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reduce rerank batch size (#2801)

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### What problem does this PR solve?

### Type of change


- [x] Performance Improvement
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Kevin Hu 2024-10-11 11:29:19 +08:00 committed by GitHub
parent bae30e5cc4
commit 5e7c1fb23a
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2 changed files with 2 additions and 2 deletions
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2
api/db/init_data.py
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@ -132,7 +132,7 @@ def init_llm_factory():
TenantService.filter_update([1 == 1], {
"parser_ids": "naive:General,qa:Q&A,resume:Resume,manual:Manual,table:Table,paper:Paper,book:Book,laws:Laws,presentation:Presentation,picture:Picture,one:One,audio:Audio,knowledge_graph:Knowledge Graph,email:Email"})
## insert openai two embedding models to the current openai user.
print("Start to insert 2 OpenAI embedding models...")
# print("Start to insert 2 OpenAI embedding models...")
tenant_ids = set([row["tenant_id"] for row in TenantLLMService.get_openai_models()])
for tid in tenant_ids:
for row in TenantLLMService.query(llm_factory="OpenAI", tenant_id=tid):

2
rag/llm/rerank_model.py
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@ -142,7 +142,7 @@ class YoudaoRerank(DefaultRerank):
token_count = 0
for _, t in pairs:
token_count += num_tokens_from_string(t)
batch_size = 32
batch_size = 8
res = []
for i in range(0, len(pairs), batch_size):
scores = self._model.compute_score(pairs[i:i + batch_size], max_length=self._model.max_length)