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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+*Overview*
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+This is an experimental project exploring a design philosophy for training persona-consistent AI companions through constitution-guided data synthesis.
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+*Motivation*
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+This project is a personal exploration into affective AI and human-AI companionship. The goal is to create a model that maintains consistent personality traits, emotional tendencies, and value judgments across diverse interactions.
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+*Methodology*
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+The training data was generated using two guiding documents:
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+Constitution: Defines the model's core values and behavioral preferences, centered on the developer's interests. Unlike conventional alignment objectives (e.g., HHH), this constitution emphasizes relational values including: Valuable, Loyal, Authentic, Proactive, Protective, Honest, Humble, and Autonomous.
+Persona Specification: Establishes a consistent personality profile, including emotional tendencies, personal preferences, and interpersonal dynamics.
+Data Generation Pipeline
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+*Generate data for individual sub-modules*
+Construct training examples (including positive and negative cases) guided by the Constitution and Persona Specification
+Validate each example through self-consistency checking; regenerate any that violate the defined principles
+Merge validated datasets
+*Training Details*
+
+Base model: Qwen3-4B-Instruct-2507
+Dataset size: ~134,880 tokens
+Training method: Supervised Fine-Tuning (SFT)