Merge branch 'dev' into update_components

scripts/aws/package-lock.json

@@ -1950,12 +1950,12 @@
       }
     },
     "node_modules/braces": {
-      "version": "3.0.2",
+      "version": "3.0.3",
-      "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.2.tgz",
+      "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.3.tgz",
-      "integrity": "sha512-b8um+L1RzM3WDSzvhm6gIz1yfTbBt6YTlcEKAvsmqCZZFw46z626lVj9j1yEPW33H5H+lBQpZMP1k8l+78Ha0A==",
+      "integrity": "sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==",
       "dev": true,
       "dependencies": {
-        "fill-range": "^7.0.1"
+        "fill-range": "^7.1.1"
       },
       "engines": {
         "node": ">=8"
@@ -2763,9 +2763,9 @@
       }
     },
     "node_modules/fill-range": {
-      "version": "7.0.1",
+      "version": "7.1.1",
-      "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.0.1.tgz",
+      "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.1.1.tgz",
-      "integrity": "sha512-qOo9F+dMUmC2Lcb4BbVvnKJxTPjCm+RRpe4gDuGrzkL7mEVl/djYSu2OdQ2Pa302N4oqkSg9ir6jaLWJ2USVpQ==",
+      "integrity": "sha512-YsGpe3WHLK8ZYi4tWDg2Jy3ebRz2rXowDxnld4bkQB00cc/1Zw9AWnC0i9ztDJitivtQvaI9KaLyKrc+hBW0yg==",
       "dev": true,
       "dependencies": {
         "to-regex-range": "^5.0.1"

src/backend/base/langflow/custom/custom_component/custom_component.py

@@ -83,7 +83,7 @@ class CustomComponent(BaseComponent):
     _flows_data: Optional[List[Data]] = None
     _outputs: List[OutputLog] = []
     _logs: List[Log] = []
-    _tracing_service: "TracingService"
+    tracing_service: Optional["TracingService"] = None
 
     def update_state(self, name: str, value: Any):
         if not self.vertex:
@@ -488,14 +488,14 @@ class CustomComponent(BaseComponent):
         Args:
             message (LoggableType | list[LoggableType]): The message to log.
         """
-        if name is None:
+        if name is None and self.display_name:
-            name = self.display_name if self.display_name else self.__class__.__name__
+            name = self.display_name
-        if hasattr(message, "model_dump") and isinstance(message, BaseModel):
+        else:
-            message = message.model_dump()
+            name = self.__class__.__name__
         log = Log(message=message, type=get_artifact_type(message), name=name)
         self._logs.append(log)
-        if self.vertex:
+        if self.tracing_service and self.vertex:
-            self._tracing_service.add_log(trace_name=self.vertex.id, log=log)
+            self.tracing_service.add_log(trace_name=self.vertex.id, log=log)
 
     def post_code_processing(self, new_build_config: dict, current_build_config: dict):
         """

src/backend/base/langflow/services/database/utils.py

@@ -18,8 +18,12 @@ def migrate_messages_from_monitor_service_to_database(session: Session) -> bool:
     from langflow.schema.message import Message
     from langflow.services.database.models.message import MessageTable
 
+    try:
         monitor_service = get_monitor_service()
         messages_df = monitor_service.get_messages()
+    except Exception as e:
+        logger.error(f"Error retrieving messages from monitor service: {e}")
+        return False
 
     if messages_df.empty:
         logger.info("No messages to migrate.")

src/backend/base/langflow/services/tracing/base.py

@@ -0,0 +1,33 @@
+from abc import ABC, abstractmethod
+from typing import Any, Dict
+from uuid import UUID
+
+
+class BaseTracer(ABC):
+    @abstractmethod
+    def __init__(self, trace_name: str, trace_type: str, project_name: str, trace_id: UUID):
+        raise NotImplementedError
+
+    @abstractmethod
+    def ready(self):
+        raise NotImplementedError
+
+    @abstractmethod
+    def add_trace(
+        self, trace_name: str, trace_type: str, inputs: Dict[str, Any], metadata: Dict[str, Any] | None = None
+    ):
+        raise NotImplementedError
+
+    @abstractmethod
+    def end_trace(self, trace_name: str, outputs: Dict[str, Any] | None = None, error: str | None = None):
+        raise NotImplementedError
+
+    @abstractmethod
+    def end(
+        self,
+        inputs: dict[str, Any],
+        outputs: Dict[str, Any],
+        error: str | None = None,
+        metadata: dict[str, Any] | None = None,
+    ):
+        raise NotImplementedError

src/backend/base/langflow/services/tracing/service.py

@@ -12,6 +12,7 @@ from loguru import logger
 
 from langflow.schema.data import Data
 from langflow.services.base import Service
+from langflow.services.tracing.base import BaseTracer
 from langflow.services.tracing.schema import Log
 
 if TYPE_CHECKING:
@@ -180,7 +181,7 @@ class TracingService(Service):
         self.outputs_metadata[trace_name] |= output_metadata or {}
 
 
-class LangSmithTracer:
+class LangSmithTracer(BaseTracer):
     def __init__(self, trace_name: str, trace_type: str, project_name: str, trace_id: UUID):
         from langsmith.run_trees import RunTree
 
@@ -292,7 +293,7 @@ class LangSmithTracer:
         inputs: dict[str, Any],
         outputs: Dict[str, Any],
         error: str | None = None,
-        metadata: Optional[dict[str, Any]] = None,
+        metadata: dict[str, Any] | None = None,
     ):
         self._run_tree.add_metadata({"inputs": inputs, "metadata": metadata or {}})
         self._run_tree.end(outputs=outputs, error=error)

src/backend/base/langflow/services/tracing/utils.py

@@ -0,0 +1,34 @@
+from typing import Any, Dict
+
+from langflow.schema.data import Data
+
+
+def convert_to_langchain_type(value):
+    from langflow.schema.message import Message
+
+    if isinstance(value, dict):
+        for key, _value in value.copy().items():
+            _value = convert_to_langchain_type(_value)
+            value[key] = _value
+    elif isinstance(value, list):
+        value = [convert_to_langchain_type(v) for v in value]
+    elif isinstance(value, Message):
+        if "prompt" in value:
+            value = value.load_lc_prompt()
+        elif value.sender:
+            value = value.to_lc_message()
+        else:
+            value = value.to_lc_document()
+    elif isinstance(value, Data):
+        if "text" in value.data:
+            value = value.to_lc_document()
+        else:
+            value = value.data
+    return value
+
+
+def convert_to_langchain_types(io_dict: Dict[str, Any]):
+    converted = {}
+    for key, value in io_dict.items():
+        converted[key] = convert_to_langchain_type(value)
+    return converted