Hi im facing the followin issue:
problem.py (github.com)
So summariuzed: it says me that the metadata are too big but i they just contain one single “source” flied witha web (.html) url in it
Could it come because the page_content + metadata maybe is too big?
What are the approaches to solve such a ploblem if I cant load my split data inside the vs?
Hi @derbenedikt.sterra, thanks for your question, and thank you so very much for sharing/linking to your code, which makes it much easier for us to help!
Here are some thoughts after reviewing the program you shared:
- Metadata size: The error suggests that the metadata is still too large, even after your attempts to reduce it. This could be because: a) The
page_content might be getting included in the metadata inadvertently. b) There might be other fields in the metadata that you’re not accounting for.
- Check total size: Your logs show that you’re calculating the size of metadata and page_content separately. However, our limit applies to the combination of both. Make sure you’re checking the total size.
- Trimming approach: Your current approach tries to trim metadata fields, but it might not be effective enough. Consider a more aggressive trimming strategy.
Here are some things you might try next:
- Separate content and metadata: Ensure that
page_content is not being included in the metadata. Double-check your Document creation process.
- Trim page_content: If the combined size of metadata and page_content is too large, you might need to trim the page_content as well. You can do this by truncating it to a maximum length.
- More aggressive metadata trimming: Instead of just emptying the ‘text’ field, consider removing all fields except ‘source’, or limiting each field to a maximum length.
- Use a smaller chunk size: Reduce your
chunk_size in the RecursiveCharacterTextSplitter to create smaller documents.
- Implement a size check before insertion: Before trying to insert a document into Pinecone, check its total size and skip or further trim documents that are too large.
Here’s some sample code implementing the above approaches you could try out / use for inspiration:
async def short_string_simple(self, split_docs: List[Document]):
"""Shortens page_content and metadata within each Document if it exceeds max_bytes."""
print("SHORT DOCs...")
max_total_bytes = 40000 # Pinecone's limit
max_metadata_bytes = 5000 # Reserve some space for metadata
try:
for doc in split_docs:
# Convert metadata to a simple dict with only 'source'
doc.metadata = {'source': doc.metadata.get('source', '')}
metadata_bytes = len(json.dumps(doc.metadata).encode('utf-8'))
content_bytes = len(doc.page_content.encode('utf-8'))
total_bytes = metadata_bytes + content_bytes
print(f"Initial sizes - Metadata: {metadata_bytes}, Content: {content_bytes}, Total: {total_bytes}")
if total_bytes > max_total_bytes:
# Trim metadata if necessary
if metadata_bytes > max_metadata_bytes:
doc.metadata['source'] = doc.metadata['source'][:max_metadata_bytes]
metadata_bytes = len(json.dumps(doc.metadata).encode('utf-8'))
# Calculate how much we can allow for content
max_content_bytes = max_total_bytes - metadata_bytes
# Trim content if necessary
if content_bytes > max_content_bytes:
doc.page_content = doc.page_content.encode('utf-8')[:max_content_bytes].decode('utf-8', 'ignore')
content_bytes = len(doc.page_content.encode('utf-8'))
total_bytes = metadata_bytes + content_bytes
print(f"Final sizes - Metadata: {metadata_bytes}, Content: {content_bytes}, Total: {total_bytes}")
if total_bytes > max_total_bytes:
print(f"Warning: Document still exceeds maximum size after trimming.")
except Exception as e:
print(f"ERROR WHILE SHORTING STRING SIMPLE: {e}")
return None
You would then use this function before creating your vectorstore:
await self.short_string_simple(split_docs)
Finally, when you do create your vectorstore, you may want to add another check to ensure you’re not trying to upsert a payload that exceeds the size limit:
valid_docs = []
for doc in split_docs:
total_size = len(json.dumps(doc.metadata).encode('utf-8')) + len(doc.page_content.encode('utf-8'))
if total_size <= 40000:
valid_docs.append(doc)
else:
print(f"Skipping document: total size {total_size} exceeds limit")
vs = await PineconeVectorStore.afrom_documents(
documents=valid_docs,
index_name=index.name,
embedding=embeddings,
namespace=namespace
)