feat: 更新 README，添加生成长度控制和测试指令；修改 main_chat.py，优化模型加载和生成逻辑；新增单元测试文件 test_smoke.py

tests/test_smoke.py

@@ -0,0 +1,100 @@
+import unittest
+
+import torch
+
+from jspaceai import (
+    CharTokenizer,
+    JSpaceConfig,
+    JSpaceLanguageModel,
+    JSpaceModel,
+    LanguageConfig,
+    MultimodalConfig,
+    MultimodalJSpaceModel,
+)
+from main_chat import generate_response
+
+
+class SmokeTests(unittest.TestCase):
+    def setUp(self):
+        torch.manual_seed(0)
+
+    def test_core_forward_shapes(self):
+        config = JSpaceConfig(
+            input_dim=8,
+            workspace_dim=16,
+            expert_dim=8,
+            num_experts=3,
+            ode_steps=2,
+            noise_std=0.0,
+        )
+        model = JSpaceModel(config)
+        xs = torch.randn(2, 5, 8)
+
+        preds, info = model(xs, record_trajectory=True)
+
+        self.assertEqual(tuple(preds.shape), (2, 5, 8))
+        self.assertEqual(tuple(info["alpha"].shape), (2, 5, 3))
+        self.assertEqual(tuple(info["w_trajectory"].shape), (2, 5, 2, 16))
+
+    def test_language_fast_generation_preserves_eval_and_rk4(self):
+        tokenizer = CharTokenizer.from_text("学而时习之")
+        config = LanguageConfig(
+            vocab_size=tokenizer.vocab_size,
+            embed_dim=8,
+            input_dim=8,
+            workspace_dim=16,
+            expert_dim=8,
+            num_experts=3,
+            ode_steps=1,
+            noise_std=0.0,
+        )
+        model = JSpaceLanguageModel(config)
+        model.eval()
+
+        response = generate_response(
+            model,
+            tokenizer,
+            "学",
+            n_new=3,
+            temperature=1.0,
+            top_k=2,
+            fast=True,
+        )
+
+        self.assertEqual(len(response), 3)
+        self.assertFalse(model.training)
+        self.assertTrue(all(expert.use_rk4 for expert in model.experts))
+
+    def test_multimodal_single_step_records_trajectory(self):
+        config = MultimodalConfig(
+            vocab_size=20,
+            embed_dim=8,
+            input_dim=8,
+            workspace_dim=16,
+            expert_dim=8,
+            num_experts=4,
+            ode_steps=2,
+            noise_std=0.0,
+            audio_frame_size=128,
+        )
+        model = MultimodalJSpaceModel(config)
+        token = torch.tensor([1])
+
+        outputs, info = model.forward_multimodal(
+            "text",
+            token,
+            record_trajectory=True,
+        )
+
+        self.assertEqual(tuple(outputs["w"].shape), (1, 16))
+        self.assertEqual(len(info["w_trajectory"]), 2)
+
+    def test_tokenizer_unknown_maps_to_zero(self):
+        tokenizer = CharTokenizer.from_text("abc")
+
+        self.assertEqual(tokenizer.encode("?"), [0])
+        self.assertEqual(tokenizer.decode([0]), "<unk>")
+
+
+if __name__ == "__main__":
+    unittest.main()