📝 (loading.py): Update the logic in build_custom_component function to handle cases where raw is None and improve artifact_type assignment for better accuracy

📝 (chat.py): Remove commented out code related to logs in build_vertex function for better code readability
📝 (schemas.py): Change the type of logs field in ResultDataResponse class to be a dictionary with string keys and Log values for consistency
📝 (schema.py): Refactor build_logs_from_artifacts function to use a dictionary instead of defaultdict for logs variable for simplicity and consistency

src/backend/base/langflow/api/v1/chat.py

@@ -181,13 +181,6 @@ async def build_vertex(
                 inputs_dict=inputs.model_dump() if inputs else {},
                 files=files,
             )
-            # logs = {}
-            # if isinstance(vertex.artifacts_raw, dict):
-            #     for key in vertex.artifacts_raw:
-            #         log_obj = Log(message=vertex.artifacts_raw[key], type=vertex.artifacts_type[key])
-            #         logs[key] = log_obj
-            # else:
-            #     logs = [Log(message=vertex.artifacts_raw, type=vertex.artifacts_type)]
 
             result_data_response = ResultDataResponse.model_validate(result_dict, from_attributes=True)
         except Exception as exc:

src/backend/base/langflow/api/v1/schemas.py

@@ -245,7 +245,7 @@ class VerticesOrderResponse(BaseModel):
 
 class ResultDataResponse(BaseModel):
     results: Optional[Any] = Field(default_factory=dict)
-    logs: dict[str, List[Log] | Log] = Field(default_factory=dict)
+    logs: dict[str, Log] = Field(default_factory=dict)
     message: Optional[Any] = Field(default_factory=dict)
     artifacts: Optional[Any] = Field(default_factory=dict)
     timedelta: Optional[float] = None

src/backend/base/langflow/interface/initialize/loading.py

@@ -157,8 +157,10 @@ async def build_custom_component(params: dict, custom_component: "CustomComponen
 
     elif hasattr(raw, "model_dump") and raw is not None:
         raw = raw.model_dump()
+    if raw is None and isinstance(build_result, (dict, Data, str)):
+        raw = build_result.data if isinstance(build_result, Data) else build_result
 
-    artifact_type = get_artifact_type(custom_component.repr_value, build_result)
+    artifact_type = get_artifact_type(custom_component.repr_value or raw, build_result)
     raw = post_process_raw(raw, artifact_type)
     artifact = {"repr": custom_repr, "raw": raw, "type": artifact_type}
     return custom_component, build_result, artifact

src/backend/base/langflow/schema/schema.py

@@ -1,4 +1,3 @@
-from collections import defaultdict
 from typing import Any, Literal
 
 from typing_extensions import TypedDict
@@ -19,7 +18,7 @@ class Log(TypedDict):
 
 
 def build_logs_from_artifacts(artifacts: dict) -> dict:
-    logs = defaultdict(list)
+    logs = {}
     for key in artifacts:
         message = artifacts[key]["raw"]
         _type = artifacts[key]["type"]
@@ -33,7 +32,7 @@ def build_logs_from_artifacts(artifacts: dict) -> dict:
         elif _type:
             log = Log(message=message, type=_type)
 
-        logs[key].append(log)
+        logs[key] = log
     return logs