Initial commit: NOVA - Neuro-Optimizing Versatile Agent
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>
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scripts/cli.py
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scripts/cli.py
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"""
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NOVA Command Line Interface
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"""
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import argparse
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import sys
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from pathlib import Path
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# Add parent directory to path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from nova_core import NovaTransformer, ModelConfig, MODEL_125M, MODEL_350M, MODEL_1_3B
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from nova_tokenizer import NovaTokenizer, train_tokenizer
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from nova_train import NovaTrainer, TrainingConfig
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from nova_chat import ChatAgent, PersonaLoader
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from nova_data import DataPipeline
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from nova_evo import EvolutionEngine, FitnessEvaluator, EvolutionConfig
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def cmd_init(args):
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"""Initialize a new NOVA project"""
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print("Initializing NOVA project...")
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# Create toy dataset
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pipeline = DataPipeline()
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toy_path = pipeline.create_toy_dataset()
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print(f"\n✓ NOVA initialized!")
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print(f" Toy dataset: {toy_path}")
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print(f"\nNext steps:")
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print(f" 1. Train tokenizer: nova tokenizer train --input {toy_path}")
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print(f" 2. Train model: nova train --config configs/model/125M.yaml")
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print(f" 3. Chat: nova chat cli")
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def cmd_tokenizer_train(args):
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"""Train a tokenizer"""
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print(f"Training tokenizer on {args.input}...")
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model_path = train_tokenizer(
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input_files=[args.input],
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model_prefix=args.output,
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vocab_size=args.vocab_size,
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model_type=args.model_type,
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)
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print(f"\n✓ Tokenizer saved: {model_path}")
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def cmd_train(args):
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"""Train a model"""
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print("Training NOVA model...")
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# Load model config
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if args.size == "125m":
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model_config = MODEL_125M
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elif args.size == "350m":
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model_config = MODEL_350M
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elif args.size == "1.3b":
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model_config = MODEL_1_3B
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else:
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raise ValueError(f"Unknown size: {args.size}")
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# Create model
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model = NovaTransformer(model_config)
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print(f"Model: {model.get_num_params() / 1e6:.1f}M parameters")
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# TODO: Load dataset and create dataloader
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# For now, this is a placeholder
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print("\n⚠️ Training not fully implemented - requires dataset")
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print("See nova_train/trainer.py for implementation")
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def cmd_chat_cli(args):
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"""Start CLI chat"""
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print("NOVA Chat Interface")
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print("=" * 60)
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# Load model and tokenizer
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# TODO: Implement model/tokenizer loading from checkpoint
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print("\n⚠️ Chat requires trained model and tokenizer")
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print("Please train a model first with: nova train")
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def cmd_chat_serve(args):
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"""Start REST API server"""
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print(f"Starting NOVA chat API server on {args.host}:{args.port}...")
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# TODO: Implement FastAPI server
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print("\n⚠️ REST API not fully implemented")
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print("See nova_chat/ for implementation")
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def cmd_evo_run(args):
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"""Run evolution"""
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print("Starting NOVA-EVO...")
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# TODO: Implement evolution with dataset
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print("\n⚠️ Evolution requires dataset and compute budget")
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print("See nova_evo/ for implementation")
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def cmd_data_build(args):
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"""Build dataset"""
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pipeline = DataPipeline()
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if args.source:
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pipeline.download_source(args.source, dry_run=args.dry_run)
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else:
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print("Available sources:")
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from nova_data import LegalDatasetRegistry
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for source in LegalDatasetRegistry.list_sources():
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print(f"\n {source.name}")
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print(f" License: {source.license.value}")
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print(f" Size: {source.estimated_size_gb} GB")
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print(f" {source.description}")
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def main():
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"""Main CLI entry point"""
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parser = argparse.ArgumentParser(
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description="NOVA - Neuro-Optimizing Versatile Agent",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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)
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subparsers = parser.add_subparsers(dest='command', help='Commands')
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# Init
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parser_init = subparsers.add_parser('init', help='Initialize NOVA project')
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parser_init.set_defaults(func=cmd_init)
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# Tokenizer
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parser_tok = subparsers.add_parser('tokenizer', help='Tokenizer commands')
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tok_sub = parser_tok.add_subparsers(dest='tokenizer_command')
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tok_train = tok_sub.add_parser('train', help='Train tokenizer')
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tok_train.add_argument('--input', required=True, help='Input text file')
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tok_train.add_argument('--output', default='tokenizer', help='Output prefix')
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tok_train.add_argument('--vocab-size', type=int, default=32000)
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tok_train.add_argument('--model-type', default='bpe', choices=['bpe', 'unigram'])
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tok_train.set_defaults(func=cmd_tokenizer_train)
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# Train
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parser_train = subparsers.add_parser('train', help='Train model')
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parser_train.add_argument('--size', default='125m', choices=['125m', '350m', '1.3b'])
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parser_train.add_argument('--config', help='Training config file')
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parser_train.set_defaults(func=cmd_train)
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# Chat
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parser_chat = subparsers.add_parser('chat', help='Chat interface')
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chat_sub = parser_chat.add_subparsers(dest='chat_command')
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chat_cli = chat_sub.add_parser('cli', help='CLI chat')
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chat_cli.add_argument('--persona', help='Persona file')
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chat_cli.set_defaults(func=cmd_chat_cli)
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chat_serve = chat_sub.add_parser('serve', help='REST API server')
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chat_serve.add_argument('--host', default='0.0.0.0')
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chat_serve.add_argument('--port', type=int, default=8000)
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chat_serve.set_defaults(func=cmd_chat_serve)
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# Evolution
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parser_evo = subparsers.add_parser('evo', help='Evolution commands')
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evo_sub = parser_evo.add_subparsers(dest='evo_command')
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evo_run = evo_sub.add_parser('run', help='Run evolution')
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evo_run.add_argument('--budget', default='small', choices=['small', 'medium', 'large'])
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evo_run.set_defaults(func=cmd_evo_run)
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# Data
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parser_data = subparsers.add_parser('data', help='Data commands')
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data_sub = parser_data.add_subparsers(dest='data_command')
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data_build = data_sub.add_parser('build', help='Build dataset')
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data_build.add_argument('--source', help='Source name')
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data_build.add_argument('--dry-run', action='store_true')
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data_build.set_defaults(func=cmd_data_build)
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# Parse and execute
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args = parser.parse_args()
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if hasattr(args, 'func'):
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args.func(args)
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else:
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parser.print_help()
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if __name__ == '__main__':
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main()
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87
scripts/quickstart.sh
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scripts/quickstart.sh
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#!/bin/bash
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# NOVA Quickstart Script
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# Sets up NOVA for first-time use
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set -e
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echo "======================================"
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echo "NOVA Quickstart"
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echo "======================================"
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echo ""
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# Check Python version
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echo "Checking Python version..."
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python_version=$(python --version 2>&1 | grep -oP '(?<=Python )\d+\.\d+')
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required_version="3.10"
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if [ "$(printf '%s\n' "$required_version" "$python_version" | sort -V | head -n1)" != "$required_version" ]; then
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echo "❌ Python 3.10+ required. Found: $python_version"
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exit 1
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fi
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echo "✓ Python $python_version"
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echo ""
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# Create virtual environment
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if [ ! -d "venv" ]; then
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echo "Creating virtual environment..."
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python -m venv venv
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echo "✓ Virtual environment created"
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else
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echo "✓ Virtual environment exists"
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fi
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echo ""
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# Activate virtual environment
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echo "Activating virtual environment..."
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if [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then
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source venv/Scripts/activate
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else
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source venv/bin/activate
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fi
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echo "✓ Virtual environment activated"
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echo ""
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# Install dependencies
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echo "Installing dependencies..."
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pip install --upgrade pip > /dev/null
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pip install -r requirements.txt
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echo "✓ Dependencies installed"
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echo ""
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# Install NOVA in development mode
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echo "Installing NOVA..."
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pip install -e .
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echo "✓ NOVA installed"
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echo ""
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# Initialize project
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echo "Initializing NOVA project..."
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python scripts/cli.py init
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echo ""
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echo "======================================"
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echo "✓ NOVA Setup Complete!"
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echo "======================================"
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echo ""
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echo "Next steps:"
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echo ""
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echo "1. Train tokenizer:"
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echo " python scripts/cli.py tokenizer train --input data/toy_dataset/toy.txt"
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echo ""
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echo "2. (Optional) Download legal datasets:"
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echo " python scripts/cli.py data build --source wikipedia-en"
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echo ""
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echo "3. Train model:"
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echo " python scripts/cli.py train --size 125m"
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echo ""
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echo "4. Chat:"
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echo " python scripts/cli.py chat cli"
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echo ""
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echo "For more info: cat README.md"
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echo ""
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