Merge branch 'logspace-ai:dev' into dev

src/backend/langflow/api/endpoints.py

@@ -1,5 +1,5 @@
-from importlib.metadata import version
 import logging
+from importlib.metadata import version
 
 from fastapi import APIRouter, HTTPException
 

src/backend/langflow/api/validate.py

@@ -54,4 +54,4 @@ def post_validate_node(node_id: str, data: dict):
         return json.dumps({"valid": True, "params": str(node._built_object_repr())})
     except Exception as e:
         logger.exception(e)
-        return json.dumps({"valid": False})
+        return json.dumps({"valid": False, "params": str(e)})

src/backend/langflow/graph/nodes.py

@@ -143,7 +143,8 @@ class DocumentLoaderNode(Node):
         # This built_object is a list of documents. Maybe we should
         # show how many documents are in the list?
         if self._built_object:
-            return f"""{self.node_type}({len(self._built_object)} documents)\nDocuments: {self._built_object[:3]}..."""
+            return f"""{self.node_type}({len(self._built_object)} documents)
+            Documents: {self._built_object[:3]}..."""
         return f"{self.node_type}()"
 
 

src/backend/langflow/interface/embeddings/base.py

@@ -1,8 +1,10 @@
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Type
 
 from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import embedding_type_to_cls_dict
 from langflow.settings import settings
+from langflow.template.base import FrontendNode
+from langflow.template.nodes import EmbeddingFrontendNode
 from langflow.utils.logger import logger
 from langflow.utils.util import build_template_from_class
 
@@ -14,6 +16,10 @@ class EmbeddingCreator(LangChainTypeCreator):
     def type_to_loader_dict(self) -> Dict:
         return embedding_type_to_cls_dict
 
+    @property
+    def frontend_node_class(self) -> Type[FrontendNode]:
+        return EmbeddingFrontendNode
+
     def get_signature(self, name: str) -> Optional[Dict]:
         """Get the signature of an embedding."""
         try:

src/backend/langflow/interface/loading.py

@@ -108,6 +108,7 @@ def instantiate_toolkit(node_type, class_object, params):
 
 def instantiate_embedding(class_object, params):
     params.pop("model", None)
+    params.pop("headers", None)
     try:
         return class_object(**params)
     except ValidationError:

src/backend/langflow/interface/run.py

@@ -3,12 +3,12 @@ import io
 from typing import Any, Dict, List, Tuple
 
 from chromadb.errors import NotEnoughElementsException  # type: ignore
+from langchain.schema import AgentAction
 
 from langflow.api.callback import AsyncStreamingLLMCallbackHandler, StreamingLLMCallbackHandler  # type: ignore
 from langflow.cache.base import compute_dict_hash, load_cache, memoize_dict
 from langflow.graph.graph import Graph
 from langflow.utils.logger import logger
-from langchain.schema import AgentAction
 
 
 def load_langchain_object(data_graph, is_first_message=False):

src/backend/langflow/template/nodes.py

@@ -614,3 +614,11 @@ class LLMFrontendNode(FrontendNode):
         elif field.name in ["model_name", "temperature"]:
             field.advanced = False
             field.show = True
+
+
+class EmbeddingFrontendNode(FrontendNode):
+    @staticmethod
+    def format_field(field: TemplateField, name: Optional[str] = None) -> None:
+        FrontendNode.format_field(field, name)
+        if field.name == "headers":
+            field.show = False