From 1eb839b77ab6c89edb4dcfc9a738f3e7221e75cd Mon Sep 17 00:00:00 2001 From: dongdaxiang Date: Tue, 19 Dec 2023 14:56:41 +0800 Subject: [PATCH] initial commit of code --- AUTHORS.md | 6 + CHANGELOG.md | 24 + LICENSE | 201 +++++ appbuilder/__init__.py | 128 ++++ appbuilder/core/__init__.py | 15 + appbuilder/core/_client.py | 90 +++ appbuilder/core/_exception.py | 73 ++ appbuilder/core/agent.py | 307 ++++++++ appbuilder/core/component.py | 181 +++++ appbuilder/core/components/__init__.py | 13 + appbuilder/core/components/asr/README.md | 47 ++ appbuilder/core/components/asr/__init__.py | 15 + appbuilder/core/components/asr/component.py | 113 +++ appbuilder/core/components/asr/model.py | 122 +++ .../core/components/dish_recognize/README.md | 37 + .../components/dish_recognize/__init__.py | 15 + .../components/dish_recognize/component.py | 99 +++ .../core/components/dish_recognize/model.py | 181 +++++ .../core/components/doc_parser/README.md | 158 ++++ .../core/components/doc_parser/__init__.py | 15 + appbuilder/core/components/doc_parser/base.py | 106 +++ .../core/components/doc_parser/doc_parser.py | 136 ++++ .../components/doc_parser/image/table.png | Bin 0 -> 96130 bytes .../core/components/doc_splitter/README.md | 100 +++ .../core/components/doc_splitter/__init__.py | 0 .../components/doc_splitter/doc_splitter.py | 311 ++++++++ .../core/components/embeddings/README.md | 81 ++ .../core/components/embeddings/__init__.py | 6 + appbuilder/core/components/embeddings/base.py | 76 ++ .../core/components/embeddings/component.py | 141 ++++ .../core/components/extract_table/README.md | 44 ++ .../core/components/extract_table/__init__.py | 15 + .../components/extract_table/component.py | 107 +++ .../core/components/general_ocr/README.md | 43 ++ .../core/components/general_ocr/__init__.py | 13 + .../core/components/general_ocr/component.py | 105 +++ .../core/components/general_ocr/model.py | 278 +++++++ 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.../llms/oral_query_generation/component.py | 88 +++ .../core/components/llms/playground/README.md | 51 ++ .../components/llms/playground/__init__.py | 2 + .../components/llms/playground/component.py | 122 +++ .../components/llms/qa_pair_mining/README.md | 81 ++ .../llms/qa_pair_mining/__init__.py | 2 + .../llms/qa_pair_mining/component.py | 83 ++ .../llms/query_decomposition/README.md | 60 ++ .../llms/query_decomposition/__init__.py | 2 + .../llms/query_decomposition/component.py | 79 ++ .../components/llms/query_rewrite/README.md | 43 ++ .../components/llms/query_rewrite/__init__.py | 2 + .../llms/query_rewrite/component.py | 130 ++++ .../llms/similar_question/README.md | 59 ++ .../llms/similar_question/__init__.py | 2 + .../llms/similar_question/component.py | 78 ++ .../components/llms/style_rewrite/README.md | 46 ++ .../components/llms/style_rewrite/__init__.py | 2 + .../llms/style_rewrite/component.py | 112 +++ .../components/llms/style_writing/README.md | 57 ++ 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appbuilder/tests/run_all_tests.py | 82 ++ appbuilder/tests/test.pdf | Bin 0 -> 1042373 bytes appbuilder/tests/test_agent.py | 60 ++ appbuilder/tests/test_asr.py | 142 ++++ appbuilder/tests/test_bes_retriever.py | 100 +++ appbuilder/tests/test_dialog_summary.py | 50 ++ appbuilder/tests/test_dish_recognize.py | 112 +++ appbuilder/tests/test_doc_parser.py | 72 ++ appbuilder/tests/test_doc_splitter.py | 98 +++ appbuilder/tests/test_embedding.py | 47 ++ appbuilder/tests/test_extract_table.py | 67 ++ appbuilder/tests/test_general_ocr.py | 133 ++++ appbuilder/tests/test_is_complex_query.py | 59 ++ appbuilder/tests/test_landmark_recognize.py | 111 +++ appbuilder/tests/test_matching.py | 59 ++ appbuilder/tests/test_message.py | 25 + appbuilder/tests/test_mrc.py | 135 ++++ appbuilder/tests/test_nl2pandas.py | 58 ++ appbuilder/tests/test_object_recognize.py | 133 ++++ .../tests/test_oral_query_generation.py | 61 ++ appbuilder/tests/test_playground.py | 68 ++ appbuilder/tests/test_qa_pair_mining.py | 62 ++ appbuilder/tests/test_query_decomposition.py | 59 ++ appbuilder/tests/test_query_rewrite.py | 64 ++ appbuilder/tests/test_similar_question.py | 65 ++ appbuilder/tests/test_style_rewrite.py | 80 ++ appbuilder/tests/test_style_writing.py | 89 +++ appbuilder/tests/test_tag_extraction.py | 47 ++ appbuilder/tests/test_text_to_image.py | 108 +++ appbuilder/tests/test_title_splitter.docx | Bin 0 -> 13845 bytes appbuilder/tests/test_translate.py | 25 + appbuilder/tests/test_tts.py | 51 ++ appbuilder/utils/__init__.py | 15 + appbuilder/utils/logger_util.py | 124 +++ docs/Makefile | 19 + docs/build.sh | 57 ++ docs/index.rst.template | 30 + docs/markdown2rst.py | 724 ++++++++++++++++++ docs/requirements.txt | 7 + docs/source/.DS_Store | Bin 0 -> 6148 bytes docs/source/_static/style.css | 3 + docs/source/conf.py | 199 +++++ docs/source/index.rst | 57 ++ docs/source/md/authentication.md | 1 + docs/source/md/components.md | 60 ++ docs/source/rst/introduction.rst | 10 + requirements.txt | 8 + setup.py | 37 + 164 files changed, 12114 insertions(+) create mode 100644 AUTHORS.md create mode 100644 CHANGELOG.md create mode 100644 LICENSE create mode 100644 appbuilder/__init__.py create mode 100644 appbuilder/core/__init__.py create mode 100644 appbuilder/core/_client.py create mode 100644 appbuilder/core/_exception.py create mode 100644 appbuilder/core/agent.py create mode 100644 appbuilder/core/component.py create mode 100644 appbuilder/core/components/__init__.py create mode 100644 appbuilder/core/components/asr/README.md create mode 100644 appbuilder/core/components/asr/__init__.py create mode 100644 appbuilder/core/components/asr/component.py create mode 100644 appbuilder/core/components/asr/model.py create mode 100644 appbuilder/core/components/dish_recognize/README.md create mode 100644 appbuilder/core/components/dish_recognize/__init__.py create mode 100644 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100644 appbuilder/tests/test_mrc.py create mode 100644 appbuilder/tests/test_nl2pandas.py create mode 100644 appbuilder/tests/test_object_recognize.py create mode 100644 appbuilder/tests/test_oral_query_generation.py create mode 100644 appbuilder/tests/test_playground.py create mode 100644 appbuilder/tests/test_qa_pair_mining.py create mode 100644 appbuilder/tests/test_query_decomposition.py create mode 100644 appbuilder/tests/test_query_rewrite.py create mode 100644 appbuilder/tests/test_similar_question.py create mode 100644 appbuilder/tests/test_style_rewrite.py create mode 100644 appbuilder/tests/test_style_writing.py create mode 100644 appbuilder/tests/test_tag_extraction.py create mode 100644 appbuilder/tests/test_text_to_image.py create mode 100644 appbuilder/tests/test_title_splitter.docx create mode 100644 appbuilder/tests/test_translate.py create mode 100644 appbuilder/tests/test_tts.py create mode 100644 appbuilder/utils/__init__.py create mode 100644 appbuilder/utils/logger_util.py create mode 100644 docs/Makefile create mode 100644 docs/build.sh create mode 100644 docs/index.rst.template create mode 100644 docs/markdown2rst.py create mode 100644 docs/requirements.txt create mode 100644 docs/source/.DS_Store create mode 100644 docs/source/_static/style.css create mode 100644 docs/source/conf.py create mode 100644 docs/source/index.rst create mode 100644 docs/source/md/authentication.md create mode 100644 docs/source/md/components.md create mode 100755 docs/source/rst/introduction.rst create mode 100644 requirements.txt create mode 100755 setup.py diff --git a/AUTHORS.md b/AUTHORS.md new file mode 100644 index 000000000..34edead0c --- /dev/null +++ b/AUTHORS.md @@ -0,0 +1,6 @@ +This is an incomplete list of authors of [Paddle](https://github.com/PaddlePaddle/Paddle/) codebase, to see a full list, please use the source control tool git. PaddlePaddle community encourages every Paddle codebase author include his/her GitHub account and fullname here. + + +| Github account | name | +|---|---| +| abhinavarora | Abhinav Arora | diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 000000000..3abd2a367 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,24 @@ +Changelog +=== +以下记录了项目中所有值得关注的变更内容,其格式基于[Keep a Changelog]。 + +本项目版本遵守[Semantic Versioning]和[PEP-440]。 + +[Unreleased] +--- +### Added +- 这里记录新添加的内容 +### Changed +- 这里记录变更的内容 + +0.1.0 - 2023-12-01 +--- +### Added +- 创建项目 + + +[Unreleased]: http://icode.baidu.com/repos/baidu/personal/apaas_sdk/merge/0.1.0...master + +[Keep a Changelog]: https://keepachangelog.com/zh-CN/1.0.0/ +[Semantic Versioning]: https://semver.org/lang/zh-CN/ +[PEP-440]: https://www.python.org/dev/peps/pep-0440/ diff --git a/LICENSE b/LICENSE new file mode 100644 index 000000000..f600e8c7d --- /dev/null +++ b/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + + APPENDIX: How to apply the Apache License to your work. + + To apply the Apache License to your work, attach the following + boilerplate notice, with the fields enclosed by brackets "[]" + replaced with your own identifying information. (Don't include + the brackets!) The text should be enclosed in the appropriate + comment syntax for the file format. We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright (c) 2023 Baidu, Inc. 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. diff --git a/appbuilder/__init__.py b/appbuilder/__init__.py new file mode 100644 index 000000000..cb9ee63ee --- /dev/null +++ b/appbuilder/__init__.py @@ -0,0 +1,128 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +__version__ = '1.0.0' + +import sys + + +class PythonVersionChecker: + def __init__(self): + self.min_version = (3, 8) + self.current_version = sys.version_info + self.check_version() + + def check_version(self): + if self.current_version < self.min_version: + raise EnvironmentError(f"Python version {self.min_version[0]}.{self.min_version[1]} or higher is required, " + f"you are using Python {self.current_version[0]}.{self.current_version[1]}.") + + +# Creating an instance to test the function +checker = PythonVersionChecker() +checker.current_version + +from .core import * + +from .core.components.llms.mrc import MRC +from .core.components.llms.oral_query_generation import OralQueryGeneration +from .core.components.llms.qa_pair_mining import QAPairMining +from .core.components.llms.similar_question import SimilarQuestion +from .core.components.llms.style_writing import StyleWriting +from .core.components.llms.style_rewrite import StyleRewrite +from .core.components.llms.tag_extraction import TagExtraction +from .core.components.llms.nl2pandas import Nl2pandasComponent +from .core.components.llms.query_rewrite import QueryRewrite +from .core.components.llms.dialog_summary import DialogSummary +from .core.components.llms.is_complex_query import IsComplexQuery +from .core.components.llms.query_decomposition import QueryDecomposition +from .core.components.llms.playground import Playground + +from .core.components.asr.component import ASR +from .core.components.general_ocr.component import GeneralOCR +from .core.components.object_recognize.component import ObjectRecognition +from .core.components.text_to_image.component import Text2Image +from .core.components.landmark_recognize.component import LandmarkRecognition +from .core.components.tts.component import TTS +from .core.components.extract_table.component import ExtractTableFromDoc +from .core.components.doc_parser.doc_parser import DocParser +from .core.components.doc_splitter.doc_splitter import DocSplitter +from .core.components.retriever.bes_retriever import BESRetriever +from .core.components.retriever.bes_retriever import BESVectorStoreIndex +from .core.components.dish_recognize.component import DishRecognition +from .core.components.translate.component import Translation + +from .core.components.embeddings import Embedding +from .core.components.matching import Matching + +from appbuilder.core.message import Message +from appbuilder.core.agent import AgentBase +from appbuilder.core.context import UserSession + +from appbuilder.utils.logger_util import logger + +from .core._exception import ( + BadRequestException, + ForbiddenException, + NotFoundException, + PreconditionFailedException, + InternalServerErrorException, + HTTPConnectionException, + AppBuilderServerException, +) + +__all__ = [ + 'logger', + + 'BadRequestException', + 'ForbiddenException', + 'NotFoundException', + 'PreconditionFailedException', + 'InternalServerErrorException', + 'HTTPConnectionException', + 'AppBuilderServerException', + + 'StyleWriting', + 'MRC', + 'Playground', + 'OralQueryGeneration', + 'QAPairMining', + 'SimilarQuestion', + 'IsComplexQuery', + 'QueryDecomposition', + 'TagExtraction', + 'StyleRewrite', + 'QueryRewrite', + 'DialogSummary', + 'ASR', + 'GeneralOCR', + 'ObjectRecognition', + 'Text2Image', + 'LandmarkRecognition', + 'TTS', + "ExtractTableFromDoc", + "DocParser", + "DocSplitter", + "BESRetriever", + "BESVectorStoreIndex", + 'DishRecognition', + 'Translation', + + 'Message', + + 'Embedding', + + 'Matching', +] diff --git a/appbuilder/core/__init__.py b/appbuilder/core/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/_client.py b/appbuilder/core/_client.py new file mode 100644 index 000000000..37ae102c6 --- /dev/null +++ b/appbuilder/core/_client.py @@ -0,0 +1,90 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +"""Base client for interact with backend server""" + +import os + +import requests + +from appbuilder.core._exception import * + + +class BaseClient: + r""" + BaseClient class provide common method for interact with backend server. + """ + + def __init__(self, secret_key: str = "", gateway: str = ""): + r"""__init__ method. + :param secret_key: authorization token, if not set get from env variable. + :param gateway: backend server host. + :rtype: + """ + + self.secret_key = secret_key if secret_key else os.getenv("APPBUILDER_TOKEN", "") + + if not self.secret_key: + raise ValueError("secret_key is empty, please pass a nonempty secret_key " + "or set a secret_key in environment variable") + + self.gateway = gateway if gateway else os.getenv("GATEWAY_URL", "") + + # self.gateway = gateway or os.getenv("GATEWAY_URL", "https://api.xbuilder.baidu.com") + if not self.gateway.startswith("http"): + self.gateway = "https://" + gateway + + @staticmethod + def check_response_header(response: requests.Response): + r"""check_response_header is a helper method for check head status . + :param response: requests.Response. + :rtype: + """ + status_code = response.status_code + if status_code == requests.codes.ok: + return + request_id = response.headers.get("X-App-Engine-Request-Id", "") + message = "request_id={} , http status code is {}".format(request_id, status_code) + if status_code == requests.codes.bad_request: + raise BadRequestException(message) + elif status_code == requests.codes.forbidden: + raise ForbiddenException(message) + elif status_code == requests.codes.not_found: + raise NotFoundException(message) + elif status_code == requests.codes.precondition_required: + raise PreconditionFailedException(message) + elif status_code == requests.codes.internal_server_error: + raise InternalServerErrorException(message) + else: + raise BaseRPCException(message) + + def service_url(self, sub_path: str, prefix=None): + r"""service_url is a helper method for concatenate service url. + :param sub_path: service unique sub path. + :param prefix: service prefix. + :rtype: str. + """ + # host + fix prefix + sub service path + prefix = prefix if prefix else "/rpc/2.0/cloud_hub" + return self.gateway + prefix + sub_path + + @staticmethod + def check_response_json(data: dict): + r"""check_response_json is a helper method for check backend server response. + :param: dict, body response data. + :rtype: str. + """ + if "code" in data and "message" in data and "requestId" in data: + raise AppBuilderServerException(data["requestId"], data["code"], data["message"]) diff --git a/appbuilder/core/_exception.py b/appbuilder/core/_exception.py new file mode 100644 index 000000000..79b389b11 --- /dev/null +++ b/appbuilder/core/_exception.py @@ -0,0 +1,73 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +"""include HTTP and backend server exception. +""" + + +class BaseRPCException(Exception): + r"""Base RPC exception. + """ + pass + + +class BadRequestException(BaseRPCException): + r""" BadRequestException represent HTTP Code 400. + """ + pass + + +class ForbiddenException(BaseRPCException): + r"""BadRequestException represent HTTP Code 403. + """ + pass + + +class NotFoundException(BaseRPCException): + r"""NotFoundException represent HTTP Code 404. + """ + pass + + +class PreconditionFailedException(BaseRPCException): + r"""PreconditionFailedException represent HTTP Code 412. + """ + pass + + +class InternalServerErrorException(BaseRPCException): + r"""InternalServerErrorException represent HTTP Code 500. + """ + pass + + +class HTTPConnectionException(BaseRPCException): + r"""HTTPConnectionException represent HTTP Connection error. + """ + pass + + +class AppBuilderServerException(BaseRPCException): + r"""AppBuilderServerException represent backend server failed response. + """ + + def __init__(self, request_id="", code="", message="", service_err_code="", service_err_message=""): + r"""__init__ a AppBuilderServerException instance. + :param request_id: str, request unique id. + :param code: str, backend . + :rtype: + """ + super().__init__("request_id={}, code={}, message={}, service_err_code={}, service_err_message={} ".format( + request_id, code, message, service_err_code, service_err_message)) diff --git a/appbuilder/core/agent.py b/appbuilder/core/agent.py new file mode 100644 index 000000000..ef4c5d8d4 --- /dev/null +++ b/appbuilder/core/agent.py @@ -0,0 +1,307 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +import sys +import os +import logging +import uuid +import json +import inspect +from pydantic import BaseModel, root_validator, Extra +from typing import Optional, Dict, List, Any + +import appbuilder +from appbuilder.core.context import UserSession +from appbuilder.core.component import Component +from appbuilder.core.message import Message + + +class AgentBase(BaseModel): + """ + AgentBase 是对组件调用的服务化封装,开发者不是必须要用 AgentBase 才能运行自己的组件服务。 + 但 AgentBase 可以快速帮助开发者服务化组件服务,并且提供API、对话框等部署方式。 + 此外,结合 Component 和 Message 自带的运行和调试接口,可以方便开发者快速获得一个调试 Agent 的服务。 + + Examples: + + .. code-block:: python + + import os + import sys + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + component = appbuilder.Playground( + prompt_template="{query}", + model="ernie-bot-4" + ) + agent = appbuilder.AgentBase(component=component) + message = appbuilder.Message({"query": "你好"}) + session_id = agent._generate_session_id() + print(agent.chat(message, session_id)) + + .. code-block:: python + + import os + import sys + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + component = appbuilder.Playground( + prompt_template="{query}", + model="ernie-bot-4" + ) + agent = appbuilder.AgentBase(component=component) + agent.serve(debug=False, port=8091) + + .. code-block:: python + + import os + import sys + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + component = appbuilder.Playground( + prompt_template="{query}", + model="ernie-bot-4" + ) + agent = appbuilder.AgentBase(component=component) + agent.chainlit_demo(port=8091) + """ + component: Component + user_session_handle: UserSession + + class Config: + """ + 检查配置 + """ + extra = Extra.forbid # 不能传入类定义中未声明的字段 + arbitrary_types_allowed = True # 此设置允许在模型中使用自定义类型的字段 + + @root_validator(pre=True) + def init(cls, values: Dict) -> Dict: + """ + 初始化 AgentBase + + Args: + component (Component): 可运行的 Component + user_session_config (str|None): Session 配置字符串,遵循 sqlalchemy 后端定义,参考文档 + https://docs.sqlalchemy.org/en/20/core/engines.html#backend-specific-urls + + Returns: + None + """ + user_session_config = values.get("user_session_config") + if "user_session_config" in values: + values.pop("user_session_config") + values.update({ + "component": values.get("component"), + "user_session_handle": UserSession(user_session_config), + }) + return values + + def _generate_session_id(self): + """ + 生成 Session ID + + Args: + None + + Returns: + str + """ + return str(uuid.uuid4()) + + def _get_user_session(self, session_id: str, limit: int) -> List[Message]: + """ + 获取历史对话数据 + + Args: + session_id (str): Session ID + limit (int): 获取最近的几条 session 数据 + + Returns: + List[Message] + """ + return self.user_session_handle.get_session_messages(session_id, limit) + + def _save_user_session( + self, + session_id: str, + query_message: Message, + answer_message: Message, + extra: Dict = {}, + ) -> None: + """ + 保存一条对话数据 + + Args: + session_id (str): Session ID + query_message (Message): 该次对话用户输入的 Message + answer_message (Message): 该次对话模型输出的 Message + extra (dict): 该次对话额外需要存储的数据 + + Returns: + None + """ + self.user_session_handle.save_session_message( + session_id, query_message, answer_message, extra) + + def chat(self, message: Message, session_id: str, stream: bool=False, **args) -> Message: + """ + 执行一次对话。对话历史会被存储到 session_id 对应的 Session 中 + + Args: + message (Message): 该次对话用户输入的 Message + session_id (str): Session ID + stream (bool): 是否流式请求 + **args: 其他参数,会被透传到 component + + Returns: + Message + """ + # user session is a list of Messages + user_session = self._get_user_session(session_id, limit=10) + params = inspect.signature(self.component.run).parameters + # online chat interface + if "user_session" in params: + answer = self.component.run(message=message, user_session=user_session, stream=stream, **args) + else: + answer = self.component.run(message=message, stream=stream, **args) + if stream: + def iterator(iters): + concat_answer = "" + for it in iters: + concat_answer += it + yield it + self._save_user_session(session_id, message, Message(concat_answer)) + return Message(iterator(answer.content)) + else: + self._save_user_session(session_id, message, answer) + return answer + + def serve(self, host='0.0.0.0', debug=True, port=8092): + """ + 将 component 服务化,提供 Flask http API 接口 + + Args: + host (str): 服务 host + debug (bool): 是否是 debug 模式 + port (int): 服务 port + + Returns: + None + """ + # serve agent chat interface + from flask import Flask, current_app, request, Response + from flask_restful import reqparse, Resource + from werkzeug.exceptions import BadRequest + + app = Flask(__name__) + + @app.errorhandler(BadRequest) + def handle_bad_request(e): + return {"code": 400, "message": 'Bad request, Please check your data.', "result": None}, 400 + + @app.errorhandler(RuntimeError) + def handle_bad_request(e): + return {"code": 1000, "message": f'RuntimeError: {e}', "result": None}, 200 + + @app.route('/chat', methods=['POST']) + def warp(): + data = request.get_json() + if "message" not in data: + raise BadRequest("message is required") + message = Message(data.pop('message')) + if "session_id" not in data: + session_id = self._generate_session_id() + else: + session_id = data.pop("session_id") + if not isinstance(session_id, str): + raise BadRequest("session_id must be str type") + if "stream" not in data: + stream = False + else: + stream = data.pop("stream") + if not isinstance(stream, bool): + raise BadRequest("stream must be bool type") + + try: + answer = self.chat(message, session_id, stream, **data) + if stream: + def gen_sse_resp(stream_message): + with app.app_context(): + for it in stream_message.content: + d = { + "code": 0, "message": "", + "result": { + "session_id": session_id, + "answer_message": json.loads(Message(it).json(exclude_none=True)), + } + } + yield "data: " + json.dumps(d, ensure_ascii=False) + "\n\n" + return Response( + gen_sse_resp(answer), 200, + {'Content-Type': 'text/event-stream; charset=utf-8'}, + ) + else: + return { + "code": 0, "message": "", + "result": { + "session_id": session_id, + "answer_message": json.loads(answer.json(exclude_none=True)), + } + } + except Exception as e: + logging.error(e, exc_info=True) + raise RuntimeError(e) + + app.run(host=host, debug=debug, port=port) + + def chainlit_demo(self, host='0.0.0.0', port=8091): + """ + 将 component 服务化,提供 chainlit demo 页面 + + Args: + host (str): 服务 host + port (int): 服务 port + + Returns: + None + """ + import chainlit as cl + import chainlit.cli + import click + from click.testing import CliRunner + + @cl.on_message # this function will be called every time a user inputs a message in the UI + async def main(message: cl.Message): + session_id = cl.user_session.get("id") + msg = cl.Message(content="") + await msg.send() + stream_message = self.chat(Message(message.content), session_id=session_id, stream=True) + + for part in stream_message.content: + if token := part or "": + await msg.stream_token(token) + await msg.update() + + # start chainlit service + if os.getenv('APPBUILDER_RUN_CHAINLIT') == '1': + pass + else: + os.environ['APPBUILDER_RUN_CHAINLIT'] = '1' + target = sys.argv[0] + runner = CliRunner() + runner.invoke( + chainlit.cli.chainlit_run, [target, '--watch', "--port", port, "--host", host]) diff --git a/appbuilder/core/component.py b/appbuilder/core/component.py new file mode 100644 index 000000000..85cf368b4 --- /dev/null +++ b/appbuilder/core/component.py @@ -0,0 +1,181 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +"""Component module include a Component class which is the +base class for customized Component class, define interface method like run() batch() etc. +subclass may choose to implement, also provide some simple helper method for interact with backend server.""" + +import os +from enum import Enum + +import requests +from pydantic import BaseModel +from requests.adapters import HTTPAdapter, Retry +from typing import Dict, List, Optional, Any + +from appbuilder.core._exception import * +from appbuilder.core.message import Message +from appbuilder.core.constants import GATEWAY_URL + + +class ComponentArguments(BaseModel): + r""""ComponentArguments define Component meta fields""" + name: str = "" + tool_desc: Dict[str, Any] = {} + + def extract_values_to_dict(self): + r"""extract ComponentArguments fields to dict""" + + inputs = {} + for field_name, field in self.__fields__.items(): + value = getattr(self, field_name) + # 获取 display_name 元数据 + variable_name = field.field_info.extra.get('variable_name') + if variable_name: + # 使用 Enum 成员的实际值 + if isinstance(value, Message): + inputs[variable_name] = str(value.content) + elif isinstance(value, Enum): + inputs[variable_name] = str(value.value) + else: + inputs[variable_name] = str(value) + else: + inputs[field_name] = value + return inputs + + +class Component: + r"""Component基类, 其它实现的Component子类需要继承该基类,并至少实现run方法.""" + + def __init__(self, + meta: Optional[ComponentArguments] = ComponentArguments(), + secret_key: Optional[str] = None, + gateway: str = "" + ): + r"""Component初始化方法. + + 参数: + meta (obj: `ComponentArguments`, 可选) : component元信息. + secret_key(str,可选): 用户鉴权token, 默认从环境变量中获取: os.getenv("APPBUILDER_TOKEN", ""). + gateway(str, 可选): 后端网关服务地址,默认从环境变量中获取: os.getenv("GATEWAY_URL", "") + 返回: + 无 + """ + self.meta = meta + self.secret_key = secret_key if secret_key else os.getenv("APPBUILDER_TOKEN", "") + if not self.secret_key: + raise ValueError("secret_key is empty, please pass a nonempty secret_key " + "or set a secret_key in environment variable") + + if not gateway and not os.getenv("GATEWAY_URL"): + self.gateway = GATEWAY_URL + else: + self.gateway = gateway if gateway else os.getenv("GATEWAY_URL", "") + + if not self.gateway.startswith("http"): + self.gateway = "https://" + self.gateway + self.s = requests.sessions.Session() + self.retry = Retry(total=0, backoff_factor=0.1) + self.s.mount(self.gateway, HTTPAdapter(max_retries=self.retry)) + + def __call__(self, *inputs, **kwargs): + r"""implement __call__ method""" + return self.run(*inputs, **kwargs) + + def run(self, *inputs, **kwargs): + r""" + Defines the computation performed at every call. + Should be overridden by all subclasses. + + Parameters: + *inputs(tuple): unpacked tuple arguments + **kwargs(dict): unpacked dict arguments + """ + raise NotImplementedError + + def batch(self, *args, **kwargs) -> List[Message]: + r"""pass""" + return None + + async def arun(self, *args, **kwargs) -> Optional[Message]: + r"""pass""" + return None + + async def abatch(self, *args, **kwargs) -> List[Message]: + r"""pass""" + return None + + def _trace(self, **data) -> None: + r"""pass""" + pass + + def _debug(self, **data) -> None: + r"""pass""" + pass + + @staticmethod + def check_response_header(response: requests.Response): + r"""check_response_header is a helper method for check head status . + :param response: requests.Response. + :rtype: + """ + status_code = response.status_code + if status_code == requests.codes.ok: + return + message = "request_id={} , http status code is {}, body is {}".format( + __class__.response_request_id(response), status_code, response.text) + if status_code == requests.codes.bad_request: + raise BadRequestException(message) + elif status_code == requests.codes.forbidden: + raise ForbiddenException(message) + elif status_code == requests.codes.not_found: + raise NotFoundException(message) + elif status_code == requests.codes.precondition_required: + raise PreconditionFailedException(message) + elif status_code == requests.codes.internal_server_error: + raise InternalServerErrorException(message) + else: + raise BaseRPCException(message) + + def service_url(self, sub_path: str, prefix: str = None): + r"""service_url is a helper method for concatenate service url. + :param sub_path: service unique sub path. + :param prefix: service prefix. + :rtype: str. + """ + # host + fix prefix + sub service path + prefix = prefix if prefix else "/rpc/2.0/cloud_hub" + return self.gateway + prefix + sub_path + + @staticmethod + def check_response_json(data: dict): + r"""check_response_json is a helper method for check backend server response. + :param: dict, body response data. + :rtype: str. + """ + if "code" in data and "message" in data and "requestId" in data: + raise AppBuilderServerException(data["requestId"], data["code"], data["message"]) + + def auth_header(self): + r"""auth_header is a helper method return auth info""" + + if self.secret_key.startswith("Bearer "): + return {"X-Appbuilder-Authorization": self.secret_key} + else: + return {"X-Appbuilder-Authorization": "Bearer {}".format(self.secret_key)} + + @staticmethod + def response_request_id(response: requests.Response): + r"""response_request_id is a helper method get unique request id""" + return response.headers.get("X-Appbuilder-Request-Id", "") diff --git a/appbuilder/core/components/__init__.py b/appbuilder/core/components/__init__.py new file mode 100644 index 000000000..c33303636 --- /dev/null +++ b/appbuilder/core/components/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2023 Baidu, Inc. 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. diff --git a/appbuilder/core/components/asr/README.md b/appbuilder/core/components/asr/README.md new file mode 100644 index 000000000..90b414304 --- /dev/null +++ b/appbuilder/core/components/asr/README.md @@ -0,0 +1,47 @@ +# 短语音识别-极速版 (Automatic Speech Recognition) + +## 简介 +短语音识别(ASR)可以将音频流实时识别为文字,并返回每句话的开始和结束时间,适用于手机语音输入、语音搜索、人机对话等语音交互场景。 + +## 基本用法 + +下面是短语音识别的代码示例: + +```python +import os +import appbuilder +# 设置环境变量和初始化 +os.environ["APPBUILDER_TOKEN"] = "..." + +asr = appbuilder.ASR() + +with open("./asr_test.pcm", "rb") as f: + audio_data = f.read() +content_data = {"audio_format": "pcm", "raw_audio": audio_data, "rate": 16000} +msg = appbuilder.Message(content_data) +result = asr.run(msg) + +print(result) +``` +## 参数说明 +### 初始化参数 + +无 + +### 调用参数 +- `run`函数中包含以下参数: + - `message`: 输入的消息,用于模型的主要输入内容。这是一个必需的参数,例如:Message(content={"raw_audio": b"..."}) + - `audio_format`: 定义语言文件的格式,包括"pcm"、"wav"、"amr"、"m4a",默认值为"pcm"。 + - `rate`: 定义录音采样率,固定值16000 + - `timeout`: HTTP超时时间 + - `retry`: HTTP重试次数 + +返回值示例:eg: {"result": ["北京科技馆。"]} + +## 高级用法 + +目前该模块仅提供基础的语音识别功能。 + + +## 更新记录和贡献 +* 短语音识别能力 (2023-12) \ No newline at end of file diff --git a/appbuilder/core/components/asr/__init__.py b/appbuilder/core/components/asr/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/asr/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/asr/component.py b/appbuilder/core/components/asr/component.py new file mode 100644 index 000000000..420955a95 --- /dev/null +++ b/appbuilder/core/components/asr/component.py @@ -0,0 +1,113 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""ASR component. +""" +import uuid +import json + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.asr.model import ShortSpeechRecognitionRequest, ShortSpeechRecognitionResponse, \ + ASRInMsg, ASROutMsg + + +class ASR(Component): + r""" + ASR组件,即对于输入的语音文件,输出语音识别结果 + + Examples: + + .. code-block:: python + + import appbuilder + asr = appbuilder.ASR() + os.environ["APPBUILDER_TOKEN"] = '...' + with open("xxxx.pcm", "rb") as f: + inp = appbuilder.Message(content={"raw_audio": f.read()}) + out = asr.run(inp) + # 打印识别结果 + print(out.content) # eg: {"result": ["北京科技馆。"]} + """ + def run(self, message: Message, audio_format: str = "pcm", rate: int = 16000, + timeout: float = None, retry: int = 0) -> Message: + """ + 输入语音文件并返回语音识别结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。举例: Message(content={"raw_audio": b"..."})。 + audio_format (str,可选): 语音文件的格式,pcm/wav/amr/m4a。不区分大小写。推荐pcm文件。 + rate (int, 可选): 采样率,16000,固定值。 + timeout (float, 可选): HTTP超时时间。 + retry (int, 可选): HTTP重试次数。 + + 返回: + obj:`Message`: 短语音识别结果。举例: Message(content={"result": ["北京科技馆。"]})。 + """ + inp = ASRInMsg(**message.content) + request = ShortSpeechRecognitionRequest() + request.format = audio_format + request.rate = rate + request.cuid = str(uuid.uuid4()) + request.dev_pid = "80001" + request.speech = inp.raw_audio + response = self._recognize(request) + out = ASROutMsg(result=list(response.result)) + return Message(content=dict(out)) + + def _recognize(self, request: ShortSpeechRecognitionRequest, timeout: float = None, + retry: int = 0) -> ShortSpeechRecognitionResponse: + """ + 使用给定的输入并返回语音识别的结果。 + + 参数: + request (obj:`ShortSpeechRecognitionRequest`): 输入请求,这是一个必需的参数。 + timeout (float, 可选): 请求的超时时间。 + retry (int, 可选): 请求的重试次数。 + + 返回: + obj:`ShortSpeechRecognitionResponse`: 接口返回的输出消息。 + """ + ContentType = "audio/" + request.format + ";rate=" + str(request.rate) + headers = self.auth_header() + headers['content-type'] = ContentType + params = { + 'dev_pid': request.dev_pid, + 'cuid': request.cuid + } + if retry != self.retry.total: + self.retry.total = retry + response = self.s.post(self.service_url("/v1/bce/aip_speech/asrpro"), params=params, headers=headers, data=request.speech, timeout=timeout) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__._check_service_error(data) + request_id = self.response_request_id(response) + response = ShortSpeechRecognitionResponse.from_json(payload=json.dumps(data)) + response.request_id = request_id + return response + + @staticmethod + def _check_service_error(data: dict): + r"""个性化服务response参数检查 + + 参数: + request (dict) : 短语音识别body返回 + 返回: + 无 + """ + if "err_no" in data and "err_msg" in data: + if data["err_no"] != 0: + raise AppBuilderServerException(service_err_code=data["err_no"], service_err_message=data["err_msg"]) diff --git a/appbuilder/core/components/asr/model.py b/appbuilder/core/components/asr/model.py new file mode 100644 index 000000000..14bf6e51c --- /dev/null +++ b/appbuilder/core/components/asr/model.py @@ -0,0 +1,122 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""ASR model.py. +""" +from typing import MutableSequence, List + +import proto +from pydantic import BaseModel + + +class ShortSpeechRecognitionRequest(proto.Message): + r"""短语音识别的请求体 + 参数: + format(str): + 语音文件的格式,pcm/wav/amr/m4a。不区分大小写。推荐pcm文件。 + rate(int): + 采样率,16000,固定值。 + cuid(str): + 用户唯一标识,用来区分用户,计算UV值。建议填写能区分用户的机器 MAC 地址或 IMEI 码,长度为60字符以内。 + dev_pid(int): + 80001(极速版输入法模型) + speech(int): + 本地语音文件的的二进制语音数据。 + """ + format: str = proto.Field( + proto.STRING, + number=1, + ) + rate: int = proto.Field( + proto.INT64, + number=2, + ) + cuid: str = proto.Field( + proto.STRING, + number=3, + ) + dev_pid: str = proto.Field( + proto.STRING, + number=4, + ) + speech: bytes = proto.Field( + proto.BYTES, + number=5, + ) + + +class ShortSpeechRecognitionResponse(proto.Message): + r"""短语音识别结果返回体. + + 参数: + request_id(str): + 网关层的请求ID. + err_no(int): + 算子层的错误码. + err_msg(str): + 算子层的错误信息. + corpus_no(str): + sn(str): + 语音数据唯一标识,系统内部产生。如果反馈及debug请提供sn。 + result(MutableSequence[str]): + 识别结果数组,返回1个最优候选结果。utf-8 编码。 + """ + request_id: str = proto.Field( + proto.STRING, + number=1, + ) + + err_no: int = proto.Field( + proto.INT32, + number=2, + ) + + err_msg: str = proto.Field( + proto.STRING, + number=3, + ) + corpus_no: str = proto.Field( + proto.STRING, + number=4, + ) + + sn: str = proto.Field( + proto.STRING, + number=5, + ) + result: MutableSequence[str] = proto.RepeatedField( + proto.STRING, + number=6 + ) + + +class ASRInMsg(BaseModel): + """ ASR输入message. + 参数: + raw_audio(bytes): + 原始的语音文件字节数组. + + """ + raw_audio: bytes + + +class ASROutMsg(BaseModel): + """ ASR输出message. + + 参数: + result(List[str]): + 输出识别后的文本结果. + """ + result: List[str] + diff --git a/appbuilder/core/components/dish_recognize/README.md b/appbuilder/core/components/dish_recognize/README.md new file mode 100644 index 000000000..f07112fc3 --- /dev/null +++ b/appbuilder/core/components/dish_recognize/README.md @@ -0,0 +1,37 @@ +# 菜品识别(DishRecognition) + +## 简介 +菜品识别组件(DishRecognition)可以识别超过9千种菜品,可准确识别图片中的菜品名称、卡路里,适用于多种客户识别菜品的业务场景中。 + + +## 基本用法 +通过如下示例代码可以快速开始使用菜品识别组件: + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' + +dish_recognition = appbuilder.DishRecognition() + +with open("xxxx.jpg", "rb") as f: + resp = dish_recognition(appbuilder.Message({"raw_image": f.read()})) +``` +其中,`APPBUILDER_TOKEN`为您的API访问授权token。 + +## 参数说明 + +### 初始化参数 + +该组件在初始化时无需任何参数。 + +### 调用参数说明 + +`DishRecognition` 组件的 `run` 方法接受以下参数: + +- `message`(Message) - 输入待识别图片,必传参数,支持传图片二进制流和图片URL。 +- `timeout`(float) - 请求超时时间,可选参数,默认为 None。 +- `retry`(int) - 重试次数,可选参数,默认为 0。 + +该方法返回一个 `Message` 对象,该对象中的 `content` 值是一个字典,包含菜品识别结果。例如,`Message(content={'result': [{'name': '剁椒鱼头', 'calorie': '127'}]})`。 \ No newline at end of file diff --git a/appbuilder/core/components/dish_recognize/__init__.py b/appbuilder/core/components/dish_recognize/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/dish_recognize/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/dish_recognize/component.py b/appbuilder/core/components/dish_recognize/component.py new file mode 100644 index 000000000..7de225864 --- /dev/null +++ b/appbuilder/core/components/dish_recognize/component.py @@ -0,0 +1,99 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +菜品识别组件. +""" +import base64 + +from appbuilder.core.message import Message +from appbuilder.core.component import Component +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.dish_recognize.model import * + + +class DishRecognition(Component): + """ + 菜品识别组件,适用于识别只含有单个菜品的图片,返回识别的菜品名称和卡路里信息 + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + dish_recognition = appbuilder.DishRecognition() + + with open("xxxx.jpg", "rb") as f: + resp = dish_recognition(appbuilder.Message({"raw_image": f.read()})) + """ + + def run(self, message: Message, timeout: float = None, retry: int = 0) -> Message: + """ + 根据输入图片进行菜品识别。 + + Args: + message (Message): 输入待识别图片,支持传图片二进制流和图片URL。 + timeout (float, optional): 请求超时时间,默认为 None。 + retry (int, optional): 重试次数,默认为 0。 + + Returns: + Message: 包含菜品识别结果的输出消息。 + 例如,Message(content={'result': [{'name': '剁椒鱼头', 'calorie': '127'}]}) + + """ + inp = DishRecognitionInMsg(**message.content) + req = DishRecognitionRequest() + if inp.raw_image: + req.image = base64.b64encode(inp.raw_image) + if inp.url: + req.url = inp.url + result = self._recognize(req, timeout=timeout, retry=retry) + result_dict = proto.Message.to_dict(result) + out = DishRecognitionOutMsg(**result_dict) + return Message(content=out.dict()) + + def _recognize(self, request: DishRecognitionRequest, timeout: float = None, + retry: int = 0) -> DishRecognitionResponse: + """ + 发起食物识别请求并返回识别结果。 + + :param request: 包含执行识别所需信息的 DishRecognitionRequest 对象。 + :param timeout: 请求超时时间(秒),默认为 None。 + :param retry: 请求失败时的重试次数,默认为 0。 + :return: 包含食物识别结果的响应对象。 + """ + if not request.image and not request.url: + raise ValueError("one of image or url must be set") + if not request.top_num: + request.top_num = 1 + if not request.filter_threshold: + request.filter_threshold = 0.95 + request_data = DishRecognitionRequest.to_dict(request) + if retry != self.retry.total: + self.retry.total = retry + headers = self.auth_header() + headers['content-type'] = 'application/x-www-form-urlencoded' + + url = self.service_url("/v1/bce/aip/image-classify/v2/dish") + response = self.s.post(url, headers=headers, data=request_data, timeout=timeout) + + self.check_response_header(response) + data = response.json() + self.check_response_json(data) + if "error_code" in data and "error_msg" in data: + raise AppBuilderServerException(service_err_code=data["error_code"], service_err_message=data["error_msg"]) + return DishRecognitionResponse(data, request_id=self.response_request_id(response)) diff --git a/appbuilder/core/components/dish_recognize/model.py b/appbuilder/core/components/dish_recognize/model.py new file mode 100644 index 000000000..f76e03997 --- /dev/null +++ b/appbuilder/core/components/dish_recognize/model.py @@ -0,0 +1,181 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +菜品识别model +""" +import proto +import pydantic +from typing import Optional, List + + +class DishRecognitionRequest(proto.Message): + """ + 菜品识别请求的请求体。 + + Attributes: + image (str): 表示图像数据的 Base64 编码字符串。 + url (str): 图像的 URL,用于识别。 + top_num (int): 要返回的顶部结果的数量。 + filter_threshold (float): 过滤识别结果的置信度阈值。 + baike_num (int): 要返回的百科结果的数量。 + + Note: + 'image' 或 'url' 字段至少传一个,两个都传默认使用 'image'。 + """ + + image: str = proto.Field( + proto.STRING, + number=1, + ) + url: str = proto.Field( + proto.STRING, + number=2, + ) + top_num: int = proto.Field( + proto.INT32, + number=3, + ) + filter_threshold: float = proto.Field( + proto.FLOAT, + number=4, + ) + baike_num: int = proto.Field( + proto.INT32, + number=5, + ) + + +class DishRecognitionResponse(proto.Message): + """ + 表示菜品识别返回的响应结果。 + + Attributes: + log_id (str): 识别请求的唯一标识符。 + request_id (str): 识别请求的唯一标识符。 + result_num (int): 返回的识别结果数量。 + result (List[DishRecognitionRes]): 识别结果列表。 + """ + log_id: str = proto.Field( + proto.INT64, + number=1, + ) + request_id: str = proto.Field( + proto.STRING, + number=2, + ) + result_num: int = proto.Field( + proto.INT32, + number=3, + ) + result: "DishRecognitionRes" = proto.RepeatedField( + proto.MESSAGE, + number=4, + message='DishRecognitionRes', + ) + + +class DishRecognitionRes(proto.Message): + """ + 表示菜品识别结果。 + + Attributes: + name (str): 识别的菜品名称。 + calorie (str): 识别的菜品热量信息。 + has_calorie (bool): 指示识别菜品是否返回了热量信息。 + probability (str): 识别置信度分数。 + baike_info (DishBaikeInfo): 与被识别菜品相关的百度百科信息。 + """ + name: str = proto.Field( + proto.STRING, + number=1, + ) + calorie: str = proto.Field( + proto.STRING, + number=2, + ) + has_calorie: bool = proto.Field( + proto.BOOL, + number=3, + ) + probability: str = proto.Field( + proto.STRING, + number=4, + ) + baike_info: "DishBaikeInfo" = proto.Field( + proto.MESSAGE, + number=5, + message='DishBaikeInfo', + ) + + +class DishBaikeInfo(proto.Message): + """ + 与被识别菜品相关的百度百科信息。 + + Attributes: + baike_url (str): 识别菜品的百度百科页面URL。 + image_url (str): 百度百科中与被识别菜品相关的图像URL。 + description (str): 百度百科中关于被识别菜品的描述或信息。 + """ + baike_url: str = proto.Field( + proto.STRING, + number=1, + ) + image_url: str = proto.Field( + proto.STRING, + number=2, + ) + description: str = proto.Field( + proto.STRING, + number=3, + ) + + +class DishRecognitionInMsg(pydantic.BaseModel): + """ + 菜品识别的输入消息模型。 + + :param raw_image: 图像的字节数组,包含要识别的菜品图像的原始数据。 + 此字段是可选的,可以为 None。 + :param url: 图像的可下载URL。如果提供,则将从此URL下载图像进行识别。 + 此字段也是可选的,可以为 None。 + 注意:raw_image 和 url 至少传一个,不能同时为 None,两个都传默认使用 raw_image。 + """ + raw_image: bytes = None + url: str = None + + +class DishRecognitionResult(pydantic.BaseModel): + """ + 表示菜品识别结果。 + + Attributes: + name (str): 识别到的菜品名称。 + calorie (Optional[str]): 菜品的卡路里信息。如果未返回卡路里信息,默认为 None。 + """ + name: str + calorie: Optional[str] = None + + +class DishRecognitionOutMsg(pydantic.BaseModel): + """ + 表示菜品识别组件返回的结构。 + + Attributes: + result (List[DishRecognitionResult]): 包含菜品识别结果的列表。 + """ + result: List[DishRecognitionResult] diff --git a/appbuilder/core/components/doc_parser/README.md b/appbuilder/core/components/doc_parser/README.md new file mode 100644 index 000000000..8fbccbf43 --- /dev/null +++ b/appbuilder/core/components/doc_parser/README.md @@ -0,0 +1,158 @@ +# 文档解析(DocParser) + +## 简介 +文档解析组件(DocParser)可以用于文档内容解析,支持PDF、JPG、DOC、TXT、XLS、PPT等17种文档格式,可解析出文档内容、版式信息、位置坐标、表格结构等内容。 + +DocParser支持解析以下几种类型的文档: +* 版式文档:「pdf」、「jpg」、「jpeg」、「png」、「bmp」、「tif」、「tiff」、「ofd」 +* 流式文档:「doc」、「docx」、「txt」、「xls」、「xlsx」、「wps」、「ppt」、「pptx」、「html」 + +支持解析的文档内容包括: +* 文档的版式分析,识别文档中的标题、正文、页眉页脚、表格等 +* 文档内的文字内容、位置坐标 +* 表格结构和内容 +* 构建文档标题段落层级树 +* 构建文档阅读顺序 +* 支持以上类型文档转成pdf格式 + +## 基本用法 + +参考tests目录下的[test_doc_parser.py](../../../tests/test_doc_parser.py),可快速搭建自己的解析用例,快速测试解析效果。 + +以下是使用DocParser快速开始的一个示例: + +```python +from appbuilder.core.components.doc_parser.doc_parser import DocParser +from appbuilder.core.message import Message +import os + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = "..." + +# 进行文档内容解析 +file_path = "./test.pdf" # 待解析的文件路径 +msg = Message(file_path) +parser = DocParser() +parse_result = parser(msg) +print(parse_result.content) +``` + + +## 详细说明 + +在base.py中定义了DocParser配置和结果结构,下面做一些详细的说明和解释: +### DocParser配置 +```python +class ParserConfig(BaseModel): + """ + DocParser解析配置 + """ + convert_file_to_pdf: bool = Field(alias="need_pdffile_data", default=False) # 是否需要将当前文件转换成pdf格式 + page_filter: List[int] = Field(alias="page_filter", default=None) # 指定解析的页码,默认传None,代表全部解析 + return_para_node_tree: bool = Field(alias="return_para_nodes", default=True) # 是否需要返回标题段落层级树 + erase_watermark: bool = Field(alias="erase_watermark", default=False) # 解析的过程中是否需要去除水印的干扰 +``` +### DocParser解析结果 +```python +class ParseResult(BaseModel): + """ + 解析结果整体结构 + """ + para_node_tree: Optional[List[ParaNode]] = [] # 标题段落层级树,当ParserConfig.return_para_node_tree为True时有内容 + page_contents: Optional[List[PageContent]] = [] # 页面的解析内容,详细内容参考base.py中的PageContent类 + pdf_data: Optional[str] = "" # pdf格式数据, 当ParserConfig.convert_file_to_pdf为True时有内容 + raw: Optional[Dict] = {} # 云端服务的原始解析结果 + +class ParaNode(BaseModel): + """ + 文档内容层级树结构 + """ + node_id: int # 标题段落层级树的节点id + text: str # 节点文本 + para_type: str # 节点类型,包括:title、text、table + parent: Optional[int] # 父节点id,文本的父节点是标题,标题的父节点是更高一级的标题 + children: List[int] # 子节点id列表,标题节点才会有子节点 + position: List[Position] # 节点位置信息,包括:页码和在对应页面的位置坐标 + table: Optional[Table] = None # 节点类型为table时,包含表格解析结果 + +class PageContent(BaseModel): + """ + 单页文档内容结构 + """ + page_num: int # 页码 + page_width: int # 页面宽度 + page_height: int # 页面高度 + page_angle: int # 页面旋转角度 + page_type: str # 页面类型 + page_layouts: List[Layout] # 页面版式信息 + titles: Optional[List[Layout]] = [] # 页面标题信息 + tables: Optional[List[Table]] = [] # 页面表格信息 + +class Layout(BaseModel): + """ + layout结构 + """ + type: str # 布局类型 + text: str # 布局文本 + box: List[int] # 布局位置信息,包括:左上角x、y坐标和宽高 + node_id: int # 布局在标题层级树中的节点id + +class Table(BaseModel): + """ + 表格结构 + """ + box: List[int] # 表格位置信息,包括:左上角x、y坐标和宽高 + cells: List[Layout] = Field(alias="children") # 表格单元格信息,列表形式 + matrix: List[List[int]] # 表格单元格矩阵,用来描述单元格的空间位置信息 + node_id: int # 表格在标题层级树中的节点id +``` +表格解析结构说明, 以下图为例: + +image + +```python +# cells中一共有26个元素,matrix中的每一个元素代表单元格在cells中的索引 +cells = [{"box": [90, 376, 21, 10], "type": "cell", "text": "序号", "node_id": 1}, ...] +matrix = [ + [0, 1, 2, 3], + [4, 5, 6, 7], + [8, 9, 10, 11], + [12, 13, 14, 15], + [16, 17, 18, 19], + [20, 21, 22, 23], + [24, 24, 25, 26] + ] +``` + +## 高级用法 +DocParser支持自定义文档解析的配置和对解析结果进行二次处理,以下是一个示例: + +```python +from appbuilder.core.components.doc_parser.doc_parser import DocParser +from appbuilder.core.message import Message +import os + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = "..." + +# 先进行文档内容解析 +file_path = "./test.docx" # 待解析的文件路径 +msg = Message(file_path) + +parser = DocParser() +config = parser.config +config.convert_file_to_pdf = True # 指定将当前文件转换成pdf格式 +config.page_filter = [0, 2] # 只解析第1页和第3页,注意:页码从0开始 + +parse_result = parser(msg) +file_content = parse_result.content +pdf_data = file_content.pdf_data # 获取原始文件转化成pdf之后的数据 +page_content = file_content.page_content[1] # 获取第3页的解析结果 +page_table = page_content.tables[0] # 第3页中第一个表格的解析结果(如有),表格的解析内容的结构详见上一章详细说明部分关于表格结果的说明 +cells = page_table.cells # 表格的单元格信息 +cell_text = cells[0] # 表格第一个单元格的文本内容 +matrix = page_table.cell_matrix # 表格的单元格矩阵,用来描述单元格的空间位置信息 +... +自定义处理表格内容 +... +``` \ No newline at end of file diff --git a/appbuilder/core/components/doc_parser/__init__.py b/appbuilder/core/components/doc_parser/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/doc_parser/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/doc_parser/base.py b/appbuilder/core/components/doc_parser/base.py new file mode 100644 index 000000000..c94147743 --- /dev/null +++ b/appbuilder/core/components/doc_parser/base.py @@ -0,0 +1,106 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +文档解析 +""" +from typing import List, Optional, Dict +from pydantic import BaseModel, Field + + +# 定义Parser解析结果的结构 +class Position(BaseModel): + """ + position结构 + """ + page_num: int = Field(alias="pageno") + box: List[int] + + +class Layout(BaseModel): + """ + layout结构 + """ + type: str + text: str + box: List[int] + node_id: int + + +class Table(BaseModel): + """ + 表格结构 + """ + box: List[int] + cells: List[Layout] = Field(alias="children") + matrix: List[List[int]] + node_id: int + + +class ParaNode(BaseModel): + """ + 文档内容层级树结构 + """ + node_id: int + text: str + para_type: str + parent: Optional[int] + children: List[int] + position: List[Position] + table: Optional[Table] = None + + +class PageContent(BaseModel): + """ + 单页文档内容结构 + """ + page_num: int + page_width: int + page_height: int + page_angle: int + page_type: str + page_layouts: List[Layout] + titles: Optional[List[Layout]] = [] + tables: Optional[List[Table]] = [] + + +class ParseResult(BaseModel): + """ + 解析结果整体结构 + """ + para_node_tree: Optional[List[ParaNode]] = [] + page_contents: Optional[List[PageContent]] = [] + pdf_data: Optional[str] = "" + raw: Optional[Dict] = {} + + +class ParserConfig(BaseModel): + """ + DocParser解析配置 + """ + convert_file_to_pdf: bool = Field(alias="need_pdffile_data", default=False) + page_filter: List[int] = Field(alias="page_filter", default=None) + return_para_node_tree: bool = Field(alias="return_para_nodes", default=True) + erase_watermark: bool = Field(alias="erase_watermark", default=False) + + +# 文档内容切分结构 +class DocSegment(BaseModel): + """ + 自定义文档内容切分的结构 + """ + content: Optional[str] = "" + title: Optional[List[str]] = [] diff --git a/appbuilder/core/components/doc_parser/doc_parser.py b/appbuilder/core/components/doc_parser/doc_parser.py new file mode 100644 index 000000000..3b4abd381 --- /dev/null +++ b/appbuilder/core/components/doc_parser/doc_parser.py @@ -0,0 +1,136 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +文档解析 +""" +import os +import json +import base64 +from typing import Dict, Any +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.component import Component, Message +from appbuilder.utils.logger_util import logger +from appbuilder.core.components.doc_parser.base import ParserConfig, ParseResult + + +class DocParser(Component): + """ + 文档解析组件,用于对文档的内容进行解析。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + file_path = "./test.pdf" # 待解析的文件路径 + msg = Message(file_path) + parser = appbuilder.DocParser() + parse_result = parser(msg) + + """ + name: str = "doc_parser" + tool_desc: Dict[str, Any] = {"description": "parse document content"} + base_url: str = "/v1/bce/xmind/parser" + config: ParserConfig = ParserConfig() + + def set_config(self, config: ParserConfig): + """ + 设置解析配置 + """ + self.config = config + + def make_parse_result(self, response: Dict): + """ + 将解析结果的内容转化成ParseResult的结构 + """ + para_nodes = response["para_nodes"] if response["para_nodes"] is not None else [] + catalog = response["catalog"] if response["catalog"] is not None else [] + pdf_data = response["pdf_data"] + title_node_ids = [title["node_id"] for title in catalog] if catalog else [] + page_contents = [] + for content in response["file_content"]: + page_content = {"page_num": content["page_num"], "page_width": content["page_size"]["width"], + "page_height": content["page_size"]["height"], "page_angle": content["page_angle"], + "page_type": content["page_content"]["type"], "page_layouts": [], "page_titles": [], + "page_tables": []} + for layout_item in content["page_content"]["layout"]: + if layout_item["node_id"] in title_node_ids: + continue + if layout_item["type"] == "table": + page_content["page_tables"].append(layout_item) + if para_nodes: + para_nodes[layout_item["node_id"]]["table"] = layout_item + table_row = [] + for i in range(len(layout_item["matrix"])): + cell_index = layout_item["matrix"][i] + row_markdown = "|" + "|".join( + [layout_item["children"][index]["text"] for index in set(cell_index)]) + "|" + if i != len(layout_item["matrix"]) - 1: + row_markdown += "\n" + table_row.append(row_markdown) + para_nodes[layout_item["node_id"]]["text"] = "".join(table_row) + else: + page_content["page_layouts"].append(layout_item) + page_contents.append(page_content) + + for title in catalog: + page_num = title["position"][0]["pageno"] + page_contents[page_num]["page_titles"].append( + {"text": title["text"], "type": title["level"], "box": title["position"][0]["box"], + "node_id": title["node_id"]}) + parse_result = {"para_node_tree": para_nodes, "page_contents": page_contents, "pdf_data": pdf_data} + # parse_result = ParseResult.parse_obj(parse_result) + return parse_result + + def run(self, input_message: Message, return_raw=False) -> Message: + """ + 对传入的文件进行解析 + 参数: + input_message (Message[str]): 输入为文件的路径 + return_raw (bool): 是否返回云端服务的原始结果 + 返回: + parse_result (Message[ParseResult]): 文件的解析结果。 + """ + file_path = input_message.content + + if not isinstance(file_path, str): + raise ValueError("file_path should be str type") + + with open(file_path, "rb") as f: + param = self.config.dict(by_alias=True) + param["data"] = base64.b64encode(f.read()).decode() + param["name"] = os.path.basename(file_path) + payload = json.dumps({"file_list": [param]}) + headers = { + "Authorization": self.secret_key, + "Content-Type": "application/json" + } + response = self.s.post(url=self.service_url(self.base_url), headers=headers, data=payload) + self.check_response_header(response) + self.check_response_json(response.json()) + response = response.json() + if response["error_code"] != 0: + logger.error("doc parser service log_id {} err {}".format(response["log_id"], response["error_msg"])) + raise AppBuilderServerException(response["error_msg"]) + parse_result = self.make_parse_result(response["result"]["result_list"][0]) + if return_raw: + parse_result["raw"] = response + + parse_result = ParseResult.parse_obj(parse_result) + return Message(parse_result) diff --git a/appbuilder/core/components/doc_parser/image/table.png b/appbuilder/core/components/doc_parser/image/table.png new file mode 100644 index 0000000000000000000000000000000000000000..6d371e9f99646cf3bc5773aea51f5390bf24d502 GIT binary patch literal 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zQWS5-zvs<)J|Mxv2KOY%!Vs)Rk_WW90SxOU1~4(9JF6+N@UyEWNzoBtgC!`iklbK{ zr=vV!7k)KpAPqdNFq#)_3`R&){}_5IB|WyGcLk$E8~tdxq`a}Vr9scZA==kprDW>sZDYqICw9PU8PniD+8XhZwB!K#O zB(wSN4khwg;qPq7vqk*$^{YPZ|L>(3lVL|aT9ft0mJ7v8bkvYW3J~k;AcY}VMR&to zUBmq=_Fx#a`khg8t?{69in ZzTvm^q~59DeTIR)0J17F)l$YG{{ Message: + """ + 对输入的解析文档结果,按照各标题层级,处理为多个段落结果 + + 参数: + message (obj:`Message`): 上游docparser的文档解析结果 + + 返回: + obj:`Message`: 文档分隔后的段落结果 + + Examples: + + .. code-block:: python + + from appbuilder.core.components.doc_parser.doc_parser import DocParser + from appbuilder.core.components.doc_splitter.doc_splitter import DocSplitter + from appbuilder.core.message import Message + + # 先解析 + msg = Message("./test_title_splitter.docx") + parser = DocParser() + parse_result = parser(msg, return_raw=True) + + # 基于parser的结果切分段落 + splitter = TitleSplitter() + res_paras = splitter(parse_result) + + # 打印结果 + print(res_paras.content) + """ + + parse_result = input_message.content + if not isinstance(parse_result, ParseResult): + raise ValueError("message.content type must be a ParseResult") + + para_node_tree = parse_result.para_node_tree + doc_segments = [] + paragraphs = [] + segment = DocSegment() + for i in range(1, len(para_node_tree)): + node = para_node_tree[i] + # 去掉页眉页脚 + if node.para_type == "head_tail": + continue + + if node.para_type[:5] != "title": + segment.content += " " + node.text + # 下一个node是title或当前node是最后一个node,代表当前的标题层级segment结束 + if i < len(para_node_tree) - 1 and para_node_tree[i + 1].para_type[:5] == "title" or i == len( + para_node_tree) - 1: + segment.title = self._get_title(para_node_tree, node.parent, []) + doc_segments.append(segment) + paragraphs_text = " ".join(segment.title) + " " + segment.content + paragraphs.append({"text": paragraphs_text, "node_id": i}) + segment = DocSegment() + + if segment.content: + segment.title = self._get_title(para_node_tree, node.parent, []) + doc_segments.append(segment) + paragraphs_text = " ".join(segment.title) + " " + segment.content + paragraphs.append({"text": paragraphs_text, "node_id": i}) + + return Message({"doc_segments": doc_segments, "paragraphs": paragraphs}) diff --git a/appbuilder/core/components/embeddings/README.md b/appbuilder/core/components/embeddings/README.md new file mode 100644 index 000000000..d96c6c3db --- /dev/null +++ b/appbuilder/core/components/embeddings/README.md @@ -0,0 +1,81 @@ +# 向量计算(Embedding) + +## 简介 + +语义向量计算组件(Embedding)支持将文本转化为用数值表示的向量形式,用于文本检索、信息推荐、知识挖掘等场景 + +Embedding-V1,是基于百度文心大模型技术的文本表示模型,在Embedding模块中,我们使用Embedding-V1作为默认模型 + +## 基本用法 + +### 初始化 + +```python +import appbuilder +from appbuilder import Message +# 请先确保您设置了密钥 +embedding = appbuilder.Embedding() +``` + +### 使用单条字符串测试 + +请注意,您必须确保字符串的token长度小于384 + +```python +out = embedding("hello world!") +# 得到一个长度为384的float数组 +print(out.content) +``` + +### 使用多条字符串测试 + +```python +outs = embedding.batch(["hello", "world"]) +# 得到一个长度为 2 x 384的float 二维数组 +print(out.conetnt) +``` + +### 使用上游的Message作为输入 + +```python +query = Message("你好,世界!") +out = embedding(query) +# 得到一个长度为384的float数组 +print(out.content) +``` + +### 批量运行 + +```python +query = Message([ + "你好", + "世界" +]) +outs = embedding.batch(query) +# 得到一个长度为 2 x 384的float 二维数组 +print(outs.content) +``` + +## 参数说明 + +### 初始化参数说明 + +无 + +### 调用参数说明 + +#### 单条字符串 + +```python +embedding("hello world!") +``` + +- text:【必须】一个类型为`string`的句子,长度不能超过384,通常为用户的输入 + +#### 多条字符串 + +```python +embedding.batch(["hello", "world"]) +``` + +- texts:【必须】一个类型为`List[string]`的句子数组,每个元素长度不能超过384,通常为和用户输入相关的文本候选集 diff --git a/appbuilder/core/components/embeddings/__init__.py b/appbuilder/core/components/embeddings/__init__.py new file mode 100644 index 000000000..4b831f64c --- /dev/null +++ b/appbuilder/core/components/embeddings/__init__.py @@ -0,0 +1,6 @@ +""" +init +""" + +from .component import Embedding +from .base import EmbeddingBaseComponent diff --git a/appbuilder/core/components/embeddings/base.py b/appbuilder/core/components/embeddings/base.py new file mode 100644 index 000000000..a6ee0b973 --- /dev/null +++ b/appbuilder/core/components/embeddings/base.py @@ -0,0 +1,76 @@ +""" +base +""" + +# Copyright (c) 2023 Baidu, Inc. 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. + + +from abc import abstractmethod +from typing import List, Union + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments + + +class EmbeddingBaseComponent(Component): + """ + EmbeddingBaseComponent + """ + + name: str + version: str + meta: ComponentArguments + base_url: str = "" + + @abstractmethod + def run(self, text: Union[Message[str], str]) -> Message[List[float]]: + """ + Args: + message: str + Returns: + embeddings: List[float] + """ + + async def arun(self, text: Union[Message[str], str]) -> Message[List[float]]: + """ + Args: + message: str + Returns: + embeddings: List[float] + """ + + # embedding don't need be async, just return it + return self.run(text) + + @abstractmethod + def batch(self, texts: Union[Message[List[str]], List[str]]) -> Message[List[List[float]]]: + """ + Args: + message: List[str] + Returns: + embeddings: List[List[float]] + """ + + def abatch(self, texts: Union[Message[List[str]], List[str]]) -> Message[List[List[float]]]: + """ + Args: + message: List[str] + Returns: + embeddings: List[List[float]] + """ + + # embedding don't need be async, just return it + return self.batch(texts) diff --git a/appbuilder/core/components/embeddings/component.py b/appbuilder/core/components/embeddings/component.py new file mode 100644 index 000000000..13911060d --- /dev/null +++ b/appbuilder/core/components/embeddings/component.py @@ -0,0 +1,141 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +""" +ernie bot embedding +""" + +from typing import Union, List + +from appbuilder.core.message import Message +from appbuilder.core.components.embeddings.base import EmbeddingBaseComponent +from appbuilder.core.component import ComponentArguments + +from appbuilder.core._exception import AppBuilderServerException + + +class EmbeddingArgs(ComponentArguments): + """ernie bot embedding配置""" + + text: Union[Message[str], str] + + +class Embedding(EmbeddingBaseComponent): + """ + Embedding + + Embedding-V1是基于百度文心大模型技术的文本表示模型,将文本转化为用数值表示的向量形式,用于文本检索、信息推荐、知识挖掘等场景。 + + Examples: + + .. code-block:: python + + import appbuilder + from appbuilder import Message + + os.environ["APPBUILDER_TOKEN"] = '...' + + embedding = appbuilder.Embedding() + + embedding_single = embedding(Message("hello world!")) + + embedding_batch = embedding.batch(Message(["hello", "world"])) + """ + + name: str = "embedding" + version: str = "v1" + + meta = EmbeddingArgs + + base_url: str = "/v1/bce/wenxinworkshop/ai_custom/v1/embeddings/" + + def __init__(self, type='embedding-v1'): + """Embedding""" + self.base_url = self.base_url + type + + super().__init__(self.meta) + + def _check_response_json(self, data: dict): + """ + check_response_json for embedding + """ + + self.check_response_json(data) + if "error_code" in data and "error_msg" in data: + raise AppBuilderServerException( + service_err_code=data['error_code'], + service_err_message=data['error_msg'], + ) + + def _request(self, payload: dict) -> dict: + """ + request to gateway + """ + + resp = self.s.post( + url=self.service_url(self.base_url), + headers={ + "X-Appbuilder-Authorization": f"{self.secret_key}", + "Content-Type": "application/json", + }, + json=payload, + ) + self.check_response_header(resp) + self._check_response_json(resp.json()) + + return resp.json() + + def _batchify(self, texts: List[str], batch_size: int = 16) -> List[List[str]]: + """ + batchify input text list + """ + + if batch_size > 16: + raise ValueError(f"The max Embedding batch_size is 16, but got {batch_size}") + + return [ + texts[i : i + batch_size] for i in range(0, len(texts), batch_size) + ] + + def _batch(self, texts: List[str]) -> Message[List[List[float]]]: + """ + batch run implement + """ + + batches = self._batchify(texts) + results = [] + for batch in batches: + result = self._request({"input": batch}) + results.extend(result['data']) + results = Message([result['embedding'] for result in results]) + + return results + + def run(self, text: Union[Message[str], str]) -> Message[List[float]]: + """ + run + """ + + _text = text if isinstance(text, str) else text.content + + return Message(self._batch([_text]).content[0]) + + def batch(self, texts: Union[Message[List[str]], List[str]]) -> Message[List[List[float]]]: + """ + batch run + """ + + _texts = texts if isinstance(texts, list) else texts.content + + return self._batch(_texts) diff --git a/appbuilder/core/components/extract_table/README.md b/appbuilder/core/components/extract_table/README.md new file mode 100644 index 000000000..6a6788fe3 --- /dev/null +++ b/appbuilder/core/components/extract_table/README.md @@ -0,0 +1,44 @@ +# 表格抽取组件(ExtractTableFromDoc) + +表格抽取组件(ExtractTableFromDoc)是用于文档表格处理的组件,从文档中抽取表格。支持对文档表格大小进行限制,限制后自动进行拆分、跨页合并等处理;支持合并表格上文,提取的表格为Markdown格式。 + +## 基本用法 +下面是一个基本用法的样例 + +```python +import os +import json + +from appbuilder.utils.logger_util import logger +from appbuilder import Message, ExtractTableFromDoc, DocParser + + +# 设置环境变量 +os.environ["GATEWAY_URL"] = "..." + + +# 测试文档解析器使用默认配置,xxx为待解析的文档路径。 +msg = Message("xxx") +parser = DocParser() +# ExtractTableFromDoc输入为文档原始解析结果,此处需要带上原始结果,return_raw=True. +doc = parser(msg, return_raw=True).content.raw + +# 抽取文档中的表格 +parser = ExtractTableFromDoc() +result = parser.run(Message(doc)) + +logger.info("Tables: {}".format( + json.dumps(result.content, ensure_ascii=False)) +) +``` + +## 参数说明 +配置参数说明: + +* message (Message): 文档原始解析结果。 +* table_max_size (int): 单个表格的长度的最大值(包含上文),按字符数即len(table_str)统计,默认为800。如果表格超长,则会被拆分成多个子表格,拆分的最小粒度为表格的行。若单行就超长,则会强制按table_max_size截断。截断时会优先截断上文,尽量保留表格内容。 +* doc_node_num_before_table (int): 表格前附加的上文DocParser Node的数量,默认为1。范围:1~10。 + +输出结果说明: + +* 类型: list(二维)。解析出来的文档表格,如果元素长度为1,则对应原文档中格式化后的长度不超过`table_max_size`的表格;如果元素长度>1,则是对应原文档中一个大表格,该表格被拆分成的多个子表格,以满足设置大小。输出结果数据结构样例:`[[{table1}], [{table2-part1}, {table2-part2}]]` \ No newline at end of file diff --git a/appbuilder/core/components/extract_table/__init__.py b/appbuilder/core/components/extract_table/__init__.py new file mode 100644 index 000000000..3d69cf78e --- /dev/null +++ b/appbuilder/core/components/extract_table/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +"""__init__""" + diff --git a/appbuilder/core/components/extract_table/component.py b/appbuilder/core/components/extract_table/component.py new file mode 100644 index 000000000..8908433b8 --- /dev/null +++ b/appbuilder/core/components/extract_table/component.py @@ -0,0 +1,107 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +文档表格转换 +""" +import os +import json + +from appbuilder.core.component import Component, Message, ComponentArguments +from appbuilder.utils.logger_util import logger + + +class ExtractTableFromDoc(Component): + """ 文档表格抽取 + """ + name: str = "extract_table_from_doc" + #TODO: 隐藏base_url,@tangwei12统一修改 + base_url = "/rpc/2.0/cloud_hub/v1/ai_engine/copilot_engine/v1/api/doc_search_tools/doc_table_to_markdown_parser" + meta: ComponentArguments = ComponentArguments(tool_desc={ + "description": "Extract table from doc, table format is markdown", + }) + + def _input_check(self, message: Message, table_max_size, doc_node_num_before_table): + """ para_check + """ + if table_max_size < 30: + raise ValueError("table_max_size must be >= 30") + if doc_node_num_before_table < 1 or doc_node_num_before_table > 10: + raise ValueError("doc_node_num_before_table must be >=1, <=10]") + obj = message.content.get("result", {}).get("result_list", []) + if len(obj) < 1: + raise ValueError("Input check failed, it must be raw_doc_parser output.") + + def _post_process(self, resp): + """ pass + """ + resp = resp["result"] + data = [] + for table in resp.get("mdtables", []): + tmp = [] + for sub_table in table: + # print(sub_table["para"]) + sub_table = sub_table.get("para", "").split("表:\n|") + if len(sub_table) < 2: + context = sub_table[0] + tmp.append({"para": context[:self.table_max_size]}) + else: + context, table_str = sub_table + table_str = "|" + table_str + remain_len = self.table_max_size - len(table_str) + if remain_len < 1: + table_str = table_str[:self.table_max_size] + else: + table_str = context[-remain_len:] + table_str + tmp.append({"para": table_str}) + data.append(tmp) + return data + + def run(self, message: Message, table_max_size: int = 800, doc_node_num_before_table: int = 1): + """ + 将文档原始解析结果,请求云端进行表格抽取,返回表格列表。 + + Args: + message (Message): 文档原始解析结果。 + table_max_size (int): 单个表格的长度的最大值(包含上文),按字符数即len(table_str)统计,默认为800。如果表格超长,则会被拆\ + 分成多个子表格,拆分的最小粒度为表格的行。若单行就超长,则会强制按table_max_size截断。截断时会优先截断上文,尽量保留表格内容。 + doc_node_num_before_table (int): 表格前附加的上文DocParser Node的数量,默认为1。范围:1~10。 + + Returns: + Message: 返回解析后的消息实体对象 + Message.content (list): 解析出来的文档表格,list(二维)。解析出来的文档表格,如果元素长度为1,则对应原文档中格式化后的\ + 长度不超过`table_max_size`的表格;如果元素长度>1,则是对应原文档中一个大表格,该表格被拆分成的多个子表格,以满足设置\ + 大小。输出结果数据结构样例:`[[{table1}], [{table2-part1}, {table2-part2}]]` + + Raises: + ValueError: 当输入参数不为文档原始解析结果时,或值不合法时,抛出异常。 + """ + self._input_check(message, table_max_size, doc_node_num_before_table) + self.table_max_size = table_max_size + params = { + "xmind_res": message.content, + "single_table_size": self.table_max_size, + "field_before_table_cnt": doc_node_num_before_table + } + url = self.service_url(sub_path="", prefix=self.base_url) + # logger.info("request url: {}, headers: {}".format(url, headers)) + resp = self.s.post(url=url, data=json.dumps(params), headers=self.auth_header()) + + self.check_response_header(resp) + resp = resp.json() + self.check_response_json(resp) + resp = self._post_process(resp) + return Message(resp) diff --git a/appbuilder/core/components/general_ocr/README.md b/appbuilder/core/components/general_ocr/README.md new file mode 100644 index 000000000..0f7c75368 --- /dev/null +++ b/appbuilder/core/components/general_ocr/README.md @@ -0,0 +1,43 @@ +# 通用文字识别-高精度版(GeneralOCR) + +## 简介 + +通用文字识别组件(GeneralOCR)支持多场景、多语种、高精度的文字识别服务,对图片/文件全部文字内容进行检测识别。 +## 基本用法 + +以下是一个简单的例子来演示如何开始使用GeneralOCR组件: + +```python +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' + +with open("./general_ocr_test.png", "rb") as f: + general_ocr = appbuilder.GeneralOCR() + out = general_ocr.run(appbuilder.Message(content={"raw_image": f.read()})) +print(out.content) +``` +首先,我们导入appbuilder,然后使用`appbuilder.GeneralOCR()`实例化一个GeneralOCR对象。然后我们设置环境变量APPBUILDER_TOKEN。然后我们打开一个图片文件,并使用run方法进行文字识别,打印得到的识别结果。 + +## 参数说明 + +### 初始化参数 + +`GeneralOCR` 初始化无需参数。 + +### 调用参数 + +- `message (obj: Message)`: 输入图片或图片url下载地址用于执行识别操作. 例如: `Message(content={"raw_image": b"..."})` 或 `Message(content={"url": "https://image/download/url"})`。 +- `timeout (float, 可选)`: HTTP超时时间。 +- `retry (int, 可选)`: HTTP重试次数。 + +返回的message定义: +- (Message): 模型识别结果。例如: Message(content={"words_result":[{"words":"100"}, {"words":"G8"}]}) + +## 高级用法 + +目前该模块仅提供基础通用文字识别功能。 + + +## 更新记录和贡献 +* 通用文字识别能力 (2023-12) diff --git a/appbuilder/core/components/general_ocr/__init__.py b/appbuilder/core/components/general_ocr/__init__.py new file mode 100644 index 000000000..c33303636 --- /dev/null +++ b/appbuilder/core/components/general_ocr/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2023 Baidu, Inc. 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. diff --git a/appbuilder/core/components/general_ocr/component.py b/appbuilder/core/components/general_ocr/component.py new file mode 100644 index 000000000..eea2a53d0 --- /dev/null +++ b/appbuilder/core/components/general_ocr/component.py @@ -0,0 +1,105 @@ +# 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. + +r"""general ocr component.""" +import base64 +import json + +import requests + +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.component import Component +from appbuilder.core.components.general_ocr.model import * +from appbuilder.core.message import Message + + +class GeneralOCR(Component): + r""" + 提供通用文字识别能力,在通用文字识别的基础上,提供更高精度的识别服务,支持更多语种识别(丹麦语、荷兰语、马来语、 + 瑞典语、印尼语、波兰语、罗马尼亚语、土耳其语、希腊语、匈牙利语、泰语、越语、阿拉伯语、印地语及部分中国少数民族语言), + 并将字库从1w+扩展到2w+,能识别所有常用字和大部分生僻字。 + + Examples: + + .. code-block:: python + + import appbuilder + general_ocr = appbuilder.GeneralOCR() + os.environ["APPBUILDER_TOKEN"] = '...' + + with open("./general_ocr_test.png", "rb") as f: + out = general_ocr.run(appbuilder.Message(content={"raw_image": f.read()})) + print(out.content) + + """ + + def run(self, message: Message, timeout: float = None, retry: int = 0) -> Message: + r""" 输入图片并识别其中的文字 + + 参数: + message (obj: `Message`): 输入图片或图片url下载地址用于执行识别操作. 举例: Message(content={"raw_image": b"..."}) + 或 Message(content={"url": "https://image/download/url"}). + timeout (float, 可选): HTTP超时时间 + retry (int, 可选): HTTP重试次数 + + 返回: message (obj: `Message`): 模型识别结果. 举例: Message(content={"words_result":[{"words":"100"}, + {"words":"G8"}]}) + """ + inp = GeneralOCRInMsg(**message.content) + request = GeneralOCRRequest() + if inp.raw_image: + request.image = base64.b64encode(inp.raw_image) + if inp.url: + request.url = inp.url + result = self._recognize(request, timeout, retry) + result_dict = proto.Message.to_dict(result) + out = GeneralOCROutMsg(**result_dict) + return Message(content=out.dict()) + + def _recognize(self, request: GeneralOCRRequest, timeout: float = None, + retry: int = 0) -> GeneralOCRResponse: + r"""调用底层接口进行通用文字识别 + 参数: + request (obj: `GeneralOCRRequest`) : 通用文字识别输入参数 + + 返回: + response (obj: `GeneralOCRResponse`): 通用文字识别返回结果 + """ + if not request.image and not request.url and not request.pdf_file and not request.ofd_file: + raise ValueError("one of image or url or must pdf_file or ofd_file be set") + data = GeneralOCRRequest.to_dict(request) + if self.retry.total != retry: + self.retry.total = retry + headers = self.auth_header() + headers['content-type'] = 'application/x-www-form-urlencoded' + url = self.service_url("/v1/bce/aip/ocr/v1/accurate_basic") + response = self.s.post(url, headers=headers, data=data, timeout=timeout) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__._check_service_error(data) + request_id = self.response_request_id(response) + ocr_response = GeneralOCRResponse.from_json(payload=json.dumps(data)) + ocr_response.request_id = request_id + return ocr_response + + @staticmethod + def _check_service_error(data: dict): + r"""个性化服务response参数检查 + 参数: + request (dict) : 通用文字识别body返回 + 返回: + 无 + """ + if "error_code" in data or "error_msg" in data: + raise AppBuilderServerException(service_err_code=data.get("error_code"), + service_err_message=data.get("error_msg")) diff --git a/appbuilder/core/components/general_ocr/model.py b/appbuilder/core/components/general_ocr/model.py new file mode 100644 index 000000000..ceaac3022 --- /dev/null +++ b/appbuilder/core/components/general_ocr/model.py @@ -0,0 +1,278 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +"""general ocr model.""" +import proto + +from typing import List +from pydantic import BaseModel + + +# PB definition +class GeneralOCRRequest(proto.Message): + """通用ocr识别请求体 + + 属性: + image (str): + 可选。图像内容的base64编码。 + url (str): + 可选。图像的URL地址,经过base64编码。 + 图像大小必须小于4MB,图像的最短边长大于15像素,最长边长大于4096像素。 + pdf_file (str): + 可选。PDF文件内容的base64编码。 + pdf_file_num (str): + 可选。PDF文件的页数。 + ofd_file (str): + 可选。OFD(Open Format Document)文件内容的base64编码。 + ofd_file_num (str): + 可选。OFD文件的页数。 + language_type (str): + 可选。文本使用的语言类型。默认为"CHN_ENG"。 + 可能的取值包括: + - "auto_detect": 自动检测语言并识别。 + - "CHN_ENG": 中英文混合。 + - "ENG": 英文。 + - "JAP": 日文。 + - "KOR": 韩文。 + - "FRE": 法文。 + - "SPA": 西班牙文。 + - "POR": 葡萄牙文。 + - "GER": 德文。 + - "ITA": 意大利文。 + - "RUS": 俄文。 + - "DAN": 丹麦文。 + - "DUT": 荷兰文。 + - "MAL": 马来文。 + - "SWE": 瑞典文。 + - "IND": 印度尼西亚文。 + - "POL": 波兰文。 + - "ROM": 罗马尼亚文。 + - "TUR": 土耳其文。 + - "GRE": 希腊文。 + - "HUN": 匈牙利文。 + - "THA": 泰文。 + - "VIE": 越南文。 + - "ARA": 阿拉伯文。 + - "HIN": 印地文。 + detect_direction (str): + 可选。是否检测文本方向。默认为"false"。 + 可能的取值包括: + - "true": 检测文本方向。 + - "false": 不检测文本方向。 + paragraph (str): + 可选。是否输出段落信息。默认为"false"。 + 可能的取值包括: + - "true": 输出段落信息。 + - "false": 不输出段落信息。 + probability (str): + 可选。是否输出置信度。默认为"false"。 + 可能的取值包括: + - "true": 返回识别结果中每行的置信度。 + - "false": 不返回置信度。 + """ + image: str = proto.Field( + proto.STRING, + number=1, + ) + url: str = proto.Field( + proto.STRING, + number=2, + ) + pdf_file: str = proto.Field( + proto.STRING, + number=3, + ) + pdf_file_num: str = proto.Field( + proto.STRING, + number=4, + optional=True, + ) + ofd_file: str = proto.Field( + proto.STRING, + number=5, + ) + ofd_file_num: str = proto.Field( + proto.STRING, + number=6, + ) + language_type: str = proto.Field( + proto.STRING, + number=7, + ) + detect_direction: str = proto.Field( + proto.STRING, + number=8, + ) + paragraph: str = proto.Field( + proto.STRING, + number=9, + ) + probability: str = proto.Field( + proto.STRING, + number=10, + ) + + +class GeneralOCRResponse(proto.Message): + """通用ocr识别结果 + + 属性: + log_id (int): + 必填。用于问题跟踪的唯一日志ID。 + direction (int): + 可选。当detect_direction=true时的图像方向。 + - -1: 未定义。 + - 0: 正常。 + - 1: 逆时针旋转90度。 + - 2: 逆时针旋转180度。 + - 3: 逆时针旋转270度。 + words_result_num (int): + 必填。识别结果的数量。 + words_result (List[Dict[str, Any]]): + 必填。识别结果的数组。 + - words (str): 识别出的文本。 + - probability (Dict[str, float]): 识别结果中每行的置信度值。 + 包括平均值、方差和最小置信度值。 + 当probability=true时返回。 + paragraphs_result (List[Dict[str, Any]]): + 可选。段落检测结果。当paragraph=true时返回。 + - words_result_idx (List[int]): 包含在段落中的行索引。 + paragraphs_result_num (int): + 可选。段落检测结果的数量。当paragraph=true时返回。 + pdf_file_size (str): + 可选。输入PDF文件的总页数。当pdf_file参数有效时返回。 + ofd_file_size (str): + 可选。输入OFD文件的总页数。当ofd_file参数有效时返回。 + + """ + request_id: str = proto.Field( + proto.STRING, + number=1, + ) + log_id: int = proto.Field( + proto.UINT64, + number=2, + ) + direction: int = proto.Field( + proto.INT32, + number=3, + ) + words_result_num: int = proto.Field( + proto.UINT32, + number=4, + ) + words_result: 'WordResult' = proto.RepeatedField( + proto.MESSAGE, + number=5, + message='WordResult' + ) + paragraphs_result: 'ParagraphResult' = proto.RepeatedField( + proto.MESSAGE, + number=6, + message='ParagraphResult' + ) + paragraphs_result_num: int = proto.Field( + proto.UINT32, + number=7, + ) + pdf_file_size: str = proto.Field( + proto.STRING, + number=8, + ) + ofd_file_size: str = proto.Field( + proto.STRING, + number=9, + ) + + +class WordResult(proto.Message): + """ 识别结果列表. + + 属性: + - words (str): 识别出的文本。 + - probability (Dict[str, float]): 识别结果中每行的置信度值。 + 包括平均值、方差和最小置信度值。 + 当probability=true时返回。 + """ + words: str = proto.Field( + proto.STRING, + number=1, + ) + probability: 'Probability' = proto.Field( + proto.MESSAGE, + number=2, + message='Probability' + ) + + +class Probability(proto.Message): + """置信度 + + 属性: + - average (float): 每行的平均置信度 + - variance (float): 每行置信度的方差 + - minimum (float):每行的最小置信度 + """ + + average: float = proto.Field( + proto.FLOAT, + number=1, + ) + variance: float = proto.Field( + proto.FLOAT, + number=2, + ) + min: float = proto.Field( + proto.FLOAT, + number=3, + ) + + +class ParagraphResult(proto.Message): + """ + 段落检测结果,当paragraph=true时将返回该字段。 + """ + words_result_idx: int = proto.Field( + proto.INT32, + number=1, + ) + + +class GeneralOCRInMsg(BaseModel): + """ 通用文字识别输入消息 + + 属性: + raw_image(bytes): 图像原始内容 + url(str): 图像下载链接 + """ + raw_image: bytes = b'' # 原始图片byte数组 + url: str = "" # 图片可下载链接 + + +class Words(BaseModel): + """ 识别文字 + + 属性: + words(str):识别文字结果 + """ + words: str + + +class GeneralOCROutMsg(BaseModel): + """ 识别文字结果列表 + + 属性: + words_result([]array):识别文字结果列表 + """ + words_result: List['Words'] diff --git a/appbuilder/core/components/landmark_recognize/README.md b/appbuilder/core/components/landmark_recognize/README.md new file mode 100644 index 000000000..98f96f99f --- /dev/null +++ b/appbuilder/core/components/landmark_recognize/README.md @@ -0,0 +1,51 @@ +# 地标识别(LandmarkRecognition) + +## 简介 +地表识别组件(LandmarkRecognition)可以识别12万中外著名地标、热门景点,可返回地标名称。 + +## 基本用法 +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' +# 使用with语句以读取文件方式打开文件,并获取文件字节流 +with open("xxxx.jpg", "rb") as f: + # 输入参数为一张图片 + inp = appbuilder.Message(content={"raw_image": f.read()}) + # 进行地标识别 + landmark_recognize = appbuilder.LandmarkRecognition() + out = landmark_recognize.run(inp) + # 打印识别结果 + print(out.content) # for example: {"landmark": "狮身人面相"} + +``` +## 参数说明 +组件不需要初始化参数。 + +### 参数说明 +run函数接收的参数定义: + +- message (Message, 必选): 输入图片或图片url下载地址用于执行识别操作。例如:Message(content={"raw_image": b"..."}) 或 Message(content={"url": "https://image/download/url"}) +- timeout (float, 可选): HTTP超时时间。 +- retry (int, 可选): HTTP重试次数。 + +返回的message定义: + +- (Message): 模型识别结果。例如: Message(content={"landmark": b"狮身人面相"}) + +## 高级用法 +该组件同时支持通过传入图片的URL地址进行地标识别 +```python + +import appbuilder + +# 输入参数为图片的url +inp = appbuilder.Message(content={"url": "https://image/download/url"}) +landmark_recognize = appbuilder.LandmarkRecognition() + +# 进行地标识别 +out = landmark_recognize.run(inp) +# 打印识别结果 +print(out.content) # for example: {"landmark": "狮身人面相"} +``` diff --git a/appbuilder/core/components/landmark_recognize/__init__.py b/appbuilder/core/components/landmark_recognize/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/landmark_recognize/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/landmark_recognize/component.py b/appbuilder/core/components/landmark_recognize/component.py new file mode 100644 index 000000000..e1f12ee32 --- /dev/null +++ b/appbuilder/core/components/landmark_recognize/component.py @@ -0,0 +1,103 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""landmark recognize component.""" +import base64 + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.landmark_recognize.model import * + + +class LandmarkRecognition(Component): + r""" + 识别地标组件,即对于输入的一张图片(可正常解码,且长宽比适宜),输出图片中的地标识别结果 + + Examples: + + .. code-block:: python + + import appbuilder + landmark_recognize = appbuilder.LandmarkRecognition() + + os.environ["APPBUILDER_TOKEN"] = '...' + with open("xxxx.jpg", "rb") as f: + inp = appbuilder.Message(content={"raw_image": f.read()}) + out = landmark_recognize.run(inp) + # 打印识别结果 + print(out.content) # eg: {"landmark": "狮身人面相"} + """ + + def run(self, message: Message, timeout: float = None, retry: int = 0) -> Message: + r""" 输入图片并识别其中的地标 + + 参数: + message (obj: `Message`): 输入图片或图片url下载地址用于执行识别操作. 举例: Message(content={"raw_image": b"..."}) + 或 Message(content={"url": "https://image/download/uel"}). + timeout (float, 可选): HTTP超时时间 + retry (int, 可选): HTTP重试次数 + + 返回: + message (obj: `Message`): 模型识别结果. 举例: Message(content={"landmark": b"狮身人面相"}) + """ + inp = LandmarkRecognitionInMsg(**message.content) + request = LandmarkRecognitionRequest() + if inp.raw_image: + request.image = base64.b64encode(inp.raw_image) + if inp.url: + request.url = inp.url + response = self.__recognize(request, timeout, retry) + out = LandmarkRecognitionOutMsg(landmark=response.result.get("landmark", "")) + return Message(content=dict(out)) + + def __recognize(self, request: LandmarkRecognitionRequest, timeout: float = None, + retry: int = 0) -> LandmarkRecognitionResponse: + r"""调用底层接口进行地标识别 + + 参数: + request (obj: `LandmarkRecognitionRequest`) : 地标识别输入参数 + + 返回: + response (obj: `LandmarkRecognitionResponse`): 地标识别返回结果 + """ + + if not request.image and not request.url: + raise ValueError("one of image or url must be set") + data = LandmarkRecognitionRequest.to_dict(request) + if retry != self.retry.total: + self.retry.total = retry + headers = self.auth_header() + headers['content-type'] = 'application/x-www-form-urlencoded' + url = self.service_url("/v1/bce/aip/image-classify/v1/landmark") + response = self.s.post(url, data=data, timeout=timeout, headers=headers) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__.__check_service_error(data) + return LandmarkRecognitionResponse(data, request_id=self.response_request_id(response)) + + @staticmethod + def __check_service_error(data: dict): + r"""个性化服务response参数检查 + + 参数: + request (dict) : 地标识别body返回 + 返回: + 无 + """ + + if "error_code" in data or "error_msg" in data: + raise AppBuilderServerException(service_err_code=data.get("error_code"), + service_err_message=data.get("error_msg")) diff --git a/appbuilder/core/components/landmark_recognize/model.py b/appbuilder/core/components/landmark_recognize/model.py new file mode 100644 index 000000000..57bbe3a3a --- /dev/null +++ b/appbuilder/core/components/landmark_recognize/model.py @@ -0,0 +1,83 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +"""Landmark recognition model.""" + +from typing import MutableMapping + +import proto +from pydantic import BaseModel + + +class LandmarkRecognitionRequest(proto.Message): + r"""地标识别请求参数 + + 属性: + image (str, 可选): 图像base64编码结果. + url (str, 可选): 图像下载链接,base64编码后结果小于4MB, 短边大于15px,长边小于4096px. + """ + image: str = proto.Field( + proto.STRING, + number=1, + optional=True, + ) + url: str = proto.Field( + proto.STRING, + number=2, + optional=True, + ) + + +class LandmarkRecognitionResponse(proto.Message): + r"""地标识别返回结果 + + 属性: + log_id (int): 随机日志ID + result (MutableMapping[str, str]): 地标识别结果, eg: {"landmark": "狮身人面像"}. + request_id(str): 服务链路追踪ID. + """ + log_id: int = proto.Field( + proto.INT64, + number=1 + ) + result: MutableMapping[str, str] = proto.MapField( + proto.STRING, + proto.STRING, + number=2, + ) + request_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class LandmarkRecognitionInMsg(BaseModel): + """ 地标识别输入消息 + + 属性: + raw_image(bytes): 图像原始内容 + url(str): 图像下载链接 + """ + raw_image: bytes = b'' + url: str = "" + + +class LandmarkRecognitionOutMsg(BaseModel): + """ 地标识别输出消息 + + 属性: + landmark(str): 地标识别结果 + """ + landmark: str diff --git a/appbuilder/core/components/llms/__init__.py b/appbuilder/core/components/llms/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/llms/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/llms/base.py b/appbuilder/core/components/llms/base.py new file mode 100644 index 000000000..e33e03503 --- /dev/null +++ b/appbuilder/core/components/llms/base.py @@ -0,0 +1,320 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +import json +import uuid +from enum import Enum + +import requests +from appbuilder.core.constants import GATEWAY_URL, GATEWAY_INNER_URL +from pydantic import BaseModel, Field, ValidationError, HttpUrl, validator +from pydantic.types import confloat + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.utils.logger_util import logger +from typing import Dict, List, Optional, Any + +from appbuilder.core.component import ComponentArguments +from appbuilder.core._exception import AppBuilderServerException + + +class CompletionRequest(object): + r"""ShortSpeechRecognitionRequest.""" + params = None + response_mode = "blocking" + + def __init__(self, params: Dict[str, Any] = None, response_mode: str = None, **kwargs): + r""" __init__ the client state. + """ + self.params = params + self.response_mode = response_mode + + +class ModelArgsConfig(BaseModel): + stream: bool = Field(default=False, description="是否流式响应。默认为 False。") + temperature: confloat(gt=0.0, le=1.0) = Field(default=1e-10, description="模型的温度参数,范围从 0.0 到 1.0。") + + +class ModelDefineConfig(BaseModel): + model: Optional[str] = Field(..., description="模型的名称") + + @validator("model") + def check_and_convert_name(cls, v): + """检查并转换模型真实调用。 + + Args: + cls (Any): 无用参数,仅在方法内部使用。 + v (str): 需要验证和转换的真实调用URL。 + + Returns: + str: 返回转换后的模型名称,如果输入的模型名称不在预定义映射表中则抛出ValueError异常。 + + Raises: + ValueError: 如果输入的模型名称不在预定义映射表中,则抛出此异常。 + + """ + name_mapping = { + "ernie-bot": '{}/rpc/2.0/cloud_hub/v1/bce/wenxinworkshop/ai_custom/v1' + '/chat/completions'.format(GATEWAY_INNER_URL), + "ernie-bot-4": '{}/rpc/2.0/cloud_hub/v1/bce/wenxinworkshop/ai_custom/v1' + '/chat/completions_pro'.format(GATEWAY_INNER_URL), + "eb-turbo-appbuilder": '{}/rpc/2.0/cloud_hub/v1/bce/wenxinworkshop/ai_custom/v1/' + 'chat/ai_apaas'.format(GATEWAY_INNER_URL) + } + + if v not in name_mapping: + allowed_names = ", ".join(name_mapping.keys()) + raise ValueError(f"model name must be one of [{allowed_names}]") + + return name_mapping[v] + + +class CompletionResponse(object): + r"""ShortSpeechRecognitionResponse.""" + error_no = 0 + error_msg = "" + result = None + log_id = "" + + def __init__(self, response, stream: bool = False): + """初始化客户端状态。""" + self.error_no = 0 + self.error_msg = "" + self.log_id = response.headers.get("X-Appbuilder-Request-Id", None) + + if stream: + # 流式数据处理 + def stream_data(): + for chunk in response.iter_content(chunk_size=None): + answer = self.parse_stream_data(chunk) + if answer is not None: + yield answer + + self.result = stream_data() + else: + # 非流式数据的处理 + if response.status_code != 200: + self.error_no = response.status_code + self.error_msg = "error" + self.result = response.text + + raise AppBuilderServerException(self.log_id, self.error_no, self.result) + + else: + data = response.json() + + if "code" in data and "message" in data and "requestId" in data: + raise AppBuilderServerException(self.log_id, data["code"], data["message"]) + + if "code" in data and "message" in data and "status" in data: + raise AppBuilderServerException(self.log_id, data["code"], data["message"]) + + self.result = data.get("answer", None) + + def parse_stream_data(self, data_chunk): + """解析流式数据块并提取answer字段""" + + data_str = data_chunk.decode('utf-8') + + if data_str.startswith("data: "): + parsed_str = data_str[6:] + else: + parsed_str = data_str + + print("xxx: " + parsed_str) + + try: + data = json.loads(parsed_str) + + if "code" in data and "message" in data and "requestId" in data: + raise AppBuilderServerException(self.log_id, data["code"], data["message"]) + + if "code" in data and "message" in data and "status" in data: + raise AppBuilderServerException(self.log_id, data["code"], data["message"]) + + return data.get("answer", "") + except json.JSONDecodeError: + # 处理可能的解析错误 + print("error: " + parsed_str) + raise AppBuilderServerException("unknown", "unknown", parsed_str) + + def get_stream_data(self): + """获取处理过的流式数据的迭代器""" + return self.result + + def to_message(self): + """将响应结果转换为Message对象。 + + Returns: + Message: Message对象。 + + """ + message = Message() + message.id = self.log_id + message.content = self.result + return message + + +class CompletionBaseComponent(Component): + name: str + version: str + base_url: str = "/rpc/2.0/cloud_hub/v1/ai_engine/copilot_engine" + model_name: str = "" + model_url: str = "" + + model_config: Dict[str, Any] = { + "model": { + "provider": "baidu", + "name": "ERNIE-Bot", + "completion_params": { + "temperature": 1e-10, + "top_p": 0, + "presence_penalty": 0, + "frequency_penalty": 0 + } + } + } + + def __init__(self, meta: ComponentArguments, model=None, secret_key: Optional[str] = None, + gateway: str = ""): + """ + Args: + meta (ComponentArguments): 组件参数信息 + model (str, optional): 模型名称. Defaults to None. + secret_key (Optional[str], optional): 可选的密钥. Defaults to None. + gateway (str, optional): 网关地址. Defaults to "". + + """ + super().__init__(meta=meta, secret_key=secret_key, gateway=gateway) + + model_config_inputs = ModelDefineConfig(**{"model": model}) + + self.model_name = model + self.model_url = model_config_inputs.model + + if not self.model_url and not self.model_name: + raise ValueError("model_name or model_url must be provided") + + self.version = self.version + + def gene_request(self, query, inputs, response_mode, message_id, model_config): + """"send request""" + + data = { + "query": query, + "inputs": inputs, + "response_mode": response_mode, + "user": message_id, + "model_config": model_config + } + + request = CompletionRequest(data, response_mode) + return request + + def gene_response(self, response, stream: bool = False): + """generate response""" + response = CompletionResponse(response, stream) + return response + + def run(self, *args, **kwargs): + """ + Run the model with given input and return the result. + + Args: + **kwargs: Keyword arguments for both StyleWritingComponent and common component inputs. + + Returns: + obj:`Message`: Output message after running model. + """ + + specific_params = {k: v for k, v in kwargs.items() if k in self.meta.__fields__} + model_config_params = {k: v for k, v in kwargs.items() if k in ModelArgsConfig.__fields__} + + try: + specific_inputs = self.meta(**specific_params) + model_config_inputs = ModelArgsConfig(**model_config_params) + except ValidationError as e: + raise ValueError(e) + + query, inputs, response_mode, user_id = self.get_compeliton_params(specific_inputs, model_config_inputs) + model_config = self.get_model_config(model_config_inputs) + request = self.gene_request(query, inputs, response_mode, user_id, model_config) + response = self.completion(self.version, self.base_url, request) + + if response.error_no != 0: + raise AppBuilderServerException(service_err_code=response.error_no, service_err_message=response.error_msg) + + return response.to_message() + + def get_compeliton_params(self, specific_inputs, model_config_inputs): + """获取模型请求参数""" + inputs = specific_inputs.extract_values_to_dict() + + query = inputs["query"] + user_id = str(uuid.uuid4()) + + if model_config_inputs.stream: + response_mode = "streaming" + else: + response_mode = "blocking" + + return query, inputs, response_mode, user_id + + def get_model_config(self, model_config_inputs): + """获取模型配置信息""" + if self.model_url: + self.model_config["model"]["url"] = self.model_url + + if self.model_name: + self.model_config["model"]["name"] = self.model_name + + self.model_config["model"]["completion_params"]["temperature"] = model_config_inputs.temperature + return self.model_config + + def completion(self, version, base_url, request: CompletionRequest, timeout: float = None, + retry: int = 0, ) -> CompletionResponse: + r"""Send a byte array of an audio file to obtain the result of speech recognition.""" + + headers = self.auth_header() + headers["Content-Type"] = "application/json" + + completion_url = "/" + self.version + "/api/llm/" + self.name + + stream = True if request.response_mode == "streaming" else False + url = self.service_url(completion_url, self.base_url) + + logger.debug( + "request url: {}, method: {}, json: {}, headers: {}".format(url, + "POST", + request.params, + headers)) + + response = self.s.post(url, json=request.params, headers=headers, timeout=timeout, stream=stream) + + logger.debug( + "request url: {}, method: {}, json: {}, headers: {}, response: {}".format(url, "POST", + request.params, + headers, + response)) + return self.gene_response(response, stream) + + @staticmethod + def check_service_error(data: dict): + r"""check service internal error. + :param: data: dict, service return body data. + :rtype: . + """ + if "err_no" in data and "err_msg" in data: + if data["err_no"] != 0: + raise AppBuilderServerException(service_err_code=data["err_no"], service_err_message=data["err_msg"]) diff --git a/appbuilder/core/components/llms/dialog_summary/README.md b/appbuilder/core/components/llms/dialog_summary/README.md new file mode 100644 index 000000000..c5bdd48b6 --- /dev/null +++ b/appbuilder/core/components/llms/dialog_summary/README.md @@ -0,0 +1,50 @@ +# 会话小结(DialogSummary) + +## 简介 +会话小结(DialogSummary)基于生成式大模型对一段用户与坐席的对话生成总结,结果按{"诉求": "", "回应": "", "解决情况": ""}格式输出。适用于运营商、金融、汽车等多种场景的对话总结。 + +## 基本用法 + +为了快速开始使用会话小结组件,您可以参考以下步骤: + +```python +import appbuilder +import os + +os.environ["APPBUILDER_TOKEN"] = '...' + +model = "eb-turbo-appbuilder" +dialog_summary = appbuilder.DialogSummary(model) +text = "用户:喂我想查一下我的话费\n坐席:好的女士您话费余的话还有87.49元钱\n用户:好的知道了谢谢\n坐席:嗯不客气祝您生活愉快再见" +answer = dialog_summary(appbuilder.Message(text)) +``` + +## 参数说明 + +### 初始化参数 +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 +- `message (Message)`: 输入消息,用于模型的主要输入内容。这是一个必需的参数。 +- `stream (bool)`: 是否以流式形式返回响应。默认为 False。 +- `temperature (float)`: 模型的生成概率调整参数。范围为 0.0 到 1.0,默认为 1e-10。 + +### 返回值 +- 返回一个 `Message` 对象,包含模型运行后的输出消息。 + +## 高级用法 + +暂无 + +## 示例和案例研究 + +目前暂无具体的实际应用案例。 + +## API文档 + +暂无 + +## 更新记录和贡献 + +- 初始版本发布。 +- 如您希望为会话小结组件贡献代码或反馈,请参考 [贡献指南](#)。 diff --git a/appbuilder/core/components/llms/dialog_summary/__init__.py b/appbuilder/core/components/llms/dialog_summary/__init__.py new file mode 100644 index 000000000..af026111d --- /dev/null +++ b/appbuilder/core/components/llms/dialog_summary/__init__.py @@ -0,0 +1,2 @@ +"""DialogSummary""" +from .component import DialogSummary \ No newline at end of file diff --git a/appbuilder/core/components/llms/dialog_summary/component.py b/appbuilder/core/components/llms/dialog_summary/component.py new file mode 100644 index 000000000..2b01371cd --- /dev/null +++ b/appbuilder/core/components/llms/dialog_summary/component.py @@ -0,0 +1,78 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +""" dialog_summary +""" +from pydantic import BaseModel, Field + +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments + + +class DialogSummaryArgs(ComponentArguments): + """会话小结生成配置 + """ + message: Message = Field(..., + variable_name='query', + description='输入对话文本,用于生成小结') + + +class DialogSummary(CompletionBaseComponent): + """ + 会话小结大模型组件, 基于生成式大模型对一段用户与坐席的对话生成总结,结果按{"诉求": "", "回应": "", "解决情况": ""}格式输出。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + dialog_summary = appbuilder.DialogSummary(model="ernie-bot-4") + text = "用户:喂我想查一下我的话费\n坐席:好的女士您话费余的话还有87.49元钱\n用户:好的知道了谢谢\n坐席:嗯不客气祝您生活愉快再见" + answer = dialog_summary(appbuilder.Message(text)) + + """ + name = "dialog_summary" + version = "v1" + meta = DialogSummaryArgs + + def __init__(self, model=None): + """初始化DialogSummary模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(DialogSummaryArgs, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, optional): 指定是否以流式形式返回响应。默认为 False。 + temperature(float, optional): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + + """ + + return super().run(message=message, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/is_complex_query/README.md b/appbuilder/core/components/llms/is_complex_query/README.md new file mode 100644 index 000000000..e8d7c57b1 --- /dev/null +++ b/appbuilder/core/components/llms/is_complex_query/README.md @@ -0,0 +1,59 @@ +# 复杂Query判定(IsComplexQuery) + +## 简介 +复杂Query判定组件(IsComplexQuery)可以根据输入的提问进行初步的分类,区分简单问题和复杂问题,以便后续运用不同的处理流程处理。可应用于知识问答场景。 + +## 基本用法 + +下面是一个基本的使用示例: + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = "..." + +is_complex_query = appbuilder.IsComplexQuery(model="eb-turbo-appbuilder") + +msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" +msg = appbuilder.Message(msg) +answer = is_complex_query(msg) + +print("Answer: \n{}".format(answer.content)) +``` + +## 参数说明 + +* 初始化参数说明 + + - `model` (str|None): model (str|None): 模型名称,用于指定要使用的千帆模型。 + +* 调用参数说明 + + - `message (obj:Message)`: 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + + - `stream (bool, 可选)`: 指定是否以流式形式返回响应。默认为 False。 + + - `temperature (float, 可选)`: 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + +返回值: + +- `obj:Message`: 模型运行后产生的输出消息。 + +## 高级用法 + +你可以根据特定的场景调整参数来获得更精确的结果,例如: + +```python +# 流式返回, 调整模型temperature参数 +answer = is_complex_query(msg, stream=True, temperature=0.5) +``` + +## 示例和案例研究 + +### 示例 + +- **场景:** 用户提出问题 +- **输入:** "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" +- **输出:** 分析:这个问题涉及到吸塑包装盒在工业化生产和物流运输中的重要性。回答这个问题需要从多个角度来考虑,比如生产方面、运输方面、环保方面等。这需要对吸塑包装盒有深入的了解,并且需要考虑到生产、运输等各个环节。因此,这是一个复杂问题。 +类型:复杂问题 \ No newline at end of file diff --git a/appbuilder/core/components/llms/is_complex_query/__init__.py b/appbuilder/core/components/llms/is_complex_query/__init__.py new file mode 100644 index 000000000..642a00742 --- /dev/null +++ b/appbuilder/core/components/llms/is_complex_query/__init__.py @@ -0,0 +1,2 @@ + +from .component import IsComplexQuery diff --git a/appbuilder/core/components/llms/is_complex_query/component.py b/appbuilder/core/components/llms/is_complex_query/component.py new file mode 100644 index 000000000..ea65fa3fc --- /dev/null +++ b/appbuilder/core/components/llms/is_complex_query/component.py @@ -0,0 +1,79 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +""" is complex query +""" +from pydantic import Field + +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from appbuilder.core.components.llms.base import CompletionBaseComponent + + +class IsComplexQueryMeta(ComponentArguments): + """ IsComplexQueryMeta + """ + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的输入,一般为问题。") + + +class IsComplexQuery(CompletionBaseComponent): + """ 基于输入的问题, 对问题进行初步的分类,方便下游使用不同类型的流程来处理当前的简单问题/复杂问题。广泛用于知识问答场景。 + + Examples: + + .. code-block:: python + import os + import appbuilder + + os.environ["APPBUILDER_TOKEN"] = "..." + + is_complex_query = appbuilder.IsComplexQuery(model="eb-turbo-appbuilder") + + msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" + msg = appbuilder.Message(msg) + answer = is_complex_query(msg) + + print("Answer: \n{}".format(answer.content)) + """ + name = "is_complex_query" + version = "v1" + meta = IsComplexQueryMeta + + def __init__(self, model=None): + """初始化IsComplexQueryMeta任务。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(IsComplexQueryMeta, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 给定输入(message)到模型运行,同时指定运行参数,并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/mrc/README.md b/appbuilder/core/components/llms/mrc/README.md new file mode 100644 index 000000000..028bf4a51 --- /dev/null +++ b/appbuilder/core/components/llms/mrc/README.md @@ -0,0 +1,95 @@ +# 阅读理解问答(MRC) + +## 简介 +阅读理解问答(MRC)组件是基于生成式大模型的阅读理解问答系统。该组件支持拒答、澄清、重点强调、友好性提升、溯源等多种功能,可用于回答用户提出的问题。 + +## 基本用法 + +### 快速开启 + +```python +import appbuilder +import os + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +# 创建MRC对象 +mrc_component = appbuilder.MRC() + +#初始化参数 +msg = "残疾人怎么办相关证件" +msg = appbuilder.Message(msg) +context_list = appbuilder.Message(["""如何办理残疾人通行证一、残疾人通行证办理条件: +1、持有中华人民共和国残疾人证,下肢残疾或者听力残疾; +2、持有准驾车型为C1(听力残疾)、C2(左下肢残疾、听力残疾)""", + """3、本人拥有本市登记核发的非营运小型载客汽车,车辆须在检验有效期内,并有有效交强险凭证, +C5车辆加装操纵辅助装置后已办理变更手续。二、办理地点:北京市朝阳区左家庄北里35号: +北京市无障碍环境建设促进中心"""]) + +# 模拟运行MRC基本组件 +result = mrc_component.run(msg, context_list) + +# 输出运行结果 +print(result) +``` + +## 参数说明 + +### 初始化参数 +- `model`: 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 + +- `msg (obj:Message)`: 输入消息,包含用户提出的问题。这是一个必需的参数。 +- `context_list (obj:Message)`: 用户输入的问题对应的段落文本列表。这是一个必需的参数。 +- `reject (bool, 可选)`: 拒绝开关,如果为 True,则启用拒绝能力。默认为 False。 +- `clarify (bool, 可选)`: 澄清开关,如果为 True,则启用澄清能力。默认为 False。 +- `highlight (bool, 可选)`: 重点强调开关,如果为 True,则启用重点强调能力。默认为 False。 +- `friendly (bool, 可选)`: 友好性提升开关,如果为 True,则启用友好性提升能力。默认为 False。 +- `cite (bool, 可选)`: 溯源开关,如果为 True,则启用溯源能力。默认为 False。 +- `stream (bool, 可选)`: 指定是否以流式形式返回响应。默认为 False。 +- `temperature (float, 可选)`: 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + +### 返回值 +- 返回一个 `Message` 对象,包含模型运行后的输出消息。 + + +## 高级用法 +该组件的高级用法包括定制化的输入处理、输出处理,以及更复杂的调用场景。用户可以根据具体需求扩展组件功能,实现个性化的问答系统。 +包括如下功能: +1、拒答 +2、澄清反问 +3、重点强调 +4、友好度提升 +5、溯源 + + +### 代码样例 +```python +import appbuilder +import os + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +# 创建MRC对象 +mrc_component = appbuilder.MRC() + +#初始化参数 +msg = "残疾人怎么办相关证件" +msg = appbuilder.Message(msg) +context_list = appbuilder.Message(["""如何办理残疾人通行证一、残疾人通行证办理条件: +1、持有中华人民共和国残疾人证,下肢残疾或者听力残疾; +2、持有准驾车型为C1(听力残疾)、C2(左下肢残疾、听力残疾)""", + """3、本人拥有本市登记核发的非营运小型载客汽车,车辆须在检验有效期内,并有有效交强险凭证, +C5车辆加装操纵辅助装置后已办理变更手续。二、办理地点:北京市朝阳区左家庄北里35号: +北京市无障碍环境建设促进中心"""]) + +# 模拟运行MRC组件,开启拒答、澄清追问、重点强调、友好性提升和溯源能力五个功能 +result = mrc_component.run(msg, context_list, reject=True, + clarify=True, highlight=True, friendly=True, cite=True) + +# 输出运行结果 +print(result) +``` \ No newline at end of file diff --git a/appbuilder/core/components/llms/mrc/__init__.py b/appbuilder/core/components/llms/mrc/__init__.py new file mode 100644 index 000000000..8873193bf --- /dev/null +++ b/appbuilder/core/components/llms/mrc/__init__.py @@ -0,0 +1,2 @@ + +from .component import MRC diff --git a/appbuilder/core/components/llms/mrc/component.py b/appbuilder/core/components/llms/mrc/component.py new file mode 100644 index 000000000..1957e2ad1 --- /dev/null +++ b/appbuilder/core/components/llms/mrc/component.py @@ -0,0 +1,150 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.llms.base import CompletionBaseComponent, ModelArgsConfig +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from pydantic import Field + + +class MrcArgs(ComponentArguments): + """阅读理解问答配置""" + message: Message = Field(..., + variable_name="query", + description="输入用户query,例如'千帆平台都有哪些大模型?'") + context_out_list: list = Field(..., + variable_name="context_out_list", + description="用户输入检索片段list," + "例如[content1, content2, content3,...],也可以为空, 即[]") + reject: bool = Field(..., + variable_name="reject", + description="控制大模型拒答能力的开关,为true即为开启拒答功能,为false即为关闭拒答功能") + clarify: bool = Field(..., + variable_name="clarify", + description="控制大模型澄清能力的开关,为true即为开启澄清反问功能,为false即为关闭澄清反问功能") + highlight: bool = Field(..., + variable_name="highlight", + description="控制大模型重点强调能力的开关,为true即为开启重点强调功能,为false即为关闭重点强调功能") + friendly: bool = Field(..., + variable_name="friendly", + description="控制大模型友好对提升难过能力的开关," + "为true即为开启友好度提升功能,为false即为关闭友好度提升功能") + cite: bool = Field(..., + variable_name="cite", + description="控制大模型溯源能力的开关,为true即为开启溯源功能,为false即为关闭溯源功能") + + +class MRC(CompletionBaseComponent): + """ + 阅读理解问答组件,基于大模型进行阅读理解问答,支持拒答、澄清、重点强调、友好性提升、溯源等多种功能,可用于回答用户提出的问题。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + mrc_component = appbuilder.MRC() + + # 获取功能说明 + instructions = mrc_component.get_instruction_set() + + # 输出功能说明 + for key, value in instructions.items(): + print(f"{key}: {value}") + + # 模拟运行MRC组件,开启澄清和友好性提升功能 + result = mrc_component.run(appbuilder.Message("什么是人工智能?"), clarify=True, friendly=True) + + # 输出运行结果 + print(result) + + """ + name = "mrc" + version = "v1" + meta: MrcArgs + + def __init__(self, model=None): + """初始化MRC(阅读理解问答)模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(MrcArgs, model=model) + + def __get_instruction_set(self): + """ + return: json格式的instruction_set + """ + return {"reject": "如果答案不在搜索结果中得到,则在答案开头说明:" + "“当前文档库找不到对应的答案,我可以尝试用我的常识来回答你”," + "并基于你的常识给出答案。", + "clarify": "当问题比较模糊,而检索结果包含多种可能的答案时,反向提问用户想问的具体内容," + "让用户补充关键信息后以完整的query重新发问。", + "highlight": "可以对答案中的核心部分进行markdown加粗(**加粗内容**)。", + "friendly": "答案尽量用礼貌用语开头,涉及到条目列举的内容需要在前面加序号并做分点描述," + "必要时可在每一点前面做小标题的汇总,并可以用总-分-总的形式展示分点式答案内容,使得答案内容可读性更强。", + "cite": "使用引用标记来标注回答内容参考的搜索结果序号,例如^[1]^ (引用单个搜索结果),^[1][2]^(引用多个搜索结果)," + "其中方括号中的数字是搜索结果序号。引用标记只能出现在句尾标点符号前。"} + + def run(self, message, context_list, reject=False, clarify=False, + highlight=False, friendly=False, cite=False, stream=False, temperature=1e-10): + """ + 运行阅读理解问答模型并返回结果。 + + 参数: + msg (obj:`Message`): 输入消息,包含用户提出的问题。这是一个必需的参数。 + context_list (obj:`Message`):用户输入的问题对应的段落文本列表。这是一个必需的参数 + reject (bool, 可选): 拒答开关,如果为 True,则启用拒答能力。默认为 False。 + clarify (bool, 可选): 澄清开关,如果为 True,则启用澄清能力。默认为 False。 + highlight (bool, 可选): 重点强调开关,如果为 True,则启用重点强调能力。默认为 False。 + friendly (bool, 可选): 友好性提升开关,如果为 True,则启用友好性提升能力。默认为 False。 + cite (bool, 可选): 溯源开关,如果为 True,则启用溯源能力。默认为 False。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + instruction_set = self.__get_instruction_set() + context_list = context_list.content + inputs = { + "query": message.content, + "context_out": "\n\n".join(f"[{i + 1}] {s}" for i, s in enumerate(context_list)), + "reject": instruction_set["reject"] if reject else None, + "clarify": instruction_set["clarify"] if clarify else None, + "highlight": instruction_set["highlight"] if highlight else None, + "friendly": instruction_set["friendly"] if friendly else None, + "cite": instruction_set["cite"] if cite else None, + } + model_config_inputs = ModelArgsConfig(**{"stream": stream, "temperature": temperature}) + model_config = self.get_model_config(model_config_inputs) + query = inputs["query"] + response_mode = "streaming" if stream else "blocking" + user_id = message.id + + request = self.gene_request(query, inputs, response_mode, user_id, model_config) + response = self.completion(self.version, self.base_url, request) + + if response.error_no != 0: + raise AppBuilderServerException(service_err_code=response.error_no, service_err_message=response.error_msg) + + return response.to_message() + diff --git a/appbuilder/core/components/llms/nl2pandas/README.md b/appbuilder/core/components/llms/nl2pandas/README.md new file mode 100644 index 000000000..107d97945 --- /dev/null +++ b/appbuilder/core/components/llms/nl2pandas/README.md @@ -0,0 +1,37 @@ +# 自然语言转pandas (nl2pandas) + +## 简介 +自然语言转pandas (nl2pandas)这个组件通过理解对表格信息的提问,生成对应语义的可执行Python代码,主要使用Pandas库。它可以用于基于表格的查询,问答等多种场景。 + +## 基本用法 +这里是一个简单示例,展示如何使用自然语言转Pandas组件: + +```python +import os +import appbuilder + +#设置环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +#定义表格信息 假设有一个小学学校表格,包含学校名、所属地区、创办时间、类别、学生人数、教职工人数、教学班数量等列。列名后给出示例(例如清华附小是学校名的示例),以及列值类型(字符串类型、数字值类型),最后给出列名的解释。列之间使用换行符分隔。 +table_info = '''表格列信息如下:\n学校名 : 清华附小 , 字符串类型,代表小学学校的名称\n所属地区 : 西城区 , 字符串类型,表示该小学学校所在的位置\n创办时间 : 1998 , 数字值类型,表示该小学学校的创办时间\n类别 : 公立小学 , 字符串类型,表示该小学学校所在的类别\n学生人数 : 2000 , 数字值类型,表示该小学学校的学生数量\n教职工人数 : 140 , 数字值类型,表示该小学学校的教职工数量\n教学班数量 : 122 , 数字值类型,表示该小学学校的教学班数量''' + +#定义查询问题 +query = "海淀区有哪些学校" +query = appbuilder.Message(query) + +#定义并运行Nl2pandas实例,得到结果 +nl2pandas = appbuilder.Nl2pandasComponent(model="eb-turbo-appbuilder") +answer = nl2pandas(query, table_info = table_info) +``` + +## 参数说明 +### 初始化参数 +* `model` (str): 千帆模型模型名称,例如”eb-turbo-appbuilder“,用于指定千帆模型。 + +### 调用参数 +* `query` (Message 必填): 输入问题,一般是针对表格信息的提问,例如'海淀区的小学有哪些'。建议长度是50字以内。 +* `table_info` (str 必填): 表格信息,是表格列名以及对应列名的举例和释义。 例如:’表格列信息如下:\n学校名 : 清华附小 , 字符串类型,代表小学学校的名称\n所属地区 : 西城区 , 字符串类型,表示该小学学校所在的位置\n创办时间 : 1998 , 数字值类型,表示该小学学校的创办时间\n类别 : 公立小学 , 字符串类型,表示该小学学校所在的类别\n学生人数 : 2000 , 数字值类型,表示该小学学校的学生数量\n教职工人数 : 140 , 数字值类型,表示该小学学校的教职工数量\n教学班数量 : 122 , 数字值类型,表示该小学学校的教学班数量‘ +* `stream` (bool, 可选): 指定是否以流式形式返回响应。默认为Fasle,既blocking的方式返回完整响应。 +* `temperature`(float 可选) :默认为 1e-10,模型配置的温度参数。 +* 返回值:Message 对象,为模型运行后的输出消息。 \ No newline at end of file diff --git a/appbuilder/core/components/llms/nl2pandas/__init__.py b/appbuilder/core/components/llms/nl2pandas/__init__.py new file mode 100644 index 000000000..eb6010646 --- /dev/null +++ b/appbuilder/core/components/llms/nl2pandas/__init__.py @@ -0,0 +1,2 @@ +"""text to pandas""" +from .component import Nl2pandasComponent \ No newline at end of file diff --git a/appbuilder/core/components/llms/nl2pandas/component.py b/appbuilder/core/components/llms/nl2pandas/component.py new file mode 100644 index 000000000..0c807cbb6 --- /dev/null +++ b/appbuilder/core/components/llms/nl2pandas/component.py @@ -0,0 +1,89 @@ +"""text to pandas""" +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" +自然语言转pandas +""" +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message +from pydantic import BaseModel, Field +from appbuilder.core.component import ComponentArguments + + +class Nl2pandasArgs(ComponentArguments): + """自然语言转pandas代码 参数配置""" + message: Message = Field(..., + variable_name="query", + description="输入问题,一般是针对表格信息的提问,例如'海淀区的小学有哪些'") + table_info: str = Field(..., + variable_name="table_info", + description="表格信息,一般是表格列名以及对应列名的举例和释义,例如'表格列信息如下:\n学校名 : 清华附小 , 字符串类型,代表小学学校的名称") + +class Nl2pandasComponent(CompletionBaseComponent): + """ + 自然语言转pandas大模型组件, 基于生成式大模型对query进行理解并生成对应语义的可执行python代码(主要使用pandas),可用于基于表格的查询、问答等多种场景。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + table_info = '''表格列信息如下: + 学校名 : 清华附小 , 字符串类型,代表小学学校的名称 + 所属地区 : 西城区 , 字符串类型,表示该小学学校所在的位置 + 创办时间 : 1998 , 数字值类型,表示该小学学校的创办时间 + 类别 : 公立小学 , 字符串类型,表示该小学学校所在的类别 + 学生人数 : 2000 , 数字值类型,表示该小学学校的学生数量 + 教职工人数 : 140 , 数字值类型,表示该小学学校的教职工数量 + 教学班数量 : 122 , 数字值类型,表示该小学学校的教学班数量 + ''' + query = "海淀区有哪些学校" + query = appbuilder.Message(query) + + nl2pandas = appbuilder.Nl2pandasComponent(model="ernie-bot-4") + answer = nl2pandas(query, table_info = table_info) + """ + name = "nl2pandas" + version = "v1" + meta = Nl2pandasArgs + + def __init__(self, model=None): + """初始化Nl2pandasComponent模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(Nl2pandasArgs, model=model) + + def run(self, message, table_info=None, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + 参数: + query (obj:`Message`): 输入问题,一般是针对表格信息的提问,例如'海淀区的小学有哪些'。这是一个必需的参数。 + table_info (obj:`Message`): 表格信息,是表格列名以及对应列名的举例和释义。无默认值,这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, table_info=table_info, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/oral_query_generation/README.md b/appbuilder/core/components/llms/oral_query_generation/README.md new file mode 100644 index 000000000..09e913e4c --- /dev/null +++ b/appbuilder/core/components/llms/oral_query_generation/README.md @@ -0,0 +1,39 @@ +# 口语化Query生成(OralQueryGeneration) + +## 简介 +口语化Query生成组件(OralQueryGeneration)可以基于输入文本生成与文档内容相关的Query。可用于增强文档索引等场景。 + +## 基本用法 +### 快速开始 +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' + +text = ('文档标题:在OPPO Reno5上使用视频超级防抖\n' + '文档摘要:OPPO Reno5上的视频超级防抖,视频超级防抖3.0,多代视频防抖算法积累,这一代依旧超级防抖超级稳。 开启视频超级' + '防抖 开启路径:打开「相机 > 视频 > 点击屏幕上方的“超级防抖”标识」 后置视频同时支持超级防抖和超级防抖Pro功能,开启超级' + '防抖后手机屏幕将出现超级防抖Pro开关,点击即可开启或关闭。 除此之外,前置视频同样加持防抖算法,边走边拍也能稳定聚焦脸部' + ',实时视频分享您的生活。') +oral_query_generation = appbuilder.OralQueryGeneration(model='eb-turbo-appbuilder') +answer = oral_query_generation(appbuilder.Message(text)) +print(answer.content) +``` + +## 参数说明 +### 初始化参数 +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 +- `message` (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 +- `stream` (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 +- `temperature` (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 +### 返回 +- `Message`: 模型运行后的输出消息。 + +## 更新日志 +### 2023.12.07 +#### [Added] +- 增加口语化Query生成能力。 +- 增加口语化Query生成单元测试。 \ No newline at end of file diff --git a/appbuilder/core/components/llms/oral_query_generation/__init__.py b/appbuilder/core/components/llms/oral_query_generation/__init__.py new file mode 100644 index 000000000..b6627eee1 --- /dev/null +++ b/appbuilder/core/components/llms/oral_query_generation/__init__.py @@ -0,0 +1 @@ +from .component import OralQueryGeneration \ No newline at end of file diff --git a/appbuilder/core/components/llms/oral_query_generation/component.py b/appbuilder/core/components/llms/oral_query_generation/component.py new file mode 100644 index 000000000..5d21581cf --- /dev/null +++ b/appbuilder/core/components/llms/oral_query_generation/component.py @@ -0,0 +1,88 @@ +""" +Copyright (c) 2023 Baidu, Inc. 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. +""" + + +from pydantic import BaseModel, Field + +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments + + +class OralQueryGenerationArgs(ComponentArguments): + """口语化Query生成配置 + """ + """ + message: Message = Field(..., + valiable_name='query', + description='输入文本,用于生成Query') + """ + query: str = Field(..., + valiable_name='query', + description='输入文本,用于生成Query') + + +class OralQueryGeneration(CompletionBaseComponent): + """ + 口语化Query生成,可用于问答场景下对文档增强索引。 + + Examples: + + .. code-block:: python + + import os + import appbuilder + + os.environ["APPBUILDER_TOKEN"] = '...' + + text = ('文档标题:在OPPO Reno5上使用视频超级防抖\n' + '文档摘要:OPPO Reno5上的视频超级防抖,视频超级防抖3.0,多代视频防抖算法积累,这一代依旧超级防抖超级稳。 开启视频超级' + '防抖 开启路径:打开「相机 > 视频 > 点击屏幕上方的“超级防抖”标识」 后置视频同时支持超级防抖和超级防抖Pro功能,开启超级' + '防抖后手机屏幕将出现超级防抖Pro开关,点击即可开启或关闭。 除此之外,前置视频同样加持防抖算法,边走边拍也能稳定聚焦脸部' + ',实时视频分享您的生活。') + oral_query_generation = appbuilder.OralQueryGeneration(model='eb-turbo-appbuilder') + answer = oral_query_generation(appbuilder.Message(text)) + print(answer.content) + """ + name = 'oral_query_generation' + version = 'v1' + meta = OralQueryGenerationArgs + + def __init__(self, model=None): + """初始化口语化Query生成模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + """ + super().__init__(OralQueryGenerationArgs, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + # return super().run(message=message, stream=stream, temperature=temperature) + return super().run(query=message.content, stream=stream, temperature=temperature) \ No newline at end of file diff --git a/appbuilder/core/components/llms/playground/README.md b/appbuilder/core/components/llms/playground/README.md new file mode 100644 index 000000000..a638e1ff3 --- /dev/null +++ b/appbuilder/core/components/llms/playground/README.md @@ -0,0 +1,51 @@ +# 空应用(Playground) + +## 简介 +Playground空应用(Playground)是一款灵活的组件,允许用户自定义prompt模板并执行。它适用于各种场景,特别是在需要自定义输入模板和使用预训练模型进行交互的情况下。 + +# Playground 组件使用手册 + +## 简介 +Playground 是一个灵活的组件,允许用户自定义prompt模板并执行。它适用于各种场景,特别是在需要自定义输入模板和使用预训练模型进行交互的情况下。 + +## 基本用法 +要开始使用 Playground,你需要设置prompt模板和模型名称。以下是一个基本示例: + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = "..." + +play = appbuilder.Playground( + prompt_template="你好,{name},我是{bot_name},{bot_name}是一个{bot_type},我可以{bot_function},你可以问我{bot_question}。", + model="ernie-bot-4" +) +play(appbuilder.Message({"name": "小明", "bot_name": "小红", "bot_type": "聊天机器人", "bot_function": "聊天", "bot_question": "你好吗?"}), stream=False) +``` + +## 参数说明 +### 初始化参数 +- `prompt_template` (str): 输入模板,用于指定prompt格式。 +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 +- `message` (obj:`Message`): 输入消息,必需参数。 +- `stream` (bool, 可选): 是否以流式形式返回响应,默认为 False。 +- `temperature` (float, 可选): 模型配置的温度参数,默认值为 1e-10。 + +### 返回值 +- obj:`Message`: 模型运行后的输出消息。 + +## 高级用法 +此部分可根据实际应用场景提供更复杂的示例和用法说明。 + +## 示例和案例研究 +目前暂无具体案例,将在未来更新。 + +## API文档 +无 + +## 更新记录和贡献 +- 初始版本发布。 +- 如您希望为空模板组件贡献代码或反馈,请参考 [贡献指南](#)。 diff --git a/appbuilder/core/components/llms/playground/__init__.py b/appbuilder/core/components/llms/playground/__init__.py new file mode 100644 index 000000000..2645b2d75 --- /dev/null +++ b/appbuilder/core/components/llms/playground/__init__.py @@ -0,0 +1,2 @@ +"""text to pandas""" +from .component import Playground \ No newline at end of file diff --git a/appbuilder/core/components/llms/playground/component.py b/appbuilder/core/components/llms/playground/component.py new file mode 100644 index 000000000..10a1bbc96 --- /dev/null +++ b/appbuilder/core/components/llms/playground/component.py @@ -0,0 +1,122 @@ +"""text to pandas""" +# Copyright (c) 2023 Baidu, Inc. 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. +from pydantic import Field +import re +from appbuilder.core.component import ComponentArguments +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message + + +class PlaygroundArgs(ComponentArguments): + """空模板参数配置""" + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的主要输入内容") + + +class Playground(CompletionBaseComponent): + """ + 空模板, 支持用户自定义prompt模板,并进行执行 + + Examples: + + .. code-block:: python + + import os + import appbuilder + os.environ["APPBUILDER_TOKEN"] = "..." + + play = appbuilder.Playground(prompt_template="你好,{name},我是{bot_name},{bot_name}是一个{bot_type},我可以{bot_function},你可以问我{bot_question}。", model="ernie-bot-4") + play(appbuilder.Message({"name": "小明", "bot_name": "小红", "bot_type": "聊天机器人", "bot_function": "聊天", "bot_question": "你好吗?"}), stream=False) + + """ + + name = "playground" + version = "v1" + meta = PlaygroundArgs + prompt_template = "" + variable_names = {} + + def __init__(self, prompt_template=None, model=None): + """初始化空模板配置模型。 + + Args: + prompt_t + emplate (str): 输入模板,用于指定prompt格式 + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(PlaygroundArgs, model=model) + + if prompt_template is None: + prompt_template = "{query}" + self.prompt_template = prompt_template + + self.variable_names = self.__parse__(prompt_template) + + def run(self, message, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + + inputs = {} + + if isinstance(message.content, str): + if len(self.variable_names) == 1: + inputs[self.variable_names[0]] = message.content + + if isinstance(message.content, dict): + inputs.update(message.content) + + for key in self.variable_names: + if key not in inputs: + raise ValueError(f"Missing input variable {key} in message {message.content}") + + prompt = self.prompt_template.format(**inputs) + query_message = Message(prompt) + return super().run(message=query_message, stream=stream, temperature=temperature) + + def __parse__(self, prompt_template): + last_end = 0 + results = [] + for match in re.finditer(r"{([a-zA-Z_]\w*)}", prompt_template): + field_name = match.group(1) + start, end = match.span() + + literal_text = prompt_template[last_end:start] + last_end = end + + results.append((literal_text, field_name, '', None)) + + remaining_literal_text = prompt_template[last_end:] + if remaining_literal_text: + results.append((remaining_literal_text, None, None, None)) + + input_variables = [v for _, v, _, _ in results if v is not None] + + return input_variables + + diff --git a/appbuilder/core/components/llms/qa_pair_mining/README.md b/appbuilder/core/components/llms/qa_pair_mining/README.md new file mode 100644 index 000000000..15b031409 --- /dev/null +++ b/appbuilder/core/components/llms/qa_pair_mining/README.md @@ -0,0 +1,81 @@ +# 问答对挖掘(QAPairMining) + +## 简介 +问答对挖掘(QAPairMining)可以基于输入文本内容,快速生成多个问题及对应答案,极大提高信息提炼的效率和准确性。广泛用于在线客服、智能问答等领域。 + +## 基本用法 + +### 快速开始 + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = "..." + +qa_mining = appbuilder.QAPairMining(model="eb-turbo-appbuilder") +# 输入文本(对此文本挖掘问答对) +msg = '2017年,工商银行根据外部宏观环境变化,及时调整业务策略,优化资产负债结构,' + \ + '保持存贷款业务协调发展,提升资产负债配置效率。' + \ + '2018年3月末,工商银行总资产264,937.81亿元,比上年末增加4,067.38亿元.' +msg = appbuilder.Message(msg) +answer = qa_mining(msg) + +print(">>> Output: {}".format(answer.content)) +``` + +## 参数说明 + +### 初始化参数 + +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 + +- `message` (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 +- `stream` (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 +- `temperature` (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + +返回: + +- `Message`: 模型运行后的输出消息。 + +## 高级用法 + +基于一篇文档,快速生成多个问题及对应答案,极大提高信息提炼的效率和准确性. +主要流程如下: + +1. 读取本地文档,文档解析分段,获取段落; +2. 段落作为问答对挖掘的输入,挖掘问答对。 + +### 代码样例 +```python +import os + +from appbuilder.utils.logger_util import logger +from appbuilder import Message, DocParser, DocSplitter, QAPairMining + + +file_path = "xxx.pdf" + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = "...." + +# 解析文档 +msg = Message(file_path) +parser = DocParser() +parse_result = parser.run(msg) + +# 对文档进行分段落 +splitter = DocSplitter() +split_result = splitter(parse_result) + +# 每个段落抽取问答对,并返回结果 +for doc_segment in split_result.content: + qa_mining = QAPairMining() + logger.info("Input: {}".format(doc_segment.content)) + answer = qa_mining(doc_segment) + logger.info("Output: {}".format(answer.content)) + break # debug,只跑1个段落 +``` + diff --git a/appbuilder/core/components/llms/qa_pair_mining/__init__.py b/appbuilder/core/components/llms/qa_pair_mining/__init__.py new file mode 100644 index 000000000..c00ef0368 --- /dev/null +++ b/appbuilder/core/components/llms/qa_pair_mining/__init__.py @@ -0,0 +1,2 @@ + +from .component import QAPairMining diff --git a/appbuilder/core/components/llms/qa_pair_mining/component.py b/appbuilder/core/components/llms/qa_pair_mining/component.py new file mode 100644 index 000000000..6c62f16f8 --- /dev/null +++ b/appbuilder/core/components/llms/qa_pair_mining/component.py @@ -0,0 +1,83 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" """ +from pydantic import Field + +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from appbuilder.core.components.llms.base import CompletionBaseComponent + + +class QAPairMiningMeta(ComponentArguments): + """ QAPairMiningMeta + """ + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的输入,一般为文档段落。") + + +class QAPairMining(CompletionBaseComponent): + """ 基于输入文本内容,快速生成多个问题及对应答案,极大提高信息提炼的效率和准确性.广泛用于在线客服、智能问答等领域。 + + Examples: + + .. code-block:: python + import os + import appbuilder + + os.environ["APPBUILDER_TOKEN"] = "..." + + qa_mining = appbuilder.QAPairMining(model="eb-turbo-appbuilder") + # 输入文本(对此文本挖掘问答对) + msg = '2017年,工商银行根据外部宏观环境变化,及时调整业务策略,优化资产负债结构,' + \ + '保持存贷款业务协调发展,提升资产负债配置效率。' + \ + '2018年3月末,工商银行总资产264,937.81亿元,比上年末增加4,067.38亿元。' + msg = appbuilder.Message(msg) + answer = qa_mining(msg) + + print(">>> Output: {}".format(answer.content)) + + """ + name = "qa_pair_mining" + version = "v1" + meta = QAPairMiningMeta + + def __init__(self, model=None): + """初始化QAPairMining(问答对挖掘)模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(QAPairMiningMeta, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 给定输入(message)到模型运行,同时指定运行参数,并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, stream=stream, temperature=temperature) + diff --git a/appbuilder/core/components/llms/query_decomposition/README.md b/appbuilder/core/components/llms/query_decomposition/README.md new file mode 100644 index 000000000..2a4ac583e --- /dev/null +++ b/appbuilder/core/components/llms/query_decomposition/README.md @@ -0,0 +1,60 @@ +# 复杂Query分解(QueryDecomposition) + +## 简介 +复杂Query分解组件(QueryDecomposition)可以将已经确定为复杂问题的原始问题拆解为一个个简单问题。广泛应用在知识问答场景。 + +## 基本用法 + +下面是一个基本的使用示例: + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = "..." + +query_decomposition = appbuilder.QueryDecomposition(model="eb-turbo-appbuilder") + +msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" +msg = appbuilder.Message(msg) +answer = query_decomposition(msg) + +print("Answer: \n{}".format(answer.content)) +``` + +## 参数说明 + +* 初始化参数说明 + + - `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +* 调用参数说明 + + - `message (obj:Message)`: 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + + - `stream (bool, 可选)`: 指定是否以流式形式返回响应。默认为 False。 + + - `temperature (float, 可选)`: 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + +返回值: + +- `obj:Message`: 模型运行后产生的输出消息。 + +## 高级用法 + +你可以根据特定的场景调整参数来获得更精确的结果,例如: + +```python +# 流式返回, 调整模型temperature参数 +answer = query_decomposition(msg, stream=True, temperature=0.5) +``` + +## 示例和案例研究 + +### 示例 + +- **场景:** 用户提出问题 +- **输入:** "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" +- **输出:** +1. 吸塑包装盒在工业化生产中有什么重要性? +2. 吸塑包装盒在物流运输中有什么重要性? \ No newline at end of file diff --git a/appbuilder/core/components/llms/query_decomposition/__init__.py b/appbuilder/core/components/llms/query_decomposition/__init__.py new file mode 100644 index 000000000..4a7dffe01 --- /dev/null +++ b/appbuilder/core/components/llms/query_decomposition/__init__.py @@ -0,0 +1,2 @@ + +from .component import QueryDecomposition diff --git a/appbuilder/core/components/llms/query_decomposition/component.py b/appbuilder/core/components/llms/query_decomposition/component.py new file mode 100644 index 000000000..90acbfeac --- /dev/null +++ b/appbuilder/core/components/llms/query_decomposition/component.py @@ -0,0 +1,79 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +""" query decomposition +""" +from pydantic import Field + +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from appbuilder.core.components.llms.base import CompletionBaseComponent + + +class QueryDecompositionMeta(ComponentArguments): + """ QueryDecomposition + """ + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的输入,一般为问题。") + + +class QueryDecomposition(CompletionBaseComponent): + """ 尝试对已经判定为复杂问题的原始问题进行拆解,把复杂问题拆解为一个个简单问题。广泛用于知识问答场景。 + + Examples: + + .. code-block:: python + import os + import appbuilder + + os.environ["APPBUILDER_TOKEN"] = "..." + + query_decomposition = appbuilder.QueryDecomposition(model="eb-turbo-appbuilder") + + msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" + msg = appbuilder.Message(msg) + answer = query_decomposition(msg) + + print("Answer: \n{}".format(answer.content)) + """ + name = "query_decomposition" + version = "v1" + meta = QueryDecompositionMeta + + def __init__(self, model=None): + """初始化QueryDecompositionMeta任务。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(QueryDecompositionMeta, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 给定输入(message)到模型运行,同时指定运行参数,并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/query_rewrite/README.md b/appbuilder/core/components/llms/query_rewrite/README.md new file mode 100644 index 000000000..16a959214 --- /dev/null +++ b/appbuilder/core/components/llms/query_rewrite/README.md @@ -0,0 +1,43 @@ +# 多轮改写 (QueryRewrite) + +## 简介 +多轮改写组件 (QueryRewrite) 是一个用于处理多轮对话和查询改写的组件。它主要用于理解和优化用户与机器人的交互过程,进行指代消解及省略补全。该组件支持不同的改写类型,可根据对话历史生成更准确的用户查询。 + +## 基本用法 + +以下是一个简单的例子,展示如何快速开始使用 QueryRewrite 组件: + +```python +import os +import appbuilder + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +# 初始化并使用 QueryRewrite 组件 +query_rewrite = appbuilder.QueryRewrite(model="ernie-bot-4") +answer = query_rewrite(appbuilder.Message(['我应该怎么办理护照?', '您可以查询官网或人工咨询', '我需要准备哪些材料?', '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', '在哪里办']), rewrite_type="带机器人回复") +``` +print(answer) +## 参数说明 + +### 初始化参数 + +model (str|None): 模型名称,用于指定要使用的千帆模型。 + +## 调用参数 + +message (Message): 必传参数,需要改写的文本。 +rewrite_type (RewriteTypeChoices): 可选参数,改写类型选项,可选值为 '带机器人回复'(改写时参考user查询历史和assistant回复历史),'仅用户查询'(改写时参考user查询历史)。 默认是"带机器人回复". +stream (bool): 可选参数,默认为 False,指定是否以流式形式返回响应。 +temperature (float): 可选参数,默认为 1e-10,模型配置的温度参数。 +返回值:Message 对象,为模型运行后的输出消息。 + +## 示例和案例研究 +实际应用中,QueryRewrite 可用于多种场景,如信息检索、智能对话等。 + +## API文档 +更详细的 API 文档将在后续版本中提供。 + +## 更新记录和贡献 +当前版本:v1 diff --git a/appbuilder/core/components/llms/query_rewrite/__init__.py b/appbuilder/core/components/llms/query_rewrite/__init__.py new file mode 100644 index 000000000..fe9a75ac9 --- /dev/null +++ b/appbuilder/core/components/llms/query_rewrite/__init__.py @@ -0,0 +1,2 @@ +"""query_rewrite""" +from .component import QueryRewrite diff --git a/appbuilder/core/components/llms/query_rewrite/component.py b/appbuilder/core/components/llms/query_rewrite/component.py new file mode 100644 index 000000000..d98bde3e1 --- /dev/null +++ b/appbuilder/core/components/llms/query_rewrite/component.py @@ -0,0 +1,130 @@ +"""QueryRewrite""" +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" +多轮改写 +""" +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from pydantic import BaseModel, Field +from enum import Enum +import appbuilder + +class RewriteTypeChoices(Enum): + """""" + user_assistant_user = "带机器人回复" + user_user = "仅用户查询" + + def to_chinese(self): + """ + 将RewriteTypeChoices枚举类中的值转换为中文描述。 + + Args: + 无参数 + + Returns: + 返回一个字典,键是RewriteTypeChoices枚举类的成员,值为对应的中文描述字符串。 + + """ + descriptions = { + RewriteTypeChoices.user_assistant_user: "带机器人回复", + RewriteTypeChoices.user_user: "仅用户查询", + } + return descriptions[self] + + +class QueryRewriteArgs(ComponentArguments): + """多轮改写配置""" + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的主要输入内容,例如'['我应该怎么办理护照?', '您可以查询官网或人工咨询', \ + '我需要准备哪些材料?', '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', '在哪里办']'") + rewrite_type: RewriteTypeChoices = Field(..., + variable_name="rewrite_type", + description="改写类型选项,可选值为 '带机器人回复'(改写时参考user查询历史和assistant回复历史),\ + '仅用户查询'(改写时参考user查询历史)。 默认是'带机器人回复'. ") + + +class QueryRewrite(CompletionBaseComponent): + """ + 多轮改写大模型组件, 基于生成式大模型进行多轮对话query改写的组件。它主要用于理解和优化用户与机器人的交互过程,进行指代消解及省略补全。该组件支持不同的改写类型,可根据对话历史生成更准确的用户查询。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + query_rewrite = appbuilder.QueryRewrite(model="ernie-bot-4") + answer = query_rewrite(appbuilder.Message(['我应该怎么办理护照?', + '您可以查询官网或人工咨询', + '我需要准备哪些材料?', + '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', + '在哪里办']), + rewrite_type="带机器人回复") + + """ + + name = "query_rewrite" + version = "v1" + meta = QueryRewriteArgs + + def __init__(self, model=None): + """QueryRewrite模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(QueryRewriteArgs, model=model) + + def run(self, message, rewrite_type="带机器人回复", stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。输入列表长度不超过10,字符总长度不超过5000. + + 变量: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + rewrite_type (str, optional): 改写类型选项,可选值为 '带机器人回复'(改写时参考user查询历史和assistant回复历史), + '仅用户查询'(改写时参考user查询历史)。 默认是"带机器人回复。 + stream (bool, optional): 指定是否以流式形式返回响应。默认为 False。 + temperature(float, optional): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + 返回: + obj:`Message`: 模型运行后的输出消息。 + + """ + + + if message is None: + raise ValueError("输入消息不能为空") + + sum_len = sum(len(item) for item in message.content) + if len(message.content) > 10 or len(message.content) % 2 == 0: + raise ValueError("非法输入,目前支持5轮以下改写,合法输入列表元素个数为低于10的奇数、即1、3、5、9") + if sum_len > 4000: + raise ValueError("非法输入,字符总长度不超过5000") + if rewrite_type == "带机器人回复": + converted_input = ''.join([f"{'User:' if i % 2 == 0 else 'Assistant:'}\ + {message.content[i]}\n" for i in range(len(message.content))]) + else: + converted_input = ''.join([f"User1: {message.content[i]}\n" for i in range(0, len(message.content), 2)]) + message.content = converted_input + + return super().run(message=message, rewrite_type=rewrite_type, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/similar_question/README.md b/appbuilder/core/components/llms/similar_question/README.md new file mode 100644 index 000000000..8f1284c07 --- /dev/null +++ b/appbuilder/core/components/llms/similar_question/README.md @@ -0,0 +1,59 @@ +# 相似问生成组件(SimilarQuestion) + +## 简介 +相似问生成组件(SimilarQuestion)可以用于基于输入的问题,挖掘出与该问题相关的类似问题。广泛用于客服、问答等场景。 + +## 基本用法 + +### 快速开始 + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = "..." + +similar_question = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder") + +msg = "我想吃冰淇淋,哪里的冰淇淋比较好吃?" +msg = appbuilder.Message(msg) +answer = similar_question(msg) + +print("Answer: \n{}".format(answer.content)) +``` + +## 参数说明 + +### 初始化参数 + +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 + +- `message` (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 +- `stream` (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 +- `temperature` (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + +### 返回值 + +- 返回一个对象 `Message`,包含模型运行后的输出消息。 + +## 高级用法 + +### 特殊场景示例 + +你可以根据特定的场景调整参数来获得更精确的结果,例如: + +```python +# 流式返回, 调整模型temperature参数 +answer = similar_question(msg, stream=True, temperature=0.5) +``` + +## 示例和案例研究 + +### 示例 + +- **场景:** 用户提出问题 +- **输入:** "我想吃冰淇淋,哪里的冰淇淋比较好吃?" +- **输出:** 1. 请问哪里的冰淇淋最美味? 2. 在哪些地方可以品尝到最好的冰淇淋? ..... + diff --git a/appbuilder/core/components/llms/similar_question/__init__.py b/appbuilder/core/components/llms/similar_question/__init__.py new file mode 100644 index 000000000..f62aa4607 --- /dev/null +++ b/appbuilder/core/components/llms/similar_question/__init__.py @@ -0,0 +1,2 @@ + +from .component import SimilarQuestion diff --git a/appbuilder/core/components/llms/similar_question/component.py b/appbuilder/core/components/llms/similar_question/component.py new file mode 100644 index 000000000..4a5352080 --- /dev/null +++ b/appbuilder/core/components/llms/similar_question/component.py @@ -0,0 +1,78 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +""" similar question +""" +from pydantic import Field + +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from appbuilder.core.components.llms.base import CompletionBaseComponent + + +class SimilarQuestionMeta(ComponentArguments): + """ SimilarQuestionMeta + """ + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的输入,一般为问题。") + + +class SimilarQuestion(CompletionBaseComponent): + """ 基于输入的问题, 挖掘出与该问题相关的类似问题。广泛用于客服、问答等场景。 + Examples: + + .. code-block:: python + import os + import appbuilder + + os.environ["APPBUILDER_TOKEN"] = "..." + + qa_mining = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder") + + msg = "我想吃冰淇淋,哪里的冰淇淋比较好吃?" + msg = appbuilder.Message(msg) + answer = qa_mining(msg) + + print("Answer: \n{}".format(answer.content)) + """ + name = "similar_question" + version = "v1" + meta = SimilarQuestionMeta + + def __init__(self, model=None): + """初始化SimilarQuestionMeta任务。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(SimilarQuestionMeta, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 给定输入(message)到模型运行,同时指定运行参数,并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/style_rewrite/README.md b/appbuilder/core/components/llms/style_rewrite/README.md new file mode 100644 index 000000000..82c724f1e --- /dev/null +++ b/appbuilder/core/components/llms/style_rewrite/README.md @@ -0,0 +1,46 @@ +# 风格转写 (StyleRewrite) + +## 简介 +风格转写组件(StyleRewrite) 可以基于生成式大模型对文本的风格进行改写。支持多种文本风格,包括营销、客服、直播、激励及教学话术。 + +## 基本用法 + +以下是一个简单的例子,展示如何快速开始使用 StyleRewrite 组件: + +```python +import os +import appbuilder + +# 设置环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +# 初始化并使用 StyleRewrite 组件 +style_rewrite = appbuilder.StyleRewrite(model="ernie-bot-4") +answer = style_rewrite(appbuilder.Message("文心大模型发布新版"), style="激励话术") +``` + +## 参数说明 + +### 初始化参数 + +model (str|None): 模型名称,用于指定要使用的千帆模型。 + +## 调用参数 + +message (Message): 必传参数,需要改写的文本。 +style (StyleChoices): 可选参数,想要转换的文本风格,默认为"营销话术",目前支持营销、客服、直播、激励及教学五种话术。 +stream (bool): 可选参数,默认为 False,指定是否以流式形式返回响应。 +temperature (float): 可选参数,默认为 1e-10,模型配置的温度参数。 +返回值:Message 对象,为模型运行后的输出消息。 + +## 高级用法 + + +## 示例和案例研究 +实际应用中,StyleRewrite 可用于多种场景,如自动化客服、教育内容生成、营销文案生成等。 + +## API文档 +更详细的 API 文档将在后续版本中提供。 + +## 更新记录和贡献 +当前版本:v1 diff --git a/appbuilder/core/components/llms/style_rewrite/__init__.py b/appbuilder/core/components/llms/style_rewrite/__init__.py new file mode 100644 index 000000000..8637dc58e --- /dev/null +++ b/appbuilder/core/components/llms/style_rewrite/__init__.py @@ -0,0 +1,2 @@ +"""StyleRewrite""" +from .component import StyleRewrite diff --git a/appbuilder/core/components/llms/style_rewrite/component.py b/appbuilder/core/components/llms/style_rewrite/component.py new file mode 100644 index 000000000..aa3d31381 --- /dev/null +++ b/appbuilder/core/components/llms/style_rewrite/component.py @@ -0,0 +1,112 @@ +"""StyleRewrite""" +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" """ +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message + +from appbuilder.core.component import ComponentArguments + +from pydantic import BaseModel, Field +from enum import Enum + + +class StyleChoices(Enum): + """""" + YINGXIAO = "营销话术" + JIAOXUE = "教学话术" + JILI = "激励话术" + KEFU = "客服话术" + ZHIBO = "直播话术" + + def to_chinese(self): + """ + 将StyleChoices枚举类中的值转换为中文描述。 + + Args: + 无参数 + + Returns: + 返回一个字典,键是StyleChoices枚举类的成员,值为对应的中文描述字符串。 + + """ + descriptions = { + StyleChoices.YINGXIAO: "营销话术", + StyleChoices.JIAOXUE: "教学话术", + StyleChoices.JILI: "激励话术", + StyleChoices.KEFU: "客服话术", + StyleChoices.ZHIBO: "直播话术" + } + return descriptions[self] + + +class StyleRewriteArgs(ComponentArguments): + """文本风格转写配置""" + message: Message = Field(..., + variable_name="query", + description="需要改写的文本,该字段为必须字段。") + style: StyleChoices = Field(..., + variable_name + ="style", + description="想要转换的文本风格,目前有营销、客服、直播、激励及教学五种话术可选") + + +class StyleRewrite(CompletionBaseComponent): + """ + 文本风格转写大模型组件, 基于生成式大模型对文本的风格进行改写,支持有营销、客服、直播、激励及教学五种话术。 + + Examples: + + .. code-block:: python + + import os + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + style_rewrite = appbuilder.StyleRewrite(model="ernie-bot-4") + answer = style_rewrite(appbuilder.Message("文心大模型发布新版本"), style="激励话术") + + """ + name = "style_rewrite" + version = "v1" + meta = StyleRewriteArgs + + def __init__(self, model=None): + """初始化StyleRewrite模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(StyleRewriteArgs, model=model) + + def run(self, message, style="营销话术", stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + Args: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + style (str, optional): 想要转换的文本风格,目前有营销、客服、直播、激励及教学五种话术可选. 默认是"营销话术". + stream (bool, optional): 指定是否以流式形式返回响应。默认为 False。 + temperature(float, optional): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + Returns: + obj:`Message`: 模型运行后的输出消息。 + + """ + return super().run(message=message, style=style, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/style_writing/README.md b/appbuilder/core/components/llms/style_writing/README.md new file mode 100644 index 000000000..2830fc429 --- /dev/null +++ b/appbuilder/core/components/llms/style_writing/README.md @@ -0,0 +1,57 @@ +# 风格写作(StyleWriting) + +## 简介 +风格写作组件(StyleWriting)是一款基于生成式大模型进行文本创作的工具,支持多种风格,包括B站、小红书等,适用于编写文案、广告等多种场景。 + +## 基本用法 + +为了快速开始使用风格写作组件,您可以参考以下步骤: + +```python +import appbuilder +import os + +os.environ["APPBUILDER_TOKEN"] = "..." + +model = "eb-turbo-appbuilder" +style_writing = appbuilder.StyleWriting(model) + +query = "帮我写一篇关于人体工学椅的文案" +style = "小红书" +length = 100 + +msg = appbuilder.Message(query) +answer = style_writing(msg, style, length) +``` + +## 参数说明 + +### 初始化参数 +- `model`: 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 +- `message (Message)`: 主要输入内容,例如“帮我生成一个介绍保温杯的话术”。这是一个必需参数。 +- `style_query (str)`: 风格查询选项,可选择 'B站', '小红书', '通用'。默认为 '通用'。 +- `length (int)`: 输出内容的长度,可选 '短' (100), '中' (300), '长' (600)。默认为 100。 +- `stream (bool)`: 是否以流式形式返回响应。默认为 False。 +- `temperature (float)`: 模型的生成概率调整参数。范围为 0.0 到 1.0,默认为 1e-10。 + +### 返回值 +- 返回一个 `Message` 对象,包含模型运行后的输出消息。 + +## 高级用法 + +使用风格写作组件进行更复杂的文本创作,例如调整不同的风格和长度参数来适应特定的写作场景。 + +## 示例和案例研究 + +目前暂无具体的实际应用案例。 + +## API文档 + +更多详细信息,请访问 [风格写作组件API文档](#)。 + +## 更新记录和贡献 + +- 初始版本发布。 +- 如您希望为风格写作组件贡献代码或反馈,请参考 [贡献指南](#)。 diff --git a/appbuilder/core/components/llms/style_writing/__init__.py b/appbuilder/core/components/llms/style_writing/__init__.py new file mode 100644 index 000000000..93fd64649 --- /dev/null +++ b/appbuilder/core/components/llms/style_writing/__init__.py @@ -0,0 +1,17 @@ +""" +Copyright (c) 2023 Baidu, Inc. 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. +""" + +from .component import StyleWriting diff --git a/appbuilder/core/components/llms/style_writing/component.py b/appbuilder/core/components/llms/style_writing/component.py new file mode 100644 index 000000000..1ae0e07a7 --- /dev/null +++ b/appbuilder/core/components/llms/style_writing/component.py @@ -0,0 +1,134 @@ +""" +Copyright (c) 2023 Baidu, Inc. 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. +""" + +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message + +from appbuilder.core.component import ComponentArguments + +from pydantic import BaseModel, Field +from enum import Enum + + +class StyleQueryChoices(Enum): + BILIBILI = "B站" + XIAOHONGSHU = "小红书" + GENERAL = "通用" + + def to_chinese(self): + """ + 将StyleQueryChoices枚举类中的值转换为中文描述。 + + Args: + 无参数 + + Returns: + 返回一个字典,键是StyleQueryChoices枚举类的成员,值为对应的中文描述字符串。 + + """ + descriptions = { + StyleQueryChoices.BILIBILI: "B站", + StyleQueryChoices.XIAOHONGSHU: "小红书", + StyleQueryChoices.GENERAL: "通用", + } + return descriptions[self] + + +class LengthChoices(Enum): + SHORT = 100 # 短 + MEDIUM = 300 # 中 + LONG = 600 # 长 + + def to_chinese(self): + """ + 将LengthChoices枚举对象转换为中文描述。 + + Args: + 无参数 + + Returns: + str: 转换后的中文描述,包括"短"、"中"和"长"。 + + """ + descriptions = { + LengthChoices.SHORT: "短", + LengthChoices.MEDIUM: "中", + LengthChoices.LONG: "长", + } + return descriptions[self] + + +class StyleWritingArgs(ComponentArguments): + """风格写作配置""" + message: Message = Field(..., + variable_name="query", + description="输入消息,用于模型的主要输入内容,例如'帮我生成一个介绍保温杯的话术'") + style_query: StyleQueryChoices = Field(..., + variable_name="style_query", + description="风格查询选项,可选值为 'B站', '小红书', '通用'。") + length: LengthChoices = Field(..., + variable_name="length", + description="输出长度,可选值为 '短' (100), '中' (300), '长' (600)。") + + +class StyleWriting(CompletionBaseComponent): + """ + 风格写作大模型组件, 基于生成式大模型进行风格写作,支持B站、小红书等多种风格,可用于文案、广告等多种场景。 + + Examples: + + .. code-block:: python + + import os + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + style_writing = appbuilder.StyleWriting(model="ernie-bot-4") + answer = style_writing(appbuilder.Message("帮我写一篇关于人体工学椅的文案"), style_query="小红书", length=100) + + """ + + name = "style_writing" + version = "v1" + meta = StyleWritingArgs + + def __init__(self, model=None): + """初始化StyleWriting模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(StyleWritingArgs, model=model) + + def run(self, message, style_query="通用", length=100, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。 + style_query (str): 风格查询选项,用于指定写作风格。有效的选项包括 'B站', '小红书', '通用'。默认值为 '通用'。 + length (int): 输出内容的长度。有效的选项包括 100(短),300(中),600(长)。默认值为 100。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, style_query=style_query, length=length, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/llms/tag_extraction/README.md b/appbuilder/core/components/llms/tag_extraction/README.md new file mode 100644 index 000000000..992557f87 --- /dev/null +++ b/appbuilder/core/components/llms/tag_extraction/README.md @@ -0,0 +1,58 @@ +# 标签抽取(TagExtraction) + +## 简介 +标签抽取组件(TagExtraction)是一款高效的标签抽取组件,基于生成式大模型,专门用于从文本中提取关键标签。它适用于各种文本分析场景,如内容分类、关键词提取等。 + +## 基本用法 + +要开始使用 `TagExtraction`,首先需要设置环境变量 `APPBUILDER_TOKEN`,然后创建 `TagExtraction` 实例并传递文本消息。 + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' + +tag_extraction = appbuilder.TagExtraction(model="ernie-bot-4") +result = tag_extraction(appbuilder.Message("从这段文本中抽取关键标签")) +``` + +这个例子展示了如何实例化 `TagExtraction` 组件并使用一个文本消息进行标签抽取。 + +## 参数说明 + +### 初始化参数 + +- `model` (str|None): 模型名称,用于指定要使用的千帆模型。 + +### 调用参数 + +- `message` (obj:`Message`,必选): 输入消息,为模型提供主要的输入内容。 +- `stream` (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 +- `temperature` (float, 可选): 模型配置的温度参数,用于调整生成概率。取值范围为 0.0 到 1.0。 + +返回值: + +- `obj:Message`: 模型运行后的输出消息,包含抽取的标签信息。 + +## 高级用法 + +高级用法可以包括自定义模型参数或使用不同的模型源。例如,可以通过指定不同的 `model` 来使用特定于域的模型进行标签抽取。 + +```python +tag_extraction = appbuilder.TagExtraction(model="custom-model") +result = tag_extraction(appbuilder.Message("自定义模型抽取的标签")) +``` + +## 示例和案例研究 + +在实际应用中,`TagExtraction` 可以用于新闻文章、社交媒体帖子或其他任何文本内容的关键标签提取,帮助内容创建者或营销分析师快速了解主要主题和趋势。 + +## API文档 + +更详细的API文档,请参考 [AppBuilder TagExtraction API Documentation](#). + +## 更新记录和贡献 + +- v1.0: 初始版本,提供基本的标签抽取功能。 +如果您有兴趣贡献代码或提供反馈,请访问 [GitHub repository](#)。 diff --git a/appbuilder/core/components/llms/tag_extraction/__init__.py b/appbuilder/core/components/llms/tag_extraction/__init__.py new file mode 100644 index 000000000..153b39f08 --- /dev/null +++ b/appbuilder/core/components/llms/tag_extraction/__init__.py @@ -0,0 +1,2 @@ + +from .component import TagExtraction \ No newline at end of file diff --git a/appbuilder/core/components/llms/tag_extraction/component.py b/appbuilder/core/components/llms/tag_extraction/component.py new file mode 100644 index 000000000..63985fc79 --- /dev/null +++ b/appbuilder/core/components/llms/tag_extraction/component.py @@ -0,0 +1,75 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +from appbuilder.core.components.llms.base import CompletionBaseComponent +from appbuilder.core.message import Message +from appbuilder.core.component import ComponentArguments +from pydantic import BaseModel, Field + + +class TagExtractionArgs(ComponentArguments): + """标签抽取配置""" + message: Message = Field(..., + variable_name="query", + description="""输入消息,用于模型的主要输入内容,例如'本实用新型公开了一种可利用热能的太阳能光伏光热一体化组件, + 包括太阳能电池,还包括有吸热板,太阳能电池粘附在吸热板顶面,吸热板内嵌入有热电材料制成的内芯,吸热板底面设置有蛇形管。 + 本实用新型结构紧凑,安装方便,能充分利用太阳能电池散发的热能,具有较高的热能利用率。'""") + + +class TagExtraction(CompletionBaseComponent): + """ + 标签抽取组件,基于生成式大模型进行关键标签的抽取。 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + tag_extraction = appbuilder.TagExtraction(model="ernie-bot-4") + answer = tag_extraction(appbuilder.Message("从这段文本中抽取关键标签")) + + """ + + name = "tag_extraction" + version = "v1" + meta = TagExtractionArgs + + def __init__(self, model=None): + """初始化TagExtraction模型。 + + Args: + model (str|None): 模型名称,用于指定要使用的千帆模型。 + + Returns: + None + + """ + super().__init__(TagExtractionArgs, model=model) + + def run(self, message, stream=False, temperature=1e-10): + """ + 使用给定的输入运行模型并返回结果。 + + Args: + message (obj:`Message`,必选): 输入消息,用于模型的主要输入内容。 + stream (bool, 可选): 指定是否以流式形式返回响应。默认为 False。 + temperature (float, 可选): 模型配置的温度参数,用于调整模型的生成概率。取值范围为 0.0 到 1.0,其中较低的值使生成更确定性,较高的值使生成更多样性。默认值为 1e-10。 + + 返回: + obj:`Message`: 模型运行后的输出消息。 + """ + return super().run(message=message, stream=stream, temperature=temperature) diff --git a/appbuilder/core/components/matching/README.md b/appbuilder/core/components/matching/README.md new file mode 100644 index 000000000..e711a2668 --- /dev/null +++ b/appbuilder/core/components/matching/README.md @@ -0,0 +1,64 @@ +# 语义匹配(Matching) + +## 简介 + +语义匹配组件(Matching)可以计算query与文本列表之间的相似度关系,并根据其进行排序。 + +## 基本用法 + +初始化 + +```python +import os +import appbuilder +os.environ["APPBUILDER_TOKEN"] = '...' + +# 初始化所需要的组件 +embedding = appbuilder.Embedding() +matching = appbuilder.Matching(embedding) + +# 定义query和文本列表 +query = appbuilder.Message("你好") +contexts = appbuilder.Message(["世界", "你好"]) +``` + +### 基于query和文本之间的相似度进行匹配排序 + +```python +contexts_matched = matching(query, contexts) +print(contexts_matched.content) +``` + +``` +['你好', '世界'] +``` + +## 参数说明 + +#### 初始化参数说明 + +- embedding:【必须】一个类型为Embedding的Component,用于初始化`Matching`的向量计算功能 + +#### 调用参数说明 + +- query:【必须】一个类型为string的句子,长度不能超过384,通常为用户输入的问题 +- contexts:【必须】一个类型为List[string]的句子数组,每个元素长度不能超过384,通常为和问题相关的文本候选集 + +## 高级用法 + +### 对query和文本计算相似度 + +使用如下的示例代码,可以直接计算query和文本间的余弦相似度,用于判别不同的embedding模型之间的性能差异 + +```python +query_embedding = embedding(query) +context_embedding = embedding.batch(contexts) + +semantics = matching.semantics(query_embedding, context_embedding) + +print(semantics.content) +``` + +``` +[0.1892052043984527, 0.9999999852985002] +``` diff --git a/appbuilder/core/components/matching/__init__.py b/appbuilder/core/components/matching/__init__.py new file mode 100644 index 000000000..1763ce87d --- /dev/null +++ b/appbuilder/core/components/matching/__init__.py @@ -0,0 +1,20 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" +init +""" + +from .component import Matching diff --git a/appbuilder/core/components/matching/base.py b/appbuilder/core/components/matching/base.py new file mode 100644 index 000000000..2e91d06bd --- /dev/null +++ b/appbuilder/core/components/matching/base.py @@ -0,0 +1,56 @@ +""" +base +""" + +# Copyright (c) 2023 Baidu, Inc. 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. + + +from abc import abstractmethod +from typing import List, Union + +from appbuilder.core.message import Message +from appbuilder.core.component import Component +from appbuilder.core.component import ComponentArguments + + +class MatchingArgs(ComponentArguments): + """Matching Args""" + + query: Union[str, Message[str]] + contexts: Union[List[str], Message[List[str]]] + + +class MatchingBaseComponent(Component): + """ + MatchingBaseComponent + """ + + name: str + version: str + meta: MatchingArgs + + @abstractmethod + def run( + self, + query: Union[Message[str], str], + contexts: Union[Message[List[str]], List[str]], + ) -> Message[List[str]]: + """ + Args: + query: Union[Message[str], str] + contexts: Union[Message[List[str]], List[str]] + Returns: + Message[List[str]]: contexts which has been Matched + """ diff --git a/appbuilder/core/components/matching/component.py b/appbuilder/core/components/matching/component.py new file mode 100644 index 000000000..8226ffb59 --- /dev/null +++ b/appbuilder/core/components/matching/component.py @@ -0,0 +1,133 @@ +""" +Matching +""" + +# Copyright (c) 2023 Baidu, Inc. 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. + + +from typing import List, Union + +import numpy as np + +from appbuilder.core.message import Message +from appbuilder.core.components.embeddings import EmbeddingBaseComponent + +from .base import MatchingBaseComponent, MatchingArgs + + +class Matching(MatchingBaseComponent): + """ + Matching + + 基于Embedding类型的文本表示模型,输入query和文本列表,对其进行排序或者相似度计算 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + # 初始化所需要的组件 + embedding = appbuilder.Embedding() + matching = appbuilder.Matching(embedding) + + # 定义输入query和文本列表 + query = appbuilder.Message("你好") + contexts = appbuilder.Message(["世界", "你好"]) + + # 根据query,对文本列表做相似度排序 + contexts_matched = matching(query, contexts) + print(contexts_matched.content) + # ['你好', '世界'] + """ + + name: str = "Matching" + version: str = "v1" + meta: MatchingArgs = MatchingArgs + + def __init__( + self, + embedding_component: EmbeddingBaseComponent, + ): + """ + EmbeddingBaseComponent: 用于计算文本的embedding + """ + + self.embedding_component = embedding_component + super().__init__(self.meta) + + def run( + self, + query: Union[Message[str], str], + contexts: Union[Message[List[str]], List[str]] + ) -> Message[List[str]]: + """ + Args: + query: Union[Message[str], str] + contexts: Union[Message[List[str]], List[str]] + Returns: + Message[List[str]]: contexts which has been matched + """ + + query_embedding = self.embedding_component(query) + contexts_embedding = self.embedding_component.batch(contexts) + + sematic = self.semantics(query_embedding, contexts_embedding) + + combined = list(zip(sematic.content, contexts.content)) + sorted_combined = sorted(combined, reverse=True) + return Message([item[1] for item in sorted_combined]) + + def _cosine_similarity(self, X, Y): + """ + Args: + X: 长度为 1 x n 的矩阵 + Y: 长度为 m x n 的矩阵 + Returns: + 长度为 m x 1 的矩阵,每个元素表示 X 与 Y的对应行m 的余弦相似度 + """ + + X_norm = X / np.linalg.norm(X) + Y_norm = Y / np.linalg.norm(Y, axis=1, keepdims=True) + + similarity = np.dot(Y_norm, X_norm.T) + return similarity + + def semantics( + self, + query_embedding: Union[Message[List[float]], List[float]], + context_embeddings: Union[Message[List[List[float]]], List[List[float]]], + ) -> Message[List[float]]: + """ + 输入query和context的embedding,输出他们的相似度 + 其中: + query_embedding是一个长度为 n 的数组,表示仅有一个query + context_embeddings是一个长度为 m x n 的矩阵,m表示有m个候选context + + Args: + query_embedding: Union[Message[List[float]], List[float]] + context_embeddings: Union[Message[List[List[float]]], List[List[float]]] + Returns: + Message[float] + """ + + _query_embedding = query_embedding.content if isinstance(query_embedding, Message) else query_embedding + _context_embeddings = context_embeddings.content if isinstance(context_embeddings, Message) else context_embeddings + + similarity_matrix = self._cosine_similarity([_query_embedding], _context_embeddings) + similarity_matrix = similarity_matrix.flatten().tolist() + + return Message(similarity_matrix) diff --git a/appbuilder/core/components/object_recognize/README.md b/appbuilder/core/components/object_recognize/README.md new file mode 100644 index 000000000..798eb5bab --- /dev/null +++ b/appbuilder/core/components/object_recognize/README.md @@ -0,0 +1,37 @@ +# 通用物体和场景识别-高级版(ObjectRecognition) + +## 简介 +通用物体和场景识别组件(ObjectRecognition)可以识别超过10万类常见物体和场景,接口返回大类及细分类的名称。广泛适用于图像或视频内容分析、拍照识图等业务场景。 +## 基本用法 + +```python +import os +import appbuilder + + +# 配置token环境变量 +os.environ["APPBUILDER_TOKEN"] = '...' + +# 打开需要识别的图像文件 +with open("./object_recognition_test.jepg", "rb") as f: + # 创建物体识别组件实例 + object_recognition = appbuilder.ObjectRecognition() + # 执行识别操作并获取结果 + out = object_recognition.run(appbuilder.Message(content={"raw_image": f.read()})) + print(out.content) +``` + +## 参数说明 + +* run函数: + * message (`Message`类型): 图片或图片url下载地址, 用于执行识别操作。例如: `Message(content={"raw_image": b"..."})` 或 `Message(content={"url": "https://image/download/url"})`. + * timeout (float类型, 可选): HTTP请求的超时时间。 + * retry (int类型, 可选): HTTP请求的重试次数。 + 返回值: + * message (`Message`类型): 模型识别结果。例如: `Message(content={"result":[{"keyword":"苹果","score":0.94553,"root":"植物-蔷薇科"},{"keyword":"姬娜果","score":0.730442,"root":"植物-其它"},{"keyword":"红富士","score":0.505194,"root":"植物-其它"}]})` + +## 高级用法 +目前该模块仅提供基础通用物体与场景识别功能。 + +## 更新记录和贡献 +* 通用物体及场景识别 (2023-12-08) \ No newline at end of file diff --git a/appbuilder/core/components/object_recognize/__init__.py b/appbuilder/core/components/object_recognize/__init__.py new file mode 100644 index 000000000..e511769e1 --- /dev/null +++ b/appbuilder/core/components/object_recognize/__init__.py @@ -0,0 +1,10 @@ +# 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. diff --git a/appbuilder/core/components/object_recognize/component.py b/appbuilder/core/components/object_recognize/component.py new file mode 100644 index 000000000..c34481f93 --- /dev/null +++ b/appbuilder/core/components/object_recognize/component.py @@ -0,0 +1,105 @@ +# 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. + +"""object recognize component.""" + +import base64 +import json + + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.object_recognize.model import * + + +class ObjectRecognition(Component): + r""" + 提供通用物体及场景识别能力,即对于输入的一张图片(可正常解码,且长宽比适宜),输出图片中的多 + 个物体及场景标签。 + + Examples: + + ... code-block:: python + + import appbuilder + object_recognition = appbuilder.ObjectRecognition() + os.environ["APPBUILDER_TOKEN"] = '...' + + with open("./object_recognition_test.jepg", "rb") as f: + out = self.component.run(appbuilder.Message(content={"raw_image": f.read()})) + print(out.content) + + """ + + def run(self, message: Message, timeout: float = None, retry: int = 0) -> Message: + r""" 通用物体识别 + + 参数: + message (obj: `Message`): 输入图片或图片url下载地址用于执行识别操作. 举例: Message(content={"raw_image": b"..."}) + 或 Message(content={"url": "https://image/download/url"}). + timeout (float, 可选): HTTP超时时间 + retry (int, 可选): HTTP重试次数 + + 返回: message (obj: `Message`): 模型识别结果. 举例: Message(content={"result":[{"keyword":"苹果", + "score":0.94553,"root":"植物-蔷薇科"},{"keyword":"姬娜果","score":0.730442,"root":"植物-其它"}, + {"keyword":"红富士","score":0.505194,"root":"植物-其它"}]}) + """ + inp = ObjectRecognitionInMsg(**message.content) + req = ObjectRecognitionRequest() + if inp.raw_image: + req.image = base64.b64encode(inp.raw_image) + if inp.url: + req.url = inp.url + result = self._recognize(req, timeout, retry) + result_dict = proto.Message.to_dict(result) + out = ObjectRecognitionOutMsg(**result_dict) + return Message(content=out.dict()) + + def _recognize(self, request: ObjectRecognitionRequest, timeout: float = None, + retry: int = 0) -> ObjectRecognitionResponse: + r"""调用底层接口进行通用物体与场景识别 + 参数: + request (obj: `ObjectRecognitionRequest`) : 通用物体与场景识别输入参数 + 返回: + response (obj: `ObjectRecognitionResponse`): 通用物体与场景识别返回结果 + """ + if not request.image and not request.url: + raise ValueError("one of image or url must be set") + + data = ObjectRecognitionRequest.to_dict(request) + if self.retry.total != retry: + self.retry.total = retry + headers = self.auth_header() + headers['content-type'] = 'application/x-www-form-urlencoded' + url = self.service_url("/v1/bce/aip/image-classify/v2/advanced_general") + response = self.s.post(url, headers=headers, data=data, timeout=timeout) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__._check_service_error(data) + request_id = self.response_request_id(response) + object_response = ObjectRecognitionResponse.from_json(payload=json.dumps(data)) + object_response.request_id = request_id + return object_response + + @staticmethod + def _check_service_error(data: dict): + r"""个性化服务response参数检查 + 参数: + request (dict) : 通用物体与场景识别body返回 + 返回: + 无 + """ + if "error_code" in data or "error_msg" in data: + raise AppBuilderServerException(service_err_code=data.get("error_code"), + service_err_message=data.get("error_msg")) diff --git a/appbuilder/core/components/object_recognize/model.py b/appbuilder/core/components/object_recognize/model.py new file mode 100644 index 000000000..f7acbc2ef --- /dev/null +++ b/appbuilder/core/components/object_recognize/model.py @@ -0,0 +1,155 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +"""object recognize client.""" +import proto + +from typing import List +from pydantic import BaseModel + + +# PB Definition +class ObjectRecognitionRequest(proto.Message): + r"""通用物体与场景识别请求体. + + 属性: + image (str): + 可选。图像内容的base64编码。 + url (str): + 可选。图像的URL地址,经过base64编码。 + 图像大小必须小于4MB,图像的最短边长大于15像素,最长边长大于4096像素。 + + 必须设置image或url属性之一,如果两者都设置了,将使用image属性。 + """ + image: str = proto.Field( + proto.STRING, + number=1, + ) + url: str = proto.Field( + proto.STRING, + number=2, + ) + baike_num: int = proto.Field( + proto.INT64, + number=3, + ) + + +class ObjectRecognitionResponse(proto.Message): + """通用物体与场景识别响应消息。 + + 属性: + request_id (str): 请求ID。 + log_id (int): 用于问题识别的唯一日志ID。 + result_num (int): 结果数量,即结果数组中的元素数量。最多返回5个结果。 + result (List[ObjectResult]): 物体识别结果列表。 + """ + request_id: str = proto.Field( + proto.STRING, + number=1, + ) + log_id: int = proto.Field( + proto.INT64, + number=2, + ) + result_num: int = proto.Field( + proto.UINT32, + number=3, + ) + result: 'ObjectResult' = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="ObjectResult", + ) + + +class ObjectResult(proto.Message): + """物体识别信息. + + 属性: + keyword (str): 图像中物体或场景的名称。 + score (float): 置信度得分,范围从0到1。 + root (str): 识别结果中的顶级标签。一些标签,如硬币、动漫、烟草等,可能没有顶级标签。 + baike_info (List[BaikeInfo]): 与识别结果对应的百科信息列表。 + """ + keyword: str = proto.Field( + proto.STRING, + number=1, + ) + score: float = proto.Field( + proto.FLOAT, + number=2, + ) + root: str = proto.Field( + proto.STRING, + number=3, + ) + baike_info: 'BaikeInfo' = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="BaikeInfo", + ) + + +class BaikeInfo(proto.Message): + """物体识别百科信息。 + + 属性: + baike_url (str): 与识别结果对应的百度百科页面的URL。 + image_url (str): 与识别结果相关联的图像的URL。 + description (str): 百度百科提供的识别结果的描述。 + """ + baike_url: str = proto.Field( + proto.STRING, + number=1, + ) + image_url: str = proto.Field( + proto.STRING, + number=2, + ) + description: str = proto.Field( + proto.STRING, + number=3, + ) + + +class ObjectRecognitionInMsg(BaseModel): + """ 通用物体与场景识别输入消息 + + 属性: + raw_image(bytes): 图像原始内容 + url(str): 图像下载链接 + """ + raw_image: bytes = b'' + url: str = "" + + +class Object(BaseModel): + """物体识别输入消息。 + 属性: + keyword(bytes): + 原始二进制图像数据。 + score(float): + 置信度得分,范围从0到1。 + root(str): + 识别结果中的顶级标签。 + """ + keyword: str + score: float + root: str + + +class ObjectRecognitionOutMsg(BaseModel): + r"""识别结果列表""" + result: List[Object] # 结果列表 diff --git a/appbuilder/core/components/retriever/README.md b/appbuilder/core/components/retriever/README.md new file mode 100644 index 000000000..3bf5b9944 --- /dev/null +++ b/appbuilder/core/components/retriever/README.md @@ -0,0 +1,57 @@ +# 向量检索(BESRetriever) + +## 简介 +向量检索组件(Baidu ElasticSearch Retriever)基于一款Baidu ElasticSearch的内容检索组件,支持根据文本的向量的相似度进行内容检索。 + +## 准备工作 +在使用Baidu ElasticSearch Retriever进行内容检索之前,需要到Baidu ElasticSearch官网创建相应的集群,详情见[教程](https://cloud.baidu.com/doc/BES/s/gke3ocf89)。 + +注:创建集群时请选择7.10.2版本的ES,否则可能无法使用本组件。 + +## 基本用法 + +以下是有关如何开始使用BESRetriever的代码示例: + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' + +embedding = appbuilder.Embedding() +segments = appbuilder.Message(["文心一言大模型", "百度在线科技有限公司"]) +# 初始化构建索引 +vector_index = appbuilder.BESVectorStoreIndex.from_segments(segments=segments, cluster_id=es_cluster_id, user_name=es_username, + password=es_password, embedding=embedding) +# 获取当前索引中的全部内容 +all_content = vector_index.get_all_segments() +print(all_content) +# 转化为retriever +retriever = vector_index.as_retriever() +# 按照query进行检索 +query = appbuilder.Message("文心一言") +res = retriever(query=query, top_k=1) +print(res) +# 删除当前索引中的全部内容 +vector_index.delete_all_segments() +``` + +## 参数说明 + +### 初始化参数说明: + +- segments (Message[List[str]],必填):需要入库的文本段落 +- cluster_id (str,必填):ElacticSearch集群的id,创建集群时获取 +- user_name (str,必填):连接ES集群所需的用户名,创建集群时获取 +- password (str,必填):连接ES集群所需的密码,创建集群时获取 +- embedding (obj,非必填):用于将文本转为向量的模型,默认为Embedding + +### 调用参数说明: + +1. `query`: 需要检索的内容,数据类型为Message[str],必要参数 +2. `top_k`: 返回匹配度最高的top_k个结果,默认为1, 非必填 + +## 高级用法: + +本组件根据向量的相似度进行检索,支持使用不同的embedding方法和索引方式来优化检索的效果。 + diff --git a/appbuilder/core/components/retriever/__init__.py b/appbuilder/core/components/retriever/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/appbuilder/core/components/retriever/bes_retriever.py b/appbuilder/core/components/retriever/bes_retriever.py new file mode 100644 index 000000000..fc1d715a2 --- /dev/null +++ b/appbuilder/core/components/retriever/bes_retriever.py @@ -0,0 +1,256 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +基于baidu ES的retriever +""" +import importlib +import os +import random +import string +from typing import Dict, Any +from appbuilder.core.component import Component, Message +from appbuilder.core.components.embeddings.component import Embedding +from appbuilder.core.constants import GATEWAY_URL +from appbuilder.utils.logger_util import logger + + +class BESVectorStoreIndex: + """ + BES向量存储检索工具 + """ + base_es_url: str = "/v1/bce/bes/cluster/" + + def __init__(self, cluster_id, user_name, password, embedding=None, index_name=None, + index_type="hnsw", prefix="/rpc/2.0/cloud_hub"): + + if embedding is None: + embedding = Embedding() + + self.embedding = embedding + self.index_name = index_name if index_name else BESVectorStoreIndex.generate_id() + self.index_type = index_type + self.prefix = prefix + + self._es = None + self._helpers = None + self.bes_client = self._create_bes_client(cluster_id, user_name, password) + + @property + def es(self): + self._lazy_import_es() + return self._es + + @property + def helpers(self): + self._lazy_import_es() + return self._helpers + + def _lazy_import_es(self): + if self._es is None or self._helpers is None: + try: + from elasticsearch import Elasticsearch, helpers + self._es = Elasticsearch + self._helpers = helpers + except ImportError: + raise ImportError("Elasticsearch module is not installed. " + "Please install it using 'pip install elasticsearch==7.11.0'.") + + @staticmethod + def generate_id(length=16): + """ + 生成随机的ID + """ + return ''.join(random.choices(string.ascii_lowercase + string.digits, k=length)) + + def _create_bes_client(self, cluster_id, user_name, password): + """ + 创建一个bes的client + """ + secret_key = os.getenv("APPBUILDER_TOKEN") + gateway = os.getenv("GATEWAY_URL") if os.getenv("GATEWAY_URL") else GATEWAY_URL + + connection_params = { + "hosts": [gateway + self.prefix + self.base_es_url + cluster_id], + "http_auth": (user_name, password), + "headers": {'X-Appbuilder-Authorization': f"{secret_key}"} + } + + bes_client = self.es(**connection_params) + + try: + bes_client.info() + except Exception as e: + logger.error("connecting to bes error: {}".format(e)) + raise ConnectionError(e) + + return bes_client + + def as_retriever(self): + """ + 转化为retriever + """ + return BESRetriever(embedding=self.embedding, index_name=self.index_name, bes_client=self.bes_client, + index_type=self.index_type) + + @staticmethod + def create_index_mappings(index_type, vector_dims): + """ + 创建索引的mapping + """ + mappings = { + 'properties': { + "vector": { + "type": "bpack_vector", + "dims": vector_dims, + }, + } + } + if index_type == "hnsw": + mappings["properties"]["vector"]["index_type"] = "hnsw" + mappings["properties"]["vector"]["space_type"] = "cosine" + mappings["properties"]["vector"]["parameters"] = {"m": 4, "ef_construction": 200} + return mappings + + def add_segments(self, segments: Message, metadata=""): + """ + 向bes中插入数据 + 参数: + query (Message[str]): 需要插入的内容 + 返回: + """ + segment_vectors = self.embedding.batch(segments) + segment_vectors = segment_vectors.content + vector_dims = len(segment_vectors[0]) + segments = segments.content + documents = [ + {"_index": self.index_name, + "_source": {"text": segment, "vector": vector, "metadata": metadata, + "id": BESVectorStoreIndex.generate_id()}} + for segment, vector in zip(segments, segment_vectors)] + + mappings = BESVectorStoreIndex.create_index_mappings(self.index_type, vector_dims) + self.bes_client.indices.create(index=self.index_name, + body={"settings": {"index": {"knn": True}}, "mappings": mappings}) + self.helpers.bulk(self.bes_client, documents) + + @classmethod + def from_segments(cls, segments, cluster_id, user_name, password, embedding=None, **kwargs): + """ + 根据段落创建一个bes向量索引 + 参数: + segments: 切分的文本段落 + cluster_id: bes集群ID + user_name: bes用户名 + password: bes用户密码 + embedding: 文本段落embedding工具 + kwargs: 其他初始化参数 + 返回: + bes索引实例 + """ + if embedding is None: + embedding = Embedding() + + index_name = kwargs.get("index_name", None) + index_type = kwargs.get("index_type", "hnsw") + prefix = kwargs.get("prefix", "/rpc/2.0/cloud_hub") + + vector_index = cls(cluster_id, user_name, password, embedding, index_name, index_type, prefix) + vector_index.add_segments(segments) + return vector_index + + def delete_all_segments(self): + """ + 删除索引中的全部内容 + """ + query = { + 'query': { + 'match_all': {} + } + } + resp = self.bes_client.delete_by_query(index=self.index_name, body=query) + logger.debug("deleted {} documents in index {}".format(resp['deleted'], self.index_name)) + + def get_all_segments(self): + """ + 获取索引中的全部内容 + """ + query = { + 'query': { + 'match_all': {} + } + } + return self.bes_client.search(index=self.index_name, body=query) + + +class BESRetriever(Component): + """ + 向量检索组件,用于检索和query相匹配的内容 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + segments = appbuilder.Message(["文心一言大模型", "百度在线科技有限公司"]) + vector_index = appbuilder.BESVectorStoreIndex.from_segments(segments, self.cluster_id, self.username, + self.password) + query = appbuilder.Message("文心一言") + time.sleep(5) + retriever = vector_index.as_retriever() + res = retriever(query) + + """ + name: str = "BaiduElasticSearchRetriever" + tool_desc: Dict[str, Any] = {"description": "a retriever based on Baidu ElasticSearch"} + base_es_url: str = "/v1/bce/bes/cluster/" + + def __init__(self, embedding, index_name, bes_client, index_type="hnsw"): + super().__init__() + + self.embedding = embedding + self.index_name = index_name + self.bes_client = bes_client + self.index_type = index_type + + def run(self, query: Message, top_k: int = 1): + """ + 根据query进行查询 + 参数: + query (Message[str]): 需要查询的内容, + top_k (bool): 查询结果中匹配度最高的top_k个结果 + 返回: + obj (Message[Dict]): 查询到的结果,包含文本和匹配得分。 + """ + query_embedding = self.embedding(query) + vector_query = {"vector": query_embedding.content, "k": top_k} + if self.index_type == "linear": + vector_query["linear"] = True + else: + vector_query["ef"] = 10 + + query_body = { + "size": top_k, + "query": {"knn": {"vector": vector_query}} + } + res = self.bes_client.search(index=self.index_name, body=query_body) + docs = [] + for r in res["hits"]["hits"]: + docs.append({"text": r["_source"]["text"], "meta": r["_source"]["metadata"], "score": r["_score"]}) + + return Message(docs) diff --git a/appbuilder/core/components/text_to_image/README.md b/appbuilder/core/components/text_to_image/README.md new file mode 100644 index 000000000..2d1470192 --- /dev/null +++ b/appbuilder/core/components/text_to_image/README.md @@ -0,0 +1,43 @@ +# AI作画-高级版 (Text2Image) + +## 简介 +AI作画-高级版(Text2Image)基于文心大模型,可以根据用户输入的文本,自动创作不限定风格的图,为内容创作者提供灵感和高质量配图。 + +## 基本用法 + +下面是AI作画的代码示例: + +```python +import os +import appbuilder +# 设置环境变量和初始化 +os.environ["APPBUILDER_TOKEN"] = "..." + +text2Image = appbuilder.Text2Image() +content_data = {"prompt": "上海的经典风景", "width": 1024, "height": 1024, "image_num": 1} +msg = appbuilder.Message(content_data) +out = text2Image.run(msg) +print(out.content) +``` + +## 参数说明 +### 初始化参数 + +无 + +### 调用参数 +- `run`函数中包含以下参数: + - `message`: 输入的消息,用于模型的主要输入内容。这是一个必需的参数,例如:Message(content={"prompt": "上海的经典风景"}) + - `width`: 图片宽度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560。 + - `height`: 图片高度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560。 + - `image_num`: 生成图片数量,默认一张,支持生成 1-8 张。 + - `timeout`: HTTP超时时间 + - `retry`: HTTP重试次数 + +返回值示例:eg: {"img_urls": ["xxx"]} + +## 高级用法 + +目前该模块仅提供基础的AI作画功能。 +## 更新记录和贡献 +* AI作画能力 (2023-12) \ No newline at end of file diff --git a/appbuilder/core/components/text_to_image/__init__.py b/appbuilder/core/components/text_to_image/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/text_to_image/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/text_to_image/component.py b/appbuilder/core/components/text_to_image/component.py new file mode 100644 index 000000000..9ad848e60 --- /dev/null +++ b/appbuilder/core/components/text_to_image/component.py @@ -0,0 +1,174 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""Text2Image component. +""" +import time +import json + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.text_to_image.model import Text2ImageSubmitRequest, Text2ImageQueryRequest, \ + Text2ImageQueryResponse, Text2ImageSubmitResponse, Text2ImageOutMessage, Text2ImageInMessage + + +class Text2Image(Component): + r""" + AI作画组件,即对于输入的文本,输出生成的图片url。 + + Examples: + + .. code-block:: python + + import appbuilder + text_to_image = appbuilder.Text2Image() + os.environ["APPBUILDER_TOKEN"] = '...' + inp = appbuilder.Message(content={"prompt": "上海的经典风景"}) + out = text_to_image.run(inp) + # 打印生成结果 + print(out.content) # eg: {"img_urls": ["xxx"]} + """ + + def run(self, message: Message, width: int = 1024, height: int = 1024, image_num: int = 1, + timeout: float = None, retry: int = 0): + """ + 输入文本并返回生成的图片url。 + + 参数: + message (obj:`Message`): 输入消息,用于模型的主要输入内容。这是一个必需的参数。举例: Message(content={"prompt": "上海的经典风景"}) + width (int,可选): 图片宽度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560。 + height (int, 可选): 图片高度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560。 + image_num (int, 可选): 生成图片数量,默认一张,支持生成 1-8 张。 + timeout (float, 可选): 请求的超时时间。 + retry (int, 可选): 请求的重试次数。 + + 返回: + obj:`Message`: 输出生成图片的url。举例: Message(content={"img_urls": ["xxx"]})。 + """ + inp = Text2ImageInMessage(**message.content) + text2ImageSubmitRequest = Text2ImageSubmitRequest() + text2ImageSubmitRequest.prompt = inp.prompt + text2ImageSubmitRequest.width = width + text2ImageSubmitRequest.height = height + text2ImageSubmitRequest.image_num = image_num + text2ImageSubmitResponse = self.submitText2ImageTask(text2ImageSubmitRequest) + taskId = text2ImageSubmitResponse.data.primary_task_id + if taskId is not None: + while True: + request = Text2ImageQueryRequest() + request.task_id = taskId + text2ImageQueryResponse = self.queryText2ImageData(request) + if text2ImageQueryResponse.data.task_progress is not None: + task_progress = text2ImageQueryResponse.data.task_progress + if task_progress == 1: + break + time.sleep(0.2) + img_urls = self.extract_img_urls(text2ImageQueryResponse) + out = Text2ImageOutMessage(img_urls=img_urls) + return Message(content=dict(out)) + + def submitText2ImageTask(self, request: Text2ImageSubmitRequest, timeout: float = None, + retry: int = 0) -> Text2ImageSubmitResponse: + + """ + 使用给定的输入并返回AI作画的任务信息。 + + 参数: + request (obj:`Text2ImageSubmitRequest`): 输入请求,这是一个必需的参数。 + timeout (float, 可选): 请求的超时时间。 + retry (int, 可选): 请求的重试次数。 + + 返回: + obj:`Text2ImageSubmitResponse`: 接口返回的输出消息。 + """ + url = self.service_url("/v1/bce/aip/ernievilg/v1/txt2imgv2") + data = Text2ImageSubmitRequest.to_json(request) + headers = self.auth_header() + headers['content-type'] = 'application/json' + if retry != self.retry.total: + self.retry.total = retry + response = self.s.post(url, data=data, headers=headers, timeout=timeout) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__.check_service_error(data) + request_id = response.headers.get('X-Appbuilder-Request-Id') + response = Text2ImageSubmitResponse.from_json(payload=json.dumps(data)) + response.request_id = request_id + return response + + def queryText2ImageData(self, request: Text2ImageQueryRequest, timeout: float = None, + retry: int = 0) -> Text2ImageQueryResponse: + + """ + 使用给定的输入并返回AI作画的结果。 + + 参数: + request (obj:`Text2ImageQueryRequest`): 输入请求,这是一个必需的参数。 + timeout (float, 可选): 请求的超时时间。 + retry (int, 可选): 请求的重试次数。 + + 返回: + obj:`Text2ImageQueryResponse`: 接口返回的输出消息。 + """ + url = self.service_url("/v1/bce/aip/ernievilg/v1/getImgv2") + data = { + "task_id": request.task_id + } + headers = self.auth_header() + headers['content-type'] = 'application/json' + if retry != self.retry.total: + self.retry.total = retry + response = self.s.post(url, json=data, headers=headers, timeout=timeout) + super().check_response_header(response) + data = response.json() + super().check_response_json(data) + self.__class__.check_service_error(data) + request_id = response.headers.get('X-Appbuilder-Request-Id') + response = Text2ImageQueryResponse.from_json(payload=json.dumps(data)) + response.request_id = request_id + return response + + def extract_img_urls(self, response: Text2ImageQueryResponse): + """ + 提取图片的url。 + + 参数: + response (obj:`Text2ImageQueryResponse`): A作画生成的返回结果。 + 返回: + List[str]:`img_urls`: 从返回体中提取的图片url列表。 + """ + img_urls = [] + if response and response.data and response.data.sub_task_result_list: + for sub_task_result in response.data.sub_task_result_list: + if sub_task_result and sub_task_result.final_image_list: + for final_image in sub_task_result.final_image_list: + if final_image and final_image.img_url: + img_urls.append(final_image.img_url) + + return img_urls + + @staticmethod + def check_service_error(data: dict): + r"""个性化服务response参数检查 + + 参数: + request (dict) : AI作画生成结果body返回 + 返回: + 无 + """ + if "error_code" in data or "error_msg" in data: + raise AppBuilderServerException(service_err_code=data.get("error_code"), + service_err_message=data.get("error_msg")) \ No newline at end of file diff --git a/appbuilder/core/components/text_to_image/model.py b/appbuilder/core/components/text_to_image/model.py new file mode 100644 index 000000000..8743242be --- /dev/null +++ b/appbuilder/core/components/text_to_image/model.py @@ -0,0 +1,291 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +r"""Text2Image model.py. +""" +from typing import MutableSequence, List + +import proto +from pydantic import BaseModel + + +class Text2ImageSubmitRequest(proto.Message): + r"""AI作画提交任务的请求体。 + + 参数: + prompt(str): + 生图的文本描述。仅支持中文、日常标点符号。不支持英文,特殊符号,限制 200 字。 + width(int): + 图片宽度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560。 + height(int): + 图片高度,支持:512x512、640x360、360x640、1024x1024、1280x720、720x1280、2048x2048、2560x1440、1440x2560. + image_num(int): + 生成图片数量,默认一张,支持生成 1-8 张。 + image(string): + 参考图,需 base64 编码,大小不超过 10M,最短边至少 15px,最长边最大 8192px,支持jpg/jpeg/png/bmp 格式。 + 优先级:image > url > pdf_file,当image 字段存在时,url、pdf_file 字段失效。 + url(str): + 参考图完整 url,url 长度不超过 1024 字节,url 对应的图片需 base64 编码,大小不超过 10M,最短边至少 15px, + 最长边最大8192px,支持 jpg/jpeg/png/bmp 格式。优先级:image > url > pdf_file,当image 字段存在时,url 字段失效请注意关闭 URL 防盗链。 + pdf_file(string): + 参考图 PDF 文件,base64 编码,大小不超过10M,最短边至少 15px,最长边最大 8192px 。 + 优先级:image > url > pdf_file,当image 字段存在时,url、pdf_file 字段失效。 + pdf_file_num(str): + 需要识别的 PDF 文件的对应页码,当pdf_file 参数有效时,识别传入页码的对应页面内容,若不传入,则默认识别第 1 页。 + change_degree(int): + 参考图影响因子,支持 1-10 内;数值越大参考图影响越大。 + """ + prompt: str = proto.Field( + proto.STRING, + number=1, + ) + width: int = proto.Field( + proto.INT32, + number=2, + ) + height: int = proto.Field( + proto.INT32, + number=3, + ) + image_num: int = proto.Field( + proto.INT32, + number=4, + optional=True, + ) + image: str = proto.Field( + proto.STRING, + number=5, + optional=True, + ) + url: str = proto.Field( + proto.STRING, + number=6, + optional=True, + ) + pdf_file: str = proto.Field( + proto.STRING, + number=7, + optional=True, + ) + pdf_file_num: str = proto.Field( + proto.STRING, + number=8, + optional=True, + ) + change_degree: int = proto.Field( + proto.INT32, + number=9, + optional=True, + ) + + +class Text2ImageQueryRequest(proto.Message): + r"""AI作画生成结果查询请求体。 + + 参数: + task_id(int): + 从提交请求的提交接口的返回值中获取,可使用task_id 查询总任务。 + """ + task_id: int = proto.Field( + proto.INT64, + number=1, + ) + + +class Text2ImageSubmitResponse(proto.Message): + r"""AI作画任务提交接口返回体。 + + 参数: + request_id(str): + 网关层的请求ID。 + log_id(str): + 算子层请求唯一标识码。 + data(Text2ImageSubmitData): + 任务提交接口返回数据。 + """ + request_id: str = proto.Field( + proto.STRING, + number=1, + ) + + log_id: int = proto.Field( + proto.INT64, + number=2, + ) + data: "Text2ImageSubmitData" = proto.Field( + proto.MESSAGE, + number=3, + message="Text2ImageSubmitData", + ) + + +class Text2ImageQueryResponse(proto.Message): + r"""AI作画任务结果查询接口返回体。. + + 参数: + request_id(str): + Request ID of gateway layer. + log_id(str): + Request ID of service layer. + data(Text2ImageQueryData): + Text to Image query response data . + """ + request_id: str = proto.Field( + proto.STRING, + number=1, + ) + + log_id: int = proto.Field( + proto.INT64, + number=2, + ) + + data: "Text2ImageQueryData" = proto.Field( + proto.MESSAGE, + number=3, + message="Text2ImageQueryData", + ) + + +class Text2ImageSubmitData(proto.Message): + r"""AI作画提交任务接口返回体数据。 + + 参数: + primary_task_id(str): + 生成图片任务long类型 id,与“task_id”参数输出相同,该 id 可用于查询任务状态。 + task_id(str): + 生成图片任务string类型 id,与“primary_task_id”参数输出相同,该 id 可用于查询任务状态。 + """ + primary_task_id: int = proto.Field( + proto.INT64, + number=1, + ) + + task_id: str = proto.Field( + proto.STRING, + number=2, + ) + + +class Text2ImageQueryData(proto.Message): + r"""AI作画任务查询接口返回体数据。 + 参数: + task_id(int): + 任务 ID. + task_status(str): + 计算总状态。有 INIT(初始化),WAIT(排队中), RUNNING(生成中), FAILED(失败), SUCCESS(成功)四种状态,只有 SUCCESS 为成功状态。 + task_progress(int): + 图片生成总进度,进度包含2种,0为未处理完,1为处理完成。 + sub_task_result_list(Text2ImageSubTaskResultList): + 子任务生成结果列表。 + """ + task_id: int = proto.Field( + proto.INT64, + number=1, + ) + task_status: str = proto.Field( + proto.STRING, + number=2, + ) + task_progress: int = proto.Field( + proto.INT64, + number=3, + ) + + sub_task_result_list: MutableSequence["Text2ImageSubTaskResultList"] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="Text2ImageSubTaskResultList", + ) + + +class Text2ImageSubTaskResultList(proto.Message): + r"""AI作画子任务结果列表。 + 参数: + sub_task_status(int): + 单风格图片状态。有 INIT(初始化),WAIT(排队中), RUNNING(生成中), FAILED(失败), SUCCESS(成功)四种状态,只有 SUCCESS 为成功状态。 + sub_task_progress(int): + 单任务图片生成进度,进度包含2种,0为未处理完,1为处理完成。 + sub_task_error_code(str): + 单风格任务错误码。0:正常;501:文本黄反拦截;201:模型生图失败。 + final_image_list(Text2ImageFinalImageList): + 单风格任务产出的最终图列表。 + """ + sub_task_status: str = proto.Field( + proto.STRING, + number=1, + ) + sub_task_progress: int = proto.Field( + proto.INT32, + number=2, + ) + sub_task_error_code: int = proto.Field( + proto.INT32, + number=3, + ) + final_image_list: MutableSequence["Text2ImageFinalImageList"] = proto.RepeatedField( + proto.MESSAGE, + number=4, + message="Text2ImageFinalImageList", + ) + + +class Text2ImageFinalImageList(proto.Message): + r"""AI作画单风格任务产出的最终图列表。 + 参数: + img_approve_conclusion(str): + 图片机审结果,"block":输出图片违规;"review": 输出图片疑似违规;"pass": 输出图片未发现问题。 + img_url(str): + 图片所在 BOS http 地址,默认 1 小时失效。 + height(int): + 图片像素信息-高度。 + width(int): + 图片像素信息-宽度。 + """ + img_approve_conclusion: str = proto.Field( + proto.STRING, + number=1, + ) + img_url: str = proto.Field( + proto.STRING, + number=2, + ) + + width: int = proto.Field( + proto.INT32, + number=3, + ) + height: int = proto.Field( + proto.INT32, + number=4, + ) + + +class Text2ImageInMessage(BaseModel): + """ AI作画组件输入message. + 参数: + prompt(str): + 生图的文本描述。仅支持中文、日常标点符号。不支持英文,特殊符号,限制 200 字。 + """ + prompt: str + + +class Text2ImageOutMessage(BaseModel): + """ AI作画组件输出message. + 参数: + img_urls(str): + 图片所在 BOS http 地址,默认 1 小时失效。 + """ + img_urls: List[str] diff --git a/appbuilder/core/components/translate/README.md b/appbuilder/core/components/translate/README.md new file mode 100644 index 000000000..664a0ad8b --- /dev/null +++ b/appbuilder/core/components/translate/README.md @@ -0,0 +1,33 @@ +# 文本翻译-通用版(Translation) + +## 简介 +文本翻译组件(Translation)提供200+语种互译的在线文本翻译服务。支持术语定制功能,用户可对翻译结果进行干预,快速提高翻译质量。可广泛应用于移动端、PC网站、智能硬件等不同产品形态中,满足多领域、多场景的翻译需求。 + +## 基本用法 +通过如下示例代码可以快速开始使用文本翻译组件: +```python +import os +import appbuilder +os.environ["APPBUILDER_TOKEN"] = '...' + +translate = appbuilder.Translation() +resp = translate(appbuilder.Message("你好\n中国"), from_lang="zh", to_lang="en") +# 输出{'from_lang': 'zh', 'to_lang': 'en', 'trans_result': [{'src': '你好', 'dst': 'hello'}, {'src': '中国', 'dst': 'China'}]} +print(resp.content) +``` +其中,`APPBUILDER_TOKEN`为您的API访问授权token。 + +## 参数说明 +### 初始化参数说明 +Translation组件无需额外初始化参数。 + +### 调用参数说明 +`run`函数的参数定义如下: +- `message`:需要翻译的文本,为Message类型,必传参数。 +- `from_lang`:翻译的源语言,默认为`auto`,表示自动检测语言。 +- `to_lang`:需要翻译的目标语言,默认为`en`,表示英语。 +- `timeout`:请求翻译的超时时间,非必传参数,默认为None。 +- `retry`:请求失败的重试次数,非必传参数,默认为0。 + +返回值为Message类型的对象,包含翻译后的文本。 +例如,`Message(content={'from_lang': 'zh', 'to_lang': 'en', 'trans_result': [{'src': '你好', 'dst': 'hello'}]})` \ No newline at end of file diff --git a/appbuilder/core/components/translate/__init__.py b/appbuilder/core/components/translate/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/translate/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/translate/component.py b/appbuilder/core/components/translate/component.py new file mode 100644 index 000000000..22ca8ab6c --- /dev/null +++ b/appbuilder/core/components/translate/component.py @@ -0,0 +1,108 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +文本翻译-通用版组件 +""" +import json + +from appbuilder.core.message import Message +from appbuilder.core.component import Component +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.translate.model import * + + +class Translation(Component): + """ + 文本翻译组件,可支持中、英、日、韩等200+语言互译,100+语种自动检测。 + 支持语种列表可参照 https://ai.baidu.com/ai-doc/MT/4kqryjku9#%E8%AF%AD%E7%A7%8D%E5%88%97%E8%A1%A8 + + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + + translate = appbuilder.Translation() + resp = translate(appbuilder.Message("你好\n中国"), to_lang="en") + """ + + name = "translate" + version = "v1" + + def run(self, message: Message, from_lang: str = "auto", to_lang: str = "en", + timeout: float = None, retry: int = 0) -> Message: + """ + 根据提供的文本以及语种参数执行文本翻译 + + Args: + message (Message): 翻译文本。 + from_lang (str): 翻译的源语言。默认为 "auto"。 + to_lang (str): 翻译的目标语言。默认为 "en"。 + timeout (float, optional): 翻译请求的超时时间。 + retry (int, optional): 重试次数。 + + Returns: + Message: 返回的文本翻译结果。 + 例如,Message(content={'from_lang': 'zh', 'to_lang': 'en', 'trans_result': [{'src': '你好', 'dst': 'hello'}]}) + """ + req = TranslateRequest() + req.q = message.content + req.from_lang = from_lang + req.to_lang = to_lang + result = self._translate(req, timeout=timeout, retry=retry) + result_dict = proto.Message.to_dict(result) + + out = TranslateOutMsg(**result_dict["result"]) + return Message(content=out.dict()) + + def _translate(self, request: TranslateRequest, timeout: float = None, + retry: int = 0) -> TranslateResponse: + """ + 根据提供的 TranslateRequest 执行文本翻译。 + + Args: + request (TranslateRequest): 翻译请求参数。 + timeout (float, optional): 请求超时时间。 + retry (int, optional): 重试次数。 + + Returns: + TranslateResponse: 文本翻译结果的响应体。 + """ + if not request.to_lang or not request.q: + raise ValueError("params `to_lang` and `q` must be set") + if not request.from_lang: + request.from_lang = "auto" + request_data = TranslateRequest.to_json(request) + if retry != self.retry.total: + self.retry.total = retry + headers = self.auth_header() + headers['content-type'] = 'application/json;charset=utf-8' + + url = self.service_url("/v1/bce/aip/mt/texttrans/v1") + + response = self.s.post(url, headers=headers, data=request_data, timeout=timeout) + + self.check_response_header(response) + data = response.json() + self.check_response_json(data) + if "error_code" in data and "error_msg" in data: + raise AppBuilderServerException(service_err_code=data["error_code"], service_err_message=data["error_msg"]) + + json_str = json.dumps(data) + return TranslateResponse(TranslateResponse.from_json(json_str)) diff --git a/appbuilder/core/components/translate/model.py b/appbuilder/core/components/translate/model.py new file mode 100644 index 000000000..5d8642e05 --- /dev/null +++ b/appbuilder/core/components/translate/model.py @@ -0,0 +1,139 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +# -*- coding: utf-8 -*- +""" +文本翻译model +""" + +import proto +from typing import List +from pydantic import BaseModel + + +class TranslateRequest(proto.Message): + """ + 文本翻译请求体。 + + Attributes: + from_lang (str): 翻译的源语言。 + to_lang (str): 翻译的目标语言。 + q (str): 待翻译的文本。 + """ + from_lang: str = proto.Field( + proto.STRING, + number=1, + json_name="from" + ) + to_lang: str = proto.Field( + proto.STRING, + number=2, + json_name="to" + ) + q: str = proto.Field( + proto.STRING, + number=3, + ) + + +class TranslateResponse(proto.Message): + """ + 文本翻译请求响应体。 + + Attributes: + log_id (int): 文本翻译请求的标识符。 + result (TranslateRes): 文本翻译结果。 + """ + log_id: int = proto.Field( + proto.INT64, + number=1, + ) + result: "TranslateRes" = proto.Field( + proto.MESSAGE, + number=2, + message='TranslateRes', + ) + + +class TranslateRes(proto.Message): + """ + 表示翻译请求的结果。 + + Attributes: + from_lang (str): 翻译的源语言。 + to_lang (str): 翻译的目标语言。 + trans_result (List[TranslateResMeta]): 翻译结果列表。 + """ + from_lang: str = proto.Field( + proto.STRING, + number=1, + json_name="from" + + ) + to_lang: str = proto.Field( + proto.STRING, + number=2, + json_name="to" + ) + trans_result: "TranslateResMeta" = proto.RepeatedField( + proto.MESSAGE, + number=3, + message='TranslateResMeta', + ) + + +class TranslateResMeta(proto.Message): + """ + 表示与翻译结果关联的proto结构元数据。 + + Attributes: + dst (str): 翻译后的文本。 + src (str): 源文本。 + """ + dst: str = proto.Field( + proto.STRING, + number=1, + ) + src: str = proto.Field( + proto.STRING, + number=2, + ) + + +class TranslateResult(BaseModel): + """ + 表示与翻译结果关联的pydantic结构元数据。 + + Attributes: + src (str): 源文本。 + dst (str): 翻译后的文本。 + """ + src: str # 源文本 + dst: str # 目标文本 + + +class TranslateOutMsg(BaseModel): + """ + 表示文本翻译输出的pydantic结构消息。 + + Attributes: + from_lang (str): 翻译的源语言。 + to_lang (str): 翻译的目标语言。 + trans_result (List[TranslateResult]): 一个包含翻译结果的列表。 + 如果请求参数 `q` 包含 `\n`,则会以分段形式返回翻译结果。 + """ + from_lang: str + to_lang: str + trans_result: List[TranslateResult] diff --git a/appbuilder/core/components/tts/README.md b/appbuilder/core/components/tts/README.md new file mode 100644 index 000000000..70c7dc6d8 --- /dev/null +++ b/appbuilder/core/components/tts/README.md @@ -0,0 +1,45 @@ +# 短文本在线合成(TTS) + +## 简介 +短文本在线合成组件(TTS)提供高度拟人、流畅自然的语音合成服务,将文本朗读出来,基础音库性价比更高,精品音库听感更逼真。 +## 基本用法 +下面是一个简单的例子来指导你开始使用这个组件 + +```python +import os +import appbuilder + +os.environ["APPBUILDER_TOKEN"] = '...' +tts = appbuilder.TTS() + +# 使用baidu-tts模型, 默认返回MP3格式 +inp = appbuilder.Message(content={"text": "欢迎使用语音合成"}) +out = tts.run(inp) +with open("sample.mp3", "wb") as f: + f.write(out.content["audio_binary"]) + +# 使用paddlespeech-tts模型,目前只支持返回WAV格式 +inp = appbuilder.Message(content={"text": "欢迎使用语音合成"}) +out = tts.run(inp, model="paddlespeech-tts", audio_type="wav") +with open("sample.wav", "wb") as f: + f.write(out.content["audio_binary"]) +``` + + +## 参数说明 +### 参数说明 +run 函数接收的参数定义: +- message (obj: `Message`): 待转为语音的文本. 举例: Message(content={"text": "欢迎使用百度语音"}) +- 如果选择`baidu-tts`模型,`text`最大文本长度为1024 GBK编码长度, 如果选择`paddlespeech-tts`模型, `text`最大文本长度是510个字符. +- model (str, 可选): 默认是`baidu-tts`模型,可设置为`paddlespeech-tts` +- speed(int, 可选): 语音语速,默认是5中等语速,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 +- pitch(int, 可选): 语音音调,默认是5中等音调,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 +- volume(int, 音量): 语音音量,默认是5中等音量,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 +- person(int, 可选): 语音人物特征,默认是0,可选值包括度小宇=1 度小美=0 度逍遥(基础)=3 度丫丫=4 度逍遥(精品)=5003 +- 度小鹿=5118 度博文=106 度小童=110 度小萌=111 度米朵=103 度小娇=5,如果选择模型为paddlespeech-tts,参数自动失效 +- audio_type(str, 可选): 音频文件格式,默认是`mp3`, 如果选择`paddlespeech-tts`模型,参数只能设为`wav` +- timeout (float, 可选): HTTP超时时间 +- retry (int, 可选): HTTP重试次数 + +返回参数说明: +- message (obj: `Message`): 文本转语音结果. 举例: Message(content={"audio_binary": b"xxx", "audio_type": "mp3"}) diff --git a/appbuilder/core/components/tts/__init__.py b/appbuilder/core/components/tts/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/components/tts/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/components/tts/component.py b/appbuilder/core/components/tts/component.py new file mode 100644 index 000000000..d05a4c155 --- /dev/null +++ b/appbuilder/core/components/tts/component.py @@ -0,0 +1,183 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""text to speech component.""" +from typing import Literal +from urllib.parse import quote_plus + +from appbuilder.core.component import Component +from appbuilder.core.message import Message +from appbuilder.core._exception import AppBuilderServerException +from appbuilder.core.components.tts.model import * + + +class TTS(Component): + r""" + 文本转语音组件,即输入一段文本将其转为一段语音 + + Examples: + + .. code-block:: python + + import appbuilder + os.environ["APPBUILDER_TOKEN"] = '...' + tts = appbuilder.TTS() + + # 默认使用baidu-tts模型, 默认返回MP3格式 + inp = appbuilder.Message(content={"text": "欢迎使用语音合成"}) + out = tts.run(inp) + with open("sample.mp3", "wb") as f: + f.write(out.content["audio_binary"]) + + # 使用paddlespeech-tts模型,目前只支持返回WAV格式 + inp = appbuilder.Message(content={"text": "欢迎使用语音合成"}) + out = tts.run(inp, model="paddlespeech-tts", audio_type="wav") + with open("sample.wav", "wb") as f: + f.write(out.content["audio_binary"]) + """ + Baidu_TTS = "baidu-tts" + PaddleSpeech_TTS = "paddlespeech-tts" + + def __init__(self, *args, **kwargs): + r"""初始化语音识别实例 + + 参数: + *args (any, 可选): 位置参数 + **kwargs(any, 可选): 关键字参数 + 返回: + 无 + """ + r""""implement __init__ method""" + super().__init__(*args, **kwargs) + self.model = "" + + def run(self, + message: Message, + model: Literal["baidu-tts", "paddlespeech-tts"] = "baidu-tts", + speed: int = 5, + pitch: int = 5, + volume: int = 5, + person: int = 0, + audio_type: Literal["mp3", "wav"] = "mp3", + timeout: float = None, + retry: int = 0 + ) -> Message: + r"""执行文本转语音 + + 参数: + message (obj: `Message`): 待转为语音的文本. 举例: Message(content={"text": "欢迎使用百度语音"}) + 如果选择`baidu-tts`模型,`text`最大文本长度为1024 GBK编码长度, 如果选择`paddlespeech-tts`模型, `text`最大文本长度是510个字符. + model (str, 可选): 默认是`baidu-tts`模型,可设置为`paddlespeech-tts` + speed(int, 可选): 语音语速,默认是5中等语速,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 + pitch(int, 可选): 语音音调,默认是5中等音调,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 + volume(int, 音量): 语音音量,默认是5中等音量,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效 + person(int, 可选): 语音人物特征,默认是0,可选值包括度小宇=1 度小美=0 度逍遥(基础)=3 度丫丫=4 度逍遥(精品)=5003 + 度小鹿=5118 度博文=106 度小童=110 度小萌=111 度米朵=103 度小娇=5,如果选择模型为paddlespeech-tts,参数自动失效 + audio_type(str, 可选): 音频文件格式,默认是`mp3`, 如果选择`paddlespeech-tts`模型,参数只能设为`wav` + timeout (float, 可选): HTTP超时时间 + retry (int, 可选): HTTP重试次数 + + 返回: + message (obj: `Message`): 文本转语音结果. 举例: Message(content={"audio_binary": b"xxx", "audio_type": "mp3"}) + """ + if model != self.Baidu_TTS and model != self.PaddleSpeech_TTS: + raise ValueError("unsupported model {}".format(model)) + self.model = model + inp = TTSInMsg(**message.content) + if len(inp.text) == 0: + raise ValueError("text field is empty") + + if model == self.Baidu_TTS and audio_type != "mp3" and audio_type != "wav": + raise ValueError("invalid audio type") + elif model == self.PaddleSpeech_TTS and audio_type != "wav": + raise ValueError("invalid audio type") + request = TTSRequest() + request.tex = inp.text + request.spd = speed + request.pit = pitch + request.vol = volume + request.per = person + if audio_type == "mp3": + request.aue = 3 + elif audio_type == "wav": + request.aue = 6 + response = self.__synthesis(request, timeout, retry) + out = TTSOutMsg(audio_binary=response.binary, audio_type=audio_type) + return Message(content=dict(out)) + + def __synthesis(self, + request: TTSRequest, + timeout: float = None, + retry: int = 0) -> TTSResponse: + r"""调用底层接口进行语音合成 + + 参数: + request (obj: `[PaddleTTSRequest, TTSRequest]`) : 语音合成输入参数 + + 返回: + response (obj: `TTSResponse`): 语音合成输出参数 + """ + request.ctp = "1" + request.lan = "zh" + request.cuid = "1" + if self.model == self.Baidu_TTS: + request.tex = quote_plus(request.tex) + request.validate_baidu_tts() + url = self.service_url("/v1/bce/aip_speech/tts_online") + elif self.model == self.PaddleSpeech_TTS: + request.tp_project_id = "paddlespeech" + request.tp_per_id = "100001" + request.validate_paddle_speech_tts() + url = self.service_url("/v1/bce/paddle_speech/text2audio") + else: + raise ValueError("model '{}' is not supported".format(self.model)) + if retry != self.retry.total: + self.retry.total = retry + auth_header = self.auth_header() + if self.model == self.Baidu_TTS: + response = self.s.post(url, data=TTSRequest.to_dict(request), timeout=timeout, headers=auth_header) + elif self.model == self.PaddleSpeech_TTS: + auth_header = self.auth_header() + auth_header['Content-type'] = "application/json" + response = self.s.post(url, json=TTSRequest.to_dict(request), timeout=timeout, headers=auth_header) + super().check_response_header(response) + content_type = response.headers.get("Content-Type", "application/json") + if content_type.find("application/json") != -1: + data = response.json() + super().check_response_json(data) + self.__class__.__check_service_error(data) + return TTSResponse( + binary=response.content, + request_id=self.response_request_id(response), + aue=request.aue + ) + + @staticmethod + def __check_service_error(data: dict): + r"""个性化服务response检查 + + 参数: + request (dict) : 文本转语音body返回 + 返回: + 无 + """ + + if "err_no" in data or "err_msg" in data or 'sn' in data or 'idx' in data: + raise AppBuilderServerException( + service_err_code=data.get("err_no", 0), + service_err_message="{} . {} . {}]". + format(data.get("err_msg", ""), + data.get("sn", ""), + data.get("idx", "")) + ) diff --git a/appbuilder/core/components/tts/model.py b/appbuilder/core/components/tts/model.py new file mode 100644 index 000000000..53b4e5fb7 --- /dev/null +++ b/appbuilder/core/components/tts/model.py @@ -0,0 +1,164 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +r"""short text to speech model.""" +import proto + +from pydantic import BaseModel + + +class TTSRequest(proto.Message): + r"""文本转语音请求参数. + + 属性: + tex (str): 如果选择`baidu-tts`模型,`tex`最大文本长度为1024 GBK编码长度, 如果选择`paddlespeech-tts`模型, + `tex`最大文本长度是510个字符. + tok (str, 可选): 用户token. + cuid (str, 可选): 用户ID. + ctp (str, 可选): 用户客户端类型. + lan (str): 目前仅支持中英-ZH. + spd(int, 可选): 语音语速,默认是5中等语速,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效. + pit(int, 可选): 语音音调,默认是5中等音调,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效. + vol(int, 音量): 语音音量,默认是5中等音量,取值范围在0~15之间,如果选择模型为paddlespeech-tts,参数自动失效. + per(int, 可选): 语音人物特征,默认是0,可选值包括度小宇=1 度小美=0 度逍遥(基础)=3 度丫丫=4 度逍遥(精品)=5003 + 度小鹿=5118 度博文=106 度小童=110 度小萌=111 度米朵=103 度小娇=5,如果选择模型为paddlespeech-tts,参数自动失效. + aue(int, 可选): 语音格式, 默认是3(mp3) 4(pcm-16k) 5(pcm-8k) 6-wav. + tp_project_id(str): paddlespeech-tts项目ID + tp_per_id(str): paddlespeech-tts音频ID + + """ + tex: str = proto.Field( + proto.STRING, + number=1, + ) + tok: str = proto.Field( + proto.STRING, + number=2, + optional=True, + ) + cuid: str = proto.Field( + proto.STRING, + number=3, + optional=True, + ) + ctp: str = proto.Field( + proto.STRING, + number=4, + ) + lan: str = proto.Field( + proto.STRING, + number=5, + ) + spd: int = proto.Field( + proto.INT32, + number=6, + ) + pit: int = proto.Field( + proto.INT32, + number=7, + ) + vol: int = proto.Field( + proto.INT32, + number=8, + ) + per: int = proto.Field( + proto.INT32, + number=9, + ) + aue: int = proto.Field( + proto.INT32, + number=10, + ) + tp_project_id: str = proto.Field( + proto.STRING, + number=11, + optional=True, + ) + tp_per_id: str = proto.Field( + proto.STRING, + number=12, + optional=True, + ) + + def __validate(self): + """检查公共参数""" + if len(self.tex) == 0: + raise ValueError("tex field must be set") + if self.spd < 0 or self.spd > 15: + raise ValueError("spd value must in [0,15]") + if self.pit < 0 or self.pit > 15: + raise ValueError("pit value must in [0,15]") + if self.vol < 0 or self.vol > 15: + raise ValueError("vol value must in [0,15]") + + def validate_baidu_tts(self): + """检查baidu-tts模型请求参数""" + self.__validate() + if self.per not in {0, 1, 3, 4, 5, 103, 106, 110, 111, 5003, 5118}: + raise ValueError("per value is illegal") + if self.aue == 0: + self.aue = 3 + if self.aue not in {3, 4, 5, 6}: + raise ValueError("aue value is illegal") + + def validate_paddle_speech_tts(self): + """验证参数是否合法""" + self.__validate() + if self.aue == 0: + self.aue = 6 + if self.aue not in {6}: + raise ValueError("aue value is illegal") + + +class TTSResponse(proto.Message): + r"""文本转语音返回. + + 属性: + binary (bytes): 语音二进制流. + aue (int):语音格式, 3(mp3), 4(pcm-16k), 5(pcm-8k) 6(wav). + request_id(str): 请求ID + """ + binary: bytes = proto.Field( + proto.BYTES, + number=1 + ) + aue: int = proto.Field( + proto.INT32, + number=2, + ) + request_id: str = proto.Field( + proto.STRING, + number=3, + ) + + +class TTSInMsg(BaseModel): + r"""文本转语音输入消息. + + 属性: + text(str): 待转为语音的文本, 如果选择`baidu-tts`模型,最大文本长度为1024 GBK编码长度 + 如果选择`paddlespeech-tts`模型, 最大文本长度是510个字符. + """ + text: str + + +class TTSOutMsg(BaseModel): + r""" 文本转语音输出消息. + + 属性: + audio_binary(bytes): 语音二进制流. + audio_type(AudioType): 语音类型,`mp3`或`wav`. + """ + audio_binary: bytes + audio_type: str diff --git a/appbuilder/core/constants.py b/appbuilder/core/constants.py new file mode 100644 index 000000000..03aa3eb87 --- /dev/null +++ b/appbuilder/core/constants.py @@ -0,0 +1,17 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +GATEWAY_URL = "https://appbuilder.baidu.com" +GATEWAY_INNER_URL = "http://appbuilder.sdns.baidu.com" diff --git a/appbuilder/core/context.py b/appbuilder/core/context.py new file mode 100644 index 000000000..c268a3bcf --- /dev/null +++ b/appbuilder/core/context.py @@ -0,0 +1,153 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +import datetime +import uuid +import json +import os +import logging +from typing import Union, List, Dict +import sqlalchemy +from sqlalchemy import create_engine, Column, Integer, String, JSON, DateTime, Boolean +from sqlalchemy.orm import declarative_base, sessionmaker +from appbuilder.core.message import Message + + +_db = declarative_base() + + +class SessionMessage(_db): + """ + 会话数据模型 + """ + __tablename__ = 'appbuilder_session_messages' + + id = Column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()), unique=True) + session_id = Column(String(36), nullable=False) + query_message = Column(JSON, nullable=False) + answer_message = Column(JSON, nullable=False) + extra = Column(JSON, nullable=False) + created_at = Column(DateTime, default=datetime.datetime.now, nullable=False) + updated_at = Column(DateTime, default=datetime.datetime.now, nullable=False) + deleted = Column(Boolean, default=False, nullable=False) + + def as_dict(self): + """ + 将模型转换为 dict 类型 + + Args: + None + + Returns: + dict + """ + fields = ["id", "query_message", "answer_message", "extra", "created_at", "updated_at"] + return {field: getattr(self, field) for field in fields} + + +class UserSession(object): + """ + 会话数据管理工具。提供保存对话数据与获取历史对话数据的方法 + + Examples: + + .. code-block:: python + + import os + import sys + import appbuilder import UserSession, Message + + user_session_config = "sqlite:///foo.db" + user_session = UserSession(user_session_config) + session_id = "634432be-9241-47ab-a055-266e89785352" + query = Message({"query": "你好"}) + answer = Message("answer": "你好,我是文心一言。"}) + + user_session.save_session_message(session_id, query, answer) + print(user_session.get_session_messages(session_id)) + """ + + def __init__(self, user_session_config: Union[sqlalchemy.engine.URL, str, None] = None): + """ + 初始化 UserSession + + Args: + user_session_config (str|None): Session 配置字符串,遵循 sqlalchemy 后端定义,参考文档 + https://docs.sqlalchemy.org/en/20/core/engines.html#backend-specific-urls + + Returns: + None + """ + if user_session_config is None: + user_session_config = "sqlite:///user_session.db" + if not isinstance(user_session_config, (sqlalchemy.engine.URL, str)): + raise ValueError("user_session_config must be sqlalchemy.URL or str") + engine = create_engine(user_session_config) + _db.metadata.create_all(engine) # 创建表 + Session = sessionmaker(engine) + self.db_session = Session() + + def get_session_messages(self, session_id: str, limit: int=10) -> List[Message]: + """ + 获取对话历史数据 + + Args: + session_id (str): Session ID + limit (int): 获取最近的几条 session 数据 + + Returns: + List[Message] + """ + session_messages = self.db_session.query(SessionMessage).filter( + SessionMessage.session_id == session_id, + SessionMessage.deleted == False).order_by( + SessionMessage.updated_at.desc()).limit(limit).all() + return [Message(content=item.as_dict()) for item in session_messages][::-1] + + def save_session_message( + self, + session_id: str, + query_message: Message, + answer_message: Message, + extra: Dict = {}, + ) -> None: + """ + 保存一条对话数据 + + Args: + session_id (str): Session ID + query_message (Message): 该次对话用户输入的 Message + answer_message (Message): 该次对话模型输出的 Message + extra (dict): 该次对话额外需要存储的数据 + + Returns: + None + """ + if not isinstance(query_message, Message): + raise ValueError("query_message must be Message") + if not isinstance(answer_message, Message): + raise ValueError("answer_message must be Message") + try: + message = SessionMessage( + query_message=json.loads(query_message.json(exclude_none=True)), + answer_message=json.loads(answer_message.json(exclude_none=True)), + extra=extra, + session_id=session_id, + created_at=datetime.datetime.now(), + updated_at=datetime.datetime.now()) + self.db_session.add(message) + self.db_session.commit() + except Exception as e: + logging.error(e) + self.db_session.rollback() + raise e \ No newline at end of file diff --git a/appbuilder/core/functional.py b/appbuilder/core/functional.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/core/functional.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/core/message.py b/appbuilder/core/message.py new file mode 100644 index 000000000..ed9d073dc --- /dev/null +++ b/appbuilder/core/message.py @@ -0,0 +1,42 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + + +import uuid + +from pydantic import BaseModel +from typing import Optional, TypeVar, Generic + + +_T = TypeVar("_T") + + +class Message(BaseModel, Generic[_T]): + content: Optional[_T] = {} + name: Optional[str] = "msg" + mtype: Optional[str] = "dict" + id: Optional[str] = str(uuid.uuid4()) + + def __init__(self, content: Optional[_T] = None, **data): + if content is not None: + data['content'] = content + super().__init__(**data) + self.mtype = type(self.content).__name__ + + def __str__(self): + return f"Message(name={self.name}, content={self.content}, mtype={self.mtype})" + + def __repr__(self): + return f"{self.__class__.__name__}(name={self.name!r}, content={self.content!r}, mtype={self.mtype!r})" diff --git a/appbuilder/core/utils.py b/appbuilder/core/utils.py new file mode 100644 index 000000000..bce92fc9c --- /dev/null +++ b/appbuilder/core/utils.py @@ -0,0 +1,20 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + + + +def utils_get_user_agent(): + return 'appbuilder-sdk-python/{}'.format("__version__") + diff --git a/appbuilder/tests/__init__.py b/appbuilder/tests/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/tests/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/tests/asr_test.pcm b/appbuilder/tests/asr_test.pcm new file mode 100644 index 0000000000000000000000000000000000000000..e5194ef726f42545b8adbfc6ad2b1c9836c90ecc GIT binary patch literal 129600 zcmXt>4@91A|M1W2s=K?VySt}1Ns?reBuSDaNs`HAW-^nRnVFf}%*@Qp%*@Qp%*DDJo#*@coagUZTGw@6=Xo68Laa=>u&nO)n zMma%Vupcc)8_|BW6a9#Gqq3kl*oz8+Fj|TZ_q`{-3-m3krbldvq8T0{VZ1i3-LNVP!|(AIHnA)1SFfxd=Sv<7J~ 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zM`hr0zSNQguc%V+T`G{0SM;H8+7>P6RGrYnMl#e);m%rR3o9>C2-ZdvW)&=!nntudiKx=JJ@@;N@<)yJNa{ zlxY$<2SfJ#_HKGcROR{h 视频 > 点击屏幕上方的“超级防抖”标识」 后置视频同时支持超级防抖和超级防抖Pro功能,开启超级' + '防抖后手机屏幕将出现超级防抖Pro开关,点击即可开启或关闭。 除此之外,前置视频同样加持防抖算法,边走边拍也能稳定聚焦脸部' + ',实时视频分享您的生活。') + + +class TestOralQueryGenerationComponent(unittest.TestCase): + + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + + self.model_name = 'eb-turbo-appbuilder' + self.node = appbuilder.OralQueryGeneration(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = TEST_TEXT + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + print(f'response:\n{answer.content}') + + # def test_run_with_stream_and_temperature(self): + # """测试不同的 stream 和 temperature 参数值""" + # query = TEST_TEXT + # msg = appbuilder.Message(query) + # answer = self.node(msg, stream=False, temperature=0.5) + # self.assertIsNotNone(answer) + + +if __name__ == '__main__': + unittest.main() \ No newline at end of file diff --git a/appbuilder/tests/test_playground.py b/appbuilder/tests/test_playground.py new file mode 100644 index 000000000..63873c8cb --- /dev/null +++ b/appbuilder/tests/test_playground.py @@ -0,0 +1,68 @@ +import unittest +import os +import appbuilder + + +class TestPlayground(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + + self.model_name = "ernie-bot-4" + self.play = appbuilder.Playground(prompt_template="你好,{name},我是{bot_name},{bot_name}是一个{bot_type},我可以{bot_function},你可以问我{bot_question}。", model=self.model_name) + + def test_run_with_valid_message(self): + """ 测试在消息有效时运行 """ + msg = appbuilder.Message({ + "name": "小明", + "bot_name": "机器人", + "bot_type": "聊天机器人", + "bot_function": "聊天", + "bot_question": "你好吗?" + }) + + answer = self.play.run(message=msg, stream=False, temperature=1) + self.assertIsNotNone(answer) + + def test_run_with_invalid_message(self): + """ 测试在消息无效时处理 """ + msg = appbuilder.Message({ + "name": "小明" + }) + + with self.assertRaises(ValueError): + self.play.run(message=msg, stream=False, temperature=1) + + def test_run_with_string_message(self): + """ 测试在消息为字符串时运行 """ + msg = appbuilder.Message("你好,小明。") + + self.play = appbuilder.Playground(prompt_template="你好,{name}。", model=self.model_name) + answer = self.play.run(message=msg, stream=False, temperature=1) + self.assertIsNotNone(answer) + + def test_run_with_stream_and_temperature(self): + """测试运行时使用参数 stream 和 temperature""" + msg = appbuilder.Message({ + "name": "小明", + "bot_name": "机器人", + "bot_type": "聊天机器人", + "bot_function": "聊天", + "bot_question": "你好吗?" + }) + + answer = self.play.run(message=msg, stream=True, temperature=0.5) + + for ans in answer.content: + self.assertIsNotNone(ans) + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_qa_pair_mining.py b/appbuilder/tests/test_qa_pair_mining.py new file mode 100644 index 000000000..fb1f6d390 --- /dev/null +++ b/appbuilder/tests/test_qa_pair_mining.py @@ -0,0 +1,62 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +import unittest +import os + +import appbuilder + + +class TestQAPairMiningComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.QAPairMining(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "2017年,工商银行根据外部宏观环境变化..." + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + self.assertIn("问题", answer.content) + self.assertIn("答案", answer.content) + + # def test_run_with_custom_params(self): + # """测试 run 方法使用自定义参数""" + # query = "2017年,工商银行根据外部宏观环境变化..." + # msg = appbuilder.Message(query) + # answer = self.node(msg, stream=True, temperature=0.5) + # self.assertIsNotNone(answer) + # # 检查 answer 是否符合预期 + + def test_run_with_invalid_params(self): + """测试 run 方法使用无效参数""" + query = "2017年,工商银行根据外部宏观环境变化..." + msg = appbuilder.Message(query) + with self.assertRaises((ValueError, TypeError)): + self.node(msg, invalid_param="invalid") + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_query_decomposition.py b/appbuilder/tests/test_query_decomposition.py new file mode 100644 index 000000000..497e7e4e4 --- /dev/null +++ b/appbuilder/tests/test_query_decomposition.py @@ -0,0 +1,59 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +import unittest +import os + +import appbuilder + + +class TestQueryDecompositionComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.QueryDecomposition(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + + # def test_run_with_custom_params(self): + # """测试 run 方法使用自定义参数""" + # query = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" + # msg = appbuilder.Message(query) + # answer = self.node(msg, stream=True, temperature=0.5) + # self.assertIsNotNone(answer) + # # 检查 answer 是否符合预期 + + def test_run_with_invalid_params(self): + """测试 run 方法使用无效参数""" + query = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性?" + msg = appbuilder.Message(query) + with self.assertRaises((ValueError, TypeError)): + self.node(msg, invalid_param="invalid") + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_query_rewrite.py b/appbuilder/tests/test_query_rewrite.py new file mode 100644 index 000000000..20bf150b3 --- /dev/null +++ b/appbuilder/tests/test_query_rewrite.py @@ -0,0 +1,64 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +# !/usr/bin/env python3 + + +import os +import unittest +from typing import List, Tuple +import appbuilder + + +class TestQueryRewriteComponent(unittest.TestCase): + def setUp(self): + """ + 初始化查询重写组件的单元测试基类。 + + Args: + 无参数。 + + Returns: + 无返回值。 + """ + # 设置环境变量和初始化TranslateComponent实例 + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.QueryRewrite(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = ['我应该怎么办理护照?', '您可以查询官网或人工咨询', '我需要准备哪些材料?', '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', '在哪里办'] + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + # 可以添加更多断言来检查 answer 的特定属性 + + def test_run_with_custom_params(self): + """测试 run 方法使用自定义参数""" + query = ['我应该怎么办理护照?', '您可以查询官网或人工咨询', '我需要准备哪些材料?', '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', '在哪里办'] + msg = appbuilder.Message(query) + type = "仅用户查询" + answer = self.node(msg, rewrite_type=type) + self.assertIsNotNone(answer) + # 检查 answer 是否符合预期 + + def test_run_with_stream_and_temperature(self): + """测试不同的 stream 和 temperature 参数值""" + node = appbuilder.QueryRewrite("eb-turbo-appbuilder") + query = ['我应该怎么办理护照?', '您可以查询官网或人工咨询', '我需要准备哪些材料?', '身份证、免冠照片一张以及填写完整的《中国公民因私出国(境)申请表》', '在哪里办'] + msg = appbuilder.Message(query) + answer = node(msg, rewrite_type="带机器人回复", stream=False, temperature=0.5) + self.assertIsNotNone(answer) + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_similar_question.py b/appbuilder/tests/test_similar_question.py new file mode 100644 index 000000000..aeb351232 --- /dev/null +++ b/appbuilder/tests/test_similar_question.py @@ -0,0 +1,65 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + +import unittest +import os + +import appbuilder + + +class TestSimilarQuestionComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.SimilarQuestion(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "我想吃冰淇淋,哪里的冰淇淋比较好吃?" + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + + # def test_run_with_custom_params(self): + # """测试 run 方法使用自定义参数""" + # query = "我想吃冰淇淋,哪里的冰淇淋比较好吃?" + # msg = appbuilder.Message(query) + # answer = self.node(msg, stream=True, temperature=0.5) + # self.assertIsNotNone(answer) + # # 检查 answer 是否符合预期 + + def test_run_with_invalid_params(self): + """测试 run 方法使用无效参数""" + query = "我想吃冰淇淋,哪里的冰淇淋比较好吃?" + msg = appbuilder.Message(query) + with self.assertRaises((ValueError, TypeError)): + self.node(msg, invalid_param="invalid") + + def test_run_with_invalid_message(self): + """测试无效的 message 参数""" + with self.assertRaises((ValueError, TypeError)): + self.node(None, stream=False, temperature=1e-10) + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_style_rewrite.py b/appbuilder/tests/test_style_rewrite.py new file mode 100644 index 000000000..50fb1415d --- /dev/null +++ b/appbuilder/tests/test_style_rewrite.py @@ -0,0 +1,80 @@ +""" +Copyright (c) 2023 Baidu, Inc. 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. +""" +import unittest +import os + +from appbuilder.core.components.llms.style_rewrite.component import StyleChoices +import appbuilder + + +class TestStyleRewriteComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.StyleRewrite(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + # 可以添加更多断言来检查 answer 的特定属性 + + def test_run_with_custom_params(self): + """测试 run 方法使用自定义参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + style = "营销话术" + answer = self.node(msg, style=style) + self.assertIsNotNone(answer) + # 检查 answer 是否符合预期 + + def test_run_with_invalid_params(self): + """测试 run 方法使用无效参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + style = "无效话术" + with self.assertRaises(ValueError): + self.node(msg, style=style) + + def test_run_with_different_style(self): + """测试不同的 style 参数值""" + node = appbuilder.StyleRewrite("eb-turbo-appbuilder") + msg = appbuilder.Message("测试消息") + for style in StyleChoices: + with self.subTest(style=style): + answer = node(msg, style=style.value) + self.assertIsNotNone(answer) + + def test_run_with_stream_and_temperature(self): + """测试不同的 stream 和 temperature 参数值""" + node = appbuilder.StyleRewrite("eb-turbo-appbuilder") + msg = appbuilder.Message("测试消息") + answer = node(msg, style="激励话术", stream=False, temperature=0.5) + self.assertIsNotNone(answer) + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_style_writing.py b/appbuilder/tests/test_style_writing.py new file mode 100644 index 000000000..0961018fa --- /dev/null +++ b/appbuilder/tests/test_style_writing.py @@ -0,0 +1,89 @@ +""" +Copyright (c) 2023 Baidu, Inc. 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. +""" +import unittest + +import appbuilder +from appbuilder.core.components.llms.style_writing.component import StyleQueryChoices, LengthChoices + + +class TestStyleWritingComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + 无参数,默认值为空。 + + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + self.model_name = "eb-turbo-appbuilder" + self.node = appbuilder.StyleWriting(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + answer = self.node(msg) + self.assertIsNotNone(answer) + # 可以添加更多断言来检查 answer 的特定属性 + + def test_run_with_custom_params(self): + """测试 run 方法使用自定义参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + style = "小红书" + length = 300 + answer = self.node(msg, style_query=style, length=length) + self.assertIsNotNone(answer) + # 检查 answer 是否符合预期 + + def test_run_with_invalid_params(self): + """测试 run 方法使用无效参数""" + query = "帮我写一篇关于人体工学椅的文案" + msg = appbuilder.Message(query) + style = "无效样式" + with self.assertRaises(ValueError): + self.node(msg, style_query=style) + + def test_run_with_different_style_query(self): + """测试不同的 style_query 参数值""" + node = appbuilder.StyleWriting("eb-turbo-appbuilder") + msg = appbuilder.Message("测试消息") + for style_query in StyleQueryChoices: + with self.subTest(style_query=style_query): + answer = node(msg, style_query=style_query.value, length=100) + self.assertIsNotNone(answer) + + def test_run_with_different_length(self): + """测试不同的 length 参数值""" + node = appbuilder.StyleWriting("eb-turbo-appbuilder") + msg = appbuilder.Message("测试消息") + for length in LengthChoices: + with self.subTest(length=length): + answer = node(msg, style_query="通用", length=length.value) + self.assertIsNotNone(answer) + + def test_run_with_stream_and_temperature(self): + """测试不同的 stream 和 temperature 参数值""" + node = appbuilder.StyleWriting("eb-turbo-appbuilder") + msg = appbuilder.Message("测试消息") + answer = node(msg, style_query="通用", length=100, stream=False, temperature=0.5) + self.assertIsNotNone(answer) + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_tag_extraction.py b/appbuilder/tests/test_tag_extraction.py new file mode 100644 index 000000000..87084d4ca --- /dev/null +++ b/appbuilder/tests/test_tag_extraction.py @@ -0,0 +1,47 @@ +# Copyright (c) 2023 Baidu, Inc. 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.import unittest import os + +import appbuilder +import os +import unittest + + +class TestTagExtractionComponent(unittest.TestCase): + def setUp(self): + """ 设置环境变量。 + Args: + 无参数,默认值为空。 + Returns: + 无返回值,方法中执行了环境变量的赋值操作。 + """ + self.model_name = "eb-turbo-appbuilder" + self.tag_extraction = appbuilder.TagExtraction(model=self.model_name) + + def test_run_with_default_params(self): + """测试 run 方法使用默认参数""" + query = "本实用新型公开了一种可利用热能的太阳能光伏光热一体化组件,包括太阳能电池,还包括有吸热板,太阳能电池粘附在吸热板顶面,吸热板内嵌入有热电材料制成的内芯,吸热板底面设置有蛇形管。本实用新型结构紧凑,安装方便,能充分利用太阳能电池散发的热能,具有较高的热能利用率。" + msg = appbuilder.Message(query) + answer = self.tag_extraction(msg) + print(answer) + self.assertIsNotNone(answer) + + def test_run_with_stream_and_temperature(self): + """测试不同的 stream 和 temperature 参数值""" + msg = appbuilder.Message("本实用新型公开了一种可利用热能的太阳能光伏光热一体化组件,包括太阳能电池,还包括有吸热板,太阳能电池粘附在吸热板顶面,吸热板内嵌入有热电材料制成的内芯,吸热板底面设置有蛇形管。本实用新型结构紧凑,安装方便,能充分利用太阳能电池散发的热能,具有较高的热能利用率。") + answer = self.tag_extraction(msg, stream=False, temperature=0.5) + self.assertIsNotNone(answer) + + +if __name__ == '__main__': + unittest.main() \ No newline at end of file diff --git a/appbuilder/tests/test_text_to_image.py b/appbuilder/tests/test_text_to_image.py new file mode 100644 index 000000000..744517fae --- /dev/null +++ b/appbuilder/tests/test_text_to_image.py @@ -0,0 +1,108 @@ +import unittest +import os +import appbuilder +from appbuilder.core.components.text_to_image.model import (Text2ImageSubmitRequest, Text2ImageSubmitResponse, + Text2ImageQueryRequest, Text2ImageQueryResponse) + + +class TestText2ImageComponent(unittest.TestCase): + def setUp(self): + """ + 设置环境变量。 + + Args: + None + + Returns: + None. + """ + self.text2Image = appbuilder.Text2Image() + + def test_run(self): + """ + 使用原始文本进行单测 + + Args: + None + + Returns: + None + + """ + inp = appbuilder.Message(content={"prompt": "上海的经典风景"}) + out = self.text2Image.run(inp) + self.assertIsNotNone(out) + self.assertIsInstance(out, appbuilder.Message) + + def test_submitText2ImageTask(self): + """ + submitText2ImageTask方法单测 + + Args: + None + + Returns: + None + + """ + request = Text2ImageSubmitRequest() + request.prompt = "上海的经典风景" + request.width = 1024 + request.height = 1024 + request.image_num = 1 + response = self.text2Image.submitText2ImageTask(request) + self.assertIsNotNone(response) + self.assertIsInstance(response, Text2ImageSubmitResponse) + + def test_queryText2ImageData(self): + """ + queryText2ImageData方法单测 + + Args: + None + + Returns: + None + + """ + request = Text2ImageQueryRequest() + request.task_id = '123456' + response = self.text2Image.queryText2ImageData(request) + self.assertIsNotNone(response) + self.assertIsInstance(response, Text2ImageQueryResponse) + + def test_extract_img_urls(self): + """ + extract_img_urls方法单测 + + Args: + None + + Returns: + None + + """ + response = Text2ImageQueryResponse() + response.data.task_progress = 1 + response.data.sub_task_result_list = [{'final_image_list': [{'img_url': 'http://example.com'}]}] + img_urls = self.text2Image.extract_img_urls(response) + self.assertEqual(img_urls, ['http://example.com']) + + def test_check_service_error(self): + """ + check_service_error方法单测 + + Args: + None + + Returns: + None + + """ + data = {"error_code": "ERROR", "error_msg": "Error message"} + with self.assertRaises(appbuilder.AppBuilderServerException): + self.text2Image.check_service_error(data) + + +if __name__ == '__main__': + 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z#910uR6%H9*Ow)q$J#RI`Wwvq!?_fK2oxO$F_D*9xvX;MatMykitS{wKp#MA$k6#c8DUsGfMl6CUNvi@75?62@&laKy_55L*>@9Tt_E-2nLm7X80f5IhhVI`28^6MT<&^&t@R{I`*8jmU|BC;W z@cRp|Li`8*7y9p43BU3~e@QSW{d4^P%NG3#{^xx87xYbonEp2UKW0xw8HhLa`0dLQ PI6&Xq3@gC;+u8pBr#HpM literal 0 HcmV?d00001 diff --git a/appbuilder/tests/test_translate.py b/appbuilder/tests/test_translate.py new file mode 100644 index 000000000..5fdbbbdce --- /dev/null +++ b/appbuilder/tests/test_translate.py @@ -0,0 +1,25 @@ +import unittest +import os +import appbuilder + + +class TestTranslationComponent(unittest.TestCase): + def setUp(self): + self.translation = appbuilder.Translation() + + def test_run_valid_request(self): + """测试 run 方法对有效请求的处理。""" + msg = appbuilder.Message(content="你好") + result = self.translation(msg) + self.assertEqual(result.content['from_lang'], 'zh') + self.assertEqual(result.content['to_lang'], 'en') + + def test_run_invalid_request(self): + """测试 run 方法对无效请求的处理。""" + msg = appbuilder.Message(content="") + with self.assertRaises(ValueError): + _ = self.translation(msg) + + +if __name__ == '__main__': + unittest.main() diff --git a/appbuilder/tests/test_tts.py b/appbuilder/tests/test_tts.py new file mode 100644 index 000000000..15620178a --- /dev/null +++ b/appbuilder/tests/test_tts.py @@ -0,0 +1,51 @@ +# Copyright (c) 2023 Baidu, Inc. 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. +import unittest +import os +import appbuilder + + +class TestTTS(unittest.TestCase): + def setUp(self): + self.tts = appbuilder.TTS() + self.text_message = appbuilder.Message(content={"text": "欢迎使用语音合成"}) + + def test_model_validation(self): + with self.assertRaises(ValueError): + self.tts.run(self.text_message, model="invalid_model") + + def test_text_validation(self): + empty_message = appbuilder.Message(content={}) + with self.assertRaises(ValueError): + self.tts.run(empty_message) + + def test_audio_type_validation_baidu_tts(self): + with self.assertRaises(ValueError): + self.tts.run(self.text_message, model="baidu-tts", audio_type="flac") + + def test_audio_type_validation_paddlespeech_tts(self): + with self.assertRaises(ValueError): + self.tts.run(self.text_message, model="paddlespeech-tts", audio_type="mp3") + + def test_run_baidu_tts(self): + out = self.tts.run(self.text_message, model="baidu-tts", audio_type="wav") + self.assertTrue("audio_binary" in out.content and "audio_type" in out.content) + + def test_run_paddlespeech_tts(self): + out = self.tts.run(self.text_message, model="paddlespeech-tts", audio_type="wav") + self.assertTrue("audio_binary" in out.content and "audio_type" in out.content) + + +if __name__ == "__main__": + unittest.main() diff --git a/appbuilder/utils/__init__.py b/appbuilder/utils/__init__.py new file mode 100644 index 000000000..fc3a1a2ea --- /dev/null +++ b/appbuilder/utils/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + diff --git a/appbuilder/utils/logger_util.py b/appbuilder/utils/logger_util.py new file mode 100644 index 000000000..cfd3cff07 --- /dev/null +++ b/appbuilder/utils/logger_util.py @@ -0,0 +1,124 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" +日志 +""" +import uuid +import os +import logging.config +from threading import current_thread + + +LOGGING_CONFIG = { + 'version': 1, + 'disable_existing_loggers': False, + 'formatters': { + 'standard': { + 'format': '[%(asctime)s.%(msecs)03d] %(filename)s [line:%(lineno)d] %(levelname)s [%(logid)s] %(message)s', + }, + }, + 'handlers': { + 'console': { + 'level': 'INFO', + 'class': 'logging.StreamHandler', + 'formatter': 'standard', + 'stream': 'ext://sys.stdout', # Use standard output + }, + }, + 'loggers': { + 'appbuilder': { + 'handlers': ['console'], + 'level': 'INFO', + 'propagate': True, + }, + } +} + + +class LoggerWithLoggerId(logging.LoggerAdapter): + """ + logger with logid + """ + def __init__(self, logger, extra, loglevel): + """ + init + """ + LOGGING_CONFIG['handlers']['console']['level'] = loglevel + LOGGING_CONFIG['loggers']['appbuilder']['level'] = loglevel + logging.config.dictConfig(LOGGING_CONFIG) + logging.LoggerAdapter.__init__(self, logger, extra) + self.logid_dict = {} + + def set_auto_logid(self): + """ + set auto log_id + """ + self.logid_dict[current_thread().ident] = str(uuid.uuid4().int & (1 << 64) - 1) + + def set_logid(self, logid): + """ + set log_id + """ + self.logid_dict[current_thread().ident] = logid + + def get_logid(self): + """ + get log_id + """ + if current_thread().ident in self.logid_dict: + return self.logid_dict[current_thread().ident] + else: + return None + + @property + def level(self): + """ + level + """ + return self.logger.level + + def process(self, msg, kwargs): + """ + processing + """ + if current_thread().ident in self.logid_dict: + # in process thread + if 'extra' not in kwargs: + kwargs['extra'] = {'logid': self.logid_dict[current_thread().ident]} + else: + kwargs['extra']['logid'] = self.logid_dict[current_thread().ident] + else: + # in main thread + if 'extra' not in kwargs: + kwargs['extra'] = {'logid': 'main-' + str(uuid.uuid4().int & (1 << 64) - 1)} + else: + kwargs['extra']['logid'] = 'main-' + str(uuid.uuid4().int & (1 << 64) - 1) + + return msg, kwargs + + +def _setup_logging(): + log_level = os.environ.get("APPBUILDER_LOGLEVEL", "INFO") + log_level = log_level.strip().lower() + + if log_level not in ["debug", "info", "warning", "error"]: + raise ValueError("expected APPBUILDER_LOGLEVEL in [debug, info, warning, error], but got %s" % log_level) + return LoggerWithLoggerId(logging.getLogger('appbuilder'), {'logid': ''}, log_level.upper()) + + +logger = _setup_logging() + + diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 000000000..69fe55ecf --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,19 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) \ No newline at end of file diff --git a/docs/build.sh b/docs/build.sh new file mode 100644 index 000000000..1bdb58dea --- /dev/null +++ b/docs/build.sh @@ -0,0 +1,57 @@ + +#!/bin/bash + +# 设置 PYTHONPATH 为当前目录 +export PYTHONPATH=${PYTHONPATH}:$(pwd)/../ +export WORKDIR="$(pwd)/../appbuilder" + + +# 遍历指定工作目录及其子目录下的所有 readme.md 文件 +find "$WORKDIR" -type f -iname "readme.md" | while read file; do + # 对每个找到的 readme.md 文件执行操作 + + dirpath=$(dirname "$file") + basename=$(basename "$dirpath") + + output_file="source/rst/components/${basename}.rst" + rst_file="rst/components/${basename}.rst" + python3 markdown2rst.py --input_file $file --output_file ${output_file} --overwrite true + + # 收集输出文件路径 + output_files+=("${rst_file}") + + # 在这里添加对文件的其他处理 + # ... +done + +# 用于收集输出文件路径的数组 +output_files=() + +# 遍历 source/rst/components/ 目录来构建 output_files 列表 +cd source/ +for file in rst/components/*.rst; do + # 检查文件是否存在 + if [ -f "$file" ]; then + output_files+=("$file") + fi +done +cd .. + +echo "output_files: ${output_files[@]}" + +# 构建替换字符串 +components_rst="" +for file in "${output_files[@]}"; do + components_rst+=" ${file}\n" +done + +# 使用模板文件创建新的 index.rst +cp index.rst.template source/index.rst + +# 替换 index.rst 文件中的占位符 +sed -i '' "s|{{components_rst}}|${components_rst}|g" source/index.rst + +# 删除旧的 index.rst.template 文件 +rm -rf build +# 生成 html +make html diff --git a/docs/index.rst.template b/docs/index.rst.template new file mode 100644 index 000000000..7efe1b26a --- /dev/null +++ b/docs/index.rst.template @@ -0,0 +1,30 @@ + +========================================================= +Appbuilder-SDK 文档主页 +========================================================= + + +Appbuilder-SDK .... + + +.. toctree:: + :maxdepth: 1 + :caption: 概览 + :name: _introduction + + rst/introduction + md/authentication.rst + md/components.rst + +.. toctree:: + :maxdepth: 1 + :caption: 组件说明 + :name: _components + +{{components_rst}} + + +======= + +Apache-2.0 + diff --git a/docs/markdown2rst.py b/docs/markdown2rst.py new file mode 100644 index 000000000..4a6282f80 --- /dev/null +++ b/docs/markdown2rst.py @@ -0,0 +1,724 @@ +#!/usr/bin/env python3 +""" + markdown to rst +""" +# -*- coding: utf-8 -*- + +from __future__ import print_function, unicode_literals +import os +import os.path +import re +import sys +from argparse import ArgumentParser, Namespace + +from docutils import statemachine, nodes, io, utils +from docutils.parsers import rst +from docutils.core import ErrorString +from docutils.utils import SafeString, column_width +import mistune + +if sys.version_info < (3, ): + from codecs import open as _open + from urlparse import urlparse +else: + _open = open + from urllib.parse import urlparse + +__version__ = '0.2.1' +_is_sphinx = False +prolog = '''\ +.. role:: raw-html-m2r(raw) + :format: html + +''' + +# for command-line use +parser = ArgumentParser() +options = Namespace() +parser.add_argument( + 'input_file', nargs='*', help='files to convert to reST format') +parser.add_argument( + '--overwrite', + action='store_true', + default=False, + help='overwrite output file without confirmaion') +parser.add_argument( + '--dry-run', + action='store_true', + default=False, + help='print conversion result and not save output file') +parser.add_argument( + '--no-underscore-emphasis', + action='store_true', + default=False, + help='do not use underscore (_) for emphasis') +parser.add_argument( + '--parse-relative-links', + action='store_true', + default=False, + help='parse relative links into ref or doc directives') +parser.add_argument( + '--anonymous-references', + action='store_true', + default=False, + help='use anonymous references in generated rst') +parser.add_argument( + '--disable-inline-math', + action='store_true', + default=False, + help='disable parsing inline math') +parser.add_argument( + '--output_file', + default=None, + help='files to save reST file') + + +def parse_options(): + """parse_options""" + parser.parse_known_args(namespace=options) + + +class RestBlockGrammar(mistune.BlockGrammar): + """RestBlockGrammar""" + directive = re.compile( + r'^( *\.\..*?)\n(?=\S)', + re.DOTALL | re.MULTILINE, ) + oneline_directive = re.compile( + r'^( *\.\..*?)$', + re.DOTALL | re.MULTILINE, ) + rest_code_block = re.compile( + r'^::\s*$', + re.DOTALL | re.MULTILINE, ) + + +class RestBlockLexer(mistune.BlockLexer): + """RestBlockLexer""" + grammar_class = RestBlockGrammar + default_rules = [ + 'directive', + 'oneline_directive', + 'rest_code_block', + ] + mistune.BlockLexer.default_rules + + def parse_directive(self, m): + """parse_directive""" + self.tokens.append({ + 'type': 'directive', + 'text': m.group(1), + }) + + def parse_oneline_directive(self, m): + """parse_oneline_directive""" + # reuse directive output + self.tokens.append({ + 'type': 'directive', + 'text': m.group(1), + }) + + def parse_rest_code_block(self, m): + """parse_rest_code_block""" + self.tokens.append({'type': 'rest_code_block', }) + + +class RestInlineGrammar(mistune.InlineGrammar): + """RestInlineGrammar""" + image_link = re.compile( + r'\[!\[(?P.*?)\]\((?P.*?)\).*?\]\((?P.*?)\)') + rest_role = re.compile(r':.*?:`.*?`|`[^`]+`:.*?:') + rest_link = re.compile(r'`[^`]*?`_') + inline_math = re.compile(r'.*\$(.*)?\$') + eol_literal_marker = re.compile(r'(\s+)?::\s*$') + # add colon and space as special text + text = re.compile(r'^[\s\S]+?(?=[\\[\s\S]+?)\1{2}(?!\1)') + # _word_ or *word* + emphasis = re.compile(r'^\b_((?:__|[^_])+?)_\b' # _word_ + r'|' + r'^\*(?P(?:\*\*|[^\*])+?)\*(?!\*)' # *word* + ) + + def no_underscore_emphasis(self): + """no_underscore_emphasis""" + self.double_emphasis = re.compile( + r'^\*{2}(?P[\s\S]+?)\*{2}(?!\*)' # **word** + ) + self.emphasis = re.compile( + r'^\*(?P(?:\*\*|[^\*])+?)\*(?!\*)' # *word* + ) + + +class RestInlineLexer(mistune.InlineLexer): + """RestInlineLexer""" + grammar_class = RestInlineGrammar + default_rules = [ + 'image_link', + 'rest_role', + 'rest_link', + 'eol_literal_marker', + ] + mistune.InlineLexer.default_rules + + def __init__(self, *args, **kwargs): + no_underscore_emphasis = kwargs.pop('no_underscore_emphasis', False) + disable_inline_math = kwargs.pop('disable_inline_math', False) + super(RestInlineLexer, self).__init__(*args, **kwargs) + if not _is_sphinx: + parse_options() + if no_underscore_emphasis or getattr(options, 'no_underscore_emphasis', + False): + self.rules.no_underscore_emphasis() + inline_maths = 'inline_math' in self.default_rules + if disable_inline_math or getattr(options, 'disable_inline_math', + False): + if inline_maths: + self.default_rules.remove('inline_math') + elif not inline_maths: + self.default_rules.insert(0, 'inline_math') + + def output_double_emphasis(self, m): + """output_double_emphasis""" + # may include code span + text = self.output(m.group('text')) + return self.renderer.double_emphasis(text) + + def output_emphasis(self, m): + """output_emphasis""" + # may include code span + text = self.output(m.group('text') or m.group(1)) + return self.renderer.emphasis(text) + + def output_image_link(self, m): + """Pass through rest role.""" + return self.renderer.image_link( + m.group('url'), m.group('target'), m.group('alt')) + + def output_rest_role(self, m): + """Pass through rest role.""" + return self.renderer.rest_role(m.group(0)) + + def output_rest_link(self, m): + """Pass through rest link.""" + return self.renderer.rest_link(m.group(0)) + + def output_inline_math(self, m): + """Pass through rest link.""" + return self.renderer.inline_math(m.group(0)) + + def output_eol_literal_marker(self, m): + """Pass through rest link.""" + marker = ':' if m.group(1) is None else '' + return self.renderer.eol_literal_marker(marker) + + +class RestRenderer(mistune.Renderer): + """RestRenderer""" + _include_raw_html = False + list_indent_re = re.compile(r'^(\s*(#\.|\*)\s)') + indent = ' ' * 3 + list_marker = '{#__rest_list_mark__#}' + hmarks = { + 1: '=', + 2: '-', + 3: '^', + 4: '~', + 5: '"', + 6: '#', + } + + def __init__(self, *args, **kwargs): + self.parse_relative_links = kwargs.pop('parse_relative_links', False) + self.anonymous_references = kwargs.pop('anonymous_references', False) + super(RestRenderer, self).__init__(*args, **kwargs) + if not _is_sphinx: + parse_options() + if getattr(options, 'parse_relative_links', False): + self.parse_relative_links = options.parse_relative_links + if getattr(options, 'anonymous_references', False): + self.anonymous_references = options.anonymous_references + + def _indent_block(self, block): + return '\n'.join(self.indent + line if line else '' + for line in block.splitlines()) + + def _raw_html(self, html): + self._include_raw_html = True + return '\ :raw-html-m2r:`{}`\ '.format(html) + + def block_code(self, code, lang=None): + """block_code""" + if lang == 'math': + first_line = '\n.. math::\n\n' + elif lang: + first_line = '\n.. code-block:: {}\n\n'.format(lang) + elif _is_sphinx: + first_line = '\n.. code-block:: guess\n\n' + else: + first_line = '\n.. code-block::\n\n' + return first_line + self._indent_block(code) + '\n' + + def block_quote(self, text): + """block_quote""" + # text includes some empty line + return '\n..\n\n{}\n\n'.format(self._indent_block(text.strip('\n'))) + + def block_html(self, html): + """Rendering block level pure html content. + + :param html: text content of the html snippet. + """ + return '\n\n.. raw:: html\n\n' + self._indent_block(html) + '\n\n' + + def header(self, text, level, raw=None): + """Rendering header/heading tags like ``

`` ``

``. + + :param text: rendered text content for the header. + :param level: a number for the header level, for example: 1. + :param raw: raw text content of the header. + """ + return '\n{0}\n{1}\n'.format(text, + self.hmarks[level] * column_width(text)) + + def hrule(self): + """Rendering method for ``
`` tag.""" + return '\n----\n' + + def list(self, body, ordered=True): + """Rendering list tags like ``
    `` and ``
      ``. + + :param body: body contents of the list. + :param ordered: whether this list is ordered or not. + """ + mark = '#. ' if ordered else '* ' + lines = body.splitlines() + for i, line in enumerate(lines): + if line and not line.startswith(self.list_marker): + lines[i] = ' ' * len(mark) + line + return '\n{}\n'.format('\n'.join(lines)).replace(self.list_marker, + mark) + + def list_item(self, text): + """Rendering list item snippet. Like ``
    1. ``.""" + return '\n' + self.list_marker + text + + def paragraph(self, text): + """Rendering paragraph tags. Like ``

      ``.""" + return '\n' + text + '\n' + + def table(self, header, body): + """Rendering table element. Wrap header and body in it. + + :param header: header part of the table. + :param body: body part of the table. + """ + table = '\n.. list-table::\n' + if header and not header.isspace(): + table = (table + self.indent + ':header-rows: 1\n\n' + + self._indent_block(header) + '\n') + else: + table = table + '\n' + table = table + self._indent_block(body) + '\n\n' + return table + + def table_row(self, content): + """Rendering a table row. Like ````. + + :param content: content of current table row. + """ + contents = content.splitlines() + if not contents: + return '' + clist = ['* ' + contents[0]] + if len(contents) > 1: + for c in contents[1:]: + clist.append(' ' + c) + return '\n'.join(clist) + '\n' + + def table_cell(self, content, **flags): + """Rendering a table cell. Like ```` ````. + + :param content: content of current table cell. + :param header: whether this is header or not. + :param align: align of current table cell. + """ + return '- ' + content + '\n' + + def double_emphasis(self, text): + """Rendering **strong** text. + + :param text: text content for emphasis. + """ + return '\ **{}**\ '.format(text) + + def emphasis(self, text): + """Rendering *emphasis* text. + + :param text: text content for emphasis. + """ + return '\ *{}*\ '.format(text) + + def codespan(self, text): + """Rendering inline `code` text. + + :param text: text content for inline code. + """ + if '``' not in text: + return '\ ``{}``\ '.format(text) + else: + # actually, docutils split spaces in literal + return self._raw_html('' + '{}' + ''.format( + text.replace('`', '`'))) + + def linebreak(self): + """Rendering line break like ``
      ``.""" + if self.options.get('use_xhtml'): + return self._raw_html('
      ') + '\n' + return self._raw_html('
      ') + '\n' + + def strikethrough(self, text): + """Rendering ~~strikethrough~~ text. + + :param text: text content for strikethrough. + """ + return self._raw_html('{}'.format(text)) + + def text(self, text): + """Rendering unformatted text. + + :param text: text content. + """ + return text + + def autolink(self, link, is_email=False): + """Rendering a given link or email address. + + :param link: link content or email address. + :param is_email: whether this is an email or not. + """ + return link + + def link(self, link, title, text): + """Rendering a given link with content and title. + + :param link: href link for ``
      `` tag. + :param title: title content for `title` attribute. + :param text: text content for description. + """ + if self.anonymous_references: + underscore = '__' + else: + underscore = '_' + if title: + return self._raw_html( + '{text}'.format( + link=link, title=title, text=text)) + if not self.parse_relative_links: + return '\ `{text} <{target}>`{underscore}\ '.format( + target=link, text=text, underscore=underscore) + else: + url_info = urlparse(link) + if url_info.scheme: + return '\ `{text} <{target}>`{underscore}\ '.format( + target=link, text=text, underscore=underscore) + else: + link_type = 'doc' + anchor = url_info.fragment + if url_info.fragment: + if url_info.path: + # Can't link to anchors via doc directive. + anchor = '' + else: + # Example: [text](#anchor) + link_type = 'ref' + doc_link = '{doc_name}{anchor}'.format( + # splittext approach works whether or not path is set. It + # will return an empty string if unset, which leads to + # anchor only ref. + doc_name=os.path.splitext(url_info.path)[0], + anchor=anchor) + return '\ :{link_type}:`{text} <{doc_link}>`\ '.format( + link_type=link_type, doc_link=doc_link, text=text) + + def image(self, src, title, text): + """Rendering a image with title and text. + + :param src: source link of the image. + :param title: title text of the image. + :param text: alt text of the image. + """ + # rst does not support title option + # and I couldn't find title attribute in HTML standard + return '\n'.join([ + '', + '.. image:: {}'.format(src), + ' :target: {}'.format(src), + ' :alt: {}'.format(text), + '', + ]) + + def inline_html(self, html): + """Rendering span level pure html content. + + :param html: text content of the html snippet. + """ + return self._raw_html(html) + + def newline(self): + """Rendering newline element.""" + return '' + + def footnote_ref(self, key, index): + """Rendering the ref anchor of a footnote. + + :param key: identity key for the footnote. + :param index: the index count of current footnote. + """ + return '\ [#fn-{}]_\ '.format(key) + + def footnote_item(self, key, text): + """Rendering a footnote item. + + :param key: identity key for the footnote. + :param text: text content of the footnote. + """ + return '.. [#fn-{0}] {1}\n'.format(key, text.strip()) + + def footnotes(self, text): + """Wrapper for all footnotes. + + :param text: contents of all footnotes. + """ + if text: + return '\n\n' + text + else: + return '' + + """Below outputs are for rst.""" + + def image_link(self, url, target, alt): + """image_link""" + return '\n'.join([ + '', + '.. image:: {}'.format(url), + ' :target: {}'.format(target), + ' :alt: {}'.format(alt), + '', + ]) + + def rest_role(self, text): + """rest_role""" + return text + + def rest_link(self, text): + """rest_link""" + return text + + def inline_math(self, math): + """Extension of recommonmark""" + return re.sub(r'\$(.*?)\$', + lambda x: '\ :math:`{}`\ '.format(x.group(1)), math) + + def eol_literal_marker(self, marker): + """Extension of recommonmark""" + return marker + + def directive(self, text): + """directive""" + return '\n' + text + '\n' + + def rest_code_block(self): + """rest_code_block""" + return '\n\n' + + +class M2R(mistune.Markdown): + """M2R""" + + def __init__(self, + renderer=None, + inline=RestInlineLexer, + block=RestBlockLexer, + **kwargs): + if renderer is None: + renderer = RestRenderer(**kwargs) + super(M2R, self).__init__( + renderer, inline=inline, block=block, **kwargs) + + def parse(self, text): + """parse""" + output = super(M2R, self).parse(text) + return self.post_process(output) + + def output_directive(self): + """output_directive""" + return self.renderer.directive(self.token['text']) + + def output_rest_code_block(self): + """output_rest_code_block""" + return self.renderer.rest_code_block() + + def post_process(self, text): + """post_process""" + output = (text.replace('\\ \n', '\n').replace('\n\\ ', '\n') + .replace(' \\ ', ' ').replace('\\ ', ' ') + .replace('\\ .', '.')) + if self.renderer._include_raw_html: + return prolog + output + else: + return output + + +class M2RParser(rst.Parser, object): + """M2RParser""" + # Explicitly tell supported formats to sphinx + supported = ('markdown', 'md', 'mkd') + + def parse(self, inputstrings, document): + """parse""" + if isinstance(inputstrings, statemachine.StringList): + inputstring = '\n'.join(inputstrings) + else: + inputstring = inputstrings + config = document.settings.env.config + converter = M2R(no_underscore_emphasis=config.no_underscore_emphasis, + parse_relative_links=config.m2r_parse_relative_links, + anonymous_references=config.m2r_anonymous_references, + disable_inline_math=config.m2r_disable_inline_math) + super(M2RParser, self).parse(converter(inputstring), document) + + +class MdInclude(rst.Directive): + """Directive class to include markdown in sphinx. + + Load a file and convert it to rst and insert as a node. Currently + directive-specific options are not implemented. + """ + required_arguments = 1 + optional_arguments = 0 + option_spec = { + 'start-line': int, + 'end-line': int, + } + + def run(self): + """Most of this method is from ``docutils.parser.rst.Directive``. + + docutils version: 0.12 + """ + if not self.state.document.settings.file_insertion_enabled: + raise self.warning('"%s" directive disabled.' % self.name) + source = self.state_machine.input_lines.source( + self.lineno - self.state_machine.input_offset - 1) + source_dir = os.path.dirname(os.path.abspath(source)) + path = rst.directives.path(self.arguments[0]) + path = os.path.normpath(os.path.join(source_dir, path)) + path = utils.relative_path(None, path) + path = nodes.reprunicode(path) + + # get options (currently not use directive-specific options) + encoding = self.options.get( + 'encoding', self.state.document.settings.input_encoding) + e_handler = self.state.document.settings.input_encoding_error_handler + tab_width = self.options.get('tab-width', + self.state.document.settings.tab_width) + + # open the including file + try: + self.state.document.settings.record_dependencies.add(path) + include_file = io.FileInput( + source_path=path, encoding=encoding, error_handler=e_handler) + except UnicodeEncodeError as error: + raise self.severe('Problems with "%s" directive path:\n' + 'Cannot encode input file path "%s" ' + '(wrong locale?).' % + (self.name, SafeString(path))) + except IOError as error: + raise self.severe('Problems with "%s" directive path:\n%s.' % + (self.name, ErrorString(error))) + + # read from the file + startline = self.options.get('start-line', None) + endline = self.options.get('end-line', None) + try: + if startline or (endline is not None): + lines = include_file.readlines() + rawtext = ''.join(lines[startline:endline]) + else: + rawtext = include_file.read() + except UnicodeError as error: + raise self.severe('Problem with "%s" directive:\n%s' % + (self.name, ErrorString(error))) + + config = self.state.document.settings.env.config + converter = M2R(no_underscore_emphasis=config.no_underscore_emphasis, + parse_relative_links=config.m2r_parse_relative_links, + anonymous_references=config.m2r_anonymous_references, + disable_inline_math=config.m2r_disable_inline_math) + include_lines = statemachine.string2lines( + converter(rawtext), tab_width, convert_whitespace=True) + self.state_machine.insert_input(include_lines, path) + return [] + + +def setup(app): + """When used for sphinx extension.""" + global _is_sphinx + _is_sphinx = True + app.add_config_value('no_underscore_emphasis', False, 'env') + app.add_config_value('m2r_parse_relative_links', False, 'env') + app.add_config_value('m2r_anonymous_references', False, 'env') + app.add_config_value('m2r_disable_inline_math', False, 'env') + app.add_source_parser('.md', M2RParser) + app.add_directive('mdinclude', MdInclude) + metadata = dict( + version=__version__, + parallel_read_safe=True, + parallel_write_safe=True, ) + return metadata + + +def convert(text, **kwargs): + """convert""" + return M2R(**kwargs)(text) + + +def parse_from_file(file, encoding='utf-8', **kwargs): + """parse_from_file""" + if not os.path.exists(file): + raise OSError('No such file exists: {}'.format(file)) + with _open(file, encoding=encoding) as f: + src = f.read() + output = convert(src, **kwargs) + return output + + +def save_to_file(target, src, encoding='utf-8', **kwargs): + """save_to_file""" + + if not options.overwrite and os.path.exists(target): + confirm = input('{} already exists. overwrite it? [y/n]: '.format( + target)) + if confirm.upper() not in ('Y', 'YES'): + print('skip {}'.format(target)) + return + with _open(target, 'w', encoding=encoding) as f: + f.write(src) + + +def main(): + """main""" + parse_options() # parse cli options + if not options.input_file: + parser.print_help() + parser.exit(0) + for file in options.input_file: + output = parse_from_file(file) + if options.dry_run: + print(output) + else: + save_to_file(options.output_file, output) + + +if __name__ == '__main__': + main() diff --git a/docs/requirements.txt b/docs/requirements.txt new file mode 100644 index 000000000..c6c9038ac --- /dev/null +++ b/docs/requirements.txt @@ -0,0 +1,7 @@ +sphinx==2.1.0 +mistune==0.8.4 +docutils==0.16 +sphinx_rtd_theme==0.4.3 +recommonmark==0.7.1 +commonmark==0.9.1 +zmq diff --git a/docs/source/.DS_Store b/docs/source/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..b1fabae9e8f4ca509774d41322b080d8db351bfa GIT binary patch literal 6148 zcmeHK%}T>S5S~p7R`gJB9{1?A-~+@G??N9yZ38Maq-eeGLGTrP7Vo~7-~1#Jl7J^E zG6S<;GCPwm`(?@Q5>Z&bmJ6ae5zXL?*)f^{<9_y@WfnOF26@Jwo@lduSgba6FWUo$ zr~rSvBf6y*+S5I}{eIQXUiYG(QPoAU-qvgM@Wgog{P?;W$|`@6wR_~*(y;M7q>L&m zbrv=8%d;jv!YwsbJ;*41U7j1}nb0$jyURrHKRqK{RyV?Cy!=#7^%r^oegEy|g HpDOSTfLU3o literal 0 HcmV?d00001 diff --git a/docs/source/_static/style.css b/docs/source/_static/style.css new file mode 100644 index 000000000..579fe077d --- /dev/null +++ b/docs/source/_static/style.css @@ -0,0 +1,3 @@ +.wy-nav-content { + max-width: none; +} \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 000000000..a05ad41d3 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,199 @@ +# -*- coding: utf-8 -*- +# +# Configuration file for the Sphinx documentation builder. +# +# This file does only contain a selection of the most common options. For a +# full list see the documentation: +# http://www.sphinx-doc.org/en/master/config + +# -- Path setup -------------------------------------------------------------- + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +# import os +# import sys +# sys.path.insert(0, os.path.abspath('.')) + +import os +import sys +sys.path.append(os.path.abspath('..')) +import sphinx_rtd_theme + +# -- Project information ----------------------------------------------------- +project = u'appbuilder-sdk' +copyright = u'2023, baidubce' +author = u'baidubce' + +# The short X.Y version +version = u'' +# The full version, including alpha/beta/rc tags +release = u'' + + +# -- General configuration --------------------------------------------------- + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'sphinx.ext.autodoc', + 'sphinx.ext.doctest', + 'sphinx.ext.intersphinx', + 'sphinx.ext.todo', + 'sphinx.ext.mathjax', + 'sphinx.ext.viewcode', + 'recommonmark', +] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# 配置 Source Parser + +source_suffix = ['.rst', '.md'] +# source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = u'cn' + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = [] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = None + + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = "sphinx_rtd_theme" +html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] +html_show_sourcelink = False + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +# +# html_theme_options = {} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# Custom sidebar templates, must be a dictionary that maps document names +# to template names. +# +# The default sidebars (for documents that don't match any pattern) are +# defined by theme itself. Builtin themes are using these templates by +# default: ``['localtoc.html', 'relations.html', 'sourcelink.html', +# 'searchbox.html']``. +# +# html_sidebars = {} + + +# -- Options for HTMLHelp output --------------------------------------------- + +# Output file base name for HTML help builder. +htmlhelp_basename = 'appbuilder-sdk' + + +# -- Options for LaTeX output ------------------------------------------------ + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + (master_doc, 'appbuilder-sdk.tex', u'appbuilder-sdk Documentation', + u'airec', 'manual'), +] + + +# -- Options for manual page output ------------------------------------------ + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + (master_doc, 'appbuilder-sdk', u'appbuilder-sdk Documentation', + [author], 1) +] + + +# -- Options for Texinfo output ---------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + (master_doc, 'appbuilder-sdk', u'appbuilder-sdk Documentation', + author, 'appbuilder-sdk', 'One line description of project.', + 'Miscellaneous'), +] + + +# -- Options for Epub output ------------------------------------------------- + +# Bibliographic Dublin Core info. +epub_title = project + +# The unique identifier of the text. This can be a ISBN number +# or the project homepage. +# +# epub_identifier = '' + +# A unique identification for the text. +# +# epub_uid = '' + +# A list of files that should not be packed into the epub file. +epub_exclude_files = ['search.html'] + + +# -- Extension configuration ------------------------------------------------- + +# -- Options for intersphinx extension --------------------------------------- + +# Example configuration for intersphinx: refer to the Python standard library. +intersphinx_mapping = {'https://docs.python.org/': None} + +# -- Options for todo extension ---------------------------------------------- + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = True diff --git a/docs/source/index.rst b/docs/source/index.rst new file mode 100644 index 000000000..6e8e9d7f3 --- /dev/null +++ b/docs/source/index.rst @@ -0,0 +1,57 @@ + +========================================================= +Appbuilder-SDK 文档主页 +========================================================= + + +Appbuilder-SDK .... + + +.. toctree:: + :maxdepth: 1 + :caption: 概览 + :name: _introduction + + rst/introduction + md/authentication.rst + md/components.rst + +.. toctree:: + :maxdepth: 1 + :caption: 组件说明 + :name: _components + + rst/components/asr.rst + rst/components/dialog_summary.rst + rst/components/dish_recognize.rst + rst/components/doc_parser.rst + rst/components/doc_splitter.rst + rst/components/embeddings.rst + rst/components/extract_table.rst + rst/components/general_ocr.rst + rst/components/is_complex_query.rst + rst/components/landmark_recognize.rst + rst/components/matching.rst + rst/components/mrc.rst + rst/components/nl2pandas.rst + rst/components/object_recognize.rst + rst/components/oral_query_generation.rst + rst/components/playground.rst + rst/components/qa_pair_mining.rst + rst/components/query_decomposition.rst + rst/components/query_rewrite.rst + rst/components/retriever.rst + rst/components/similar_question.rst + rst/components/style_rewrite.rst + rst/components/style_writing.rst + rst/components/tag_extraction.rst + rst/components/text_to_image.rst + rst/components/translate.rst + rst/components/tts.rst + + + +======= + +Apache-2.0 + diff --git a/docs/source/md/authentication.md b/docs/source/md/authentication.md new file mode 100644 index 000000000..c229041b4 --- /dev/null +++ b/docs/source/md/authentication.md @@ -0,0 +1 @@ +# 认证鉴权 \ No newline at end of file diff --git a/docs/source/md/components.md b/docs/source/md/components.md new file mode 100644 index 000000000..55a564164 --- /dev/null +++ b/docs/source/md/components.md @@ -0,0 +1,60 @@ +# 组件总览 +Appbuilder-SDK 提供了一系列组件,用于快速构建AI原生应用, 包括 大模型组件、AI能力组件、基础云组件、软硬一体组件等。 + +## 组件详细说明 + +### 大模型组件 +| 组件名称 | 类型 | 描述 | 链接 | +|------------------|--------------|------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------| +| Query改写 | RAG | Query改写组件(QueryRewrite)用于处理多轮对话和查询改写,理解和优化用户与机器人的交互,进行指代消解及省略补全。 | [链接](https://console.bce.baidu.com/qianfan-charge/#/create/?apiId=1358) | +| 相似问生成 | 文本生成 | 相似问生成组件(SimilarQuestion)可以基于输入的问题,挖掘出与该问题相关的类似问题,广泛用于客服、问答等场景。 | | +| 自然语言转pandas | 文本生成 | 自然语言转pandas组件(Nl2pandas)通过理解对表格信息的提问,生成对应语义的可执行Python代码,主要使用Pandas库。 | | +| 标签抽取 | 文本生成 | 标签抽取组件(TagExtraction)是一款高效的标签抽取组件,基于生成式大模型,用于从文本中提取关键标签。 | | +| 会话小结 | 文本生成 | 会话小结组件(DialogSummary)基于生成式大模型对用户与坐席的对话生成总结,结果按{"诉求": "", "回应": "", "解决情况": ""}格式输出。 | | +| 口语化Query生成 | 文本生成 | 口语化Query生成组件(OralQueryGeneration)可以基于输入文本生成与文档内容相关的Query,适用于增强文档索引等场景。 | | +| 复杂Query分解 | RAG | 复杂Query分解组件(QueryDecomposition)可以将复杂问题拆解为简单问题,广泛应用于知识问答场景。 | | +| 复杂Query判定 | RAG | 复杂Query判定组件(IsComplexQuery)可以根据输入的提问进行分类,区分简单问题和复杂问题,适用于知识问答场景。 | | +| 风格转写 | 文本生成 | 风格转写组件(StyleRewrite)可以基于生成式大模型对文本的风格进行改写,支持多种文本风格。 | | +| 风格写作 | 文本生成 | 风格写作组件(StyleWriting)是一款基于生成式大模型进行文本创作的工具,支持多种风格,适用于编写文案、广告等多种场景。 | [链接](https://console.bce.baidu.com/ai_apaas/app/preview/generation/4e9b74f0-a78e-458b-b70d-3445050bf7ce/54e5dfb3-032a-46b6-92d8-99ca7a7a0bc4) | +| 问答对挖掘 | 文本生成 | 问答对挖掘(QAPairMining)可以基于输入文本内容,快速生成多个问题及对应答案,广泛用于在线客服、智能问答等领域。 | [链接](https://console.bce.baidu.com/ai_apaas/app/preview/generation/ce969ab9-2f5b-417e-b25f-9e44ee650ebb/0b9a3658-45ef-49bf-aec8-1b77ba331a79) | +| 阅读理解问答 | RAG | 阅读理解问答(MRC)组件是基于生成式大模型的阅读理解问答系统。支持拒答、澄清、重点强调、友好性提升、溯源等多种功能。 | | +| playground空应用 | 文本生成 | playground空应用(Playground)是一款灵活的组件,允许用户自定义prompt模板并执行。它适用于各种场景,特别是在需要自定义输入模板和使用预训练模型进行交互的情况下。 | | + + +### AI能力组件 +以下是上述文档内容,按照您的要求,格式化为 Markdown 表格,分为五列:组件名称、类型、描述、额度详情、链接: + +| 组件名称 | 类型 | 描述 | 额度详情 | 链接 | +|----------------------|--------------------|---------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------|-----------------------------------------------------------| +| 文本翻译-通用版 | Translation | 提供200+语种互译的在线文本翻译服务,支持术语定制功能,适用于移动端、PC网站、智能硬件等。 | 个人认证:总量500万字符,10qps
      企业认证:总量1000万字符,100qps | [详情](https://console.bce.baidu.com/ai/#/ai/machinetranslation/overview/index) | +| AI作画-高级版 | Text2Image | 根据用户输入的文本,自动创作不限定风格的图,为内容创作者提供灵感和高质量配图。 | 个人认证:总量20点,1并发
      企业认证:总量40点,1并发 | [详情](https://console.bce.baidu.com/ai/#/ai/intelligentwriting/overview/index) | +| 通用物体和场景识别-高级版 | ObjectRecognition | 识别超过10万类常见物体和场景,返回大类及细分类名称,适用于图像或视频内容分析、拍照识图等。 | 个人认证:总量10000次,2qps
      企业认证:总量30000次,2qps | [详情](https://console.bce.baidu.com/ai/#/ai/imagerecognition/overview/index) | +| 通用文字识别-高精度版 | GeneralOCR | 支持多场景、多语种、高精度的文字识别服务,对图片/文件全部文字内容进行检测识别。 | 个人认证:1000次/月,2qps
      企业认证:2000次/月,2qps | [详情](https://console.bce.baidu.com/ai/#/ai/ocr/overview/index) | +| 菜品识别 | DishRecognition | 识别超过9千种菜品,可准确识别图片中的菜品名称、卡路里,适用于多种客户识别菜品的业务场景。 | 个人认证:总量1000次,2qps
      企业认证:总量3000次,2qps | [详情](https://console.bce.baidu.com/ai/#/ai/imagerecognition/overview/index) | +| 地标识别 | LandmarkRecognition | 识别12万中外著名地标、热门景点,返回地标名称。 | 个人认证:总量1000次,2qps
      企业认证:总量3000次,2qps | [详情](https://console.bce.baidu.com/ai/#/ai/imagerecognition/overview/index) | +| 短语音识别-极速版 | ASR | 将音频流实时识别为文字,并返回每句话的开始和结束时间。适用于手机语音输入、语音搜索、人机对话等。 | 个人认证/企业认证:5并发,5w次 | [详情](https://console.bce.baidu.com/ai/#/ai/speech/overview/index) | +| 短文本在线合成-基础音库 | TTS | 提供高度拟人、流畅自然的语音合成服务,将文本朗读出来,基础音库性价比更高。 | 个人认证:总量50000次,10并发
      企业认证:总量100000000次,100并发 | [详情](https://console.bce.baidu.com/ai#/ai/speech/overview/index) | +| 短文本在线合成-精品音库 | TTS | 提供高度拟人、流畅自然的语音合成服务,将文本朗读出来,精品音库听感更逼真。 | 个人认证:总量2000次,3并发
      企业认证:总量5000次,5并发 | [详情](https://console.bce.baidu.com/ai/#/ai/speech/overview/index) | +| 文本转语音 | TTS | 将输入的文本转化为音频文件,主要用于语音合成,适用于智能语音交互,自动语音播报等场景。 | 每个账号限额最高5 QPS | - | +| 文档解析 | DocParser | 用于文档内容解析,支持PDF、JPG、DOC、TXT、XLS、PPT等17种文档格式,可解析出文档版式、位置坐标、表格结构等。 | 暂时免费,每个账号限额最高5 QPS | - | +| 文档切分 | DocSplitter | 用于对文档进行段落切分,支持将文档划分为多个段落,便于后续处理和分析。 | 暂时免费,每个账号限额最高5 QPS | - | +| 语义匹配 | Matching | 用于计算query与文本列表之间的相似度关系,并根据其进行排序。适用于文本检索、信息推荐、知识挖掘等场景。 | - | [购买](https://console.bce.baidu.com/qianfan-charge/#/create/?apiId=1231) | +| 语义向量计算 | Embedding | 支持将文本转化为用数值表示的向量形式,用于文本检索、信息推荐、知识挖掘等场景。 | - | [购买](https://console.bce.baidu.com/qianfan-charge/#/create/?apiId=1231) | +| 表格抽取 | ExtractTableFromDoc | 用于文档表格处理,从文档中抽取表格。支持对文档表格大小进行限制,限制后自动进行拆分、跨页合并等处理;支持合并表格上文,提取的表格为Markdown格式。 | 暂时免费,每个账号限额最高5 QPS | - | + + +### 基础云组件 +以下是上述文档内容,格式化为 Markdown 表格: + +| 组件名称 | 类型 | 描述 | 链接 | 文档 | +|-----------|---------------|------------------------------------------------------------------------------------------------------|-----------------------------------------------------------|------------------------------------------------------------| +| 百度Elasticsearch | BES | 提供高性能、灵活扩展的向量与标量混合存储检索服务,支持多种索引类型和相似度计算方法,仅支持V7.x版本。 | [购买](https://console.bce.baidu.com/bes/#/bes/V2/create) | [使用文档](https://cloud.baidu.com/doc/BES/index.html?from=productToDoc) | +| 向量检索 | BESRetriever | 基于Baidu ElasticSearch的内容检索组件,支持根据文本的向量的相似度进行内容检索。 | - | - | + + +### 软硬一体组件等 +以下是您提供的文档内容,格式化为 Markdown 表格: + +| 组件名称 | 类型 | 描述 | 链接 | +|--------------|---------|------------------------------------------------------------|-------------------------------------------------------------| +| 多模态AI模组LUCA系列 | - | 一款具备视觉、语音、文本、音频、视频采集识别和理解能力的多模态AI模组 | [详情](https://aim.baidu.com/product/42f4b425-61b3-440e-8648-eb21c90e4e02) | \ No newline at end of file diff --git a/docs/source/rst/introduction.rst b/docs/source/rst/introduction.rst new file mode 100755 index 000000000..d5c43e413 --- /dev/null +++ b/docs/source/rst/introduction.rst @@ -0,0 +1,10 @@ +整体介绍与内容概览 +================== + +appbuilder-sdk + +参考文献 +--------- + +`[1] https://github.com/baidubce/app-builder` + diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 000000000..5f3aa4d41 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,8 @@ +requests +proto-plus==1.22.3 +pydantic==1.10.12 +numpy~=1.24.2 +SQLAlchemy~=1.4.50 +flask~=2.3.2 +flask-restful==0.3.9 +chainlit~=0.7.700 diff --git a/setup.py b/setup.py new file mode 100755 index 000000000..695641c40 --- /dev/null +++ b/setup.py @@ -0,0 +1,37 @@ +# Copyright (c) 2023 Baidu, Inc. 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. + + +""" +Setup script. + +Authors: dongdaxiang(dongdaxiang@baidu.com) +Date: 2023/12/01 11:19:24 +""" + +from setuptools import setup, find_packages + +with open('requirements.txt') as f: + requirements = f.read().splitlines() + +setup( + name='appbuilder-sdk', + version='0.1.0', + author='dongdaxiang', + author_email='dongdaxiang@baidu.com', + packages=find_packages(), + install_requires=requirements, + python_requires='>=3.8', +) +

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