chore: add initial github ci & fix tests (#17)

* chore: add github ci

fix: tests

* chore: offline mode paring code deduplication

Author: bsbds

.github/workflows/ci.yml

@@ -0,0 +1,31 @@
+name: Tests
+
+on:
+    push:
+    pull_request:
+    workflow_dispatch:
+
+jobs:
+    pytest:
+        name: Pytest (${{ matrix.python-version }})
+        runs-on: ubuntu-latest
+        strategy:
+            matrix:
+                python-version: ["3.10", "3.11", "3.12", "3.13"]
+
+        steps:
+            - uses: actions/checkout@v4
+
+            - name: Set up Python
+              uses: actions/setup-python@v5
+              with:
+                  python-version: ${{ matrix.python-version }}
+                  cache: "pip"
+
+            - name: Install dependencies
+              run: |
+                  python -m pip install --upgrade pip
+                  python -m pip install -e . pytest
+
+            - name: Run tests
+              run: python -m pytest tests

deepdoc/common/misc_utils.py

@@ -15,6 +15,7 @@
 #
 
 import logging
+import os
 
 logger = logging.getLogger(__name__)
 
@@ -31,3 +32,13 @@ def pip_install_torch():
         return True
     except ImportError:
         return False
+
+
+def parse_bool(value: str | None, default: bool = False) -> bool:
+    if value is None:
+        return default
+    return value.strip().lower() in {"1", "true", "yes", "on"}
+
+
+def offline_mode_or_from_env(offline: bool | None = None) -> bool:
+    return offline if offline is not None else parse_bool(os.getenv("DEEPDOC_OFFLINE"), default=False)

deepdoc/common/model_store.py

@@ -22,17 +22,14 @@
 import logging
 import os
 from dataclasses import dataclass
+from importlib import resources
 from pathlib import Path
+from ..common.misc_utils import offline_mode_or_from_env
 
 
 GLOBAL_MODELSCOPE_REPO_ENV = "DEEPDOC_MODELSCOPE_REPO"
 GLOBAL_MODELSCOPE_REVISION_ENV = "DEEPDOC_MODELSCOPE_REVISION"
-
-
-def _parse_bool(value: str | None, default: bool = False) -> bool:
-    if value is None:
-        return default
-    return value.strip().lower() in {"1", "true", "yes", "on"}
+TOKENIZER_MODEL_DIR_ENV = "DEEPDOC_TOKENIZER_MODEL_DIR"
 
 
 def _normalize_provider(provider: str | None) -> str:
@@ -56,6 +53,18 @@ def _model_home_path(model_home: str | None) -> Path:
     return Path.home().joinpath(".cache", "deepdoc")
 
 
+def _resolve_tokenizer_dict_path() -> Path:
+    configured_dir = os.getenv(TOKENIZER_MODEL_DIR_ENV)
+    if configured_dir:
+        dictionary = Path(configured_dir).expanduser().resolve().joinpath("huqie.txt")
+    else:
+        dictionary = Path(str(resources.files("deepdoc").joinpath("dict", "huqie.txt"))).resolve()
+
+    if not dictionary.exists():
+        raise FileNotFoundError("Tokenizer dictionary not found: {}. Set {} to a directory containing huqie.txt.".format(dictionary, TOKENIZER_MODEL_DIR_ENV))
+    return dictionary
+
+
 @dataclass(frozen=True)
 class BundleSpec:
     name: str
@@ -243,7 +252,7 @@ def resolve_bundle_dir(
 
     spec = BUNDLES[bundle]
     provider_name = _normalize_provider(provider)
-    offline_mode = offline if offline is not None else _parse_bool(os.getenv("DEEPDOC_OFFLINE"), default=False)
+    offline_mode = offline_mode_or_from_env(offline)
 
     explicit_local = os.getenv(spec.local_dir_env)
     if explicit_local:
@@ -356,5 +365,5 @@ def resolve_tokenizer_dict_prefix(
     provider: str | None = None,
     offline: bool | None = None,
 ) -> str:
-    bundle_dir = Path(resolve_bundle_dir("tokenizer", model_home=model_home, provider=provider, offline=offline))
-    return str(bundle_dir.joinpath("huqie"))
+    del model_home, provider, offline
+    return str(_resolve_tokenizer_dict_path().with_suffix(""))

deepdoc/config.py

@@ -11,16 +11,11 @@
     resolve_xgb_model_dir,
     validate_bundle_dir,
 )
+from .common.misc_utils import offline_mode_or_from_env
 
 ProviderType = Literal["local", "modelscope", "auto"]
 
 
-def _parse_bool(value: str | None, default: bool = False) -> bool:
-    if value is None:
-        return default
-    return value.strip().lower() in {"1", "true", "yes", "on"}
-
-
 def _normalize_provider(provider: str) -> ProviderType:
     normalized = provider.strip().lower()
     aliases = {
@@ -31,9 +26,7 @@ def _normalize_provider(provider: str) -> ProviderType:
     }
     normalized = aliases.get(normalized, normalized)
     if normalized not in {"local", "modelscope", "auto"}:
-        raise ValueError(
-            "Unsupported model provider '{}'. Use one of: local, modelscope, auto.".format(provider)
-        )
+        raise ValueError("Unsupported model provider '{}'. Use one of: local, modelscope, auto.".format(provider))
     return normalized  # type: ignore[return-value]
 
 
@@ -64,13 +57,10 @@ def resolve_dict_path(self) -> str:
             if dictionary.is_dir():
                 dictionary = dictionary.joinpath("huqie.txt")
             if dictionary.suffix != ".txt":
-                raise ValueError(
-                    "TokenizerConfig.dict_path must point to a '.txt' dictionary file, got: {}".format(dictionary)
-                )
+                raise ValueError("TokenizerConfig.dict_path must point to a '.txt' dictionary file, got: {}".format(dictionary))
             _require_file(
                 dictionary,
-                "Tokenizer dictionary not found: {}. Provide a valid TokenizerConfig.dict_path."
-                .format(dictionary),
+                "Tokenizer dictionary not found: {}. Provide a valid TokenizerConfig.dict_path.".format(dictionary),
             )
             return str(dictionary)
 
@@ -86,7 +76,7 @@ def from_env(cls) -> "TokenizerConfig":
 
         return cls(
             dict_path=dict_path,
-            offline=_parse_bool(os.getenv("DEEPDOC_OFFLINE"), default=False),
+            offline=offline_mode_or_from_env(None),
             nltk_data_dir=os.getenv("DEEPDOC_NLTK_DATA_DIR"),
         )
 
@@ -107,10 +97,7 @@ def _resolve_bundle_dir(self, bundle: str, explicit_dir: str | None) -> str:
             candidate = Path(explicit_dir).expanduser().resolve()
             exists, missing = validate_bundle_dir(bundle, candidate)
             if not exists:
-                raise FileNotFoundError(
-                    "Missing required files for '{}' bundle in {}: {}"
-                    .format(bundle, candidate, ", ".join(missing))
-                )
+                raise FileNotFoundError("Missing required files for '{}' bundle in {}: {}".format(bundle, candidate, ", ".join(missing)))
             return str(candidate)
 
         model_provider = self.normalized_provider()

deepdoc/depend/nltk_manager.py

@@ -2,19 +2,13 @@
 import os
 import threading
 from pathlib import Path
+from ..common.misc_utils import offline_mode_or_from_env
 
 logger = logging.getLogger(__name__)
 
 _RESOURCE_SPECS: tuple[tuple[str, tuple[str, ...]], ...] = (
-    (
-        "punkt",
-        (
-            "tokenizers/punkt",
-            "tokenizers/punkt.zip",
-            "tokenizers/punkt_tab",
-            "tokenizers/punkt_tab.zip",
-        ),
-    ),
+    ("punkt", ("tokenizers/punkt", "tokenizers/punkt.zip")),
+    ("punkt_tab", ("tokenizers/punkt_tab", "tokenizers/punkt_tab.zip")),
     ("wordnet", ("corpora/wordnet", "corpora/wordnet.zip")),
     (
         "averaged_perceptron_tagger",
@@ -31,12 +25,6 @@
 _ensured_keys: set[tuple[str, bool]] = set()
 
 
-def _parse_bool(value: str | None, default: bool = False) -> bool:
-    if value is None:
-        return default
-    return value.strip().lower() in {"1", "true", "yes", "on"}
-
-
 def _resolve_nltk_data_dir(data_dir: str | None) -> Path | None:
     # Resolution precedence:
     # 1) explicit arg
@@ -88,7 +76,7 @@ def ensure_nltk_data(
     import nltk
 
     resolved_dir = _resolve_nltk_data_dir(data_dir)
-    offline_mode = offline if offline is not None else _parse_bool(os.getenv("DEEPDOC_OFFLINE"), default=False)
+    offline_mode = offline_mode_or_from_env(offline)
     auto_download_mode = not offline_mode
 
     _ensure_search_path(nltk, resolved_dir)
@@ -117,10 +105,7 @@ def ensure_nltk_data(
         if missing_packages:
             searched_paths = ", ".join(nltk.data.path)
             raise RuntimeError(
-                "Missing required NLTK packages: {}. Searched paths: {}. "
-                "Set DEEPDOC_NLTK_DATA_DIR to a local NLTK data path, or disable offline mode by setting "
-                "DEEPDOC_OFFLINE=0."
-                .format(
+                "Missing required NLTK packages: {}. Searched paths: {}. Set DEEPDOC_NLTK_DATA_DIR to a local NLTK data path, or disable offline mode by setting DEEPDOC_OFFLINE=0.".format(
                     ", ".join(missing_packages),
                     searched_paths,
                 )

pyproject.toml

@@ -89,6 +89,11 @@ extend-select = ["ASYNC", "ASYNC1"]
 ignore = ["E402"]
 
 [tool.pytest.ini_options]
+addopts = [
+    "--ignore=tests/test_data",
+    "--ignore=tests/test_results",
+]
+testpaths = ["tests"]
 markers = [
     "p1: high priority test cases",
     "p2: medium priority test cases",

tests/test_model_store.py

@@ -22,10 +22,6 @@ def _create_combined_repo_layout(root: Path) -> None:
     for name in ms.BUNDLES["xgb"].required_files:
         _touch(root / "xgb" / name)
 
-    # Tokenizer bundle
-    for name in ms.BUNDLES["tokenizer"].required_files:
-        _touch(root / "tokenizer" / name)
-
 
 class TestModelStoreSharedRepo(unittest.TestCase):
     def setUp(self) -> None:
@@ -68,12 +64,10 @@ def snapshot_download(
             with patch.object(ms, "_import_modelscope_snapshot_download", return_value=snapshot_download):
                 vision_dir = Path(ms.resolve_bundle_dir("vision", model_home=tmp, provider="modelscope", offline=False))
                 xgb_dir = Path(ms.resolve_bundle_dir("xgb", model_home=tmp, provider="modelscope", offline=False))
-                tok_dir = Path(ms.resolve_bundle_dir("tokenizer", model_home=tmp, provider="modelscope", offline=False))
 
             expected_root = (Path(tmp) / "modelscope" / "Xorbits__deepdoc" / "v1").resolve()
             self.assertEqual(vision_dir.resolve(), (expected_root / "vision").resolve())
             self.assertEqual(xgb_dir.resolve(), (expected_root / "xgb").resolve())
-            self.assertEqual(tok_dir.resolve(), (expected_root / "tokenizer").resolve())
 
             self.assertGreaterEqual(len(calls), 1)
             for call in calls:
@@ -134,8 +128,22 @@ def snapshot_download(*args, **kwargs) -> str:  # pragma: no cover
             with patch.object(ms, "_import_modelscope_snapshot_download", return_value=snapshot_download):
                 vision_dir = Path(ms.resolve_bundle_dir("vision", model_home=tmp, provider="auto", offline=False))
                 xgb_dir = Path(ms.resolve_bundle_dir("xgb", model_home=tmp, provider="auto", offline=False))
-                tok_dir = Path(ms.resolve_bundle_dir("tokenizer", model_home=tmp, provider="auto", offline=False))
 
             self.assertEqual(vision_dir.resolve(), (expected_root / "vision").resolve())
             self.assertEqual(xgb_dir.resolve(), (expected_root / "xgb").resolve())
-            self.assertEqual(tok_dir.resolve(), (expected_root / "tokenizer").resolve())
+
+    def test_resolve_tokenizer_dict_prefix_uses_packaged_dict_by_default(self) -> None:
+        prefix = Path(ms.resolve_tokenizer_dict_prefix())
+
+        self.assertEqual(prefix.name, "huqie")
+        self.assertTrue(prefix.with_suffix(".txt").exists())
+
+    def test_resolve_tokenizer_dict_prefix_uses_env_dir_when_set(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            tokenizer_dir = Path(tmp) / "tokenizer"
+            _touch(tokenizer_dir / "huqie.txt")
+            os.environ[ms.TOKENIZER_MODEL_DIR_ENV] = str(tokenizer_dir)
+
+            prefix = Path(ms.resolve_tokenizer_dict_prefix())
+
+            self.assertEqual(prefix.resolve(), (tokenizer_dir / "huqie").resolve())