@ -375,36 +375,35 @@ class Search:
llm_predictor_mock = MockLLMPredictor ( 4096 )
embed_model_mock = MockEmbedding ( embed_dim = 1536 )
# if ctx:
# await self.try_edit(
# in_progress_message, self.build_search_determining_price_embed(query_refined_text)
# )
#
# await self.loop.run_in_executor(
# None,
# partial(
# GPTKnowledgeGraphIndex,
# documents,
# chunk_size_limit=512,
# max_triplets_per_chunk=2,
# embed_model=embed_model_mock,
# llm_predictor=llm_predictor_mock,
# ),
# )
# total_usage_price = await self.usage_service.get_price(
# llm_predictor_mock.last_token_usage, chatgpt=True,
# ) + await self.usage_service.get_price(
# embed_model_mock.last_token_usage, embeddings=True
# )
# print(f"Total usage price: {total_usage_price}")
# if total_usage_price > MAX_SEARCH_PRICE:
# await self.try_delete(in_progress_message)
# raise ValueError(
# "Doing this deep search would be prohibitively expensive. Please try a narrower search scope. This deep search indexing would have cost ${:.2f}.".format(
# total_usage_price
# )
# )
# # TODO Add back the mock when fixed!
if ctx :
await self . try_edit (
in_progress_message , self . build_search_determining_price_embed ( query_refined_text )
)
await self . loop . run_in_executor (
None ,
partial (
GPTKnowledgeGraphIndex ,
documents ,
chunk_size_limit = 512 ,
max_triplets_per_chunk = 2 ,
embed_model = embed_model_mock ,
llm_predictor = llm_predictor_mock ,
) ,
)
total_usage_price = await self . usage_service . get_price (
llm_predictor_mock . last_token_usage , chatgpt = True ,
) + await self . usage_service . get_price (
embed_model_mock . last_token_usage , embeddings = True
)
print ( f " Total usage price: { total_usage_price } " )
if total_usage_price > MAX_SEARCH_PRICE :
await self . try_delete ( in_progress_message )
raise ValueError (
" Doing this deep search would be prohibitively expensive. Please try a narrower search scope. This deep search indexing would have cost $ {:.2f} . " . format (
total_usage_price
)
)
index = await self . loop . run_in_executor (
None ,