feat: Run AWEL flow in CLI (#1341)

dbgpt/core/awel/operators/base.py

@@ -127,6 +127,8 @@ class BaseOperator(DAGNode, ABC, Generic[OUT], metaclass=BaseOperatorMeta):
     """
 
     streaming_operator: bool = False
+    incremental_output: bool = False
+    output_format: Optional[str] = None
 
     def __init__(
         self,
@@ -147,6 +149,10 @@ class BaseOperator(DAGNode, ABC, Generic[OUT], metaclass=BaseOperatorMeta):
             from dbgpt.core.awel import DefaultWorkflowRunner
 
             runner = DefaultWorkflowRunner()
+        if "incremental_output" in kwargs:
+            self.incremental_output = bool(kwargs["incremental_output"])
+        if "output_format" in kwargs:
+            self.output_format = kwargs["output_format"]
 
         self._runner: WorkflowRunner = runner
         self._dag_ctx: Optional[DAGContext] = None

dbgpt/core/awel/trigger/iterator_trigger.py

@@ -132,9 +132,11 @@ class IteratorTrigger(Trigger[List[Tuple[Any, Any]]]):
         task_id = self.node_id
 
         async def call_stream(call_data: Any):
-            async for out in await end_node.call_stream(call_data):
-                yield out
-            await dag._after_dag_end(end_node.current_event_loop_task_id)
+            try:
+                async for out in await end_node.call_stream(call_data):
+                    yield out
+            finally:
+                await dag._after_dag_end(end_node.current_event_loop_task_id)
 
         async def run_node(call_data: Any) -> Tuple[Any, Any]:
             async with semaphore:

dbgpt/core/interface/llm.py

@@ -161,6 +161,7 @@ class ModelOutput:
     error_code: int
     """The error code of the model inference. If the model inference is successful,
     the error code is 0."""
+    incremental: bool = False
     model_context: Optional[Dict] = None
     finish_reason: Optional[str] = None
     usage: Optional[Dict[str, Any]] = None
@@ -171,6 +172,11 @@ class ModelOutput:
         """Convert the model output to dict."""
         return asdict(self)
 
+    @property
+    def success(self) -> bool:
+        """Check if the model inference is successful."""
+        return self.error_code == 0
+
 
 _ModelMessageType = Union[List[ModelMessage], List[Dict[str, Any]]]
 

dbgpt/core/interface/operators/llm_operator.py

@@ -470,6 +470,8 @@ class CommonStreamingOutputOperator(TransformStreamAbsOperator[ModelOutput, str]
     Transform model output to the string output to show in DB-GPT chat flow page.
     """
 
+    output_format = "SSE"
+
     metadata = ViewMetadata(
         label=_("Common Streaming Output Operator"),
         name="common_streaming_output_operator",
@@ -510,8 +512,8 @@ class CommonStreamingOutputOperator(TransformStreamAbsOperator[ModelOutput, str]
                 yield f"data:{error_msg}"
                 return
             decoded_unicode = model_output.text.replace("\ufffd", "")
-            msg = decoded_unicode.replace("\n", "\\n")
-            yield f"data:{msg}\n\n"
+            # msg = decoded_unicode.replace("\n", "\\n")
+            yield f"data:{decoded_unicode}\n\n"
 
 
 class StringOutput2ModelOutputOperator(MapOperator[str, ModelOutput]):

dbgpt/core/schema/api.py

@@ -114,3 +114,11 @@ class ChatCompletionResponse(BaseModel):
         ..., description="Chat completion response choices"
     )
     usage: UsageInfo = Field(..., description="Usage info")
+
+
+class ErrorResponse(BaseModel):
+    """Error response entity."""
+
+    object: str = Field("error", description="Object type")
+    message: str = Field(..., description="Error message")
+    code: int = Field(..., description="Error code")