chore: 添加虚拟环境到仓库
- 添加 backend_service/venv 虚拟环境 - 包含所有Python依赖包 - 注意：虚拟环境约393MB，包含12655个文件
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# Copyright (c) Alibaba, Inc. and its affiliates.
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"""
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@File : application.py
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@Date : 2024-02-24
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@Desc : Application calls for both http and http sse
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"""
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import copy
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from typing import Generator, List, Union
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from dashscope.api_entities.api_request_factory import _build_api_request
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from dashscope.api_entities.dashscope_response import Message, Role
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from dashscope.app.application_response import ApplicationResponse
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from dashscope.client.base_api import BaseApi
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from dashscope.common.api_key import get_default_api_key
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from dashscope.common.constants import (DEPRECATED_MESSAGE, HISTORY, MESSAGES,
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PROMPT)
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from dashscope.common.error import InputRequired, InvalidInput
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from dashscope.common.logging import logger
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class Application(BaseApi):
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task_group = 'apps'
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function = 'completion'
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"""API for app completion calls.
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"""
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class DocReferenceType:
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""" doc reference type for rag completion """
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simple = 'simple'
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indexed = 'indexed'
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@classmethod
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def _validate_params(cls, api_key, app_id):
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if api_key is None:
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api_key = get_default_api_key()
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if app_id is None or not app_id:
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raise InputRequired('App id is required!')
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return api_key, app_id
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@classmethod
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def call(
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cls,
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app_id: str,
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prompt: str = None,
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history: list = None,
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workspace: str = None,
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api_key: str = None,
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messages: List[Message] = None,
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**kwargs
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) -> Union[ApplicationResponse, Generator[ApplicationResponse, None,
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None]]:
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"""Call app completion service.
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Args:
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app_id (str): Id of bailian application
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prompt (str): The input prompt.
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history (list):The user provided history
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examples:
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[{'user':'The weather is fine today.',
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'bot': 'Suitable for outings'}].
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Defaults to None.
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workspace(str, `optional`): Workspace for app completion call
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api_key (str, optional): The api api_key, can be None,
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if None, will get by default rule(TODO: api key doc).
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messages(list): The generation messages.
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**kwargs:
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stream(bool, `optional`): Enable server-sent events
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(ref: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events) # noqa E501
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the result will back partially[qwen-turbo,bailian-v1].
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temperature(float, `optional`): Used to control the degree
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of randomness and diversity. Specifically, the temperature
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value controls the degree to which the probability distribution
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of each candidate word is smoothed when generating text.
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A higher temperature value will reduce the peak value of
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the probability, allowing more low-probability words to be
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selected, and the generated results will be more diverse;
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while a lower temperature value will enhance the peak value
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of the probability, making it easier for high-probability
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words to be selected, the generated results are more
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deterministic, range(0, 2) .[qwen-turbo,qwen-plus].
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top_p(float, `optional`): A sampling strategy, called nucleus
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sampling, where the model considers the results of the
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tokens with top_p probability mass. So 0.1 means only
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the tokens comprising the top 10% probability mass are
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considered[qwen-turbo,bailian-v1].
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top_k(int, `optional`): The size of the sample candidate set when generated. # noqa E501
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For example, when the value is 50, only the 50 highest-scoring tokens # noqa E501
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in a single generation form a randomly sampled candidate set. # noqa E501
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The larger the value, the higher the randomness generated; # noqa E501
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the smaller the value, the higher the certainty generated. # noqa E501
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The default value is 0, which means the top_k policy is # noqa E501
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not enabled. At this time, only the top_p policy takes effect. # noqa E501
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seed(int, `optional`): When generating, the seed of the random number is used to control the
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randomness of the model generation. If you use the same seed, each run will generate the same results;
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you can use the same seed when you need to reproduce the model's generated results.
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The seed parameter supports unsigned 64-bit integer types. Default value 1234
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session_id(str, `optional`): Session if for multiple rounds call.
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biz_params(dict, `optional`): The extra parameters for flow or plugin.
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has_thoughts(bool, `optional`): Flag to return rag or plugin process details. Default value false.
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doc_tag_codes(list[str], `optional`): Tag code list for doc retrival.
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doc_reference_type(str, `optional`): The type of doc reference.
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simple: simple format of doc retrival which not include index in response text but in doc reference list.
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indexed: include both index in response text and doc reference list
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memory_id(str, `optional`): Used to store long term context summary between end users and assistant.
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image_list(list, `optional`): Used to pass image url list.
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rag_options(dict, `optional`): Rag options for retrieval augmented generation options.
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Raises:
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InvalidInput: The history and auto_history are mutually exclusive.
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Returns:
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Union[CompletionResponse,
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Generator[CompletionResponse, None, None]]: If
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stream is True, return Generator, otherwise GenerationResponse.
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"""
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api_key, app_id = Application._validate_params(api_key, app_id)
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if (prompt is None or not prompt) and (messages is None
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or len(messages) == 0):
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raise InputRequired('prompt or messages is required!')
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if workspace is not None and workspace:
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headers = kwargs.pop('headers', {})
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headers['X-DashScope-WorkSpace'] = workspace
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kwargs['headers'] = headers
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input, parameters = cls._build_input_parameters(
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prompt, history, messages, **kwargs)
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request = _build_api_request(model='',
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input=input,
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task_group=Application.task_group,
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task=app_id,
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function=Application.function,
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workspace=workspace,
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api_key=api_key,
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is_service=False,
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**parameters)
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# call request service.
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response = request.call()
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is_stream = kwargs.get('stream', False)
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if is_stream:
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return (ApplicationResponse.from_api_response(rsp)
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for rsp in response)
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else:
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return ApplicationResponse.from_api_response(response)
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@classmethod
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def _build_input_parameters(cls, prompt, history, messages, **kwargs):
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parameters = {}
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input_param = {}
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if messages is not None:
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msgs = copy.deepcopy(messages)
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if prompt is not None and prompt:
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msgs.append({'role': Role.USER, 'content': prompt})
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input_param = {MESSAGES: msgs}
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elif history is not None and history:
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logger.warning(DEPRECATED_MESSAGE)
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input_param[HISTORY] = history
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if prompt is not None and prompt:
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input_param[PROMPT] = prompt
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else:
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input_param[PROMPT] = prompt
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session_id = kwargs.pop('session_id', None)
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if session_id is not None and session_id:
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input_param['session_id'] = session_id
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doc_reference_type = kwargs.pop('doc_reference_type', None)
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if doc_reference_type is not None and doc_reference_type:
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input_param['doc_reference_type'] = doc_reference_type
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doc_tag_codes = kwargs.pop('doc_tag_codes', None)
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if doc_tag_codes is not None:
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if isinstance(doc_tag_codes, list) and all(
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isinstance(item, str) for item in doc_tag_codes):
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input_param['doc_tag_codes'] = doc_tag_codes
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else:
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raise InvalidInput('doc_tag_codes is not a List[str]')
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memory_id = kwargs.pop('memory_id', None)
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if memory_id is not None:
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input_param['memory_id'] = memory_id
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biz_params = kwargs.pop('biz_params', None)
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if biz_params is not None and biz_params:
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input_param['biz_params'] = biz_params
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image_list = kwargs.pop('image_list', None)
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if image_list is not None and image_list:
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input_param['image_list'] = image_list
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file_list = kwargs.pop('file_list', None)
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if file_list is not None and file_list:
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input_param['file_list'] = file_list
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return input_param, {**parameters, **kwargs}
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