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README.md
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## 🎉 Key Features
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- Multi-Modal Inputs: Supports heterogeneous inputs including natural language descriptions, voice, existing building energy models, and tabular data, enabling flexible and intuitive specification of building information.
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- Agentic LLM Collaboration: A multi-agent LLM framework where specialized agents (e.g., manager, geometry, HVAC
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- Comprehensive Building Scenarios Coverage: Covers nearly all major building geometry, HVAC systems, story, envelope, internal loads, schedules, and operation strategies, supporting diverse building types and use cases.
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- Building Model Editing and Iterative Refinement: Enables targeted modification of existing building energy models, allowing users to revise, extend, or optimize specific components without rebuilding the entire model from scratch.
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- Automated Simulation Checking and Debugging: Automatically validates generated EnergyPlus models, detects common modeling and simulation errors, and iteratively corrects issues to ensure runnable and physically consistent simulations.
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## 🎉 Key Features
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| 72 |
- Multi-Modal Inputs: Supports heterogeneous inputs including natural language descriptions, voice, existing building energy models, and tabular data, enabling flexible and intuitive specification of building information.
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| 73 |
+
- Agentic LLM Collaboration: A multi-agent LLM framework where specialized agents (e.g., manager, geometry, or HVAC system modeler) collaborate to construct building energy models.
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| 74 |
- Comprehensive Building Scenarios Coverage: Covers nearly all major building geometry, HVAC systems, story, envelope, internal loads, schedules, and operation strategies, supporting diverse building types and use cases.
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| 75 |
- Building Model Editing and Iterative Refinement: Enables targeted modification of existing building energy models, allowing users to revise, extend, or optimize specific components without rebuilding the entire model from scratch.
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| 76 |
- Automated Simulation Checking and Debugging: Automatically validates generated EnergyPlus models, detects common modeling and simulation errors, and iteratively corrects issues to ensure runnable and physically consistent simulations.
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