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fix: baichuan max chunks (#1990)
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@ -1,4 +1,4 @@
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from typing import Optional
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from typing import Optional, Tuple
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from core.model_runtime.entities.model_entities import PriceType
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from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult, EmbeddingUsage
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@ -38,6 +38,50 @@ class BaichuanTextEmbeddingModel(TextEmbeddingModel):
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raise ValueError('Invalid model name')
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if not api_key:
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raise CredentialsValidateFailedError('api_key is required')
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# split into chunks of batch size 16
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chunks = []
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for i in range(0, len(texts), 16):
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chunks.append(texts[i:i + 16])
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embeddings = []
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token_usage = 0
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for chunk in chunks:
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# embeding chunk
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chunk_embeddings, chunk_usage = self.embedding(
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model=model,
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api_key=api_key,
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texts=chunk,
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user=user
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)
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embeddings.extend(chunk_embeddings)
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token_usage += chunk_usage
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result = TextEmbeddingResult(
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model=model,
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embeddings=embeddings,
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usage=self._calc_response_usage(
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model=model,
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credentials=credentials,
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tokens=token_usage
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)
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)
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return result
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def embedding(self, model: str, api_key, texts: list[str], user: Optional[str] = None) \
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-> Tuple[list[list[float]], int]:
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"""
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Embed given texts
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:param model: model name
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:param credentials: model credentials
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:param texts: texts to embed
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:param user: unique user id
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:return: embeddings result
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"""
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url = self.api_base
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headers = {
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'Authorization': 'Bearer ' + api_key,
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@ -85,17 +129,10 @@ class BaichuanTextEmbeddingModel(TextEmbeddingModel):
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except Exception as e:
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raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}")
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usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage['total_tokens'])
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return [
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data['embedding'] for data in embeddings
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], usage['total_tokens']
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result = TextEmbeddingResult(
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model=model,
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embeddings=[[
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float(data) for data in x['embedding']
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] for x in embeddings],
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usage=usage
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)
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return result
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def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
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"""
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@ -59,3 +59,40 @@ def test_get_num_tokens():
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)
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assert num_tokens == 2
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def test_max_chunks():
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model = BaichuanTextEmbeddingModel()
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result = model.invoke(
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model='baichuan-text-embedding',
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credentials={
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'api_key': os.environ.get('BAICHUAN_API_KEY'),
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},
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texts=[
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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"hello",
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"world",
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]
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)
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assert isinstance(result, TextEmbeddingResult)
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assert len(result.embeddings) == 22
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