Hi guys, i'm running into an issue in production, i can't tell if this because my chunks are too big when trying to get embeddings or if my batch size is too big in qdrant client. (right now the batch size is 16). If the chunks are too big shouldn't that be handled by the NodeParser, I'm currently using SemanticSplitterNodeParser?
"2024-07-17 14:03:22,630 - ERROR - 13 - ThreadPoolExecutor-0_0 - root - index_asset - index_asset.py:39 - index_asset() >>> Error indexing asset into Qdrant: Error code: 400 - {'error': {'message': "This model's maximum context length is 8192 tokens, however you requested 10125 tokens (10125 in your prompt; 0 for the completion). Please reduce your prompt; or completion length.", 'type': 'invalid_request_error', 'param': None, 'code': None}}"
