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refactor: rename the application package to docsgpt
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.
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@@ -14,15 +14,15 @@ from unittest.mock import MagicMock, patch
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import pytest
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from application.storage.db.bootstrap import ensure_vector_schema
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from docsgpt.storage.db.bootstrap import ensure_vector_schema
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_APP_PY = Path(__file__).resolve().parents[3] / "application" / "app.py"
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_APP_PY = Path(__file__).resolve().parents[3] / "docsgpt" / "app.py"
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@pytest.fixture
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def vector_settings(monkeypatch):
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"""Settings configured for a pgvector deployment."""
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from application.core import settings as settings_module
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from docsgpt.core import settings as settings_module
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settings = settings_module.settings
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monkeypatch.setattr(settings, "VECTOR_STORE", "pgvector", raising=False)
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@@ -74,17 +74,17 @@ class TestEnsureVectorSchemaCreates:
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cursor = MagicMock()
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conn.cursor.return_value = cursor
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with patch("psycopg.connect", return_value=conn) as connect, patch(
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"application.vectorstore.model_registry.dimension_for",
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"docsgpt.vectorstore.model_registry.dimension_for",
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return_value=dimension,
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=table_dimension,
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), patch(
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"application.graphrag.store.GraphStore.create_schema"
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"docsgpt.graphrag.store.GraphStore.create_schema"
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) as graph_schema, patch(
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"application.vectorstore.pgvector._pool_for"
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"docsgpt.vectorstore.pgvector._pool_for"
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) as pool_for:
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ensure_vector_schema()
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return connect, conn, cursor, vector_schema, graph_schema, pool_for
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@@ -130,10 +130,10 @@ class TestEnsureVectorSchemaDimensionCheck:
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):
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conn = MagicMock()
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with patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.model_registry.dimension_for",
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"docsgpt.vectorstore.model_registry.dimension_for",
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return_value=1536,
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), patch("application.vectorstore.pgvector.PGVectorStore.create_schema"), patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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), patch("docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"), patch(
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=768,
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):
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with pytest.raises(RuntimeError) as excinfo:
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@@ -151,11 +151,11 @@ class TestEnsureVectorSchemaDimensionCheck:
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stub = MagicMock()
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del stub.dimension
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with patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.base.get_embeddings", return_value=stub
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"docsgpt.vectorstore.base.get_embeddings", return_value=stub
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=1536,
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):
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ensure_vector_schema() # must not raise
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@@ -165,12 +165,12 @@ class TestEnsureVectorSchemaDimensionCheck:
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def test_skips_the_check_when_the_model_cannot_be_loaded(self, vector_settings):
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conn = MagicMock()
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with patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.base.get_embeddings",
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"docsgpt.vectorstore.base.get_embeddings",
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side_effect=RuntimeError("no model"),
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=1536,
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):
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ensure_vector_schema() # must not raise
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@@ -182,7 +182,7 @@ class TestEnsureVectorSchemaDimensionCheck:
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class TestBootGating:
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"""The boot hook must stay behind AUTO_VECTOR_SCHEMA.
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Asserted on the source because importing ``application.app`` runs the hook,
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Asserted on the source because importing ``docsgpt.app`` runs the hook,
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and a test that imports it cannot observe the gate it just executed.
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"""
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@@ -216,7 +216,7 @@ class TestBootGating:
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), "ensure_vector_schema() at import time must be wrapped in try/except"
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def test_setting_defaults_on(self):
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from application.core.settings import Settings
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from docsgpt.core.settings import Settings
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assert Settings.model_fields["AUTO_VECTOR_SCHEMA"].default is True
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@@ -241,14 +241,14 @@ class TestBootDoesNotLoadTheModel:
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conn = MagicMock()
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conn.cursor.return_value = MagicMock()
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with patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.model_registry.dimension_for",
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"docsgpt.vectorstore.model_registry.dimension_for",
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return_value=registry_dim,
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), patch(
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"application.vectorstore.base.build_local_embeddings", loader
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"docsgpt.vectorstore.base.build_local_embeddings", loader
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=None,
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):
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ensure_vector_schema()
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@@ -280,13 +280,13 @@ class TestUnknownWidthIsProbed:
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conn = MagicMock()
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conn.cursor.return_value = MagicMock()
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with patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.model_registry.dimension_for", return_value=None
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"docsgpt.vectorstore.model_registry.dimension_for", return_value=None
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), patch(
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"application.vectorstore.base.build_local_embeddings", return_value=remote
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"docsgpt.vectorstore.base.build_local_embeddings", return_value=remote
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=table_dimension,
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):
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try:
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@@ -340,7 +340,7 @@ class TestBootLoadedModelIsReleased:
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"""
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def _run(self, vector_settings, *, delegate, base_url=None):
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from application.vectorstore.base import EmbeddingsSingleton
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from docsgpt.vectorstore.base import EmbeddingsSingleton
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monkeyed = _embeddings(1024)
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conn = MagicMock()
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@@ -356,13 +356,13 @@ class TestBootLoadedModelIsReleased:
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), patch.object(
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vector_settings, "EMBEDDINGS_BASE_URL", base_url
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), patch("psycopg.connect", return_value=conn), patch(
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"application.vectorstore.model_registry.dimension_for", return_value=None
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"docsgpt.vectorstore.model_registry.dimension_for", return_value=None
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), patch(
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"application.vectorstore.base.build_local_embeddings", side_effect=_build
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"docsgpt.vectorstore.base.build_local_embeddings", side_effect=_build
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), patch(
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"application.vectorstore.pgvector.PGVectorStore.create_schema"
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"docsgpt.vectorstore.pgvector.PGVectorStore.create_schema"
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) as vector_schema, patch(
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"application.vectorstore.pgvector.PGVectorStore.table_dimension",
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"docsgpt.vectorstore.pgvector.PGVectorStore.table_dimension",
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return_value=1024,
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):
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ensure_vector_schema()
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