Files
DocsGPT/docsgpt/core/settings/vectorstores.py
T
arc53-machine 5578039c19 refactor(settings): treat unset spellings of every optional string as None
Review follow-up. The per-group secret validators normalised a hand-picked
list of API keys, which left other optional credentials and overrides
(OPEN_ROUTER_API_KEY, S3 and Daytona keys, ELASTIC_PASSWORD, the OIDC
trio, connector client ids, MICROSOFT_AUTHORITY, MCP_OAUTH_REDIRECT_URI)
holding the literal "None" or "" a .env file spells "unset" with, so
truthiness checks and fallbacks downstream saw a value. One rule on the
group base replaces those lists: every Optional[str] field maps "", "None"
and whitespace to None and strips real values. Plain str fields are left
alone. The OIDC required-settings check therefore also rejects those
spellings.

EMBEDDINGS_POOLING is Literal["cls", "mean"] with case-insensitive
parsing; its consumer silently ignored anything else.

Bounds added where the consumer rejects or misbehaves on the value:
SCHEDULE_RUN_OUTPUT_RETENTION_DAYS and MESSAGE_EVENTS_RETENTION_DAYS (the
cleanup repositories raise on <= 0), EMBEDDINGS_DELEGATE_TIMEOUT, the
remote-device idle/pairing/invocation TTLs and CELERY_VISIBILITY_TIMEOUT
(> 0), REMOTE_DEVICE_CMD_QUEUE_TTL_SECONDS (> 605, the documented drain
deadline), GRAPHRAG_MAX_CHUNKS_FOR_EXTRACTION (>= 0; negative would slice
the pending list from the end).

The generated reference now renders generic type arguments
(dict[str, int] rather than dict).
2026-09-17 11:37:57 +01:00

85 lines
4.1 KiB
Python

"""Connection settings for each vector store backend."""
from __future__ import annotations
from typing import Optional
from pydantic import Field, field_validator
from docsgpt.core.db_uri import normalize_pgvector_connection_string
from docsgpt.core.paths import home_dir
from docsgpt.core.settings._shared import SettingsGroup
class VectorStoreSettings(SettingsGroup):
"""Per-backend connection details; only the backend named by VECTOR_STORE is read."""
MONGO_URI: Optional[str] = Field(
default=None,
description=(
"Only consulted when VECTOR_STORE=mongodb or when running scripts/db/backfill.py; user data lives "
"in Postgres."
),
)
# Elasticsearch.
ELASTIC_CLOUD_ID: Optional[str] = Field(default=None, description="Elastic Cloud id.")
ELASTIC_USERNAME: Optional[str] = Field(default=None, description="Elasticsearch username.")
ELASTIC_PASSWORD: Optional[str] = Field(default=None, description="Elasticsearch password.")
ELASTIC_URL: Optional[str] = Field(default=None, description="Elasticsearch URL.")
ELASTIC_INDEX: str = Field(default="docsgpt", description="Elasticsearch index name.")
# Qdrant.
QDRANT_COLLECTION_NAME: str = Field(default="docsgpt", description="Qdrant collection name.")
QDRANT_LOCATION: Optional[str] = Field(default=None, description="Qdrant location (':memory:' or a URL).")
QDRANT_URL: Optional[str] = Field(default=None, description="Qdrant server URL.")
QDRANT_PORT: int = Field(default=6333, description="Qdrant REST port.")
QDRANT_GRPC_PORT: int = Field(default=6334, description="Qdrant gRPC port.")
QDRANT_PREFER_GRPC: bool = Field(default=False, description="Use gRPC instead of REST where possible.")
QDRANT_HTTPS: Optional[bool] = Field(default=None, description="Use HTTPS for the Qdrant connection.")
QDRANT_API_KEY: Optional[str] = Field(default=None, description="Qdrant API key.")
QDRANT_PREFIX: Optional[str] = Field(default=None, description="URL prefix for a Qdrant behind a proxy.")
QDRANT_TIMEOUT: Optional[float] = Field(default=None, description="Qdrant request timeout in seconds.")
QDRANT_HOST: Optional[str] = Field(default=None, description="Qdrant host (alternative to QDRANT_URL).")
QDRANT_PATH: Optional[str] = Field(default=None, description="Path for an embedded on-disk Qdrant.")
QDRANT_DISTANCE_FUNC: str = Field(default="Cosine", description="Qdrant distance function.")
# PGVector.
PGVECTOR_CONNECTION_STRING: Optional[str] = Field(
default=None,
description=(
"pgvector connection string. postgres://, postgresql:// and postgresql+psycopg:// are all accepted "
"and normalized internally for psycopg.connect(). Unset falls back to POSTGRES_URI."
),
)
PGVECTOR_POOL_MAX_SIZE: int = Field(
default=8, ge=0, description="Per-process connection pool size; 0 uses one direct connection per store."
)
PGVECTOR_IVFFLAT_PROBES: Optional[int] = Field(
default=None,
description="IVFFlat probes; unset derives sqrt(lists) from the index. Higher means better recall, more scan.",
)
# Milvus.
MILVUS_COLLECTION_NAME: str = Field(default="docsgpt", description="Milvus collection name.")
MILVUS_URI: Optional[str] = Field(
default_factory=lambda: str(home_dir() / "milvus_local.db"),
description=(
"Milvus server URI. The default is a milvus-lite (embedded) database file under the data home, "
"like the other local stores."
),
)
MILVUS_TOKEN: str = Field(default="", description="Milvus auth token.")
# LanceDB.
LANCEDB_PATH: str = Field(
default_factory=lambda: str(home_dir() / "data" / "lancedb"),
description="LanceDB local data directory.",
)
LANCEDB_TABLE_NAME: str = Field(default="docsgpts", description="LanceDB table for stored vectors.")
@field_validator("PGVECTOR_CONNECTION_STRING", mode="before")
@classmethod
def _normalize_pgvector_connection_string(cls, v):
return normalize_pgvector_connection_string(v)