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@ -54,7 +54,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
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_iter = range(0, len(tokens), max_chunks)
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for i in _iter:
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embeddings, embedding_used_tokens = self._embedding_invoke(
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embeddings_batch, embedding_used_tokens = self._embedding_invoke(
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model=model,
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client=client,
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texts=tokens[i: i + max_chunks],
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@ -62,7 +62,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
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)
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used_tokens += embedding_used_tokens
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batched_embeddings += [data for data in embeddings]
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batched_embeddings += embeddings_batch
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results: list[list[list[float]]] = [[] for _ in range(len(texts))]
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num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))]
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@ -73,7 +73,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
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for i in range(len(texts)):
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_result = results[i]
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if len(_result) == 0:
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embeddings, embedding_used_tokens = self._embedding_invoke(
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embeddings_batch, embedding_used_tokens = self._embedding_invoke(
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model=model,
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client=client,
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texts=[""],
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@ -81,7 +81,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
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)
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used_tokens += embedding_used_tokens
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average = embeddings[0]
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average = embeddings_batch[0]
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else:
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average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
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embeddings[i] = (average / np.linalg.norm(average)).tolist()
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