SurfSense/surfsense_backend/app/tasks/connector_indexers/notion_indexer.py
2025-08-12 15:28:13 -07:00

406 lines
16 KiB
Python

"""
Notion connector indexer.
"""
from datetime import datetime, timedelta
from sqlalchemy.exc import SQLAlchemyError
from sqlalchemy.ext.asyncio import AsyncSession
from app.config import config
from app.connectors.notion_history import NotionHistoryConnector
from app.db import Document, DocumentType, SearchSourceConnectorType
from app.prompts import SUMMARY_PROMPT_TEMPLATE
from app.services.llm_service import get_user_long_context_llm
from app.services.task_logging_service import TaskLoggingService
from app.utils.document_converters import generate_content_hash
from .base import (
build_document_metadata_string,
check_duplicate_document_by_hash,
create_document_chunks,
get_connector_by_id,
logger,
update_connector_last_indexed,
)
async def index_notion_pages(
session: AsyncSession,
connector_id: int,
search_space_id: int,
user_id: str,
start_date: str | None = None,
end_date: str | None = None,
update_last_indexed: bool = True,
) -> tuple[int, str | None]:
"""
Index Notion pages from all accessible pages.
Args:
session: Database session
connector_id: ID of the Notion connector
search_space_id: ID of the search space to store documents in
user_id: ID of the user
start_date: Start date for indexing (YYYY-MM-DD format)
end_date: End date for indexing (YYYY-MM-DD format)
update_last_indexed: Whether to update the last_indexed_at timestamp (default: True)
Returns:
Tuple containing (number of documents indexed, error message or None)
"""
task_logger = TaskLoggingService(session, search_space_id)
# Log task start
log_entry = await task_logger.log_task_start(
task_name="notion_pages_indexing",
source="connector_indexing_task",
message=f"Starting Notion pages indexing for connector {connector_id}",
metadata={
"connector_id": connector_id,
"user_id": str(user_id),
"start_date": start_date,
"end_date": end_date,
},
)
try:
# Get the connector
await task_logger.log_task_progress(
log_entry,
f"Retrieving Notion connector {connector_id} from database",
{"stage": "connector_retrieval"},
)
connector = await get_connector_by_id(
session, connector_id, SearchSourceConnectorType.NOTION_CONNECTOR
)
if not connector:
await task_logger.log_task_failure(
log_entry,
f"Connector with ID {connector_id} not found or is not a Notion connector",
"Connector not found",
{"error_type": "ConnectorNotFound"},
)
return (
0,
f"Connector with ID {connector_id} not found or is not a Notion connector",
)
# Get the Notion token from the connector config
notion_token = connector.config.get("NOTION_INTEGRATION_TOKEN")
if not notion_token:
await task_logger.log_task_failure(
log_entry,
f"Notion integration token not found in connector config for connector {connector_id}",
"Missing Notion token",
{"error_type": "MissingToken"},
)
return 0, "Notion integration token not found in connector config"
# Initialize Notion client
await task_logger.log_task_progress(
log_entry,
f"Initializing Notion client for connector {connector_id}",
{"stage": "client_initialization"},
)
logger.info(f"Initializing Notion client for connector {connector_id}")
notion_client = NotionHistoryConnector(token=notion_token)
# Calculate date range
if start_date is None or end_date is None:
# Fall back to calculating dates
calculated_end_date = datetime.now()
calculated_start_date = calculated_end_date - timedelta(
days=365
) # Check for last 1 year of pages
# Use calculated dates if not provided
if start_date is None:
start_date_iso = calculated_start_date.strftime("%Y-%m-%dT%H:%M:%SZ")
else:
# Convert YYYY-MM-DD to ISO format
start_date_iso = datetime.strptime(start_date, "%Y-%m-%d").strftime(
"%Y-%m-%dT%H:%M:%SZ"
)
if end_date is None:
end_date_iso = calculated_end_date.strftime("%Y-%m-%dT%H:%M:%SZ")
else:
# Convert YYYY-MM-DD to ISO format
end_date_iso = datetime.strptime(end_date, "%Y-%m-%d").strftime(
"%Y-%m-%dT%H:%M:%SZ"
)
else:
# Convert provided dates to ISO format for Notion API
start_date_iso = datetime.strptime(start_date, "%Y-%m-%d").strftime(
"%Y-%m-%dT%H:%M:%SZ"
)
end_date_iso = datetime.strptime(end_date, "%Y-%m-%d").strftime(
"%Y-%m-%dT%H:%M:%SZ"
)
logger.info(f"Fetching Notion pages from {start_date_iso} to {end_date_iso}")
await task_logger.log_task_progress(
log_entry,
f"Fetching Notion pages from {start_date_iso} to {end_date_iso}",
{
"stage": "fetch_pages",
"start_date": start_date_iso,
"end_date": end_date_iso,
},
)
# Get all pages
try:
pages = notion_client.get_all_pages(
start_date=start_date_iso, end_date=end_date_iso
)
logger.info(f"Found {len(pages)} Notion pages")
except Exception as e:
await task_logger.log_task_failure(
log_entry,
f"Failed to get Notion pages for connector {connector_id}",
str(e),
{"error_type": "PageFetchError"},
)
logger.error(f"Error fetching Notion pages: {e!s}", exc_info=True)
return 0, f"Failed to get Notion pages: {e!s}"
if not pages:
await task_logger.log_task_success(
log_entry,
f"No Notion pages found for connector {connector_id}",
{"pages_found": 0},
)
logger.info("No Notion pages found to index")
return 0, "No Notion pages found"
# Track the number of documents indexed
documents_indexed = 0
documents_skipped = 0
skipped_pages = []
await task_logger.log_task_progress(
log_entry,
f"Starting to process {len(pages)} Notion pages",
{"stage": "process_pages", "total_pages": len(pages)},
)
# Process each page
for page in pages:
try:
page_id = page.get("page_id")
page_title = page.get("title", f"Untitled page ({page_id})")
page_content = page.get("content", [])
logger.info(f"Processing Notion page: {page_title} ({page_id})")
if not page_content:
logger.info(f"No content found in page {page_title}. Skipping.")
skipped_pages.append(f"{page_title} (no content)")
documents_skipped += 1
continue
# Convert page content to markdown format
markdown_content = f"# Notion Page: {page_title}\n\n"
# Process blocks recursively
def process_blocks(blocks, level=0):
result = ""
for block in blocks:
block_type = block.get("type")
block_content = block.get("content", "")
children = block.get("children", [])
# Add indentation based on level
indent = " " * level
# Format based on block type
if block_type in ["paragraph", "text"]:
result += f"{indent}{block_content}\n\n"
elif block_type in ["heading_1", "header"]:
result += f"{indent}# {block_content}\n\n"
elif block_type == "heading_2":
result += f"{indent}## {block_content}\n\n"
elif block_type == "heading_3":
result += f"{indent}### {block_content}\n\n"
elif block_type == "bulleted_list_item":
result += f"{indent}* {block_content}\n"
elif block_type == "numbered_list_item":
result += f"{indent}1. {block_content}\n"
elif block_type == "to_do":
result += f"{indent}- [ ] {block_content}\n"
elif block_type == "toggle":
result += f"{indent}> {block_content}\n"
elif block_type == "code":
result += f"{indent}```\n{block_content}\n```\n\n"
elif block_type == "quote":
result += f"{indent}> {block_content}\n\n"
elif block_type == "callout":
result += f"{indent}> **Note:** {block_content}\n\n"
elif block_type == "image":
result += f"{indent}![Image]({block_content})\n\n"
else:
# Default for other block types
if block_content:
result += f"{indent}{block_content}\n\n"
# Process children recursively
if children:
result += process_blocks(children, level + 1)
return result
logger.debug(
f"Converting {len(page_content)} blocks to markdown for page {page_title}"
)
markdown_content += process_blocks(page_content)
# Format document metadata
metadata_sections = [
("METADATA", [f"PAGE_TITLE: {page_title}", f"PAGE_ID: {page_id}"]),
(
"CONTENT",
[
"FORMAT: markdown",
"TEXT_START",
markdown_content,
"TEXT_END",
],
),
]
# Build the document string
combined_document_string = build_document_metadata_string(
metadata_sections
)
content_hash = generate_content_hash(
combined_document_string, search_space_id
)
# Check if document with this content hash already exists
existing_document_by_hash = await check_duplicate_document_by_hash(
session, content_hash
)
if existing_document_by_hash:
logger.info(
f"Document with content hash {content_hash} already exists for page {page_title}. Skipping processing."
)
documents_skipped += 1
continue
# Get user's long context LLM
user_llm = await get_user_long_context_llm(session, user_id)
if not user_llm:
logger.error(f"No long context LLM configured for user {user_id}")
skipped_pages.append(f"{page_title} (no LLM configured)")
documents_skipped += 1
continue
# Generate summary
logger.debug(f"Generating summary for page {page_title}")
summary_chain = SUMMARY_PROMPT_TEMPLATE | user_llm
summary_result = await summary_chain.ainvoke(
{"document": combined_document_string}
)
summary_content = summary_result.content
summary_embedding = config.embedding_model_instance.embed(
summary_content
)
# Process chunks
logger.debug(f"Chunking content for page {page_title}")
chunks = await create_document_chunks(markdown_content)
# Create and store new document
document = Document(
search_space_id=search_space_id,
title=f"Notion - {page_title}",
document_type=DocumentType.NOTION_CONNECTOR,
document_metadata={
"page_title": page_title,
"page_id": page_id,
"indexed_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
},
content=summary_content,
content_hash=content_hash,
embedding=summary_embedding,
chunks=chunks,
)
session.add(document)
documents_indexed += 1
logger.info(f"Successfully indexed new Notion page: {page_title}")
except Exception as e:
logger.error(
f"Error processing Notion page {page.get('title', 'Unknown')}: {e!s}",
exc_info=True,
)
skipped_pages.append(
f"{page.get('title', 'Unknown')} (processing error)"
)
documents_skipped += 1
continue # Skip this page and continue with others
# Update the last_indexed_at timestamp for the connector only if requested
# and if we successfully indexed at least one page
total_processed = documents_indexed
if total_processed > 0:
await update_connector_last_indexed(session, connector, update_last_indexed)
# Commit all changes
await session.commit()
# Prepare result message
result_message = None
if skipped_pages:
result_message = f"Processed {total_processed} pages. Skipped {len(skipped_pages)} pages: {', '.join(skipped_pages)}"
else:
result_message = f"Processed {total_processed} pages."
# Log success
await task_logger.log_task_success(
log_entry,
f"Successfully completed Notion indexing for connector {connector_id}",
{
"pages_processed": total_processed,
"documents_indexed": documents_indexed,
"documents_skipped": documents_skipped,
"skipped_pages_count": len(skipped_pages),
"result_message": result_message,
},
)
logger.info(
f"Notion indexing completed: {documents_indexed} new pages, {documents_skipped} skipped"
)
return total_processed, result_message
except SQLAlchemyError as db_error:
await session.rollback()
await task_logger.log_task_failure(
log_entry,
f"Database error during Notion indexing for connector {connector_id}",
str(db_error),
{"error_type": "SQLAlchemyError"},
)
logger.error(
f"Database error during Notion indexing: {db_error!s}", exc_info=True
)
return 0, f"Database error: {db_error!s}"
except Exception as e:
await session.rollback()
await task_logger.log_task_failure(
log_entry,
f"Failed to index Notion pages for connector {connector_id}",
str(e),
{"error_type": type(e).__name__},
)
logger.error(f"Failed to index Notion pages: {e!s}", exc_info=True)
return 0, f"Failed to index Notion pages: {e!s}"