File size: 2,168 Bytes
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Script chat với Nexus Agent
=============================
Chạy: python scripts/chat.py
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import torch
from nexus.config import NexusConfig
from nexus.model.nexus_coder import NexusCoderForCausalLM
from nexus.tokenizer.tokenizer import NexusTokenizer
from nexus.inference.generator import NexusGenerator
from nexus.agent.agent import NexusAgent
from nexus.training.dataset import AUTHOR_TRAINING_DATA
def get_tiny_config() -> NexusConfig:
"""Tiny config cho demo chat."""
return NexusConfig(
vocab_size=2000,
hidden_size=256,
num_hidden_layers=4,
num_attention_heads=8,
num_kv_heads=2,
head_dim=32,
intermediate_size=512,
num_experts=4,
num_active_experts=2,
max_position_embeddings=512,
)
def main():
print("=" * 60)
print(" NEXUS CODER v0.1 - Chat Demo")
print(" Tác giả: Hieu Louis")
print(" Năm: 2026")
print("=" * 60)
# Init config (dùng tiny cho demo, vì full 10B cần GPU)
config = get_tiny_config()
print(f"\n📝 Cấu hình demo: hidden={config.hidden_size}, layers={config.num_hidden_layers}")
# Tokenizer
print("\n🔨 Đang huấn luyện tokenizer...")
tokenizer = NexusTokenizer(vocab_size=config.vocab_size)
corpus = [f"{d['system']} {d['user']} {d['assistant']}" for d in AUTHOR_TRAINING_DATA]
tokenizer.train(corpus)
print(f" ✓ {tokenizer.vocab_size} tokens")
# Model
print("\n🧠 Đang khởi tạo model...")
model = NexusCoderForCausalLM(config)
print(" ✓ Model ready (random weights - đây chỉ là demo kiến trúc)")
# Generator
generator = NexusGenerator(
model=model,
tokenizer=tokenizer,
config=config,
)
# Agent
agent = NexusAgent(
generator=generator,
config=config,
name="Nexus",
personality="humorous",
language="bilingual",
)
# Print info
agent._print_info()
# Start chat
agent.chat()
if __name__ == "__main__":
main()
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