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suppport confluence pages indexing
This commit is contained in:
CREDO23
parent
e5bb26ea13
commit
131d362f1e
1 changed files with 369 additions and 0 deletions
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@ -8,6 +8,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.future import select
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from app.config import config
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from app.connectors.confluence_connector import ConfluenceConnector
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from app.connectors.discord_connector import DiscordConnector
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from app.connectors.github_connector import GitHubConnector
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from app.connectors.jira_connector import JiraConnector
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@ -2329,3 +2330,371 @@ async def index_jira_issues(
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)
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logger.error(f"Failed to index JIRA issues: {e!s}", exc_info=True)
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return 0, f"Failed to index JIRA issues: {e!s}"
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async def index_confluence_pages(
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session: AsyncSession,
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connector_id: int,
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search_space_id: int,
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user_id: str,
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start_date: str | None = None,
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end_date: str | None = None,
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update_last_indexed: bool = True,
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) -> tuple[int, str | None]:
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"""
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Index Confluence pages and comments.
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Args:
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session: Database session
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connector_id: ID of the Confluence connector
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search_space_id: ID of the search space to store documents in
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user_id: User ID
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start_date: Start date for indexing (YYYY-MM-DD format)
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end_date: End date for indexing (YYYY-MM-DD format)
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update_last_indexed: Whether to update the last_indexed_at timestamp (default: True)
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Returns:
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Tuple containing (number of documents indexed, error message or None)
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"""
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task_logger = TaskLoggingService(session, search_space_id)
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# Log task start
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log_entry = await task_logger.log_task_start(
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task_name="confluence_pages_indexing",
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source="connector_indexing_task",
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message=f"Starting Confluence pages indexing for connector {connector_id}",
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metadata={
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"connector_id": connector_id,
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"user_id": str(user_id),
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"start_date": start_date,
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"end_date": end_date,
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},
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)
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try:
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# Get the connector from the database
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result = await session.execute(
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select(SearchSourceConnector).filter(
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SearchSourceConnector.id == connector_id,
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SearchSourceConnector.connector_type
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== SearchSourceConnectorType.CONFLUENCE_CONNECTOR,
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)
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)
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connector = result.scalars().first()
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if not connector:
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await task_logger.log_task_failure(
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log_entry,
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f"Connector with ID {connector_id} not found",
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"Connector not found",
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{"error_type": "ConnectorNotFound"},
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)
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return 0, f"Connector with ID {connector_id} not found"
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# Get the Confluence credentials from the connector config
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confluence_email = connector.config.get("CONFLUENCE_EMAIL")
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confluence_api_token = connector.config.get("CONFLUENCE_API_TOKEN")
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confluence_base_url = connector.config.get("CONFLUENCE_BASE_URL")
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if not confluence_email or not confluence_api_token or not confluence_base_url:
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await task_logger.log_task_failure(
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log_entry,
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f"Confluence credentials not found in connector config for connector {connector_id}",
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"Missing Confluence credentials",
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{"error_type": "MissingCredentials"},
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)
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return 0, "Confluence credentials not found in connector config"
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# Initialize Confluence client
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await task_logger.log_task_progress(
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log_entry,
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f"Initializing Confluence client for connector {connector_id}",
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{"stage": "client_initialization"},
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)
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confluence_client = ConfluenceConnector(
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base_url=confluence_base_url, email=confluence_email, api_token=confluence_api_token
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)
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# Calculate date range
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if start_date is None or end_date is None:
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# Fall back to calculating dates based on last_indexed_at
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calculated_end_date = datetime.now()
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# Use last_indexed_at as start date if available, otherwise use 365 days ago
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if connector.last_indexed_at:
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# Convert dates to be comparable (both timezone-naive)
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last_indexed_naive = (
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connector.last_indexed_at.replace(tzinfo=None)
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if connector.last_indexed_at.tzinfo
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else connector.last_indexed_at
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)
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# Check if last_indexed_at is in the future or after end_date
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if last_indexed_naive > calculated_end_date:
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logger.warning(
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f"Last indexed date ({last_indexed_naive.strftime('%Y-%m-%d')}) is in the future. Using 365 days ago instead."
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)
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calculated_start_date = calculated_end_date - timedelta(days=365)
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else:
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calculated_start_date = last_indexed_naive
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logger.info(
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f"Using last_indexed_at ({calculated_start_date.strftime('%Y-%m-%d')}) as start date"
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)
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else:
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calculated_start_date = calculated_end_date - timedelta(
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days=365
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) # Use 365 days as default
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logger.info(
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f"No last_indexed_at found, using {calculated_start_date.strftime('%Y-%m-%d')} (365 days ago) as start date"
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)
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# Use calculated dates if not provided
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start_date_str = (
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start_date if start_date else calculated_start_date.strftime("%Y-%m-%d")
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)
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end_date_str = (
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end_date if end_date else calculated_end_date.strftime("%Y-%m-%d")
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)
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else:
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# Use provided dates
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start_date_str = start_date
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end_date_str = end_date
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await task_logger.log_task_progress(
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log_entry,
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f"Fetching Confluence pages from {start_date_str} to {end_date_str}",
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{
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"stage": "fetching_pages",
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"start_date": start_date_str,
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"end_date": end_date_str,
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},
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)
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# Get pages within date range
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try:
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pages, error = confluence_client.get_pages_by_date_range(
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start_date=start_date_str, end_date=end_date_str, include_comments=True
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)
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if error:
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logger.error(f"Failed to get Confluence pages: {error}")
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# Don't treat "No pages found" as an error that should stop indexing
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if "No pages found" in error:
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logger.info(
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"No pages found is not a critical error, continuing with update"
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)
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if update_last_indexed:
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connector.last_indexed_at = datetime.now()
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await session.commit()
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logger.info(
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f"Updated last_indexed_at to {connector.last_indexed_at} despite no pages found"
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)
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await task_logger.log_task_success(
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log_entry,
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f"No Confluence pages found in date range {start_date_str} to {end_date_str}",
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{"pages_found": 0},
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)
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return 0, None
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else:
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await task_logger.log_task_failure(
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log_entry,
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f"Failed to get Confluence pages: {error}",
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"API Error",
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{"error_type": "APIError"},
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)
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return 0, f"Failed to get Confluence pages: {error}"
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logger.info(f"Retrieved {len(pages)} pages from Confluence API")
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except Exception as e:
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logger.error(f"Error fetching Confluence pages: {e!s}", exc_info=True)
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return 0, f"Error fetching Confluence pages: {e!s}"
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# Process and index each page
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documents_indexed = 0
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skipped_pages = []
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documents_skipped = 0
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for page in pages:
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try:
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page_id = page.get("id")
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page_title = page.get("title", "")
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space_id = page.get("spaceId", "")
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if not page_id or not page_title:
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logger.warning(
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f"Skipping page with missing ID or title: {page_id or 'Unknown'}"
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)
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skipped_pages.append(
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f"{page_title or 'Unknown'} (missing data)"
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)
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documents_skipped += 1
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continue
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# Extract page content
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page_content = ""
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if page.get("body") and page["body"].get("storage"):
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page_content = page["body"]["storage"].get("value", "")
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# Add comments to content
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comments = page.get("comments", [])
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comments_content = ""
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if comments:
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comments_content = "\n\n## Comments\n\n"
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for comment in comments:
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comment_body = ""
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if comment.get("body") and comment["body"].get("storage"):
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comment_body = comment["body"]["storage"].get("value", "")
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comment_author = comment.get("version", {}).get("authorId", "Unknown")
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comment_date = comment.get("version", {}).get("createdAt", "")
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comments_content += f"**Comment by {comment_author}** ({comment_date}):\n{comment_body}\n\n"
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# Combine page content with comments
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full_content = f"# {page_title}\n\n{page_content}{comments_content}"
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if not full_content.strip():
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logger.warning(
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f"Skipping page with no content: {page_title}"
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)
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skipped_pages.append(f"{page_title} (no content)")
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documents_skipped += 1
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continue
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# Create a simple summary
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summary_content = f"Confluence Page: {page_title}\n\nSpace ID: {space_id}\n\n"
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if page_content:
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# Take first 500 characters of content for summary
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content_preview = page_content[:500]
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if len(page_content) > 500:
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content_preview += "..."
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summary_content += f"Content Preview: {content_preview}\n\n"
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# Add comment count
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comment_count = len(comments)
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summary_content += f"Comments: {comment_count}"
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# Generate content hash
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content_hash = generate_content_hash(full_content, search_space_id)
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# Check if document already exists
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existing_doc_by_hash_result = await session.execute(
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select(Document).where(Document.content_hash == content_hash)
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)
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existing_document_by_hash = (
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existing_doc_by_hash_result.scalars().first()
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)
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if existing_document_by_hash:
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logger.info(
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f"Document with content hash {content_hash} already exists for page {page_title}. Skipping processing."
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)
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documents_skipped += 1
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continue
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# Generate embedding for the summary
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summary_embedding = config.embedding_model_instance.embed(
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summary_content
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)
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# Process chunks - using the full page content with comments
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chunks = [
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Chunk(
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content=chunk.text,
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embedding=config.embedding_model_instance.embed(chunk.text),
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)
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for chunk in config.chunker_instance.chunk(full_content)
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]
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# Create and store new document
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logger.info(
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f"Creating new document for page {page_title}"
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)
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document = Document(
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search_space_id=search_space_id,
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title=f"Confluence - {page_title}",
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document_type=DocumentType.CONFLUENCE_CONNECTOR,
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document_metadata={
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"page_id": page_id,
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"page_title": page_title,
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"space_id": space_id,
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"comment_count": comment_count,
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"indexed_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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},
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content=summary_content,
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content_hash=content_hash,
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embedding=summary_embedding,
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chunks=chunks,
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)
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session.add(document)
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documents_indexed += 1
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logger.info(
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f"Successfully indexed new page {page_title}"
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)
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except Exception as e:
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logger.error(
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f"Error processing page {page.get('title', 'Unknown')}: {e!s}",
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exc_info=True,
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)
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skipped_pages.append(
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f"{page.get('title', 'Unknown')} (processing error)"
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)
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documents_skipped += 1
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continue # Skip this page and continue with others
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# Update the last_indexed_at timestamp for the connector only if requested
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total_processed = documents_indexed
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if update_last_indexed:
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connector.last_indexed_at = datetime.now()
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logger.info(f"Updated last_indexed_at to {connector.last_indexed_at}")
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# Commit all changes
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await session.commit()
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logger.info("Successfully committed all Confluence document changes to database")
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# Log success
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await task_logger.log_task_success(
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log_entry,
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f"Successfully completed Confluence indexing for connector {connector_id}",
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{
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"pages_processed": total_processed,
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"documents_indexed": documents_indexed,
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"documents_skipped": documents_skipped,
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"skipped_pages_count": len(skipped_pages),
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},
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)
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logger.info(
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f"Confluence indexing completed: {documents_indexed} new pages, {documents_skipped} skipped"
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)
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return (
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total_processed,
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None,
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) # Return None as the error message to indicate success
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except SQLAlchemyError as db_error:
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await session.rollback()
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await task_logger.log_task_failure(
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log_entry,
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f"Database error during Confluence indexing for connector {connector_id}",
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str(db_error),
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{"error_type": "SQLAlchemyError"},
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)
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logger.error(f"Database error: {db_error!s}", exc_info=True)
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return 0, f"Database error: {db_error!s}"
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except Exception as e:
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await session.rollback()
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await task_logger.log_task_failure(
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log_entry,
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f"Failed to index Confluence pages for connector {connector_id}",
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str(e),
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{"error_type": type(e).__name__},
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)
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logger.error(f"Failed to index Confluence pages: {e!s}", exc_info=True)
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return 0, f"Failed to index Confluence pages: {e!s}"
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