mirror of
https://github.com/camel-ai/owl.git
synced 2026-03-22 05:57:17 +08:00
120 lines
4.1 KiB
Python
120 lines
4.1 KiB
Python
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
|
|
|
|
|
|
from __future__ import annotations
|
|
|
|
import os
|
|
from typing import Any, Union
|
|
|
|
from openai import AzureOpenAI
|
|
|
|
from camel.embeddings.base import BaseEmbedding
|
|
from camel.types import EmbeddingModelType
|
|
from camel.utils import api_keys_required # Add this import
|
|
|
|
|
|
class AzureEmbedding(BaseEmbedding[str]):
|
|
r"""Provides text embedding functionalities using Azure's OpenAI models.
|
|
|
|
Args:
|
|
model_type (EmbeddingModelType, optional): The model type to be
|
|
used for text embeddings.
|
|
(default: :obj:`TEXT_EMBEDDING_3_SMALL`)
|
|
url (Optional[str], optional): The url to the Azure OpenAI service.
|
|
(default: :obj:`None`)
|
|
api_key (str, optional): The API key for authenticating with the
|
|
Azure OpenAI service. (default: :obj:`None`)
|
|
api_version (str, optional): The API version for Azure OpenAI service.
|
|
(default: :obj:`None`)
|
|
dimensions (Optional[int], optional): The text embedding output
|
|
dimensions. (default: :obj:`None`)
|
|
|
|
Raises:
|
|
RuntimeError: If an unsupported model type is specified.
|
|
ValueError: If required API configuration is missing.
|
|
"""
|
|
|
|
@api_keys_required(
|
|
[
|
|
("api_key", 'AZURE_OPENAI_API_KEY'),
|
|
("url", 'AZURE_OPENAI_BASE_URL'),
|
|
]
|
|
)
|
|
def __init__(
|
|
self,
|
|
model_type: EmbeddingModelType = (
|
|
EmbeddingModelType.TEXT_EMBEDDING_3_SMALL
|
|
),
|
|
url: Union[str, None] = None,
|
|
api_key: Union[str, None] = None,
|
|
api_version: Union[str, None] = None,
|
|
dimensions: Union[int, None] = None,
|
|
) -> None:
|
|
self.model_type = model_type
|
|
self.api_version = api_version or os.environ.get("AZURE_API_VERSION")
|
|
if dimensions is None:
|
|
self.output_dim = model_type.output_dim
|
|
else:
|
|
if not isinstance(dimensions, int):
|
|
raise ValueError("dimensions must be an integer")
|
|
self.output_dim = dimensions
|
|
|
|
self._api_key = api_key or os.environ.get("AZURE_OPENAI_API_KEY")
|
|
self._url = url or os.environ.get("AZURE_OPENAI_BASE_URL")
|
|
|
|
self.client = AzureOpenAI(
|
|
api_key=self._api_key,
|
|
api_version=self.api_version,
|
|
azure_endpoint=str(self._url),
|
|
)
|
|
|
|
def embed_list(
|
|
self,
|
|
objs: list[str],
|
|
**kwargs: Any,
|
|
) -> list[list[float]]:
|
|
r"""Embeds a list of texts using the Azure OpenAI model.
|
|
|
|
Args:
|
|
objs (list[str]): The list of texts to embed.
|
|
**kwargs (Any): Additional keyword arguments to pass to the API.
|
|
|
|
Returns:
|
|
list[list[float]]: The embeddings for the input texts.
|
|
"""
|
|
if self.model_type == EmbeddingModelType.TEXT_EMBEDDING_ADA_2:
|
|
response = self.client.embeddings.create(
|
|
input=objs,
|
|
model=self.model_type.value,
|
|
**kwargs,
|
|
)
|
|
return [data.embedding for data in response.data]
|
|
|
|
response = self.client.embeddings.create(
|
|
input=objs,
|
|
model=self.model_type.value,
|
|
dimensions=self.output_dim,
|
|
**kwargs,
|
|
)
|
|
return [data.embedding for data in response.data]
|
|
|
|
def get_output_dim(self) -> int:
|
|
r"""Returns the output dimension of the embeddings.
|
|
|
|
Returns:
|
|
int: The dimensionality of the embedding for the current model.
|
|
"""
|
|
return self.output_dim
|