mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-04 00:13:14 +00:00
Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
112 lines
4.8 KiB
Python
112 lines
4.8 KiB
Python
"""Model pre-fetching, which the Docker build runs to bake artifacts in."""
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import sys
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import types
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from unittest.mock import MagicMock, patch
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import pytest
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from docsgpt.scripts import prefetch_models
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from docsgpt.vectorstore.model_registry import GRANITE_311M, MPNET, OPENAI_ADA_002
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@pytest.fixture
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def fake_fastembed():
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"""Stand in for FastEmbed so nothing is downloaded."""
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text_embedding = MagicMock()
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pooling = types.SimpleNamespace(CLS="CLS", MEAN="MEAN")
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module = types.ModuleType("fastembed")
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module.TextEmbedding = text_embedding
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desc = types.ModuleType("fastembed.common.model_description")
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desc.PoolingType = pooling
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desc.ModelSource = lambda hf=None: {"hf": hf}
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with patch.dict(
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sys.modules,
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{"fastembed": module, "fastembed.common.model_description": desc},
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):
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yield text_embedding
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class TestPrefetch:
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def test_defaults_cover_legacy_and_new_install(self):
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"""An upgraded image must still serve mpnet; a new one needs granite."""
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assert MPNET.name in prefetch_models.DEFAULT_MODELS
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assert GRANITE_311M.name in prefetch_models.DEFAULT_MODELS
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def test_fetches_named_models(self, fake_fastembed):
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fetched = prefetch_models.prefetch([GRANITE_311M.name])
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assert fetched == [GRANITE_311M.repo]
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assert fake_fastembed.call_args.kwargs["model_name"] == GRANITE_311M.repo
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def test_registers_with_registry_pooling_and_dim(self, fake_fastembed):
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prefetch_models.prefetch([GRANITE_311M.name])
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kwargs = fake_fastembed.add_custom_model.call_args.kwargs
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assert kwargs["model"] == GRANITE_311M.repo
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assert kwargs["pooling"] == "CLS"
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assert kwargs["dim"] == GRANITE_311M.dimension
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assert kwargs["model_file"] == GRANITE_311M.onnx_file
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def test_mean_pooled_model_registers_as_mean(self, fake_fastembed):
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prefetch_models.prefetch([MPNET.name])
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assert fake_fastembed.add_custom_model.call_args.kwargs["pooling"] == "MEAN"
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def test_aliases_resolve(self, fake_fastembed):
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assert prefetch_models.prefetch(["granite-311m"]) == [GRANITE_311M.repo]
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def test_cache_dir_is_forwarded(self, fake_fastembed):
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prefetch_models.prefetch([MPNET.name], cache_dir="/models")
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assert fake_fastembed.call_args.kwargs["cache_dir"] == "/models"
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def test_cache_dir_omitted_when_absent(self, fake_fastembed):
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prefetch_models.prefetch([MPNET.name])
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assert "cache_dir" not in fake_fastembed.call_args.kwargs
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def test_remote_only_model_is_skipped(self, fake_fastembed):
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"""OpenAI embeddings have no local artifacts to cache."""
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assert prefetch_models.prefetch([OPENAI_ADA_002.name]) == []
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fake_fastembed.assert_not_called()
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def test_unknown_model_fails_loudly(self, fake_fastembed):
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"""A silent skip at build time is a download at run time, offline."""
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with pytest.raises(SystemExit) as excinfo:
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prefetch_models.prefetch(["nope/nope"])
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assert "nope/nope" in str(excinfo.value)
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assert MPNET.name in str(excinfo.value)
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def test_several_models_in_one_run(self, fake_fastembed):
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fetched = prefetch_models.prefetch([MPNET.name, GRANITE_311M.name])
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assert fetched == [MPNET.repo, GRANITE_311M.repo]
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class TestMain:
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def test_no_args_fetches_the_defaults(self, fake_fastembed):
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with patch.object(prefetch_models, "prefetch", return_value=[]) as spy:
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assert prefetch_models.main([]) == 0
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assert spy.call_args.args[0] == list(prefetch_models.DEFAULT_MODELS)
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def test_explicit_args_override_the_defaults(self, fake_fastembed):
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with patch.object(prefetch_models, "prefetch", return_value=[]) as spy:
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prefetch_models.main(["granite-97m"])
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assert spy.call_args.args[0] == ["granite-97m"]
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def test_cache_dir_read_from_environment(self, fake_fastembed, monkeypatch):
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monkeypatch.setenv("EMBEDDINGS_CACHE_DIR", "/app/models")
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with patch.object(prefetch_models, "prefetch", return_value=[]) as spy:
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prefetch_models.main(["granite-97m"])
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assert spy.call_args.args[1] == "/app/models"
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class TestPrefetchTiktoken:
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def test_warms_every_listed_encoding(self):
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"""The image sets TIKTOKEN_CACHE_DIR; warming fills it at build time."""
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fake = MagicMock()
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module = types.ModuleType("tiktoken")
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module.get_encoding = fake
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with patch.dict(sys.modules, {"tiktoken": module}):
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fetched = prefetch_models.prefetch_tiktoken()
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assert fetched == list(prefetch_models.TIKTOKEN_ENCODINGS)
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assert [c.args[0] for c in fake.call_args_list] == list(prefetch_models.TIKTOKEN_ENCODINGS)
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def test_cl100k_is_the_encoding_token_counting_uses(self):
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assert "cl100k_base" in prefetch_models.TIKTOKEN_ENCODINGS
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