fix: 修复 to_dict list 类型丢失与 OpenAI stop 参数失效

- to_dict() 增加 list 类型序列化支持，metrics 等字段不再丢失
- OpenAIHandler 补充 get_stop_sequences/on_token，读取 request.stop 并检测停止序列
- 文档类图补充缺失字段、修正关系分类、ChatCompletionRequest 字段增加 Optional

assets/docs/architecture.md

@@ -77,6 +77,9 @@ classDiagram
             +int start_batch
             +str ckpt_dir
             +int ckpt_interval
+            +str log_dir
+            +int log_interval
+            +List[str] metrics
             +int random_seed
             +int num_workers
             +Optional[int] prefetch_factor
@@ -472,6 +475,10 @@ classDiagram
         class CheckpointCallback {
             +str save_dir
             +int interval
+            +bool weight_only
+            +Callable state_dict_fn
+            +Callable save_extra_fn
+            +Callable load_extra_fn
             +_save_checkpoint(context)
             +on_train_begin(context)
             +on_batch_end(context)
@@ -483,6 +490,8 @@ classDiagram
 
         class ProgressBarCallback {
             +int num_epoch
+            +int log_interval
+            +IO file
             +on_epoch_begin(context)
             +on_batch_end(context)
             +on_epoch_end(context)
@@ -491,6 +500,8 @@ classDiagram
         class MetricLoggerCallback {
             +str log_dir
             +int save_interval
+            +int log_interval
+            +List[str] metrics
             +on_batch_end(context)
             +on_train_end(context)
             +on_error(context)
@@ -687,7 +698,7 @@ classDiagram
         }
 
         class SamplingPipeline {
-            +List strategies
+            +List[BaseSamplingStrategy] strategies
             +apply(logits, filter_value) Tensor
             +sample(logits, filter_value) Tensor
         }
@@ -711,16 +722,16 @@ classDiagram
         class ChatCompletionRequest {
             +str model
             +List[ChatMessage] messages
-            +float temperature
-            +float top_p
-            +int top_k
-            +int max_tokens
-            +bool stream
+            +Optional[float] temperature
+            +Optional[float] top_p
+            +Optional[int] top_k
+            +Optional[int] max_tokens
+            +Optional[bool] stream
             +Optional[Union[str, List[str]]] stop
             +Optional[int] n
             +Optional[float] presence_penalty
             +Optional[float] frequency_penalty
-            +Optional[Dict] logit_bias
+            +Optional[Dict[int, float]] logit_bias
             +Optional[str] user
         }
 
@@ -872,7 +883,6 @@ classDiagram
     InferenceScheduler *-- KVCache
     InferenceScheduler *-- Executor
     InferenceScheduler *-- TaskManager
-    SamplingPipeline *-- BaseSamplingStrategy
     AutoRegressiveLM *-- DecoderBlock
     AutoRegressiveLM *-- RotaryEmbedding
     AutoRegressiveLM *-- Embedding
@@ -880,9 +890,10 @@ classDiagram
     EmbeddingEncoder *-- RotaryEmbedding
     EmbeddingEncoder *-- Embedding
     DecoderBlock *-- RMSNorm
-    BaseDataset o-- BaseStorage
     ChatCompletionRequest *-- ChatMessage
     MessagesRequest *-- AnthropicMessage
+    AutoTokenizer *-- ChatTemplate
+    BaseFactory *-- Registry
 
     %% --- Aggregation (weak ownership) ---
     AutoModel o-- BaseModelConfig
@@ -890,9 +901,9 @@ classDiagram
     TrainContext o-- BaseStrategy
     TrainContext o-- BaseScheduler
     TrainContext o-- Checkpoint
-    AutoTokenizer o-- ChatTemplate
     KvcacheView o-- Storage
-    BaseFactory o-- Registry
+    SamplingPipeline o-- BaseSamplingStrategy
+    BaseDataset o-- BaseStorage
 
     %% --- Dependency (uses temporarily) ---
     TrainConfig ..> BaseStrategy : selects

astrai/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "1.3.5"
+__version__ = "1.3.6"
 __author__ = "ViperEkura"
 
 from astrai.config import (

astrai/config/__init__.py

@@ -11,7 +11,6 @@ __all__ = [
     "BaseModelConfig",
     "AutoRegressiveLMConfig",
     "EncoderConfig",
-    "ModelConfig",
     "ConfigFactory",
     "TrainConfig",
 ]

astrai/config/base.py

@@ -13,7 +13,7 @@ class BaseConfig:
                 d[fld.name] = v
             elif v is None:
                 d[fld.name] = None
-            elif isinstance(v, dict):
+            elif isinstance(v, (dict, list)):
                 try:
                     json.dumps(v)
                     d[fld.name] = v

astrai/inference/api/protocol.py

@@ -226,6 +226,17 @@ class OpenAIHandler(ProtocolHandler):
     def create_response_id(self) -> str:
         return f"chatcmpl-{uuid.uuid4().hex[:12]}"
 
+    def get_stop_sequences(self) -> List[str]:
+        stop = self.request.stop
+        if stop is None:
+            return []
+        return [stop] if isinstance(stop, str) else stop
+
+    def on_token(
+        self, ctx: StreamContext, token: str, stop_checker: StopChecker
+    ) -> Optional[str]:
+        return stop_checker.check(ctx.accumulated)
+
     def format_stream_start(self, ctx: StreamContext) -> List[str]:
         return [
             _sse_event(

tests/inference/test_server.py

@@ -157,5 +157,60 @@ def test_messages_with_system(client, loaded_model):
     assert data["type"] == "message"
 
 
+def test_chat_completions_stop_sequence(client, loaded_model):
+    """POST /v1/chat/completions with stop parameter truncates at stop sequence."""
+
+    async def async_gen():
+        yield "Hello"
+        yield "X"
+        yield "world"
+
+    app.state.engine = loaded_model
+    loaded_model.generate_async.return_value = async_gen()
+    response = client.post(
+        "/v1/chat/completions",
+        json={
+            "messages": [{"role": "user", "content": "Hello"}],
+            "max_tokens": 100,
+            "stream": False,
+            "stop": ["X"],
+        },
+    )
+    assert response.status_code == 200
+    data = response.json()
+    content = data["choices"][0]["message"]["content"]
+    assert "X" in content
+    assert "world" not in content
+
+
+def test_chat_completions_stop_sequence_stream(client, loaded_model):
+    """POST /v1/chat/completions with stop parameter truncates SSE stream."""
+
+    async def async_gen():
+        yield "Hello"
+        yield "X"
+        yield "world"
+
+    app.state.engine = loaded_model
+    loaded_model.generate_async.return_value = async_gen()
+    response = client.post(
+        "/v1/chat/completions",
+        json={
+            "messages": [{"role": "user", "content": "Hello"}],
+            "max_tokens": 100,
+            "stream": True,
+            "stop": ["X"],
+        },
+        headers={"Accept": "text/event-stream"},
+    )
+    assert response.status_code == 200
+    content = response.content.decode("utf-8")
+    assert "Hello" in content
+    assert "world" not in content
+    assert any(
+        "finish_reason" in line for line in content.split("\n") if "stop" in line
+    )
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-v"])