Download lib/python3.11/site-packages/dashscope/app/application.py from michaelu0826/phantom_env: direct link, hf CLI and curl.
- Browser
- Download file 10.1 kB
-
https://huggingface.co/datasets/michaelu0826/phantom_env/resolve/main/lib/python3.11/site-packages/dashscope/app/application.py
- Command line
-
hf download hf://datasets/michaelu0826/phantom_env/lib/python3.11/site-packages/dashscope/app/application.py
-
curl -L -o application.py https://huggingface.co/datasets/michaelu0826/phantom_env/resolve/main/lib/python3.11/site-packages/dashscope/app/application.py
10.1 kB
| # -*- coding: utf-8 -*- | |
| # Copyright (c) Alibaba, Inc. and its affiliates. | |
| """ | |
| @File : application.py | |
| @Date : 2024-02-24 | |
| @Desc : Application calls for both http and http sse | |
| """ | |
| import copy | |
| from typing import Generator, List, Union | |
| from dashscope.api_entities.api_request_factory import _build_api_request | |
| from dashscope.api_entities.dashscope_response import Message, Role | |
| from dashscope.app.application_response import ApplicationResponse | |
| from dashscope.client.base_api import BaseApi | |
| from dashscope.common.api_key import get_default_api_key | |
| from dashscope.common.constants import ( | |
| DEPRECATED_MESSAGE, | |
| HISTORY, | |
| MESSAGES, | |
| PROMPT, | |
| ) | |
| from dashscope.common.error import InputRequired, InvalidInput | |
| from dashscope.common.logging import logger | |
| class Application(BaseApi): | |
| task_group = "apps" | |
| function = "completion" | |
| """API for app completion calls. | |
| """ | |
| class DocReferenceType: | |
| """doc reference type for rag completion""" | |
| simple = "simple" | |
| indexed = "indexed" | |
| def _validate_params( # pylint: disable=arguments-renamed | |
| cls, | |
| api_key, | |
| app_id, | |
| ): | |
| if api_key is None: | |
| api_key = get_default_api_key() | |
| if app_id is None or not app_id: | |
| raise InputRequired("App id is required!") | |
| return api_key, app_id | |
| def call( # type: ignore[override] | |
| cls, | |
| app_id: str, | |
| prompt: str = None, | |
| history: list = None, | |
| workspace: str = None, | |
| api_key: str = None, | |
| messages: List[Message] = None, | |
| **kwargs, | |
| ) -> Union[ | |
| ApplicationResponse, | |
| Generator[ | |
| ApplicationResponse, | |
| None, | |
| None, | |
| ], | |
| ]: | |
| """Call app completion service. | |
| Args: | |
| app_id (str): Id of bailian application | |
| prompt (str): The input prompt. | |
| history (list):The user provided history | |
| examples: | |
| [{'user':'The weather is fine today.', | |
| 'bot': 'Suitable for outings'}]. | |
| Defaults to None. | |
| workspace(str, `optional`): Workspace for app completion call | |
| api_key (str, optional): The api api_key, can be None, | |
| if None, will get by default rule(TODO: api key doc). | |
| messages(list): The generation messages. | |
| **kwargs: | |
| stream(bool, `optional`): Enable server-sent events | |
| (ref: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events) # noqa E501 # pylint: disable=line-too-long | |
| the result will back partially[qwen-turbo,bailian-v1]. | |
| temperature(float, `optional`): Used to control the degree | |
| of randomness and diversity. Specifically, the temperature | |
| value controls the degree to which the probability distribution | |
| of each candidate word is smoothed when generating text. | |
| A higher temperature value will reduce the peak value of | |
| the probability, allowing more low-probability words to be | |
| selected, and the generated results will be more diverse; | |
| while a lower temperature value will enhance the peak value | |
| of the probability, making it easier for high-probability | |
| words to be selected, the generated results are more | |
| deterministic, range(0, 2) .[qwen-turbo,qwen-plus]. | |
| top_p(float, `optional`): A sampling strategy, called nucleus | |
| sampling, where the model considers the results of the | |
| tokens with top_p probability mass. So 0.1 means only | |
| the tokens comprising the top 10% probability mass are | |
| considered[qwen-turbo,bailian-v1]. | |
| top_k(int, `optional`): The size of the sample candidate set when generated. # noqa E501 # pylint: disable=line-too-long | |
| For example, when the value is 50, only the 50 highest-scoring tokens # noqa E501 # pylint: disable=line-too-long | |
| in a single generation form a randomly sampled candidate set. # noqa E501 | |
| The larger the value, the higher the randomness generated; # noqa E501 | |
| the smaller the value, the higher the certainty generated. # noqa E501 | |
| The default value is 0, which means the top_k policy is # noqa E501 | |
| not enabled. At this time, only the top_p policy takes effect. # noqa E501 | |
| seed( | |
| int, | |
| `optional` | |
| ): When generating, the seed of the random number is used to control the | |
| randomness of the model generation. If you use the same seed, each run will generate the same results; # pylint: disable=line-too-long | |
| you can use the same seed when you need to reproduce the model's generated results. # pylint: disable=line-too-long | |
| The seed parameter supports unsigned 64-bit integer types. Default value 1234 | |
| session_id(str, `optional`): Session if for multiple rounds call. | |
| biz_params(dict, `optional`): The extra parameters for flow or plugin. | |
| has_thoughts(bool, `optional`): Flag to return rag or plugin process details. Default value false. # pylint: disable=line-too-long | |
| doc_tag_codes(list[str], `optional`): Tag code list for doc retrival. | |
| doc_reference_type(str, `optional`): The type of doc reference. | |
| simple: simple format of doc retrival which not include index in response text but in doc reference list. # pylint: disable=line-too-long | |
| indexed: include both index in response text and doc reference list | |
| memory_id(str, `optional`): Used to store long term context summary between end users and assistant. # pylint: disable=line-too-long | |
| image_list(list, `optional`): Used to pass image url list. | |
| rag_options(dict, `optional`): Rag options for retrieval augmented generation options. # pylint: disable=line-too-long | |
| Raises: | |
| InvalidInput: The history and auto_history are mutually exclusive. | |
| Returns: | |
| Union[CompletionResponse, | |
| Generator[CompletionResponse, None, None]]: If | |
| stream is True, return Generator, otherwise GenerationResponse. | |
| """ | |
| api_key, app_id = Application._validate_params(api_key, app_id) | |
| if (prompt is None or not prompt) and ( | |
| messages is None or len(messages) == 0 | |
| ): | |
| raise InputRequired("prompt or messages is required!") | |
| if workspace is not None and workspace: | |
| headers = kwargs.pop("headers", {}) | |
| headers["X-DashScope-WorkSpace"] = workspace | |
| kwargs["headers"] = headers | |
| ( | |
| input, # pylint: disable=redefined-builtin | |
| parameters, | |
| ) = cls._build_input_parameters( | |
| prompt, | |
| history, | |
| messages, | |
| **kwargs, | |
| ) | |
| request = _build_api_request( | |
| model="", | |
| input=input, | |
| task_group=Application.task_group, | |
| task=app_id, | |
| function=Application.function, | |
| workspace=workspace, | |
| api_key=api_key, | |
| is_service=False, | |
| **parameters, | |
| ) | |
| # call request service. | |
| response = request.call() | |
| is_stream = kwargs.get("stream", False) | |
| if is_stream: | |
| return ( | |
| ApplicationResponse.from_api_response(rsp) for rsp in response | |
| ) | |
| else: | |
| return ApplicationResponse.from_api_response(response) | |
| def _build_input_parameters( # pylint: disable=too-many-branches | |
| cls, | |
| prompt, | |
| history, | |
| messages, | |
| **kwargs, | |
| ): | |
| parameters = {} | |
| input_param = {} | |
| if messages is not None: | |
| msgs = copy.deepcopy(messages) | |
| if prompt is not None and prompt: | |
| msgs.append({"role": Role.USER, "content": prompt}) | |
| input_param = {MESSAGES: msgs} | |
| elif history is not None and history: | |
| logger.warning(DEPRECATED_MESSAGE) | |
| input_param[HISTORY] = history | |
| if prompt is not None and prompt: | |
| input_param[PROMPT] = prompt | |
| else: | |
| input_param[PROMPT] = prompt | |
| session_id = kwargs.pop("session_id", None) | |
| if session_id is not None and session_id: | |
| input_param["session_id"] = session_id | |
| doc_reference_type = kwargs.pop("doc_reference_type", None) | |
| if doc_reference_type is not None and doc_reference_type: | |
| input_param["doc_reference_type"] = doc_reference_type | |
| doc_tag_codes = kwargs.pop("doc_tag_codes", None) | |
| if doc_tag_codes is not None: | |
| if isinstance(doc_tag_codes, list) and all( | |
| isinstance(item, str) for item in doc_tag_codes | |
| ): | |
| input_param["doc_tag_codes"] = doc_tag_codes | |
| else: | |
| raise InvalidInput("doc_tag_codes is not a List[str]") | |
| memory_id = kwargs.pop("memory_id", None) | |
| if memory_id is not None: | |
| input_param["memory_id"] = memory_id | |
| biz_params = kwargs.pop("biz_params", None) | |
| if biz_params is not None and biz_params: | |
| input_param["biz_params"] = biz_params | |
| image_list = kwargs.pop("image_list", None) | |
| if image_list is not None and image_list: | |
| input_param["image_list"] = image_list | |
| file_list = kwargs.pop("file_list", None) | |
| if file_list is not None and file_list: | |
| input_param["file_list"] = file_list | |
| return input_param, {**parameters, **kwargs} | |