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Fixed all ruff lint and formatting errors

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Utkarsh-Patel-13 2025-07-24 14:43:48 -07:00
parent 0a03c42cc5
commit d359a59f6d
85 changed files with 5520 additions and 3870 deletions
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28
surfsense_backend/app/utils/document_converters.py
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@ -32,7 +32,7 @@ async def convert_element_to_markdown(element) -> str:
"Footer": lambda x: f"*{x}*\n\n",
"CodeSnippet": lambda x: f"```\n{x}\n```",
"PageNumber": lambda x: f"*Page {x}*\n\n",
"UncategorizedText": lambda x: f"{x}\n\n"
"UncategorizedText": lambda x: f"{x}\n\n",
}
converter = markdown_mapping.get(element_category, lambda x: x)
@ -74,7 +74,7 @@ def convert_chunks_to_langchain_documents(chunks):
except ImportError:
raise ImportError(
"LangChain is not installed. Please install it with `pip install langchain langchain-core`"
)
) from None
langchain_docs = []
@ -92,17 +92,20 @@ def convert_chunks_to_langchain_documents(chunks):
# Add document information to metadata
if "document" in chunk:
doc = chunk["document"]
metadata.update({
"document_id": doc.get("id"),
"document_title": doc.get("title"),
"document_type": doc.get("document_type"),
})
metadata.update(
{
"document_id": doc.get("id"),
"document_title": doc.get("title"),
"document_type": doc.get("document_type"),
}
)
# Add document metadata if available
if "metadata" in doc:
# Prefix document metadata keys to avoid conflicts
doc_metadata = {f"doc_meta_{k}": v for k,
v in doc.get("metadata", {}).items()}
doc_metadata = {
f"doc_meta_{k}": v for k, v in doc.get("metadata", {}).items()
}
metadata.update(doc_metadata)
# Add source URL if available in metadata
@ -131,10 +134,7 @@ def convert_chunks_to_langchain_documents(chunks):
"""
# Create LangChain Document
langchain_doc = LangChainDocument(
page_content=new_content,
metadata=metadata
)
langchain_doc = LangChainDocument(page_content=new_content, metadata=metadata)
langchain_docs.append(langchain_doc)
@ -144,4 +144,4 @@ def convert_chunks_to_langchain_documents(chunks):
def generate_content_hash(content: str, search_space_id: int) -> str:
"""Generate SHA-256 hash for the given content combined with search space ID."""
combined_data = f"{search_space_id}:{content}"
return hashlib.sha256(combined_data.encode('utf-8')).hexdigest()
return hashlib.sha256(combined_data.encode("utf-8")).hexdigest()