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'}}
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？