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fix: generate content hash based on search space id as well.

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- Allows Reindexing in selperate seatch spaces.
This commit is contained in:
DESKTOP-RTLN3BA\$punk 2025-06-10 13:56:23 -07:00
parent fa54de1f41
commit d8f2c5f7cf
3 changed files with 15 additions and 14 deletions
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10
surfsense_backend/app/tasks/connectors_indexing_tasks.py
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@ -200,7 +200,7 @@ async def index_slack_messages(
document_parts.append("</DOCUMENT>")
combined_document_string = '\n'.join(document_parts)
content_hash = generate_content_hash(combined_document_string)
content_hash = generate_content_hash(combined_document_string, search_space_id)
# Check if document with this content hash already exists
existing_doc_by_hash_result = await session.execute(
@ -474,7 +474,7 @@ async def index_notion_pages(
document_parts.append("</DOCUMENT>")
combined_document_string = '\n'.join(document_parts)
content_hash = generate_content_hash(combined_document_string)
content_hash = generate_content_hash(combined_document_string, search_space_id)
# Check if document with this content hash already exists
existing_doc_by_hash_result = await session.execute(
@ -658,7 +658,7 @@ async def index_github_repos(
logger.warning(f"Could not retrieve content for {full_path_key}. Skipping.")
continue # Skip if content fetch failed
content_hash = generate_content_hash(file_content)
content_hash = generate_content_hash(file_content, search_space_id)
# Check if document with this content hash already exists
existing_doc_by_hash_result = await session.execute(
@ -897,7 +897,7 @@ async def index_linear_issues(
comment_count = len(formatted_issue.get("comments", []))
summary_content += f"Comments: {comment_count}"
content_hash = generate_content_hash(issue_content)
content_hash = generate_content_hash(issue_content, search_space_id)
# Check if document with this content hash already exists
existing_doc_by_hash_result = await session.execute(
@ -1151,7 +1151,7 @@ async def index_discord_messages(
document_parts.append(f"</{section_title}>")
document_parts.append("</DOCUMENT>")
combined_document_string = '\n'.join(document_parts)
content_hash = generate_content_hash(combined_document_string)
content_hash = generate_content_hash(combined_document_string, search_space_id)
# Check if document with this content hash already exists
existing_doc_by_hash_result = await session.execute(