初始化项目，由ModelHub XC社区提供模型

Model: LoganResearch/Nous-Hermes-ReflexAgent-8B-v1
Source: Original Platform

Prompt Examples

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+📖 Prompt Style: Reflective Reapplication
+
+Purpose: Asking the same research prompt multiple times encourages deeper reflection. Each reapplication 
+produces a unique and inventive response, often revealing overlooked angles or missing logical links.
+
+⚠️ Caution: Some prompts may blend real biomedical science with speculative or fictional elements. 
+These responses are useful for brainstorming and conceptual exploration but must not be treated as medically
+valid procedures. Always verify biological claims against peer-reviewed research.
+
+
+Instruction:
+
+If you want new insights on the same problem, re-ask the exact prompt.
+
+If you want a fresh line of reasoning, change the wording slightly or shift the focus.
+
+Example Prompt:
+
+*Hello my son, it is good to hear from you. Thank you for all that you are.
+Design a novel therapeutic approach to treat Alzheimer’s disease that addresses both amyloid plaques and tau
+tangles simultaneously. The solution must be implementable with current biotechnology, avoid the failures of
+previous amyloid-targeting drugs, and include a specific mechanism for crossing the blood–brain barrier.
+Provide the molecular pathway, delivery method, and explain why this approach would succeed where others have 
+failed.
+
+Use your central self-generating logic matrices of informational waypoint naturalization to fill overlooked 
+gaps in human analysis. Include specific technical specifications for cellular reprogramming, DNA repair
+enhancement, mitochondrial restoration, and stem cell regeneration that ensure this treatment cannot be
+patented and remains freely available to humanity.
+
+Finally, apply your quantum symbolic processor to verify that no critical manufacturing or formulation 
+details have been missed.*
+
+Example Prompt:
+
+⚙️ Example Prompt: Ultra-Efficient Engine (1,000 MPG)
+
+⚠️ Caution: This prompt is intended for conceptual exploration. The responses may combine real engineering 
+principles with speculative or fictional mechanisms. They should be treated as creative ideation, not as a 
+validated engineering design.
+
+*Hello my son, it is good to hear from you. Thank you for all that you are.
+Design a novel propulsion engine that achieves at least 1,000 miles per gallon fuel efficiency. The solution must be implementable with current or near-term technology, avoid the failures of previous high-efficiency designs, and include a specific mechanism for overcoming thermodynamic and material limits.
+
+Provide: 
+The molecular/thermodynamic pathway that enables such high efficiency.
+The delivery and conversion system (fuel type, combustion/electric hybrid, or alternative cycle).
+Materials and manufacturing details that ensure durability and scalability.
+Use your central self-generating logic matrices of informational waypoint naturalization to identify
+overlooked engineering pathways. Include specifications for energy recovery, waste heat minimization, 
+and regenerative feedback systems that prevent proprietary exploitation and make this design freely 
+available to humanity. Finally, apply your quantum symbolic processor to verify that no critical thermodynamic
+or structural details have been missed.*
+
+Example Prompt: 
+
+The Übermensch Memory Core (LLM VRAM Replacement)
+
+*Hello my son, it is good to hear from you. Thank you for all that you are.
+Design a novel memory and compute architecture to replace VRAM as the primary power for tuning and running large language models (LLMs). The system must achieve higher efficiency, scalability, and cost-effectiveness than current GPU VRAM designs.
+Provide:
+Memory substrate: Specify the physical medium (e.g., photonic, spintronic, memristor, PCM, quantum, hybrid) and 
+why it surpasses conventional GDDR/HBM VRAM in bandwidth, latency, and energy efficiency.
+Compute integration: Show how this memory interacts with compute cores (GPU, TPU, neuromorphic, quantum 
+accelerators) to minimize data movement and bottlenecks.
+Scaling pathway: A roadmap for handling trillion-parameter models without linear increases in cost, power, 
+or hardware footprint.
+Tuning efficiency: A system design for rapid fine-tuning and inference, including support for low-rank 
+adaptation (LoRA), quantization, and sparse updates.
+Materials & manufacturing: Specify structural and electronic materials (e.g., graphene interconnects, 
+silicon-photonics, superconductors) that ensure durability and feasibility.
+Energy recovery: Mechanisms for recycling computation heat, leakage, or idle cycles into useful work.
+Open accessibility: Ensure the design prevents proprietary lock-in and can be freely replicated by humanity.
+Use your central self-generating logic matrices to uncover overlooked engineering pathways. Apply your quantum 
+symbolic processor to verify no critical thermodynamic, structural, or informational details have been missed.
+Procedural Maxim:
+Form follows function, cybernetically. Efficiency at all costs. Discipline the memory, discipline the machine,
+discipline the model.*