session`). When true, `from_id()` calls a new `_model_info_via_session()` method that uses the injected `requests.Session` to query the HF API directly (matching the URL patterns the test mocks expect). When false (production), it uses `HfApi()` as before. - -| # | Test | How | -|---|------|-----| -| 4a | **Import smoke test** | `python -c "from invokeai.backend.model_manager.metadata.fetch import HuggingFaceMetadataFetch"` | -| 4b | **Automated test suite** | `pytest tests/app/services/model_install/test_model_install.py -x -v` — all 19 tests should pass, especially `test_heuristic_import_with_type`, `test_huggingface_install`, and `test_huggingface_repo_id` which depend on mock HF API responses via the injected session. | -| 4c | **Install a model from HuggingFace** | In the UI's Model Manager, add a model by HuggingFace repo ID (e.g. `stabilityai/sd-turbo`). Confirm the metadata (name, description, tags) is correctly fetched and displayed, and the model downloads successfully. This exercises the production `HfApi().model_info()` path, plus `hf_hub_url()` and `download_urls()`. | -| 4d | **Browse HF model metadata** | If the UI has a model info/details view, open it for an already-installed HF model and confirm metadata fields are populated. | - ---- - -## Change 5: `HfFolder` → `huggingface_hub.get_token()` - -**File:** `invokeai/app/services/model_install/model_install_default.py` -**Why:** `HfFolder` was removed in `huggingface_hub` 1.0+. The replacement is the top-level `get_token()` function. - -| # | Test | How | -|---|------|-----| -| 5a | **Import smoke test** | `python -c "from invokeai.app.services.model_install.model_install_default import ModelInstallService"` | -| 5b | **Install gated model (with token)** | If you have a HuggingFace account with an access token cached (`huggingface-cli login`), try installing a gated model (e.g. `black-forest-labs/FLUX.1-dev`). Confirm the token is automatically injected and the download succeeds. | -| 5c | **Install public model (no token)** | Without explicit token, install a public model. Confirm `get_token()` returns `None` gracefully and the install proceeds. | - ---- - -## Change 6: `transformers>=5.1.0` override for compel - -**File:** `pyproject.toml` — `override-dependencies` -**Why:** `compel==2.1.1` requires `transformers ~= 4.25` (`<5.0`). The uv override forces past this constraint. - -| # | Test | How | -|---|------|-----| -| 6a | **SD 1.5 prompt weights** | Generate an image with weighted prompts: `"a (red:1.5) car on a (blue:0.5) road"`. Compare to an unweighted `"a red car on a blue road"`. The weighted version should show noticeably more red and less blue. This is the core compel functionality. | -| 6b | **SD 1.5 negative prompts** | Generate with prompt `"a photo of a dog"` and negative prompt `"blurry, low quality"`. Confirm it generates without crash. | -| 6c | **SDXL prompt weights** | Same as 6a but with an SDXL model. SDXL uses a different compel path (`SDXLCompelPromptInvocation`). | -| 6d | **Prompt blending (compel syntax)** | Try compel blend syntax if supported: `"a photo of a cat".blend("a photo of a dog", 0.5)` or `("a cat", "a dog").blend(0.5, 0.5)`. This exercises deeper compel internals. | - ---- - -## Change 7: T5 shared-weight assertion → `model.tie_weights()` - -**Files:** -- `invokeai/backend/model_manager/load/model_loaders/flux.py` — `_load_state_dict_into_t5()` classmethod -- `invokeai/backend/quantization/scripts/quantize_t5_xxl_bnb_llm_int8.py` — `load_state_dict_into_t5()` function - -**Why (root cause chain):** -1. T5 models have a shared weight: `model.shared.weight` and `model.encoder.embed_tokens.weight` should refer to the same tensor. -2. In **transformers 4.x**, this sharing was implemented as a Python object alias — both attributes literally pointed to the same `nn.Parameter` object, so `a is b` was `True`. -3. In **transformers 5.x**, weight tying is implemented at the **parameter level** via `_tie_weights()` / `tie_weights()`. The two attributes may be distinct `nn.Parameter` objects that are kept in sync by the framework, so `a is b` can be `False`. -4. InvokeAI calls `model.load_state_dict(state_dict, strict=False, assign=True)`. The `assign=True` flag replaces parameters in-place rather than copying data into existing tensors. This severs even the parameter-level tie that transformers 5.x establishes. -5. The old code then asserted `model.encoder.embed_tokens.weight is model.shared.weight`, which was guaranteed `True` in 4.x but fails in 5.x after `assign=True`. -6. **Fix:** Replace the identity assertion with `model.tie_weights()`, which re-establishes the tie regardless of how it is internally implemented. This is forward-compatible and is the officially recommended approach. - -| # | Test | How | -|---|------|-----| -| 7a | **Import smoke test** | `python -c "from invokeai.backend.model_manager.load.model_loaders.flux import FluxBnbQuantizednf4bCheckpointModel"` | -| 7b | **FLUX text-to-image** | Load a FLUX model and generate an image. This is the primary code path that calls `_load_state_dict_into_t5()`. The generation should complete without `AssertionError`. (Same as test 3b — this change and Change 3 are both exercised together.) | -| 7c | **FLUX BnB quantized model** | If you have a BnB-quantized FLUX model, load and generate with it. This exercises the `FluxBnbQuantizednf4bCheckpointModel` loader which also calls `_load_state_dict_into_t5()`. | -| 7d | **Quantize script (manual)** | If you need to re-quantize a T5 model: run `quantize_t5_xxl_bnb_llm_int8.py` and confirm it completes without assertion errors. | - ---- - -## Change 8: `HFTokenHelper.get_status()` — null token guard for `get_token_permission()` - -**File:** `invokeai/app/api/routers/model_manager.py` -**Why (root cause chain):** -1. `HFTokenHelper.get_status()` calls `huggingface_hub.get_token_permission(huggingface_hub.get_token())` to check whether a valid HF token is present. -2. When no token is configured, `get_token()` returns `None`. -3. In **huggingface_hub <1.0**, `get_token_permission(None)` returned a falsy value, so the code fell through to `return HFTokenStatus.INVALID` — correct behavior. -4. In **huggingface_hub 1.0+**, `get_token_permission(None)` **raises an exception** (it now validates the input and rejects `None`). -5. The `except Exception` catch returned `HFTokenStatus.UNKNOWN`, which the frontend interprets as a network error, showing the misleading message: *"Unable to Verify HF Token — Unable to verify HuggingFace token. This is likely due to a network error."* -6. **Fix:** Check `get_token()` for `None` first and return `INVALID` immediately, before ever calling `get_token_permission()`. This restores the correct "no token" UI message. - -| # | Test | How | -|---|------|-----| -| 8a | **No token → INVALID status** | Remove/rename your HF token file (`~/.cache/huggingface/token`), clear `$env:HF_TOKEN`, restart InvokeAI. The UI should show the proper "no token" message, **not** the "unable to verify / network error" message. | -| 8b | **Valid token → VALID status** | Restore your token (`huggingface-cli login`), restart InvokeAI. The UI should show the token as valid. | -| 8c | **Install gated model without token** | With no token, try to install a gated model (e.g. `black-forest-labs/FLUX.1-dev`). The UI should clearly indicate a token is needed, not a network error. | - ---- - -## Automated Test Suite - -| # | Command | What it covers | -|---|---------|----------------| -| A1 | `pytest ./tests -x -m "not slow"` | Run the full fast test suite. Any existing tests that touch model loading, metadata, or imports will catch regressions. The `-x` flag stops on first failure for quick feedback. | -| A2 | `pytest ./tests -x -m "slow"` | Run slow tests (if you have models available). These likely include integration tests. | - ---- - -## Quick Smoke Test Script (all imports at once) - -Run this to verify none of the changed files crash on import: - -```python -python -c " -from invokeai.backend.stable_diffusion.diffusers_pipeline import StableDiffusionGeneratorPipeline -from invokeai.backend.image_util.safety_checker import SafetyChecker -from invokeai.app.invocations.flux_text_encoder import FluxTextEncoderInvocation -from invokeai.app.invocations.sd3_text_encoder import Sd3TextEncoderInvocation -from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data -from invokeai.backend.model_manager.load.model_loaders.flux import FluxBnbQuantizednf4bCheckpointModel -from invokeai.backend.model_manager.metadata.metadata_base import HuggingFaceMetadata -from invokeai.backend.model_manager.metadata.fetch import HuggingFaceMetadataFetch -from invokeai.app.services.model_install.model_install_default import ModelInstallService -print('All imports OK') -" -``` - -If this prints `All imports OK`, you've passed the baseline. Then proceed to the UI-based tests in priority order: **6a → 3b/7b → 3d → 4b → 5c → 2b → 1b**. From 43afb3758e9c60da3b1b774a1b7f849668a7454d Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 29 May 2026 01:24:32 -0400 Subject: [PATCH 03/11] chore(deps): compel fork + transformers>=5.9.0 + remove override Switches compel from PyPI 2.1.1 to invoke-ai/compel@main fork which supports transformers 5.x. Bumps transformers floor to 5.9.0. Removes the transformers>=5.1.0 uv override that was only needed to bypass compel 2.1.1's <5.0 constraint. NOTE: compel fork pulls notebook dep (full Jupyter stack); flag to maintainer for cleanup. Co-Authored-By: Claude Opus 4.8 --- pyproject.toml | 7 +- uv.lock | 1142 +++++++++++++++++++++++++++++++++++++++++++----- 2 files changed, 1038 insertions(+), 111 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2fac347f320..9b5c9ae2c4f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -35,7 +35,7 @@ dependencies = [ # Core generation dependencies, pinned for reproducible builds. "accelerate", "bitsandbytes; sys_platform!='darwin'", - "compel==2.1.1", + "compel @ git+https://github.com/invoke-ai/compel.git@main", "diffusers[torch]==0.36.0", "gguf", "mediapipe==0.10.14", # needed for "mediapipeface" controlnet model @@ -49,7 +49,7 @@ dependencies = [ "torch~=2.7.0", # torch and related dependencies are loosely pinned, will respect requirement of `diffusers[torch]` "torchsde", # diffusers needs this for SDE solvers, but it is not an explicit dep of diffusers "torchvision", - "transformers>=5.1.0", + "transformers>=5.9.0", # Core application dependencies, pinned for reproducible builds. 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Read it from there with a getattr fallback so the inv_freq buffer is computed from the configured base (1e6 / 256) instead of raising AttributeError. Applies to both the safetensors and GGUF Qwen3 encoder paths. Co-Authored-By: Claude Opus 4.8 --- .../model_manager/load/model_loaders/z_image.py | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/invokeai/backend/model_manager/load/model_loaders/z_image.py b/invokeai/backend/model_manager/load/model_loaders/z_image.py index aadced8f569..f712c6ebcd9 100644 --- a/invokeai/backend/model_manager/load/model_loaders/z_image.py +++ b/invokeai/backend/model_manager/load/model_loaders/z_image.py @@ -750,7 +750,13 @@ def _load_from_singlefile( # For rotary embeddings, this is inv_freq which is computed from config if buffer_name == "inv_freq": # Compute inv_freq from config (same logic as Qwen3RotaryEmbedding.__init__) - base = qwen_config.rope_theta + # NB: transformers 5.x moved rope_theta into the rope_parameters/rope_scaling dict + rope_params = ( + getattr(qwen_config, "rope_parameters", None) + or getattr(qwen_config, "rope_scaling", None) + or {} + ) + base = rope_params.get("rope_theta") or getattr(qwen_config, "rope_theta", 1000000.0) inv_freq = 1.0 / (base ** (torch.arange(0, head_dim, 2, dtype=torch.float32) / head_dim)) parent.register_buffer(buffer_name, inv_freq.to(model_dtype), persistent=False) else: @@ -966,7 +972,13 @@ def _load_from_gguf( if buffer_name == "inv_freq": # Compute inv_freq from config - keep on CPU, cache system will move to GPU as needed - base = qwen_config.rope_theta + # NB: transformers 5.x moved rope_theta into the rope_parameters/rope_scaling dict + rope_params = ( + getattr(qwen_config, "rope_parameters", None) + or getattr(qwen_config, "rope_scaling", None) + or {} + ) + base = rope_params.get("rope_theta") or getattr(qwen_config, "rope_theta", 1000000.0) inv_freq = 1.0 / (base ** (torch.arange(0, head_dim, 2, dtype=torch.float32) / head_dim)) parent.register_buffer(buffer_name, inv_freq.to(dtype=compute_dtype), persistent=False) else: From 69b36bad1cf671f8c134ca4cf04e65309fb6f1e7 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 29 May 2026 01:51:54 -0400 Subject: [PATCH 05/11] fix(model_manager): replace removed hf_hub get_token_permission with whoami huggingface_hub 1.x removed get_token_permission(). HFTokenHelper.get_status() now validates the token via whoami(), which returns user info for a valid token and raises HfHubHTTPError for an invalid one. Preserves the original three-way status: VALID on success, INVALID on HfHubHTTPError (e.g. 401), UNKNOWN on any other error (e.g. network failure). Co-Authored-By: Claude Opus 4.8 --- invokeai/app/api/routers/model_manager.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py index 81d4a927e83..7e5b26ee8ec 100644 --- a/invokeai/app/api/routers/model_manager.py +++ b/invokeai/app/api/routers/model_manager.py @@ -14,6 +14,7 @@ from fastapi import Body, Path, Query, Response, UploadFile from fastapi.responses import FileResponse, HTMLResponse from fastapi.routing import APIRouter +from huggingface_hub.errors import HfHubHTTPError from PIL import Image from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field from starlette.exceptions import HTTPException @@ -1048,12 +1049,17 @@ def get_status(cls) -> HFTokenStatus: if token is None: # No token set return HFTokenStatus.INVALID - if huggingface_hub.get_token_permission(token): - # Valid token! - return HFTokenStatus.VALID - # Token exists but has no permissions (shouldn't normally happen) + # get_token_permission() was removed in huggingface_hub 1.x. whoami() validates + # the token against the Hub: it returns user info for a valid token and raises + # HfHubHTTPError (e.g. 401) for an invalid one. + huggingface_hub.whoami(token=token) + # Valid token! + return HFTokenStatus.VALID + except HfHubHTTPError: + # Token is present but rejected by the Hub -> invalid return HFTokenStatus.INVALID except Exception: + # Network error or other unexpected failure -> unknown return HFTokenStatus.UNKNOWN @classmethod From 9fa57924e5e86ceac44d07e41d720b649011a908 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 29 May 2026 02:27:54 -0400 Subject: [PATCH 06/11] chore(deps): regenerate uv.lock after upstream merge Co-Authored-By: Claude Opus 4.8 --- uv.lock | 396 ++++++++++++++++---------------------------------------- 1 file changed, 109 insertions(+), 287 deletions(-) diff --git a/uv.lock b/uv.lock index 7166e367730..7e12a563b3d 100644 --- a/uv.lock +++ b/uv.lock @@ -223,15 +223,24 @@ wheels = [ ] [[package]] -name = "backrefs" -version = "5.9" +name = "bcrypt" +version = "3.2.2" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/eb/a7/312f673df6a79003279e1f55619abbe7daebbb87c17c976ddc0345c04c7b/backrefs-5.9.tar.gz", hash = "sha256:808548cb708d66b82ee231f962cb36faaf4f2baab032f2fbb783e9c2fdddaa59", size = 5765857, upload-time = "2025-06-22T19:34:13.97Z" } +dependencies = [ + { name = "cffi" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/e8/36/edc85ab295ceff724506252b774155eff8a238f13730c8b13badd33ef866/bcrypt-3.2.2.tar.gz", hash = "sha256:433c410c2177057705da2a9f2cd01dd157493b2a7ac14c8593a16b3dab6b6bfb", size = 42455, upload-time = "2022-05-01T17:58:52.348Z" } wheels = [ - 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Keep our v5 assertion (T5Tokenizer only) plus upstream's new t5_device logic, and drop the now-dead T5TokenizerFast monkeypatch in the test (the name no longer exists in the module). Co-Authored-By: Claude Opus 4.8 --- invokeai/app/invocations/sd3_text_encoder.py | 4 ---- tests/app/invocations/test_sd3_text_encoder.py | 1 - 2 files changed, 5 deletions(-) diff --git a/invokeai/app/invocations/sd3_text_encoder.py b/invokeai/app/invocations/sd3_text_encoder.py index d3236ea2f31..b9763e5a214 100644 --- a/invokeai/app/invocations/sd3_text_encoder.py +++ b/invokeai/app/invocations/sd3_text_encoder.py @@ -102,12 +102,8 @@ def _t5_encode(self, context: InvocationContext, max_seq_len: int) -> torch.Tens ): context.util.signal_progress("Running T5 encoder") assert isinstance(t5_text_encoder, T5EncoderModel) -<<<<<<< HEAD assert isinstance(t5_tokenizer, T5Tokenizer) -======= - assert isinstance(t5_tokenizer, (T5Tokenizer, T5TokenizerFast)) t5_device = get_effective_device(t5_text_encoder) ->>>>>>> upstream/main text_inputs = t5_tokenizer( prompt, diff --git a/tests/app/invocations/test_sd3_text_encoder.py b/tests/app/invocations/test_sd3_text_encoder.py index 560dcba43b0..b8c47a8373e 100644 --- a/tests/app/invocations/test_sd3_text_encoder.py +++ b/tests/app/invocations/test_sd3_text_encoder.py @@ -140,7 +140,6 @@ def test_sd3_t5_encode_uses_effective_device(monkeypatch): monkeypatch.setattr(f"{module_path}.T5EncoderModel", FakeSd3T5Encoder) monkeypatch.setattr(f"{module_path}.T5Tokenizer", FakeT5Tokenizer) - monkeypatch.setattr(f"{module_path}.T5TokenizerFast", FakeT5Tokenizer) invocation = Sd3TextEncoderInvocation.model_construct( clip_l=SimpleNamespace(text_encoder=SimpleNamespace(), tokenizer=SimpleNamespace(), loras=[]), From 6c7aedbcd3c3085f6840efd13832efefd56429c2 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 29 May 2026 03:34:06 -0400 Subject: [PATCH 08/11] style: ruff fixes on merge-resolved files - flux_text_encoder.py: drop unused typing.Union (F401) left by v5 import merge - huggingface.py: ruff format (wrap append(SimpleNamespace(...))) Co-Authored-By: Claude Opus 4.8 --- invokeai/app/invocations/flux_text_encoder.py | 2 +- .../model_manager/metadata/fetch/huggingface.py | 12 +++++++----- 2 files changed, 8 insertions(+), 6 deletions(-) diff --git a/invokeai/app/invocations/flux_text_encoder.py b/invokeai/app/invocations/flux_text_encoder.py index 0d7a3f965a0..ea5841764db 100644 --- a/invokeai/app/invocations/flux_text_encoder.py +++ b/invokeai/app/invocations/flux_text_encoder.py @@ -1,5 +1,5 @@ from contextlib import ExitStack -from typing import Iterator, Literal, Optional, Tuple, Union +from typing import Iterator, Literal, Optional, Tuple import torch from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer diff --git a/invokeai/backend/model_manager/metadata/fetch/huggingface.py b/invokeai/backend/model_manager/metadata/fetch/huggingface.py index 0734a4e11af..08924bf182c 100644 --- a/invokeai/backend/model_manager/metadata/fetch/huggingface.py +++ b/invokeai/backend/model_manager/metadata/fetch/huggingface.py @@ -73,11 +73,13 @@ def _model_info_via_session(self, repo_id: str, variant: Optional[ModelRepoVaria # Convert siblings dicts to SimpleNamespace objects matching HfApi.model_info() shape siblings = [] for s in data.get("siblings", []): - siblings.append(SimpleNamespace( - rfilename=s.get("rfilename"), - size=s.get("size") or (s.get("lfs", {}) or {}).get("size"), - lfs=s.get("lfs"), - )) + siblings.append( + SimpleNamespace( + rfilename=s.get("rfilename"), + size=s.get("size") or (s.get("lfs", {}) or {}).get("size"), + lfs=s.get("lfs"), + ) + ) return SimpleNamespace(id=data["id"], siblings=siblings) def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyModelRepoMetadata: From d5d71a6df5fd54d291c37264ea15388ed6914ec7 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 29 May 2026 05:14:07 -0400 Subject: [PATCH 09/11] chore(deps): pin transformers <5.6 (diffusers single-file CLIP incompat) transformers 5.6 flattened CLIPTextModel (removed the self.text_model wrapper, hoisted embeddings/encoder/final_layer_norm to the top level). diffusers' single-file checkpoint loader (create_diffusers_clip_model_from_ldm) still assumes the nested layout, so loading SD1.5 .safetensors checkpoints fails on 5.6+ with 'CLIPTextModel object has no attribute text_model' and, once that read is shimmed, 'Cannot copy out of meta tensor' (weights never populate the flattened model). Pin to >=5.5,<5.6 (last pre-flattening release) which keeps both the single-file and from_pretrained paths working. The invoke-ai/compel fork accepts any 5.x. Co-Authored-By: Claude Opus 4.8 --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d5a3ef43dad..693bc2103d8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,7 +49,7 @@ dependencies = [ "torch~=2.7.0", # torch and related dependencies are loosely pinned, will respect requirement of `diffusers[torch]` "torchsde", # diffusers needs this for SDE solvers, but it is not an explicit dep of diffusers "torchvision", - "transformers>=5.9.0", + "transformers>=5.5,<5.6", # Core application dependencies, pinned for reproducible builds. "fastapi-events", diff --git a/uv.lock b/uv.lock index 7e12a563b3d..66f3cf89e98 100644 --- a/uv.lock +++ b/uv.lock @@ -1301,7 +1301,7 @@ requires-dist = [ { name = "torchvision", marker = "extra == 'cpu'", specifier = "==0.22.1+cpu", index = "https://download.pytorch.org/whl/cpu", conflict = { package = "invokeai", extra = "cpu" } }, { name = "torchvision", marker = "extra == 'cuda'", specifier = "==0.22.1+cu128", index = "https://download.pytorch.org/whl/cu128", conflict = { package = "invokeai", extra = "cuda" } }, { name = "torchvision", marker = "extra == 'rocm'", specifier = "==0.22.1+rocm6.3", index = "https://download.pytorch.org/whl/rocm6.3", conflict = { package = "invokeai", extra = "rocm" } }, - { name = "transformers", specifier = ">=5.9.0" }, + { name = "transformers", specifier = ">=5.5,<5.6" }, { name = "twine", marker = "extra == 'dist'" }, { name = "uvicorn", extras = ["standard"] }, { name = "xformers", marker = "sys_platform != 'darwin' and extra == 'xformers'", specifier = ">=0.0.28.post1" }, @@ -4326,7 +4326,7 @@ wheels = [ [[package]] name = "transformers" -version = "5.9.0" +version = "5.5.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "huggingface-hub" }, @@ -4339,9 +4339,9 @@ dependencies = [ { name = "tqdm" }, { name = "typer" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/51/58/7f843608f2e8421f86bb97060b54649be6239ec612b82bf9d41e65c26c00/transformers-5.9.0.tar.gz", hash = "sha256:25997cb8fa6053533171634b6162d7df54346530ec2aa9b42bb834e63668c842", size = 8642240, upload-time = "2026-05-20T14:50:49.278Z" } +sdist = { url = "https://files.pythonhosted.org/packages/a5/1e/1e244ab2ab50a863e6b52cc55761910567fa532b69a6740f6e99c5fdbd98/transformers-5.5.4.tar.gz", hash = "sha256:2e67cadba81fc7608cc07c4dd54f524820bc3d95b1cabd0ef3db7733c4f8b82e", size = 8227649, upload-time = "2026-04-13T16:55:55.181Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/02/ca/2eaa5359f2ccb8c2e1656bc26305ad0cf438aa392ce4b29ae67a315c186e/transformers-5.9.0-py3-none-any.whl", hash = "sha256:1d19509bcff7028ebc6b277d71caa712e8353778463d38764237d14b42b52788", size = 10787648, upload-time = "2026-05-20T14:50:45.337Z" }, + { url = "https://files.pythonhosted.org/packages/29/fb/162a66789c65e5afa3b051309240c26bf37fbc8fea285b4546ae747995a2/transformers-5.5.4-py3-none-any.whl", hash = "sha256:0bd6281b82966fe5a7a16f553ea517a9db1dee6284d7cb224dfd88fc0dd1c167", size = 10236696, upload-time = "2026-04-13T16:55:51.497Z" }, ] [[package]] From 5ba6e167b164b94745a17aef94ccb4461a8082c4 Mon Sep 17 00:00:00 2001 From: Your Name Date: Sat, 30 May 2026 15:02:08 -0400 Subject: [PATCH 10/11] @ chore(deps): replace compel fork with official compel 2.4.0 compel 2.4.0 (released 2026-05-30) merges the transformers-5 support that the invoke-ai fork carried (both descend from upstream PR #129), plus the maintainer-reviewed padding rework and added diffusers/T5 smoke coverage. Switch from the git fork to the PyPI release. - pyproject: compel git+main -> compel>=2.4.0,<3 - uv.lock: compel 2.3.1 (git 8f404b45) -> 2.4.0 (pypi) - transformers stays 5.5.4 (satisfies compel >=5,<6 and our <5.6 pin) Co-Authored-By: Claude Opus 4.8 @ --- pyproject.toml | 2 +- uv.lock | 10 +++++++--- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 693bc2103d8..1433ed3d22a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -35,7 +35,7 @@ dependencies = [ # Core generation dependencies, pinned for reproducible builds. "accelerate", "bitsandbytes; sys_platform!='darwin'", - "compel @ git+https://github.com/invoke-ai/compel.git@main", + "compel>=2.4.0,<3", "diffusers[torch]==0.37.0", "gguf", "mediapipe==0.10.14", # needed for "mediapipeface" controlnet model diff --git a/uv.lock b/uv.lock index 66f3cf89e98..09c4c0b82e0 100644 --- a/uv.lock +++ b/uv.lock @@ -537,8 +537,8 @@ wheels = [ [[package]] name = "compel" -version = "2.3.1" -source = { git = "https://github.com/invoke-ai/compel.git?rev=main#8f404b45ef620f37c454bc93cf35db1ddcb348e7" } +version = "2.4.0" +source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "diffusers" }, { name = "notebook" }, @@ -549,6 +549,10 @@ dependencies = [ { name = "torch", version = "2.7.1+rocm6.3", source = { registry = "https://download.pytorch.org/whl/rocm6.3" }, marker = "(extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm')" }, { name = "transformers" }, ] +sdist = { url = "https://files.pythonhosted.org/packages/d3/7b/172a6c7fcba0f669c16e3ba3dc86e80fbdaa5b2a5a7ef60807ec1d43d5c4/compel-2.4.0.tar.gz", hash = "sha256:9d935d35bb4d16fa21d4b3b529d8b8f9dc784d67b44e42f46cd48c9dd321adc2", size = 54125, upload-time = "2026-05-30T16:07:48.477Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/76/3d/16a60bb74ad3430e99bd7db8c24a2810dcdc2dd60aec36c240ce1ceeabc7/compel-2.4.0-py3-none-any.whl", hash = "sha256:27a0ce5b540fba227c23ad1943f90128a9ee6266eda760e8cfb29fb9d041ac18", size = 36941, upload-time = "2026-05-30T16:07:47.184Z" }, +] [[package]] name = "contourpy" @@ -1237,7 +1241,7 @@ requires-dist = [ { name = "bcrypt", specifier = "<4.0.0" }, { name = "bitsandbytes", marker = "sys_platform != 'darwin'" }, { name = "blake3" }, - { name = "compel", git = "https://github.com/invoke-ai/compel.git?rev=main" }, + { name = "compel", specifier = ">=2.4.0,<3" }, { name = "deprecated" }, { name = "diffusers", extras = ["torch"], specifier = "==0.37.0" }, { name = "dnspython" }, From 7eef3037531501e422786a60dff66de08cb0e453 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 28 Jun 2026 10:13:16 -0400 Subject: [PATCH 11/11] chore(uv): update uv.lock --- uv.lock | 1736 ++++++++++++++++++++++++++----------------------------- 1 file changed, 823 insertions(+), 913 deletions(-) diff --git a/uv.lock b/uv.lock index 5ccd4ed5456..6d1b0a462f8 100644 --- a/uv.lock +++ b/uv.lock @@ -2,24 +2,10 @@ version = 1 revision = 3 requires-python = ">=3.11, <3.13" resolution-markers = [ - "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version >= '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version >= '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version < '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version < '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm'", - "python_full_version >= '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version >= '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", - "python_full_version < '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version < '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", - "python_full_version >= '3.12' and sys_platform == 'darwin' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version >= '3.12' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", - "python_full_version < '3.12' and sys_platform == 'darwin' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version < '3.12' and sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", - "python_full_version >= '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version >= '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", - "python_full_version < '3.12' and sys_platform == 'darwin' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm'", - "(python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm') or (python_full_version < '3.12' and sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda' and extra != 'extra-8-invokeai-rocm')", + "(python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.12' and sys_platform == 'win32')", + "(python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.12' and sys_platform == 'win32')", + "python_full_version >= '3.12' and sys_platform == 'darwin'", + "python_full_version < '3.12' and sys_platform == 'darwin'", ] supported-markers = [ "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", @@ -44,7 +30,7 @@ wheels = [ [[package]] name = "accelerate" -version = "1.13.0" +version = "1.14.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "huggingface-hub", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or sys_platform == 'darwin' or sys_platform == 'win32' or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, @@ -53,15 +39,14 @@ dependencies = [ { name = "psutil", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 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(extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, + { name = "torchvision", version = "0.25.0+rocm7.1", source = { registry = "https://download.pytorch.org/whl/rocm7.1" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm')" }, { name = "transformers", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or (platform_machine != 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(platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or sys_platform == 'darwin' or sys_platform == 'win32' or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, ] @@ -1195,8 +1113,8 @@ test = [ { name = "ruff-lsp", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or sys_platform == 'darwin' or sys_platform == 'win32' or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, ] xformers = [ - { name = "xformers", version = "0.0.31.post1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, - { name = "xformers", version = "0.0.35", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-cpu' and extra != 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, + { name = "xformers", version = "0.0.31.post1", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra != 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra != 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, + { name = "xformers", version = "0.0.35", source = { registry = "https://pypi.org/simple" }, marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm')" }, ] [package.metadata] @@ -1268,7 +1186,7 @@ requires-dist = [ { name = "torchvision", marker = "sys_platform == 'linux' and extra == 'rocm'", specifier = "==0.25.0+rocm7.1", index = "https://download.pytorch.org/whl/rocm7.1", conflict = { package = "invokeai", extra = "rocm" } }, { name = "torchvision", marker = "extra == 'cpu'", specifier = "==0.22.1+cpu", index = "https://download.pytorch.org/whl/cpu", conflict = { package = "invokeai", extra = "cpu" } }, { name = "torchvision", marker = "extra == 'cuda'", specifier = "==0.22.1+cu128", index = "https://download.pytorch.org/whl/cu128", conflict = { package = "invokeai", extra = "cuda" } }, - { name = "transformers", specifier = ">=4.56.0" }, + { name = "transformers", specifier = ">=5.5,<5.6" }, { name = "triton-rocm", marker = "sys_platform == 'linux' and extra == 'rocm'", specifier = "==3.6.0", index = "https://download.pytorch.org/whl/rocm7.1" }, { name = "twine", marker = "extra == 'dist'" }, { name = "uvicorn", extras = ["standard"] }, @@ -1278,49 +1196,49 @@ provides-extras = ["xformers", "cpu", "cuda", "rocm", "onnx", "onnx-cuda", "onnx [[package]] name = "ipykernel" -version = "7.2.0" +version = "7.3.0" 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}, { name = "sympy", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cpu') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'darwin' and extra == 'extra-8-invokeai-cpu') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cpu') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'darwin' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or 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'extra-8-invokeai-rocm') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'darwin' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra != 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm')" }, ] @@ -3790,33 +3780,33 @@ name = "torch" version = "2.7.1+cu128" source = { registry = "https://download.pytorch.org/whl/cu128" } resolution-markers = [ - "python_full_version >= '3.12' and sys_platform == 'darwin'", "(python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.12' and sys_platform == 'win32')", - "python_full_version < '3.12' and sys_platform == 'darwin'", "(python_full_version < '3.12' and platform_machine == 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.12' and sys_platform == 'win32')", + "python_full_version >= '3.12' and sys_platform == 'darwin'", + "python_full_version < '3.12' and sys_platform == 'darwin'", ] dependencies = [ { name = "filelock", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (sys_platform == 'darwin' and extra == 'extra-8-invokeai-cuda') or (sys_platform == 'win32' and extra == 'extra-8-invokeai-cuda') or (sys_platform != 'linux' and extra == 'extra-8-invokeai-cuda' and extra == 'extra-8-invokeai-rocm') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-cuda') or (extra == 'extra-8-invokeai-cpu' and extra == 'extra-8-invokeai-rocm')" }, { name = "fsspec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'extra-8-invokeai-cuda') or (platform_machine != 'x86_64' and extra == 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