nlmatics/llmsherpa

InternalServerError: Error code: 503

Fly-betterme opened this issue · 0 comments

from llama_index.readers.schema.base import Document
from llama_index import VectorStoreIndex

index = VectorStoreIndex([])
for chunk in doc.chunks():
index.insert(Document(text=chunk.to_context_text(), extra_info={}))
query_engine = index.as_query_engine()

InternalServerError Traceback (most recent call last)
Input In [17], in <cell line: 5>()
4 index = VectorStoreIndex([])
5 for chunk in doc.chunks():
----> 6 index.insert(Document(text=chunk.to_context_text(), extra_info={'embed_model':'text-embedding-V2'}))
7 query_engine = index.as_query_engine()

InternalServerError: Error code: 503 - {'error': {'message': 'There are no available channels for model text embedding ada-002 under the current group VIP (request id: 20240108173434543639222FMD9UnZh)', 'type': 'new_api_error'}}

question:How to define parameter change models?