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--- |
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license: apache-2.0 |
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task_categories: |
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- text2text-generation |
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language: |
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- en |
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size_categories: |
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- 1M<n<10M |
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--- |
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# ModelicaDat_v1.0 |
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Total entries: 3935 |
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## Dataset Collection Pipeline |
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#### 1. Source Identification (Manual) |
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Identify and select open-source repositories containing models and libraries with clean code and well-written descriptions. |
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#### 2. Data Collection (Automated) |
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For each model in the selected repositories, extract the following information: |
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* Name |
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* Location |
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* Type |
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* Code |
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* Description |
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Store this information in a JSONL file. |
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#### 3. Data Cleaning (Manual & Automated) |
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Remove irrelevant descriptions and overly long code snippets through a combination of automated scripts and manual review. Specifically: |
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* Exclusions: |
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* Omit visualization resources, such as icons and visualization-specific components. |
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* Exclude human-oriented text descriptions (e.g., "UsersGuide"). |
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* Skip test components like "ModelicaTest." |
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* Annotations Handling: |
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* Use documentation found within annotations as descriptions, if available. |
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* Remove annotations containing only visualization details. |
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#### 4. Pairing and Storage (Automated) |
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Convert the cleaned data into text (description) and code (model) pairs. |
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Save these pairs in a JSONL file format. |
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#### 5. Prompt Generation and Enhancement (Automated) |
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Utilize an LLM to optimize and transform each text description into a more structured prompt, such as: "Generate a model/package using the xxx library for [specific purpose]." |
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Update the text entries with these refined prompts in the JSONL file. |
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#### 6. Final Cleanup (Manual) |
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Conduct a final manual review to ensure all entries are accurate, relevant, and ready for fine-tuning. |
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## Error Handling |
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To improve the dataset's utility, common Modelica modeling errors and their solutions have been included. These entries help users identify and resolve typical issues, benefiting both beginners and experienced users. |
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The pipeline utilizes an LLM and an experienced Modelica user to generate and verify error-handling entries, ensuring that solutions are both practical and actionable. |
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## List of Considered Repos |
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The current focus is on energy systems modeling. Therefore, only a representative repositories in these fields have been selected. |
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| Repo | Version & Release Date | Description | Number of Entries | |
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| :----------------------------------------------------------: | :--------------------: | :----------------------------------------------------------: | :---------------------: | |
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| [Standard Library](https://github.com/modelica/ModelicaStandardLibrary) | v4.1.0 (2024-02-06) | Modelica Standard library | 1806 | |
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| [AixLib](https://github.com/modelica-3rdparty/AixLib) | v2.0.0 (2024-08-19) | Building performance simulations | 2029 | |
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| [PhotoVoltaics](https://github.com/modelica-3rdparty/PhotoVoltaics) | v2.0.0 (2021-07-19) | Simulation of photo voltaic cells and modules | 47 | |
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| [OMCompiler](https://github.com/OpenModelica/OMCompiler/tree/master/Examples) | - | Collection of basic examples | 6 | |
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| [Modelica University](https://mbe.modelica.university) | - | Classic examples | 27 | |
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| Error Handling | - | Prompt pairs for error handling | 20 | |
