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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.model_entities import PriceType
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from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult, EmbeddingUsage
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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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raise ValueError('Invalid model name')
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if not api_key:
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if not api_key:
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raise CredentialsValidateFailedError('api_key is required')
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raise CredentialsValidateFailedError('api_key is required')
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+
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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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+
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+ embeddings = []
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+ token_usage = 0
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+
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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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+
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+ embeddings.extend(chunk_embeddings)
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+ token_usage += chunk_usage
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+
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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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+
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+ return result
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+
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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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+
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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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url = self.api_base
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headers = {
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headers = {
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'Authorization': 'Bearer ' + api_key,
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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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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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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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-
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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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def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
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"""
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"""
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