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### What problem does this PR solve? Closes #15465. RAGFlow supports S3, Google Cloud Storage, R2, and OCI as data sources but not Azure Blob Storage, leaving Azure users without a way to index container objects into a knowledge base. This adds a first-class Azure Blob Storage data-source connector — distinct from RAGFlow's existing Azure storage *backends* (`rag/utils/azure_sas_conn.py`, `rag/utils/azure_spn_conn.py`) which store RAGFlow's own files. **Highlights** - `common/data_source/azure_blob_connector.py`: new `AzureBlobConnector` (`CheckpointedConnectorWithPermSync` + `SlimConnectorWithPermSync`). - Uses the existing `azure-storage-blob` dependency (already in `pyproject.toml`). - Three auth modes, tried in order of precedence: 1. **Account key** — `account_name` + `account_key` + `container_name`. 2. **Connection string** — `connection_string` + `container_name`. 3. **SAS token** — `container_url` + `sas_token` (same shape as `RAGFlowAzureSasBlob`). - ETag fingerprint stored per blob in `AzureBlobCheckpoint.etags` — unchanged blobs (same ETag as last run) are skipped without a download. Only new/modified blobs are fetched. - Optional `prefix` scopes indexing to a virtual folder. - `validate_connector_settings()` probes `get_container_properties()` and maps `AuthenticationFailed / 403 / ContainerNotFound` to typed connector exceptions. - Slim-doc IDs are blob names so prune reconciles correctly. - `common/constants.py`, `common/data_source/config.py`, `common/data_source/__init__.py`: register `azure_blob` in `FileSource` / `DocumentSource` and export `AzureBlobConnector`. - `rag/svr/sync_data_source.py`: new `AzureBlob(SyncBase)` class routed through `load_from_checkpoint` (ETag fingerprint owns change-detection) and added to `func_factory`. - Frontend: - `web/src/pages/user-setting/data-source/constant/index.tsx`: new `DataSourceKey.AZURE_BLOB`, auth-mode selector (account key / connection string / SAS token), all credential fields, prefix + batch-size, `syncDeletedFiles` capability, default form values, tile entry with icon. - `web/src/locales/{en,zh}.ts`: description + per-field tooltips for all 9 new keys. - `web/src/assets/svg/data-source/azure-blob.svg`: Azure-branded stacked-cylinders icon. **Verification** - `npm run build` (vite + esbuild) passes (37 s). ### Type of change - [x] New Feature (non-breaking change which adds functionality)
438 lines
18 KiB
Python
438 lines
18 KiB
Python
"""Azure Blob Storage data-source connector.
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Ingests blobs from a user's Azure container into a RAGFlow knowledge
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base. This is distinct from RAGFlow's own Azure storage *backend*
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(``rag/utils/azure_sas_conn.py``, ``rag/utils/azure_spn_conn.py``),
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which stores RAGFlow's own files.
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Auth supports three mutually exclusive modes, selected explicitly by the
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caller-supplied ``auth_mode`` (the UI hides the other modes' fields but
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does not clear them, so we must not guess from whichever field happens to
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be populated). When ``auth_mode`` is absent (older configs / direct API
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callers) we fall back to field precedence:
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1. **Connection string** — ``connection_string`` credential; one line,
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everything embedded. Good for dev / testing.
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2. **Account key** — ``account_name`` + ``account_key``; maps to the
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same underlying SAS-less AccountKey credential.
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3. **SAS token** — ``container_url`` + ``sas_token``; the shape that
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``RAGFlowAzureSasBlob`` already uses.
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Incremental runs are scoped by the poll time window
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(``since_epoch`` < last-modified <= ``until_epoch``).
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Each blob's ETag is also emitted as the document fingerprint, which the
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indexing pipeline persists as ``content_hash`` so unchanged blobs are not
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re-embedded. The connector itself keeps no cross-run ETag state.
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"""
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from __future__ import annotations
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import logging
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from datetime import datetime, timezone
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from typing import Any, Generator
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from common.data_source.config import INDEX_BATCH_SIZE
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from common.data_source.exceptions import (
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ConnectorMissingCredentialError,
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ConnectorValidationError,
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InsufficientPermissionsError,
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UnexpectedValidationError,
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)
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from common.data_source.interfaces import (
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CheckpointedConnectorWithPermSync,
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SecondsSinceUnixEpoch,
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SlimConnectorWithPermSync,
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)
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from common.data_source.models import ConnectorCheckpoint, SlimDocument
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logger = logging.getLogger(__name__)
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# Extensions we ingest; mirrors the same set used by the OneDrive
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# connector so behaviour is consistent across all file-based sources.
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_SUPPORTED_EXTENSIONS = {
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".pdf", ".docx", ".doc", ".xlsx", ".xls",
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".pptx", ".ppt", ".txt", ".md", ".csv",
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".html", ".htm", ".json", ".xml",
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}
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_AZURE_ENDPOINT_SUFFIX = "blob.core.windows.net"
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class AzureBlobCheckpoint(ConnectorCheckpoint):
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"""Checkpoint marker for the Azure Blob connector.
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The connector keeps no cross-run state of its own: a single
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``load_from_checkpoint`` pass lists the container once and sets
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``has_more=False``. Incremental scoping comes from the poll time
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window, and per-blob change detection from the document fingerprint
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(ETag) the pipeline persists as ``content_hash``.
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"""
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class AzureBlobConnector(CheckpointedConnectorWithPermSync, SlimConnectorWithPermSync):
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"""Azure Blob Storage data-source connector.
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Authenticates with one of three credential modes (connection string,
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account key, or SAS token), chosen by ``auth_mode``, and enumerates
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blobs in the configured container under an optional prefix. Each blob's
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ETag is surfaced as the document fingerprint so the pipeline can skip
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re-embedding unchanged blobs across runs.
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"""
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def __init__(
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self,
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batch_size: int = INDEX_BATCH_SIZE,
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prefix: str | None = None,
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allow_images: bool = False,
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auth_mode: str | None = None,
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) -> None:
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self.batch_size = batch_size
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self.prefix = (prefix or "").lstrip("/")
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self.allow_images = allow_images
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# Explicitly selected credential mode: "connection_string",
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# "account_key", or "sas_token". Empty falls back to precedence.
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self.auth_mode = (auth_mode or "").strip().lower()
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self._container_client = None
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# ------------------------------------------------------------------
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# Auth
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# ------------------------------------------------------------------
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def load_credentials(self, credentials: dict[str, Any]) -> dict[str, Any] | None:
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from azure.storage.blob import BlobServiceClient, ContainerClient
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conn_str = credentials.get("connection_string")
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account_name = credentials.get("account_name")
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account_key = credentials.get("account_key")
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container_url = (credentials.get("container_url") or "").rstrip("/")
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sas_token = credentials.get("sas_token")
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container_name = credentials.get("container_name") or ""
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# Honor the explicitly selected auth mode. The UI hides inactive
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# credential fields but does not clear them, so a user who fills one
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# mode and then switches can leave stale values behind; selecting by
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# field precedence would then authenticate with the wrong mode.
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# Fall back to precedence only when no auth_mode was supplied.
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mode = self.auth_mode
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if not mode:
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if conn_str:
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mode = "connection_string"
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elif account_name and account_key:
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mode = "account_key"
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elif container_url and sas_token:
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mode = "sas_token"
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try:
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if mode == "connection_string":
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if not conn_str:
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raise ConnectorMissingCredentialError(
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"Azure Blob: connection_string is required for the connection_string auth mode"
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)
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if not container_name:
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raise ConnectorMissingCredentialError(
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"Azure Blob: container_name is required together with connection_string"
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)
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svc = BlobServiceClient.from_connection_string(conn_str)
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self._container_client = svc.get_container_client(container_name)
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elif mode == "account_key":
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if not (account_name and account_key):
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raise ConnectorMissingCredentialError(
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"Azure Blob: account_name and account_key are required for the account_key auth mode"
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)
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if not container_name:
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raise ConnectorMissingCredentialError(
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"Azure Blob: container_name is required together with account_name + account_key"
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)
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account_url = f"https://{account_name}.{_AZURE_ENDPOINT_SUFFIX}"
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svc = BlobServiceClient(
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account_url=account_url,
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credential=account_key,
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)
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self._container_client = svc.get_container_client(container_name)
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elif mode == "sas_token":
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if not (container_url and sas_token):
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raise ConnectorMissingCredentialError(
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"Azure Blob: container_url and sas_token are required for the sas_token auth mode"
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)
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# mirrors RAGFlowAzureSasBlob; strip a leading "?" so we
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# never produce a double-"?" that breaks SAS auth.
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normalized_sas = str(sas_token).lstrip("?")
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full_url = f"{container_url}?{normalized_sas}"
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self._container_client = ContainerClient.from_container_url(full_url)
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else:
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raise ConnectorMissingCredentialError(
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"Azure Blob credentials are incomplete. Provide one of: "
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"(a) connection_string + container_name, "
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"(b) account_name + account_key + container_name, "
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"(c) container_url + sas_token."
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)
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except ConnectorMissingCredentialError:
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raise
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except Exception as exc:
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raise ConnectorMissingCredentialError(
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f"Failed to initialise Azure Blob client: {exc}"
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) from exc
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return None
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# ------------------------------------------------------------------
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# Validation
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# ------------------------------------------------------------------
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def validate_connector_settings(self) -> None:
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if self._container_client is None:
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raise ConnectorMissingCredentialError("Azure Blob")
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try:
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# get_container_properties() costs one API call; it returns
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# the ETag and last-modified of the container, proving both
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# the credential and the container name are valid.
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self._container_client.get_container_properties()
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except Exception as exc:
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msg = str(exc)
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code = getattr(getattr(exc, "error_code", None), "value", None) or getattr(exc, "error_code", "")
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if "AuthenticationFailed" in msg or "InvalidAuthenticationInfo" in msg:
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raise ConnectorMissingCredentialError(
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f"Azure Blob credential rejected: {msg[:300]}"
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) from exc
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if "AuthorizationPermissionMismatch" in msg or "403" in msg:
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raise InsufficientPermissionsError(
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f"Azure Blob: insufficient permissions on container: {msg[:300]}"
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) from exc
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if "ContainerNotFound" in msg or "404" in msg:
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raise ConnectorValidationError(
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f"Azure Blob: container not found: {msg[:300]}"
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) from exc
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raise UnexpectedValidationError(
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f"Azure Blob validation failed ({code}): {msg[:300]}"
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) from exc
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# ------------------------------------------------------------------
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# Checkpoint helpers
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# ------------------------------------------------------------------
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def build_dummy_checkpoint(self) -> AzureBlobCheckpoint:
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return AzureBlobCheckpoint(has_more=True)
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def validate_checkpoint_json(self, checkpoint_json: str) -> AzureBlobCheckpoint:
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try:
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return AzureBlobCheckpoint.model_validate_json(checkpoint_json)
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except Exception:
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return self.build_dummy_checkpoint()
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# ------------------------------------------------------------------
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# Core data loading
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# ------------------------------------------------------------------
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def poll_source(
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self, start: SecondsSinceUnixEpoch, end: SecondsSinceUnixEpoch
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) -> Any:
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return self._iter_documents(since_epoch=start, until_epoch=end)
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def load_from_checkpoint(
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self,
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start: SecondsSinceUnixEpoch,
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end: SecondsSinceUnixEpoch,
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checkpoint: ConnectorCheckpoint,
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) -> Any:
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if not isinstance(checkpoint, AzureBlobCheckpoint):
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checkpoint = self.build_dummy_checkpoint()
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since = start if start else None
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until = end if end else None
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return self._iter_documents(
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checkpoint=checkpoint, since_epoch=since, until_epoch=until
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)
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def load_from_checkpoint_with_perm_sync(
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self,
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start: SecondsSinceUnixEpoch,
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end: SecondsSinceUnixEpoch,
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checkpoint: ConnectorCheckpoint,
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) -> Any:
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return self.load_from_checkpoint(start, end, checkpoint)
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def retrieve_all_slim_docs_perm_sync(
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self,
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callback: Any = None,
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) -> Generator[list[SlimDocument], None, None]:
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"""Yield batches of slim documents for prune / permission sync."""
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if self._container_client is None:
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raise ConnectorMissingCredentialError("Azure Blob")
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batch: list[SlimDocument] = []
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try:
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for blob_props in self._container_client.list_blobs(name_starts_with=self.prefix or None):
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name = blob_props.name
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if not _has_supported_extension(name, self.allow_images):
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continue
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if callback:
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callback(name, name)
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batch.append(SlimDocument(id=name))
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if len(batch) >= self.batch_size:
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yield batch
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batch = []
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except Exception as exc:
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raise UnexpectedValidationError(
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f"Azure Blob prune listing failed: {exc}"
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) from exc
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if batch:
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yield batch
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# ------------------------------------------------------------------
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# Internal document iteration
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# ------------------------------------------------------------------
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def _iter_documents(
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self,
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checkpoint: AzureBlobCheckpoint | None = None,
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since_epoch: float | None = None,
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until_epoch: float | None = None,
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):
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from common.data_source.models import Document
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if self._container_client is None:
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raise ConnectorMissingCredentialError("Azure Blob")
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batch: list[Document] = []
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try:
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for blob_props in self._container_client.list_blobs(
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name_starts_with=self.prefix or None
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):
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name: str = blob_props.name
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if not _has_supported_extension(name, self.allow_images):
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continue
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# Raw ETag (always present); Azure updates it on every
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# write. Emitted below as the document fingerprint so the
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# pipeline persists it as content_hash and skips re-embedding
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# unchanged blobs across runs.
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current_etag = (blob_props.etag or "").strip('"')
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# Time-window filter: strict lower bound, inclusive upper
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# bound (``since_epoch`` < last-modified <= ``until_epoch``).
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# Excluding last-modified == since_epoch (the prior run's
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# watermark, which that run already yielded) avoids stable
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# duplicate re-fetches on the boundary — matching the
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# Salesforce connector's ``> since``. Enforcing the upper
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# bound keeps blobs modified mid-run from leaking into this
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# window; they're picked up by the next run (whose lower bound
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# is this run's upper bound), so an update can never fall into
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# a gap between windows.
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last_modified: datetime | None = blob_props.last_modified
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if last_modified:
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ts = last_modified.timestamp()
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if since_epoch and ts <= since_epoch:
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continue
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if until_epoch and ts > until_epoch:
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continue
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# Download blob content. A blob that was deleted between the
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# listing and this fetch is genuinely gone — skip it. Any
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# other failure (throttling, transient 5xx, network) must
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# abort the run: the sync framework advances its watermark
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# from successfully yielded docs, so silently skipping a
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# transiently-failed blob while newer blobs succeed would
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# move the watermark past it and drop it permanently.
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try:
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blob_client = self._container_client.get_blob_client(name)
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data = blob_client.download_blob().readall()
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except Exception as exc:
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if _is_blob_gone(exc):
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logger.warning(
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"Azure Blob: %s vanished between listing and fetch; skipping",
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name,
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)
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continue
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raise UnexpectedValidationError(
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f"Azure Blob: failed to download {name}: {exc}"
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) from exc
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doc_updated_at = (
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last_modified.astimezone(timezone.utc)
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if last_modified
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else datetime.now(timezone.utc)
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)
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ext = _extension(name)
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doc = Document(
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id=name,
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source="azure_blob",
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semantic_identifier=name,
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extension=ext,
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blob=data,
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doc_updated_at=doc_updated_at,
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size_bytes=len(data),
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fingerprint=current_etag or None,
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metadata={
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"container": _container_name(self._container_client),
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"etag": current_etag,
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"prefix": self.prefix,
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},
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)
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batch.append(doc)
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if len(batch) >= self.batch_size:
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yield batch
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batch = []
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except UnexpectedValidationError:
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raise
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except Exception as exc:
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raise UnexpectedValidationError(
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f"Azure Blob listing failed: {exc}"
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) from exc
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if batch:
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yield batch
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if checkpoint is not None:
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checkpoint.has_more = False
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# ----------------------------------------------------------------------
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# Module-level helpers
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# ----------------------------------------------------------------------
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def _extension(name: str) -> str:
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if "." not in name:
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return ""
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return "." + name.rsplit(".", 1)[-1].lower()
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def _has_supported_extension(name: str, allow_images: bool) -> bool:
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ext = _extension(name)
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if ext in _SUPPORTED_EXTENSIONS:
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return True
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if allow_images and ext in {".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp", ".tiff"}:
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return True
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return False
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def _is_blob_gone(exc: Exception) -> bool:
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"""True when a download failed because the blob no longer exists.
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Azure raises ``ResourceNotFoundError`` (status 404, error code
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``BlobNotFound``) when a blob listed moments earlier has since been
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deleted. That is not data loss — the blob is gone — so it is safe to
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skip. Detected by attribute and string so we need not import the Azure
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exception type at module load.
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"""
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if getattr(exc, "status_code", None) == 404:
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return True
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code = getattr(exc, "error_code", "") or ""
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if "BlobNotFound" in str(code):
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return True
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msg = str(exc)
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return "BlobNotFound" in msg or "ResourceNotFound" in msg
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def _container_name(client: Any) -> str:
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"""Extract the container name from a ContainerClient without
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importing the Azure SDK at module level."""
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try:
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return client.container_name
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except AttributeError:
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return ""
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