Source code for camel.models.azure_openai_model
# =========== Copyright 2023 @ 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 @ CAMEL-AI.org. All Rights Reserved. ===========
import os
from typing import Any, Dict, List, Optional, Union
from openai import AzureOpenAI, Stream
from camel.configs import OPENAI_API_PARAMS
from camel.messages import OpenAIMessage
from camel.models.base_model import BaseModelBackend
from camel.types import ChatCompletion, ChatCompletionChunk, ModelType
from camel.utils import BaseTokenCounter, OpenAITokenCounter, api_keys_required
[docs]
class AzureOpenAIModel(BaseModelBackend):
r"""Azure OpenAI API in a unified BaseModelBackend interface.
Doc: https://learn.microsoft.com/en-us/azure/ai-services/openai/
"""
def __init__(
self,
model_type: ModelType,
model_config_dict: Dict[str, Any],
api_key: Optional[str] = None,
url: Optional[str] = None,
api_version: Optional[str] = None,
azure_deployment_name: Optional[str] = None,
) -> None:
r"""Constructor for OpenAI backend.
Args:
model_type (ModelType): Model for which a backend is created,
one of GPT_* series.
model_config_dict (Dict[str, Any]): A dictionary that will
be fed into openai.ChatCompletion.create().
api_key (Optional[str]): The API key for authenticating with the
OpenAI service. (default: :obj:`None`)
url (Optional[str]): The url to the OpenAI service. (default:
:obj:`None`)
api_version (Optional[str]): The api version for the model.
azure_deployment_name (Optional[str]): The deployment name you
chose when you deployed an azure model. (default: :obj:`None`)
"""
super().__init__(model_type, model_config_dict, api_key, url)
self._url = url or os.environ.get("AZURE_OPENAI_ENDPOINT")
self._api_key = api_key or os.environ.get("AZURE_OPENAI_API_KEY")
self.api_version = api_version or os.environ.get("AZURE_API_VERSION")
self.azure_deployment_name = azure_deployment_name or os.environ.get(
"AZURE_DEPLOYMENT_NAME"
)
if self._url is None:
raise ValueError(
"Must provide either the `url` argument "
"or `AZURE_OPENAI_ENDPOINT` environment variable."
)
if self._api_key is None:
raise ValueError(
"Must provide either the `api_key` argument "
"or `AZURE_OPENAI_API_KEY` environment variable."
)
if self.api_version is None:
raise ValueError(
"Must provide either the `api_version` argument "
"or `AZURE_API_VERSION` environment variable."
)
if self.azure_deployment_name is None:
raise ValueError(
"Must provide either the `azure_deployment_name` argument "
"or `AZURE_DEPLOYMENT_NAME` environment variable."
)
self.model = str(self.azure_deployment_name)
self._client = AzureOpenAI(
azure_endpoint=str(self._url),
azure_deployment=self.azure_deployment_name,
api_version=self.api_version,
api_key=self._api_key,
timeout=60,
max_retries=3,
)
self._token_counter: Optional[BaseTokenCounter] = None
@property
def token_counter(self) -> BaseTokenCounter:
r"""Initialize the token counter for the model backend.
Returns:
BaseTokenCounter: The token counter following the model's
tokenization style.
"""
if not self._token_counter:
self._token_counter = OpenAITokenCounter(self.model_type)
return self._token_counter
[docs]
@api_keys_required("AZURE_OPENAI_API_KEY", "AZURE_API_VERSION")
def run(
self,
messages: List[OpenAIMessage],
) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]:
r"""Runs inference of Azure OpenAI chat completion.
Args:
messages (List[OpenAIMessage]): Message list with the chat history
in OpenAI API format.
Returns:
Union[ChatCompletion, Stream[ChatCompletionChunk]]:
`ChatCompletion` in the non-stream mode, or
`Stream[ChatCompletionChunk]` in the stream mode.
"""
response = self._client.chat.completions.create(
messages=messages,
model=self.model,
**self.model_config_dict,
)
return response
[docs]
def check_model_config(self):
r"""Check whether the model configuration contains any
unexpected arguments to Azure OpenAI API.
Raises:
ValueError: If the model configuration dictionary contains any
unexpected arguments to Azure OpenAI API.
"""
for param in self.model_config_dict:
if param not in OPENAI_API_PARAMS:
raise ValueError(
f"Unexpected argument `{param}` is "
"input into Azure OpenAI model backend."
)
@property
def stream(self) -> bool:
r"""Returns whether the model is in stream mode,
which sends partial results each time.
Returns:
bool: Whether the model is in stream mode.
"""
return self.model_config_dict.get("stream", False)