multimodal generative ai for bpm下載 - multimodal generative ai for bpm原始碼下載

multimodal generative ai for bpm

Ai源碼

1.0.0

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多模態人工智慧

關於這個項目

該儲存庫包含論文「 Generative AI for Business Process Management - Suitability of Modalities的原始程式碼。目標是評估使用生成式人工智慧從多模式文件建立流程模型的可行性。此儲存庫使用 SAP SAM 儲存庫中的一些程式碼和資料。

執照

此儲存庫中的範例程式碼的許可如下。請注意，不同的許可證適用於資料集本身！

 Copyright (c) 2024 by SAP.

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.

以下許可證適用於資料資料夾中的資料集。

 Copyright (c) 2024 by SAP.

SAP grants to Recipient a non-exclusive copyright license to the Model Collection to use the Model Collection for Non-Commercial Research purposes of evaluating Recipient’s algorithms or other academic research artefacts against the Model Collection. Any rights not explicitly granted herein are reserved to SAP. For the avoidance of doubt, no rights to make derivative works of the Model Collection is granted and the license granted hereunder is for Non-Commercial Research purposes only.

"Model Collection" shall mean all files in the archive (which are JSON, XML, or other representation of business process models or other models).

"Recipient" means any natural person receiving the Model Collection.

"Non-Commercial Research" means research solely for the advancement of knowledge whether by a university or other learning institution and does not include any commercial or other sales objectives.

包括第三方組件及其許可/版權資訊在內的詳細資訊可透過 REUSE 工具取得。

要求和設置

我們提供了兩個 condaenvironment.yml 文件，可用於建立新環境並安裝所需的依賴項：

environment.yml ：包含抽象依賴項（pandas、numpy，...）。
environment-lock.yml ：包含所有依賴項和傳遞依賴項的版本，以確保可重現的結果。

您可以使用以下 conda 命令來建立環境：

conda env create -f environment.yml

或者

conda env create -f environment-lock.yml

入門

我們提供多個 Jupyter Notebook。

data_set_preparation Jupyter Notebook 提供如何建立資料集的演練。

Explore_the_dataset Jupyter Notebook 提供了有關所建立資料集特徵的見解。

bpmn_ Generation Jupyter Notebook 使用 GPT-4V 以及零次、一次和幾次提示從多模式文件建立流程模型。

評估Jupyter Notebook引入了一個評估框架來計算生成的過程模型和地面實況模型的相似度分數。此外，它應用了該框架並呈現了結果。

專案組織

 ├── data
│   ├── examples          <- Some example models for illustrating main ideas.
|   └── sapsam
│       ├── cleaned       <- The created dataset.
|       ├── enriched      <- Original SAP-SAM data set enriched by some meta data
|       ├── evaluations   <- Evaluation results
|       ├── generated     <- Generated process models
|       ├── raw           <- Original SAP-SAM data set
|       └── tmp           <- Temporary data
├── notebooks             <- Jupyter notebooks.
├── src               
|   ├── multimodalgenai   <- Source code for use in this project.
│   └── sapsam            <- Adapted clone of the [SAP SAM repo](https://github.com/signavio/sap-sam)
├── LICENSE               <- License that applies to the example code in this repository.
├── README.md             <- The top-level README for developers using this project.
├── Thesis_Gen-AI-for-BPM-Modalities_Marvin-Voelter_v04_2024-03-21_final_blurred.pdf <- Thesis with more detailed explanations and thoughts
├── environment-lock.yml  <- Contains versions for all dependencies and the transitive dependencies to ensure reproducible results.
├── environment.yml       <- Contains the abstract dependencies (pandas, numpy, ...).
└── setup.py              <- Makes project pip installable (pip install -e .) such that src can be imported.