Epyc Orchestrator
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Catalog Information
The epyc-orchestrator project is designed to manage and orchestrate multiple machine learning models locally for efficient inference.
Description
This project enables hierarchical multi-model orchestration for local large language model (LLM) inference. It allows users to efficiently manage and combine the capabilities of various LLMs, making it a valuable tool for applications that require complex reasoning and decision-making. The epyc-orchestrator is built using Python and leverages popular libraries such as FastAPI, Gradio, NumPy, Pandas, Pydantic, Rich, Scikit-Learn, and Uvicorn.
الوصف
هذا المشروع يسمح بترتيب متعدد النماذج على مستوى المحلية للاستفادة من الاستدلال الكبير. يتيح للمستخدمين إدارة وتحليل قدرات مختلفة من نماذج الاستدلال الكبيرة، مما يجعلها أداة قيمة للتطبيقات التي تتطلب التفكير والقرار المعمقي. تم بناء المشروع باستخدام لغة بايثون و يستفيد من مكتبات شعبية مثل FastAPI, Gradio, NumPy, Pandas, Pydantic, Rich, Scikit-Learn, و Uvicorn.
Novelty
7/10Tags
Technologies
Claude Models
Quality Score
Strengths
- Good test coverage (56% test-to-source ratio)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Properly licensed project
Weaknesses
- No CI/CD configuration \u2014 manual testing and deployment
- 1 files with critical complexity need refactoring
- 9992 duplicate lines detected \u2014 consider DRY refactoring
- 49 'god files' with >500 LOC need decomposition
Recommendations
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Address 29 TODO/FIXME items \u2014 consider tracking them as issues
Security & Health
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Frameworks
Concepts (2)
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| Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | Hierarchical multi-model orchestration for local LLM inference. Routes tasks across multiple model tiers with automatic escalation, speculative decoding, and episodic memory. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Web Backend | web-backend | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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