Files
ragflow/common/data_source/dingtalk_ai_table_connector.py
Heyang Wang c217b8f3d8 Feat: add DingTalk AI Table connector and integration for data synch… (#13413)
### What problem does this PR solve?

Add DingTalk AI Table connector and integration for data synchronization

Issue #13400

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

Co-authored-by: wangheyang <wangheyang@corp.netease.com>
2026-03-06 21:13:23 +08:00

434 lines
14 KiB
Python

"""DingTalk AI Table connector for RAGFlow. By the way, "notable" is a reference to the DingTalk AI Table.
This connector ingests records from DingTalk AI Table as documents.
It first retrieves all sheets from a specified table, then fetches all records
from each sheet.
API Documentation:
- GetAllSheets: https://open.dingtalk.com/document/development/api-notable-getallsheets
- ListRecords: https://open.dingtalk.com/document/development/api-notable-listrecords
"""
import json
import logging
from datetime import datetime, timezone
from typing import Any
from alibabacloud_dingtalk.notable_1_0.client import Client as NotableClient
from alibabacloud_dingtalk.notable_1_0 import models as notable_models
from alibabacloud_tea_openapi import models as open_api_models
from alibabacloud_tea_util import models as util_models
from alibabacloud_tea_util.client import Client as UtilClient
from common.data_source.config import INDEX_BATCH_SIZE, DocumentSource
from common.data_source.exceptions import ConnectorMissingCredentialError, ConnectorValidationError
from common.data_source.interfaces import LoadConnector, PollConnector, SecondsSinceUnixEpoch
from common.data_source.models import Document, GenerateDocumentsOutput
logger = logging.getLogger(__name__)
# Document ID prefix for DingTalk Notable
_DINGTALK_AI_TABLE_DOC_ID_PREFIX = "dingtalk_ai_table:"
class DingTalkAITableClientNotSetUpError(PermissionError):
"""Exception raised when DingTalk Notable client is not initialized."""
def __init__(self) -> None:
super().__init__("DingTalk Notable client is not set up. Did you forget to call load_credentials()?")
class DingTalkAITableConnector(LoadConnector, PollConnector):
"""
DingTalk AI Table (Notable) connector for accessing table records.
This connector:
1. Retrieves all sheets from a specified Notable table using GetAllSheets API
2. For each sheet, fetches all records using ListRecords API with pagination
3. Converts each record into a Document for RAGFlow ingestion
Required credentials:
- access_token: DingTalk access token (x-acs-dingtalk-access-token)
- operator_id: User's unionId for API calls
Configuration:
- table_id: The Notable table ID (e.g., 'qnYxxx')
"""
def __init__(
self,
table_id: str,
operator_id: str,
batch_size: int = INDEX_BATCH_SIZE,
) -> None:
"""
Initialize the DingTalk Notable connector.
Args:
table_id: The Notable table ID
operator_id: User's unionId for API calls
batch_size: Number of records per batch for document generation
"""
self.table_id = table_id
self.operator_id = operator_id
self.batch_size = batch_size
self._client: NotableClient | None = None
self._access_token: str | None = None
def _create_client(self) -> NotableClient:
"""Create DingTalk Notable API client."""
config = open_api_models.Config()
config.protocol = "https"
config.region_id = "central"
return NotableClient(config)
def load_credentials(self, credentials: dict[str, Any]) -> dict[str, Any] | None:
"""
Load DingTalk credentials.
Args:
credentials: Dictionary containing 'access_token'
Returns:
None
"""
access_token = credentials.get("access_token")
if not access_token:
raise ConnectorMissingCredentialError("DingTalk access_token is required")
self._access_token = access_token
self._client = self._create_client()
return None
@property
def client(self) -> NotableClient:
"""Get the DingTalk AITable client."""
if self._client is None:
raise DingTalkAITableClientNotSetUpError()
return self._client
@property
def access_token(self) -> str:
"""Get the access token."""
if self._access_token is None:
raise ConnectorMissingCredentialError("DingTalk access_token not loaded")
return self._access_token
def validate_connector_settings(self) -> None:
"""Validate DingTalk connector settings by trying to get all sheets."""
if self._client is None or self._access_token is None:
raise ConnectorMissingCredentialError("DingTalk Notable")
try:
# Try to get sheets to validate credentials
headers = notable_models.GetAllSheetsHeaders()
headers.x_acs_dingtalk_access_token = self._access_token
request = notable_models.GetAllSheetsRequest(
operator_id=self.operator_id,
)
self.client.get_all_sheets_with_options(
self.table_id,
request,
headers,
util_models.RuntimeOptions(),
)
except Exception as e:
logger.exception("[DingTalk Notable]: Failed to validate credentials")
raise ConnectorValidationError(f"DingTalk Notable credential validation failed: {e}")
def _get_all_sheets(self) -> list[dict[str, Any]]:
"""
Retrieve all sheets from the Notable table.
Returns:
List of sheet information dictionaries
"""
headers = notable_models.GetAllSheetsHeaders()
headers.x_acs_dingtalk_access_token = self._access_token
request = notable_models.GetAllSheetsRequest(
operator_id=self.operator_id,
)
try:
response = self.client.get_all_sheets_with_options(
self.table_id,
request,
headers,
util_models.RuntimeOptions(),
)
sheets = []
if response.body and response.body.value:
for sheet in response.body.value:
sheets.append(
{
"id": sheet.id,
"name": sheet.name,
}
)
logger.info(f"[DingTalk Notable]: Found {len(sheets)} sheets in table {self.table_id}")
return sheets
except Exception as e:
logger.exception(f"[DingTalk Notable]: Failed to get sheets: {e}")
raise
def _list_records(
self,
sheet_id: str,
next_token: str | None = None,
max_results: int = 100,
) -> tuple[list[dict[str, Any]], str | None]:
"""
List records from a specific sheet with pagination.
Args:
sheet_id: The sheet ID
next_token: Token for pagination
max_results: Maximum number of results per page
Returns:
Tuple of (records list, next_token or None if no more)
"""
headers = notable_models.ListRecordsHeaders()
headers.x_acs_dingtalk_access_token = self._access_token
request = notable_models.ListRecordsRequest(
operator_id=self.operator_id,
max_results=max_results,
next_token=next_token or "",
)
try:
response = self.client.list_records_with_options(
self.table_id,
sheet_id,
request,
headers,
util_models.RuntimeOptions(),
)
records = []
new_next_token = None
if response.body:
if response.body.records:
for record in response.body.records:
records.append(
{
"id": record.id,
"fields": record.fields,
}
)
if response.body.next_token:
new_next_token = response.body.next_token
return records, new_next_token
except Exception as e:
if not UtilClient.empty(getattr(e, "code", None)) and not UtilClient.empty(getattr(e, "message", None)):
logger.error(f"[DingTalk AITable]: API error - code: {e.code}, message: {e.message}")
raise
def _get_all_records(self, sheet_id: str) -> list[dict[str, Any]]:
"""
Retrieve all records from a sheet with pagination.
Args:
sheet_id: The sheet ID
Returns:
List of all records
"""
all_records = []
next_token = None
while True:
records, next_token = self._list_records(
sheet_id=sheet_id,
next_token=next_token,
)
all_records.extend(records)
if not next_token:
break
logger.info(f"[DingTalk Notable]: Retrieved {len(all_records)} records from sheet {sheet_id}")
return all_records
def _convert_record_to_document(
self,
record: dict[str, Any],
sheet_id: str,
sheet_name: str,
) -> Document:
"""
Convert a Notable record to a Document.
Args:
record: The record dictionary
sheet_id: The sheet ID
sheet_name: The sheet name
Returns:
Document object
"""
record_id = record.get("id", "unknown")
fields = record.get("fields", {})
# Convert fields to JSON string for blob content
content = json.dumps(fields, ensure_ascii=False, indent=2)
blob = content.encode("utf-8")
# Create semantic identifier from record fields
# Try to find a meaningful title/name field
semantic_identifier = f"{sheet_name} - Record {record_id}"
# Try to find a title-like field
for key, value in fields.items():
if isinstance(value, str) and len(value) > 0 and len(value) < 100:
semantic_identifier = f"{sheet_name} - {value[:50]}"
break
# Metadata
metadata: dict[str, str | list[str]] = {
"table_id": self.table_id,
"sheet_id": sheet_id,
"sheet_name": sheet_name,
"record_id": record_id,
}
# Create document
doc = Document(
id=f"{_DINGTALK_AI_TABLE_DOC_ID_PREFIX}{self.table_id}:{sheet_id}:{record_id}",
source=DocumentSource.DINGTALK_AI_TABLE,
semantic_identifier=semantic_identifier,
extension=".json",
blob=blob,
size_bytes=len(blob),
doc_updated_at=datetime.now(timezone.utc),
metadata=metadata,
)
return doc
def _yield_documents_from_table(
self,
start: SecondsSinceUnixEpoch | None = None,
end: SecondsSinceUnixEpoch | None = None,
) -> GenerateDocumentsOutput:
"""
Yield documents from all sheets in the table.
Args:
start: Optional start timestamp for filtering
end: Optional end timestamp for filtering
Yields:
Lists of Document objects
"""
# Get all sheets
sheets = self._get_all_sheets()
batch: list[Document] = []
for sheet in sheets:
sheet_id = sheet["id"]
sheet_name = sheet["name"]
# Get all records from this sheet
records = self._get_all_records(sheet_id)
for record in records:
doc = self._convert_record_to_document(
record=record,
sheet_id=sheet_id,
sheet_name=sheet_name,
)
# Apply time filtering if specified
if start is not None or end is not None:
doc_time = doc.doc_updated_at.timestamp() if doc.doc_updated_at else None
if doc_time is not None:
if start is not None and doc_time < start:
continue
if end is not None and doc_time > end:
continue
batch.append(doc)
if len(batch) >= self.batch_size:
yield batch
batch = []
if batch:
yield batch
def load_from_state(self) -> GenerateDocumentsOutput:
"""
Load all documents from the DingTalk Notable table.
Yields:
Lists of Document objects
"""
return self._yield_documents_from_table()
def poll_source(
self,
start: SecondsSinceUnixEpoch,
end: SecondsSinceUnixEpoch,
) -> GenerateDocumentsOutput:
"""
Poll for documents within a time range.
Args:
start: Start timestamp
end: End timestamp
Yields:
Lists of Document objects
"""
return self._yield_documents_from_table(start=start, end=end)
if __name__ == "__main__":
import os
logging.basicConfig(level=logging.DEBUG)
# Example usage
table_id = os.environ.get("DINGTALK_AI_TABLE_BASE_ID", "")
operator_id = os.environ.get("DINGTALK_OPERATOR_ID", "")
access_token = os.environ.get("DINGTALK_ACCESS_TOKEN", "")
if not all([table_id, operator_id, access_token]):
print("Please set DINGTALK_AI_TABLE_BASE_ID, DINGTALK_OPERATOR_ID, and DINGTALK_ACCESS_TOKEN environment variables")
exit(1)
connector = DingTalkAITableConnector(
table_id=table_id,
operator_id=operator_id,
)
connector.load_credentials({"access_token": access_token})
try:
connector.validate_connector_settings()
print("Connector settings validated successfully")
except Exception as e:
print(f"Validation failed: {e}")
exit(1)
document_batches = connector.load_from_state()
try:
first_batch = next(document_batches)
print(f"Loaded {len(first_batch)} documents in first batch.")
for doc in first_batch[:5]: # Print first 5 docs
print(f"- {doc.semantic_identifier} ({doc.size_bytes} bytes)")
print(f" Metadata: {doc.metadata}")
except StopIteration:
print("No documents available in DingTalk Notable table.")