InvokeAI/invokeai/backend/model_manager/metadata/fetch/huggingface.py
Lincoln Stein 5745ce9c7d Multiple refinements on loaders:
- Cache stat collection enabled.
- Implemented ONNX loading.
- Add ability to specify the repo version variant in installer CLI.
- If caller asks for a repo version that doesn't exist, will fall back
  to empty version rather than raising an error.
2024-03-01 10:42:33 +11:00

105 lines
3.9 KiB
Python

# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Development Team
"""
This module fetches model metadata objects from the HuggingFace model repository,
using either a `repo_id` or the model page URL.
Usage:
from invokeai.backend.model_manager.metadata.fetch import HuggingFaceMetadataFetch
fetcher = HuggingFaceMetadataFetch()
metadata = fetcher.from_url("https://huggingface.co/stabilityai/sdxl-turbo")
print(metadata.tags)
"""
import re
from pathlib import Path
from typing import Optional
import requests
from huggingface_hub import HfApi, configure_http_backend, hf_hub_url
from huggingface_hub.utils._errors import RepositoryNotFoundError, RevisionNotFoundError
from pydantic.networks import AnyHttpUrl
from requests.sessions import Session
from invokeai.backend.model_manager import ModelRepoVariant
from ..metadata_base import (
AnyModelRepoMetadata,
HuggingFaceMetadata,
RemoteModelFile,
UnknownMetadataException,
)
from .fetch_base import ModelMetadataFetchBase
HF_MODEL_RE = r"https?://huggingface.co/([\w\-.]+/[\w\-.]+)"
class HuggingFaceMetadataFetch(ModelMetadataFetchBase):
"""Fetch model metadata from HuggingFace."""
def __init__(self, session: Optional[Session] = None):
"""
Initialize the fetcher with an optional requests.sessions.Session object.
By providing a configurable Session object, we can support unit tests on
this module without an internet connection.
"""
self._requests = session or requests.Session()
configure_http_backend(backend_factory=lambda: self._requests)
@classmethod
def from_json(cls, json: str) -> HuggingFaceMetadata:
"""Given the JSON representation of the metadata, return the corresponding Pydantic object."""
metadata = HuggingFaceMetadata.model_validate_json(json)
return metadata
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.
# If not available, then set variant to None and get the default.
# If this too fails, raise exception.
model_info = None
while not model_info:
try:
model_info = HfApi().model_info(repo_id=id, files_metadata=True, revision=variant)
except RepositoryNotFoundError as excp:
raise UnknownMetadataException(f"'{id}' not found. See trace for details.") from excp
except RevisionNotFoundError:
if variant is None:
raise
else:
variant = None
_, name = id.split("/")
return HuggingFaceMetadata(
id=model_info.id,
author=model_info.author,
name=name,
last_modified=model_info.last_modified,
tag_dict=model_info.card_data.to_dict() if model_info.card_data else {},
tags=model_info.tags,
files=[
RemoteModelFile(
url=hf_hub_url(id, x.rfilename, revision=variant),
path=Path(name, x.rfilename),
size=x.size,
sha256=x.lfs.get("sha256") if x.lfs else None,
)
for x in model_info.siblings
],
)
def from_url(self, url: AnyHttpUrl) -> AnyModelRepoMetadata:
"""
Return a HuggingFaceMetadata object given the model's web page URL.
In the case of an invalid or missing URL, raises a ModelNotFound exception.
"""
if match := re.match(HF_MODEL_RE, str(url), re.IGNORECASE):
repo_id = match.group(1)
return self.from_id(repo_id)
else:
raise UnknownMetadataException(f"'{url}' does not look like a HuggingFace model page")