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"""Configuration constants and enum definitions"""
import json
import os
from datetime import datetime, timezone
from enum import Enum
from typing import cast
def get_current_tz_offset() -> int:
# datetime now() gets local time, datetime.now(timezone.utc) gets UTC time.
# remove tzinfo to compare non-timezone-aware objects.
time_diff = datetime.now() - datetime.now(timezone.utc).replace(tzinfo=None)
return round(time_diff.total_seconds() / 3600)
# Default request timeout, mostly used by connectors
REQUEST_TIMEOUT_SECONDS = int(os.environ.get("REQUEST_TIMEOUT_SECONDS") or 60)
ONE_MINUTE = 60
ONE_HOUR = 3600
ONE_DAY = ONE_HOUR * 24
# Slack API limits
_SLACK_LIMIT = 900
# Redis lock configuration
ONYX_SLACK_LOCK_TTL = 1800
ONYX_SLACK_LOCK_BLOCKING_TIMEOUT = 60
ONYX_SLACK_LOCK_TOTAL_BLOCKING_TIMEOUT = 3600
class BlobType(str, Enum):
"""Supported storage types"""
S3 = "s3"
R2 = "r2"
GOOGLE_CLOUD_STORAGE = "google_cloud_storage"
OCI_STORAGE = "oci_storage"
S3_COMPATIBLE = "s3_compatible"
class DocumentSource(str, Enum):
"""Document sources"""
RSS = "rss"
S3 = "s3"
NOTION = "notion"
Feature/generic api connector (#13545) # feat: Add Generic REST API Connector ## What problem does this PR solve? RAGFlow supports many specific data source connectors (MySQL, Slack, Google Drive, etc.), but there was no way to connect an arbitrary REST API as a data source. Users with custom or third-party APIs had to write a new connector class for each one. This PR adds a **generic, configuration-driven REST API connector** that lets users connect any REST API as a data source entirely through the UI — no code changes needed per API. --- ## Features ### Core Connector (`common/data_source/rest_api_connector.py`) - Implements `LoadConnector` and `PollConnector` interfaces for full and incremental sync - **Configurable authentication:** None, API Key (custom header), Bearer Token, Basic Auth - **Pluggable pagination:** Page-based, Offset-based, Cursor-based, or None - Smart page-size inference from user's query parameters to avoid duplicate/conflicting params - Configurable request delay between pages to prevent API rate limiting - Auto-detection of the items array in JSON responses (`items`, `results`, `data`, `records`, or first list found) - **Advanced field mapping** with dot-notation (`country.name`), array wildcards (`newsType[*].name`), type hints, and default values - Optional content template rendering (`"Title: {title}\nBody: {body}"`) - HTML stripping for content fields - Stable document IDs via `hash128` from a configurable ID field or auto-generated from item content - Pydantic configuration schema with automatic coercion of UI string inputs to dicts/lists ### Backend Registration (`rag/svr/sync_data_source.py`, `common/constants.py`, `common/data_source/config.py`) - `REST_API` sync class wired into RAGFlow's `func_factory` - Full sync (`load_from_state`) and incremental polling (`poll_source`) support - Credentials and config passed from task to connector following existing patterns (MySQL, SeaFile, etc.) ### Test Connection Endpoint (`api/apps/connector_app.py`) - `POST /v1/connector/<id>/test` validates config schema, authentication, and API connectivity without triggering a sync - Clear error messages for auth failures vs. config issues ### Frontend UI (`web/src/pages/user-setting/data-source/constant/`) - **Postman-style configuration:** Base URL, Query Parameters (key=value per line), Auth, Content Fields, Metadata Fields, Pagination Type - Auth-type-aware form: fields for API key header/value, Bearer token, or Basic username/password appear only when relevant - **Advanced Settings** toggle for: Custom Headers, Max Pages, Request Delay, Poll Timestamp Field, Request Body (POST) - Connector icon (SVG) and i18n strings (English) - **"Test Connection"** button to validate before syncing --- ## Controls & Safety - Configurable max pages safety cap (default: 1000, adjustable in UI) - Configurable request delay between pages (default: 0.5s, adjustable in UI) - Auth errors (401/403) fail immediately without retries; transient errors retry with exponential backoff - Diagnostic logging: auth setup confirmation, request details on failure, content field extraction status --- ## Type of change - [x] New Feature (non-breaking change which adds functionality) ##Visual Screenshots of Features <img width="482" height="510" alt="Screenshot 2026-03-11 at 5 19 52 PM" src="https://github.com/user-attachments/assets/dcb7ab4a-1622-44f3-bb02-d6f0527314c4" /> (Connector can be configured within the external data sources tab) Configuration Parameters: <img width="661" height="682" alt="Screenshot 2026-03-11 at 5 20 46 PM" src="https://github.com/user-attachments/assets/5e154e71-4ab5-4872-bfb2-04f02b73c18a" /> <img width="661" height="682" alt="Screenshot 2026-03-11 at 5 20 54 PM" src="https://github.com/user-attachments/assets/00cb14b7-0bcf-4b94-9d71-34e93369ecb2" /> Connection can be tested before attaching to dataset: <img width="981" height="681" alt="Screenshot 2026-03-11 at 5 21 40 PM" src="https://github.com/user-attachments/assets/aaa6eeeb-89a7-4349-bc34-2423bf8be9ee" /> Ingestion tested with API connector (works perfectly fine): <img width="1062" height="705" alt="Screenshot 2026-03-11 at 5 22 30 PM" src="https://github.com/user-attachments/assets/afcd0d58-cadd-4152-badc-d2f14d96fbec" /> Search & Retrieval works as well with metadata flow: <img width="1062" height="705" alt="Screenshot 2026-03-11 at 5 23 05 PM" src="https://github.com/user-attachments/assets/d41ee935-dcf7-4456-b317-22a76ca032c0" /> --------- Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-05-13 17:35:01 +05:00
REST_API = "rest_api"
R2 = "r2"
GOOGLE_CLOUD_STORAGE = "google_cloud_storage"
OCI_STORAGE = "oci_storage"
SLACK = "slack"
CONFLUENCE = "confluence"
JIRA = "jira"
GOOGLE_DRIVE = "google_drive"
GMAIL = "gmail"
DISCORD = "discord"
WEBDAV = "webdav"
MOODLE = "moodle"
S3_COMPATIBLE = "s3_compatible"
DROPBOX = "dropbox"
BOX = "box"
AIRTABLE = "airtable"
ASANA = "asana"
GITHUB = "github"
GITLAB = "gitlab"
IMAP = "imap"
BITBUCKET = "bitbucket"
ZENDESK = "zendesk"
feat/add MySQL and PostgreSQL data source connectors (#12817) ### What problem does this PR solve? This PR adds MySQL and PostgreSQL as data source connectors, allowing users to import data directly from relational databases into RAGFlow for RAG workflows. Many users store their knowledge in databases (product catalogs, documentation, FAQs, etc.) and currently have no way to sync this data into RAGFlow without exporting to files first. This feature lets them connect directly to their databases, run SQL queries, and automatically create documents from the results. Closes #763 Closes #11560 ### Type of change - [ ] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe): ### What this PR does **New capabilities:** - Connect to MySQL and PostgreSQL databases - Run custom SQL queries to extract data - Map database columns to document content (vectorized) and metadata (searchable) - Support incremental sync using a timestamp column - Full frontend UI with connection form and tooltips **Files changed:** Backend: - `common/constants.py` - Added MYSQL/POSTGRESQL to FileSource enum - `common/data_source/config.py` - Added to DocumentSource enum - `common/data_source/rdbms_connector.py` - New connector (368 lines) - `common/data_source/__init__.py` - Exported the connector - `rag/svr/sync_data_source.py` - Added MySQL and PostgreSQL sync classes - `pyproject.toml` - Added mysql-connector-python dependency Frontend: - `web/src/pages/user-setting/data-source/constant/index.tsx` - Form fields - `web/src/locales/en.ts` - English translations - `web/src/assets/svg/data-source/mysql.svg` - MySQL icon - `web/src/assets/svg/data-source/postgresql.svg` - PostgreSQL icon ### Testing done Tested with MySQL 8.0 and PostgreSQL 16: - Connection validation works correctly - Full sync imports all query results as documents - Incremental sync only fetches rows updated since last sync - Custom SQL queries filter data as expected - Invalid credentials show clear error messages - Lint checks pass (`ruff check` returns no errors) --------- Co-authored-by: mkdev11 <YOUR_GITHUB_ID+MkDev11@users.noreply.github.com>
2026-02-03 23:14:32 -03:00
SEAFILE = "seafile"
MYSQL = "mysql"
POSTGRESQL = "postgresql"
BIGQUERY = "bigquery"
DINGTALK_AI_TABLE = "dingtalk_ai_table"
feat(connector): implement OneDrive data source connector (issue #15330) (#15331) ### What problem does this PR solve? Closes #15330. RAGFlow had no connector for OneDrive / OneDrive for Business. Users who store working documents in OneDrive could not index them into a knowledge base without manually downloading and re-uploading files. This PR adds a net-new OneDrive data source that: - Authenticates against Microsoft Graph with the same MSAL client-credentials flow already used by the SharePoint and Teams connectors (no new auth primitives). - Enumerates every drive visible to the service principal and pages through `/drives/{id}/root/delta`, persisting `@odata.deltaLink` values per drive so subsequent syncs only fetch changed items. - Optionally narrows ingestion to a sub-folder (`folder_path`) without needing a separate code path. - Surfaces typed errors on the validation probe (`GET /drives?$top=1`): 401 → `ConnectorMissingCredentialError`, 403 → `InsufficientPermissionsError` (with a `Files.Read.All` hint), 5xx → `UnexpectedValidationError`. - Filters folders, soft-deleted items, and unsupported extensions (`.pdf .docx .doc .xlsx .xls .pptx .ppt .txt .md .csv`). #### Files | File | Change | |------|--------| | `common/data_source/onedrive_connector.py` | **New** — `OneDriveConnector` + `OneDriveCheckpoint`. | | `common/data_source/config.py` | `DocumentSource.ONEDRIVE = "onedrive"`. | | `common/constants.py` | `FileSource.ONEDRIVE = "onedrive"`. | | `common/data_source/__init__.py` | Export `OneDriveConnector`. | | `rag/svr/sync_data_source.py` | `OneDrive(SyncBase)` with `batch_size` normalisation; registered in `func_factory`. | | `web/src/pages/user-setting/data-source/constant/index.tsx` | `DataSourceKey.ONEDRIVE`, visibility map (`syncDeletedFiles: true`), info entry, form fields (tenant_id, client_id, client_secret, folder_path, batch_size), default values. | | `web/src/locales/en.ts`, `web/src/locales/zh.ts` | `onedriveDescription` + 4 tooltip keys (EN + ZH). | | `test/unit_test/data_source/test_onedrive_connector_unit.py` | **New** — 13 unit tests (`p1`/`p2`) covering auth, validation, checkpoint helpers, and document filtering. | #### Required Azure AD permission `Files.Read.All` (Application, admin-granted). #### Out of scope - Interactive end-user OAuth (delegated permissions) — the connector uses app-only credentials, consistent with the SharePoint / Teams precedent. - Binary download of file contents — the sync layer emits `Document`s carrying `webUrl` + metadata; bytes are hydrated downstream by the parse pipeline. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-29 05:26:06 -06:00
ONEDRIVE = "onedrive"
feat(connector): implement Outlook data source connector (issue #15332) (#15333) ### What problem does this PR solve? Closes #15332. RAGFlow can index Gmail and generic IMAP mailboxes but had no native connector for Outlook / Microsoft 365 mail. Organisations on Microsoft 365 had no way to bring mailbox content into a knowledge base through Microsoft Graph. This PR adds a net-new Outlook data source that: - Authenticates against Microsoft Graph with the same MSAL client-credentials flow already used by the SharePoint and Teams connectors (no new auth primitives). - Pages over `/users/{id}/mailFolders/{folder}/messages/delta` per mailbox and persists `@odata.deltaLink` values in `OutlookCheckpoint.delta_links`, so incremental syncs only fetch changed messages. - Supports two scoping modes: - **Tenant-wide** (default): enumerates every user in the tenant via `/users` and syncs each mailbox. Requires `User.Read.All`. - **Targeted**: when `user_ids` is provided (comma-separated UPNs or object IDs), only those mailboxes are synced. `User.Read.All` is not needed in this mode. - Lets the caller pick the mail folder (`inbox`, `sentitems`, `archive`, ...). Defaults to `inbox`. - Maps each message to a `Document` shaped after the Gmail connector: one `TextSection` carrying `From/To/Cc/Subject` headers + body, with HTML bodies stripped to text inline (no extra dependency). - Surfaces typed errors on the validation probe: 401 → `ConnectorMissingCredentialError`, 403 → `InsufficientPermissionsError` (with `Mail.Read` / `User.Read.All` hint), 404 on a configured mailbox → `ConnectorValidationError`, 5xx → `UnexpectedValidationError`. - Skips messages flagged `@removed` by the delta semantics and messages whose `receivedDateTime` is older than `poll_range_start`. #### Files | File | Change | |------|--------| | `common/data_source/outlook_connector.py` | **New** — `OutlookConnector` (`CheckpointedConnectorWithPermSync` + `SlimConnectorWithPermSync`) + `OutlookCheckpoint` + tiny `_strip_html` helper. | | `common/data_source/config.py` | `DocumentSource.OUTLOOK = "outlook"`. | | `common/constants.py` | `FileSource.OUTLOOK = "outlook"`. | | `common/data_source/__init__.py` | Export `OutlookConnector`. | | `rag/svr/sync_data_source.py` | `Outlook(SyncBase)` with `batch_size` normalisation, CSV/list parsing of `user_ids`; registered in `func_factory`. | | `web/src/pages/user-setting/data-source/constant/index.tsx` | `DataSourceKey.OUTLOOK`, visibility map (`syncDeletedFiles: true`), info entry, form fields (tenant_id, client_id, client_secret, folder, user_ids, batch_size), default values. | | `web/src/locales/en.ts`, `web/src/locales/zh.ts` | `outlookDescription` + 5 tooltip keys (EN + ZH). | | `test/unit_test/data_source/test_outlook_connector_unit.py` | **New** — 19 unit tests (`p1`/`p2`/`p3`) covering auth, validation (tenant-wide vs specific user vs error paths), checkpoint helpers, user enumeration pagination, message filtering, HTML body stripping. | #### Required Azure AD permissions - `Mail.Read` (Application, admin-granted) — always. - `User.Read.All` (Application, admin-granted) — only when `user_ids` is left blank so the connector can enumerate mailboxes. #### Out of scope - **Attachment indexing.** The current connector emits message body + headers; binary attachments are flagged via `metadata.has_attachments` but not pulled. Adding attachment hydration is straightforward but scoped out per the issue's "decide whether attachments are indexed in the first version" note. - **Delegated (per-user) OAuth.** The connector uses app-only credentials, consistent with the SharePoint / Teams precedent in this codebase. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-29 07:52:29 -06:00
OUTLOOK = "outlook"
feat(connectors): add Salesforce CRM data source connector (#15462) ### What problem does this PR solve? Closes #15461. RAGFlow had no way to ingest Salesforce CRM data, so support / sales teams couldn't ground responses on live Accounts, Contacts, Opportunities, Cases, or Knowledge articles. This adds a first-class Salesforce data source connector that authenticates against a Connected App via OAuth 2.0 client-credentials, queries selected SObjects via SOQL, and turns each record into an indexable document with incremental sync. **Highlights** - `common/data_source/salesforce_connector.py`: new `SalesforceConnector` (`CheckpointedConnectorWithPermSync` + `SlimConnectorWithPermSync`). - OAuth 2.0 client-credentials flow; canonical `instance_url` from the token response so multi-pod orgs route correctly. - Per-object `SystemModstamp` cursor stored in `SalesforceCheckpoint.cursors` — a failure mid-object doesn't rewind sibling objects, and re-syncs only fetch changed rows. - Deterministic record-to-text formatter (sorted keys) so SOQL field reordering on the server doesn't mark every row "changed" on each poll. - `_get_json` raises on non-2xx so 429 / 5xx never silently advance the checkpoint past missing data. - `Knowledge__kav` is in the default object set but is skipped silently when the org doesn't have Salesforce Knowledge enabled (404 on describe). - Slim-doc IDs are scoped as `<Object>/<Id>` so prune deletes can't collide across object types. - `common/constants.py`, `common/data_source/config.py`, `common/data_source/__init__.py`: register `salesforce` in `FileSource` / `DocumentSource` and export `SalesforceConnector`. - `rag/svr/sync_data_source.py`: new `Salesforce(SyncBase)` class routed through `load_from_checkpoint` (poll_source would re-walk every object each run) and added to `func_factory`. - Frontend: - `web/src/pages/user-setting/data-source/constant/index.tsx`: new `DataSourceKey.SALESFORCE`, form fields (instance URL, client ID/secret, objects, api_version, batch size), `syncDeletedFiles` capability, default form values, and tile entry with the new icon. - `web/src/locales/{en,zh}.ts`: description + per-field tooltips. - `web/src/assets/svg/data-source/salesforce.svg`: 48x48 brand-style icon to match the other Microsoft / cloud tiles. **Verification** - `npm run build` (vite + esbuild) passes (1m 26s). ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-06-04 23:24:36 -06:00
SALESFORCE = "salesforce"
feat(connectors): add Azure Blob Storage data source connector (#15466) ### 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)
2026-06-04 07:06:01 -06:00
AZURE_BLOB = "azure_blob"
class FileOrigin(str, Enum):
"""File origins"""
CONNECTOR = "connector"
# Standard image MIME types supported by most vision LLMs
IMAGE_MIME_TYPES = [
"image/png",
"image/jpeg",
"image/jpg",
"image/webp",
]
# Image types that should be excluded from processing
EXCLUDED_IMAGE_TYPES = [
"image/bmp",
"image/tiff",
"image/gif",
"image/svg+xml",
"image/avif",
]
_PAGE_EXPANSION_FIELDS = [
"body.storage.value",
"version",
"space",
"metadata.labels",
"history.lastUpdated",
"ancestors",
]
# Configuration constants
BLOB_STORAGE_SIZE_THRESHOLD = 20 * 1024 * 1024 # 20MB
INDEX_BATCH_SIZE = 2
SLACK_NUM_THREADS = 4
ENABLE_EXPENSIVE_EXPERT_CALLS = False
# Slack related constants
_SLACK_LIMIT = 900
FAST_TIMEOUT = 1
MAX_RETRIES = 7
MAX_CHANNELS_TO_LOG = 50
BOT_CHANNEL_MIN_BATCH_SIZE = 256
BOT_CHANNEL_PERCENTAGE_THRESHOLD = 0.95
# Download configuration
DOWNLOAD_CHUNK_SIZE = 1024 * 1024 # 1MB
SIZE_THRESHOLD_BUFFER = 64
NOTION_CONNECTOR_DISABLE_RECURSIVE_PAGE_LOOKUP = (
os.environ.get("NOTION_CONNECTOR_DISABLE_RECURSIVE_PAGE_LOOKUP", "").lower()
== "true"
)
SLIM_BATCH_SIZE = 100
# Notion API constants
_NOTION_PAGE_SIZE = 100
_NOTION_CALL_TIMEOUT = 30 # 30 seconds
_ITERATION_LIMIT = 100_000
#####
# Indexing Configs
#####
# NOTE: Currently only supported in the Confluence and Google Drive connectors +
# only handles some failures (Confluence = handles API call failures, Google
# Drive = handles failures pulling files / parsing them)
CONTINUE_ON_CONNECTOR_FAILURE = os.environ.get(
"CONTINUE_ON_CONNECTOR_FAILURE", ""
).lower() not in ["false", ""]
#####
# Confluence Connector Configs
#####
CONFLUENCE_CONNECTOR_LABELS_TO_SKIP = [
ignored_tag
for ignored_tag in os.environ.get("CONFLUENCE_CONNECTOR_LABELS_TO_SKIP", "").split(
","
)
if ignored_tag
]
# Avoid to get archived pages
CONFLUENCE_CONNECTOR_INDEX_ARCHIVED_PAGES = (
os.environ.get("CONFLUENCE_CONNECTOR_INDEX_ARCHIVED_PAGES", "").lower() == "true"
)
# Attachments exceeding this size will not be retrieved (in bytes)
CONFLUENCE_CONNECTOR_ATTACHMENT_SIZE_THRESHOLD = int(
os.environ.get("CONFLUENCE_CONNECTOR_ATTACHMENT_SIZE_THRESHOLD", 10 * 1024 * 1024)
)
# Attachments with more chars than this will not be indexed. This is to prevent extremely
# large files from freezing indexing. 200,000 is ~100 google doc pages.
CONFLUENCE_CONNECTOR_ATTACHMENT_CHAR_COUNT_THRESHOLD = int(
os.environ.get("CONFLUENCE_CONNECTOR_ATTACHMENT_CHAR_COUNT_THRESHOLD", 200_000)
)
_RAW_CONFLUENCE_CONNECTOR_USER_PROFILES_OVERRIDE = os.environ.get(
"CONFLUENCE_CONNECTOR_USER_PROFILES_OVERRIDE", ""
)
CONFLUENCE_CONNECTOR_USER_PROFILES_OVERRIDE = cast(
list[dict[str, str]] | None,
(
json.loads(_RAW_CONFLUENCE_CONNECTOR_USER_PROFILES_OVERRIDE)
if _RAW_CONFLUENCE_CONNECTOR_USER_PROFILES_OVERRIDE
else None
),
)
# enter as a floating point offset from UTC in hours (-24 < val < 24)
# this will be applied globally, so it probably makes sense to transition this to per
# connector as some point.
# For the default value, we assume that the user's local timezone is more likely to be
# correct (i.e. the configured user's timezone or the default server one) than UTC.
# https://developer.atlassian.com/cloud/confluence/cql-fields/#created
CONFLUENCE_TIMEZONE_OFFSET = float(
os.environ.get("CONFLUENCE_TIMEZONE_OFFSET", get_current_tz_offset())
)
CONFLUENCE_SYNC_TIME_BUFFER_SECONDS = int(
os.environ.get("CONFLUENCE_SYNC_TIME_BUFFER_SECONDS", ONE_DAY)
)
GOOGLE_DRIVE_SYNC_TIME_BUFFER_SECONDS = int(
os.environ.get("GOOGLE_DRIVE_SYNC_TIME_BUFFER_SECONDS", ONE_DAY)
)
GOOGLE_DRIVE_CONNECTOR_SIZE_THRESHOLD = int(
os.environ.get("GOOGLE_DRIVE_CONNECTOR_SIZE_THRESHOLD", 10 * 1024 * 1024)
)
JIRA_CONNECTOR_LABELS_TO_SKIP = [
ignored_tag
for ignored_tag in os.environ.get("JIRA_CONNECTOR_LABELS_TO_SKIP", "").split(",")
if ignored_tag
]
JIRA_CONNECTOR_MAX_TICKET_SIZE = int(
os.environ.get("JIRA_CONNECTOR_MAX_TICKET_SIZE", 100 * 1024)
)
JIRA_SYNC_TIME_BUFFER_SECONDS = int(
os.environ.get("JIRA_SYNC_TIME_BUFFER_SECONDS", ONE_MINUTE)
)
JIRA_TIMEZONE_OFFSET = float(
os.environ.get("JIRA_TIMEZONE_OFFSET", get_current_tz_offset())
)
OAUTH_SLACK_CLIENT_ID = os.environ.get("OAUTH_SLACK_CLIENT_ID", "")
OAUTH_SLACK_CLIENT_SECRET = os.environ.get("OAUTH_SLACK_CLIENT_SECRET", "")
OAUTH_CONFLUENCE_CLOUD_CLIENT_ID = os.environ.get(
"OAUTH_CONFLUENCE_CLOUD_CLIENT_ID", ""
)
OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET = os.environ.get(
"OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET", ""
)
OAUTH_JIRA_CLOUD_CLIENT_ID = os.environ.get("OAUTH_JIRA_CLOUD_CLIENT_ID", "")
OAUTH_JIRA_CLOUD_CLIENT_SECRET = os.environ.get("OAUTH_JIRA_CLOUD_CLIENT_SECRET", "")
OAUTH_GOOGLE_DRIVE_CLIENT_ID = os.environ.get("OAUTH_GOOGLE_DRIVE_CLIENT_ID", "")
OAUTH_GOOGLE_DRIVE_CLIENT_SECRET = os.environ.get(
"OAUTH_GOOGLE_DRIVE_CLIENT_SECRET", ""
)
GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI = os.environ.get("GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI", "http://localhost:9380/v1/connector/google-drive/oauth/web/callback")
GMAIL_WEB_OAUTH_REDIRECT_URI = os.environ.get("GMAIL_WEB_OAUTH_REDIRECT_URI", "http://localhost:9380/v1/connector/gmail/oauth/web/callback")
CONFLUENCE_OAUTH_TOKEN_URL = "https://auth.atlassian.com/oauth/token"
RATE_LIMIT_MESSAGE_LOWERCASE = "Rate limit exceeded".lower()
_DEFAULT_PAGINATION_LIMIT = 1000
_PROBLEMATIC_EXPANSIONS = "body.storage.value"
_REPLACEMENT_EXPANSIONS = "body.view.value"
BOX_WEB_OAUTH_REDIRECT_URI = os.environ.get("BOX_WEB_OAUTH_REDIRECT_URI", "http://localhost:9380/v1/connector/box/oauth/web/callback")
GITHUB_CONNECTOR_BASE_URL = os.environ.get("GITHUB_CONNECTOR_BASE_URL") or None
class HtmlBasedConnectorTransformLinksStrategy(str, Enum):
# remove links entirely
STRIP = "strip"
# turn HTML links into markdown links
MARKDOWN = "markdown"
HTML_BASED_CONNECTOR_TRANSFORM_LINKS_STRATEGY = os.environ.get(
"HTML_BASED_CONNECTOR_TRANSFORM_LINKS_STRATEGY",
HtmlBasedConnectorTransformLinksStrategy.STRIP,
)
PARSE_WITH_TRAFILATURA = os.environ.get("PARSE_WITH_TRAFILATURA", "").lower() == "true"
WEB_CONNECTOR_IGNORED_CLASSES = os.environ.get(
"WEB_CONNECTOR_IGNORED_CLASSES", "sidebar,footer"
).split(",")
WEB_CONNECTOR_IGNORED_ELEMENTS = os.environ.get(
"WEB_CONNECTOR_IGNORED_ELEMENTS", "nav,footer,meta,script,style,symbol,aside"
).split(",")
AIRTABLE_CONNECTOR_SIZE_THRESHOLD = int(
os.environ.get("AIRTABLE_CONNECTOR_SIZE_THRESHOLD", 10 * 1024 * 1024)
)
ASANA_CONNECTOR_SIZE_THRESHOLD = int(
os.environ.get("ASANA_CONNECTOR_SIZE_THRESHOLD", 10 * 1024 * 1024)
)
IMAP_CONNECTOR_SIZE_THRESHOLD = int(
os.environ.get("IMAP_CONNECTOR_SIZE_THRESHOLD", 10 * 1024 * 1024)
)
ZENDESK_CONNECTOR_SKIP_ARTICLE_LABELS = os.environ.get(
"ZENDESK_CONNECTOR_SKIP_ARTICLE_LABELS", ""
).split(",")
_USER_NOT_FOUND = "Unknown Confluence User"
_COMMENT_EXPANSION_FIELDS = ["body.storage.value"]
_ATTACHMENT_EXPANSION_FIELDS = [
"version",
"space",
"metadata.labels",
]
_RESTRICTIONS_EXPANSION_FIELDS = [
"space",
"restrictions.read.restrictions.user",
"restrictions.read.restrictions.group",
"ancestors.restrictions.read.restrictions.user",
"ancestors.restrictions.read.restrictions.group",
]
_SLIM_DOC_BATCH_SIZE = 5000