# ========= 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. =========
import os
from typing import Any, Dict, List, Optional, Type, Union
from openai import AsyncStream
from pydantic import BaseModel
from camel.configs import BEDROCK_API_PARAMS, BedrockConfig
from camel.messages import OpenAIMessage
from camel.models.openai_compatible_model import OpenAICompatibleModel
from camel.types import (
ChatCompletion,
ChatCompletionChunk,
ModelType,
)
from camel.utils import BaseTokenCounter, api_keys_required
[docs]
class AWSBedrockModel(OpenAICompatibleModel):
r"""AWS Bedrock API in a unified OpenAICompatibleModel interface.
Args:
model_type (Union[ModelType, str]): Model for which a backend is
created.
model_config_dict (Dict[str, Any], optional): A dictionary
that will be fed into:obj:`openai.ChatCompletion.create()`.
If:obj:`None`, :obj:`BedrockConfig().as_dict()` will be used.
(default: :obj:`None`)
api_key (str, optional): The API key for authenticating with
the AWS Bedrock service. (default: :obj:`None`)
url (str, optional): The url to the AWS Bedrock service.
token_counter (BaseTokenCounter, optional): Token counter to
use for the model. If not provided, :obj:`OpenAITokenCounter(
ModelType.GPT_4O_MINI)` will be used.
(default: :obj:`None`)
timeout (Optional[float], optional): The timeout value in seconds for
API calls. If not provided, will fall back to the MODEL_TIMEOUT
environment variable or default to 180 seconds.
(default: :obj:`None`)
References:
https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html
"""
@api_keys_required(
[
("url", "BEDROCK_API_BASE_URL"),
("api_key", "BEDROCK_API_KEY"),
]
)
def __init__(
self,
model_type: Union[ModelType, str],
model_config_dict: Optional[Dict[str, Any]] = None,
api_key: Optional[str] = None,
url: Optional[str] = None,
token_counter: Optional[BaseTokenCounter] = None,
timeout: Optional[float] = None,
) -> None:
if model_config_dict is None:
model_config_dict = BedrockConfig().as_dict()
api_key = api_key or os.environ.get("BEDROCK_API_KEY")
url = url or os.environ.get(
"BEDROCK_API_BASE_URL",
)
timeout = timeout or float(os.environ.get("MODEL_TIMEOUT", 180))
super().__init__(
model_type=model_type,
model_config_dict=model_config_dict,
api_key=api_key,
url=url,
token_counter=token_counter,
timeout=timeout,
)
async def _arun(
self,
messages: List[OpenAIMessage],
response_format: Optional[Type[BaseModel]] = None,
tools: Optional[List[Dict[str, Any]]] = None,
) -> Union[ChatCompletion, AsyncStream[ChatCompletionChunk]]:
raise NotImplementedError(
"AWS Bedrock does not support async inference."
)
[docs]
def check_model_config(self):
r"""Check whether the input model configuration contains unexpected
arguments.
Raises:
ValueError: If the model configuration dictionary contains any
unexpected argument for this model class.
"""
for param in self.model_config_dict:
if param not in BEDROCK_API_PARAMS:
raise ValueError(
f"Invalid parameter '{param}' in model_config_dict. "
f"Valid parameters are: {BEDROCK_API_PARAMS}"
)
