Total Vectors limited to 100?

I’m trying to upsert 100 vectors at a time with 1536 dimensions. However, if I check the total number of vectors after the job is finished, it always says 100 vectors in total even though it just upserted a lot more vectors than that.

I basically use the following code to do this.

df = pd.read_csv("embeddings.csv")

def chunker(seq, size):
 'Yields a series of slices of the original iterable, up to the limit of what size is.'
 for pos in range(0, len(seq), size):
  yield seq.iloc[pos:pos + size]

def convert_data(chunk):
  data = []
  for key, value in enumerate(chunk.to_dict('records')):
    data.append((str(key["id"]), ast.literal_eval(value["embedding"])))
  return data

if 'bible' not in pinecone.list_indexes():
  pinecone.create_index('key', 1536)

index = pinecone.Index('key')

for chunk in chunker(df,100):

hi @KCC,

Can you share the sample embeddings you’re working with? It’ll make it easier to see where the problem might be.

Did this get resolved? I can only upsert 99 vectors - 100th one fails with an “error calling upsert”. I tried batches of 20 - and the 5th batch fails, batches of 90 and second batch fails too. Is this something to do with the starter plan?