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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.
99 lines
3.4 KiB
Python
99 lines
3.4 KiB
Python
"""SQLAlchemy Core engine factory for the user-data Postgres database.
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The engine is lazily constructed on first use and cached as a module-level
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singleton. Repositories and the Alembic env module both obtain connections
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through this factory, so pool tuning lives in one place.
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``POSTGRES_URI`` can be written in any of the common Postgres URI forms::
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postgres://user:pass@host:5432/docsgpt
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postgresql://user:pass@host:5432/docsgpt
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Both are accepted and normalized internally to the psycopg3 dialect
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(``postgresql+psycopg://``) by ``docsgpt.core.settings``. Operators
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don't need to know about SQLAlchemy dialect prefixes.
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"""
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from typing import Optional
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from sqlalchemy import Engine, create_engine, event
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from docsgpt.core.settings import settings
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_engine: Optional[Engine] = None
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def _resolve_uri() -> str:
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"""Return the Postgres URI for user-data tables.
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Raises:
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RuntimeError: If ``settings.POSTGRES_URI`` is unset. Callers that
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reach this path without a configured URI have a setup bug — the
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error message points them at the right setting.
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"""
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if not settings.POSTGRES_URI:
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raise RuntimeError(
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"POSTGRES_URI is not configured. Set it in your .env to a "
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"psycopg3 URI such as "
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"'postgresql+psycopg://user:pass@host:5432/docsgpt'."
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)
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return settings.POSTGRES_URI
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#: Per-statement wall-clock cap applied to every connection handed out by
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#: the engine. 30s is generous for interactive hot paths (reads under a few
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#: hundred ms are normal) but still catches a runaway query before it
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#: stacks up on PgBouncer or holds locks indefinitely.
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STATEMENT_TIMEOUT_MS = 30_000
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def get_engine() -> Engine:
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"""Return the process-wide SQLAlchemy Engine, creating it if needed.
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The engine applies a server-side ``statement_timeout`` to every
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connection it hands out via a ``connect`` event, so both
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:func:`db_session` and :func:`db_readonly` inherit the same
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guardrail.
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Returns:
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A SQLAlchemy ``Engine`` configured with a pooled connection to
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Postgres via psycopg3.
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"""
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global _engine
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if _engine is None:
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_engine = create_engine(
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_resolve_uri(),
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pool_size=10,
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max_overflow=20,
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pool_pre_ping=True, # survive PgBouncer / idle-disconnect recycles
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pool_recycle=1800,
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future=True,
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)
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@event.listens_for(_engine, "connect")
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def _apply_session_guardrails(dbapi_conn, _record):
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# Apply as a SQL ``SET`` (not a libpq ``options=-c ...``
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# startup parameter) so the engine works behind
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# PgBouncer-style poolers — notably Neon's ``-pooler``
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# endpoint, which rejects startup options. Explicit
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# ``commit()`` so the session-level SET survives SA's
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# transaction resets on pool return.
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with dbapi_conn.cursor() as cur:
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cur.execute(f"SET statement_timeout = {STATEMENT_TIMEOUT_MS}")
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dbapi_conn.commit()
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return _engine
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def dispose_engine() -> None:
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"""Dispose the pooled connections and reset the singleton.
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Called from the Celery ``worker_process_init`` signal so each forked
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worker gets a fresh pool instead of sharing file descriptors with the
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parent process (which corrupts the pool on fork).
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"""
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global _engine
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if _engine is not None:
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_engine.dispose()
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_engine = None
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