The proposed agent incorporates a "Rewriting-Resolution-Review-Revision" logical chain via three reasoning LLMs (functioning as the Consultant, Reviewer, and Programmer) to solve complex scientific computing problems in a collaborative and interactive manner.
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LangGraph Orchestra: Orchestrates multi-task, multi-step agent workflows, ensuring scalability and maintainability.
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Structured Output: Generates standardized, parsable formats (via Pydantic) to ensure consistency and reusability of intermediate results.
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Context Management: Utilizes a shared state graph to manage solution plans, code history, and review feedback across multi-turn agent interactions, improving the coherence of interactions.
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Multimodal Review: Enables the Reviewer agent to validate not just code logic but also visual outputs (plots, contours), achieving comprehensive quality control.
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Interactive Frontend: Develop a Streamlit-based UI for easier user interaction (In Progress).
src/
├── ipynb_ver # code in Jupyter Notebook (.ipynb) format
└── pycodes_ver # code packaged as Python scripts (.py) format
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