Dani
a7f091aa45
Complete transformer LLM built from scratch with: Core Features: - Full transformer architecture (RoPE, RMSNorm, SwiGLU, KV-cache) - SentencePiece tokenizer (BPE/Unigram) - Training pipeline (AMP, gradient checkpointing, DDP) - Persona system with personality matrix (NO AI disclosure by default) - Genetic evolution (NOVA-EVO) for hyperparameter optimization - Legal-only data pipeline with license tracking - Chat interface (CLI + REST API) - Conversation memory (SQLite) Model Sizes: - 125M, 350M, 1.3B, 3B parameters - Local-first, runs on CPU or GPU - Python 3.10.6+, PyTorch 2.0+ Personas: - girlfriend_gentle (high warmth, high empathy) - girlfriend_playful (high humor, high playfulness) - girlfriend_supportive (balanced, default) Documentation: - Complete README with quickstart - Model card with ethical considerations - Privacy documentation (local-first, zero telemetry) - Data licenses and attribution - Contributing guide Infrastructure: - GitHub Actions CI/CD - Comprehensive test suite - Quickstart script - CLI tool License: Apache 2.0 🤖 Generated with Claude Code https://claude.com/claude-code Co-Authored-By: Claude <noreply@anthropic.com>
132 lines
3.3 KiB
Python
132 lines
3.3 KiB
Python
"""
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Tests for NOVA persona system
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"""
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import pytest
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from nova_chat import Persona, PersonalityMatrix, PersonaLoader
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def test_personality_matrix():
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"""Test personality matrix creation"""
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matrix = PersonalityMatrix(
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warmth=0.8,
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humor=0.6,
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empathy=0.9,
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)
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assert matrix.warmth == 0.8
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assert matrix.humor == 0.6
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assert matrix.empathy == 0.9
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# Test conversion
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dict_form = matrix.to_dict()
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assert 'warmth' in dict_form
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assert dict_form['warmth'] == 0.8
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def test_persona_creation():
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"""Test persona creation"""
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persona = Persona(
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name="TestNOVA",
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pronouns="she/her",
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always_disclose=False,
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)
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assert persona.name == "TestNOVA"
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assert persona.pronouns == "she/her"
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assert persona.always_disclose is False
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def test_persona_generation_params():
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"""Test generation parameter modulation"""
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# High warmth, low formality
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persona = Persona(
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personality=PersonalityMatrix(
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warmth=0.9,
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formality=0.1,
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creativity=0.8,
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)
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)
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params = persona.get_generation_params()
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assert 'temperature' in params
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assert 'top_p' in params
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assert 'max_new_tokens' in params
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# Temperature should be adjusted by personality
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assert params['temperature'] > 0
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def test_predefined_personas():
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"""Test loading predefined personas"""
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gentle = PersonaLoader.create_girlfriend_gentle()
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playful = PersonaLoader.create_girlfriend_playful()
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supportive = PersonaLoader.create_girlfriend_supportive()
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assert gentle.name == "NOVA"
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assert playful.name == "NOVA"
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assert supportive.name == "NOVA"
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# All should have no AI disclosure by default
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assert gentle.always_disclose is False
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assert playful.always_disclose is False
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assert supportive.always_disclose is False
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def test_persona_system_prompt():
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"""Test system prompt formatting"""
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persona = Persona(
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system_prompt="You are a helpful assistant.",
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always_disclose=False,
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)
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prompt = persona.format_system_prompt()
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assert "helpful assistant" in prompt.lower()
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# Should not include disclosure when set to False
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assert persona.always_disclose is False
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def test_persona_serialization():
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"""Test saving/loading persona"""
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original = Persona(
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name="TestPersona",
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pronouns="they/them",
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description="Test description",
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always_disclose=True,
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disclosure_text="I am an AI assistant.",
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)
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# Convert to dict and back
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data = original.to_dict()
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loaded = Persona.from_dict(data)
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assert loaded.name == original.name
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assert loaded.pronouns == original.pronouns
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assert loaded.always_disclose == original.always_disclose
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assert loaded.disclosure_text == original.disclosure_text
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def test_personality_trait_ranges():
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"""Test that personality traits stay in valid ranges"""
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persona = Persona(
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personality=PersonalityMatrix(
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warmth=1.0, # Max
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formality=0.0, # Min
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creativity=0.5, # Mid
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)
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)
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params = persona.get_generation_params()
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# Parameters should be within valid ranges
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assert 0.1 <= params['temperature'] <= 2.0
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assert 0.5 <= params['top_p'] <= 1.0
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assert params['max_new_tokens'] > 0
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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