Fix import statements and formatting issues

src/backend/langflow/components/documentloaders/GatherRecords.py

@@ -70,11 +70,17 @@ class GatherRecordsComponent(CustomComponent):
 
         glob = "**/*" if recursive else "*"
         paths = walk_level(path_obj, depth) if depth else path_obj.glob(glob)
-        file_paths = [Text(p) for p in paths if p.is_file() and match_types(p) and is_not_hidden(p)]
+        file_paths = [
+            Text(p)
+            for p in paths
+            if p.is_file() and match_types(p) and is_not_hidden(p)
+        ]
 
         return file_paths
 
-    def parse_file_to_record(self, file_path: str, silent_errors: bool) -> Optional[Record]:
+    def parse_file_to_record(
+        self, file_path: str, silent_errors: bool
+    ) -> Optional[Record]:
         # Use the partition function to load the file
         from unstructured.partition.auto import partition  # type: ignore
 
@@ -100,9 +106,14 @@ class GatherRecordsComponent(CustomComponent):
         use_multithreading: bool,
     ) -> List[Optional[Record]]:
         if use_multithreading:
-            records = self.parallel_load_records(file_paths, silent_errors, max_concurrency)
+            records = self.parallel_load_records(
+                file_paths, silent_errors, max_concurrency
+            )
         else:
-            records = [self.parse_file_to_record(file_path, silent_errors) for file_path in file_paths]
+            records = [
+                self.parse_file_to_record(file_path, silent_errors)
+                for file_path in file_paths
+            ]
         records = list(filter(None, records))
         return records
 
@@ -131,13 +142,20 @@ class GatherRecordsComponent(CustomComponent):
         if types is None:
             types = []
         resolved_path = self.resolve_path(path)
-        file_paths = self.retrieve_file_paths(resolved_path, types, load_hidden, recursive, depth)
+        file_paths = self.retrieve_file_paths(
+            resolved_path, types, load_hidden, recursive, depth
+        )
         loaded_records = []
 
         if use_multithreading:
-            loaded_records = self.parallel_load_records(file_paths, silent_errors, max_concurrency)
+            loaded_records = self.parallel_load_records(
+                file_paths, silent_errors, max_concurrency
+            )
         else:
-            loaded_records = [self.parse_file_to_record(file_path, silent_errors) for file_path in file_paths]
+            loaded_records = [
+                self.parse_file_to_record(file_path, silent_errors)
+                for file_path in file_paths
+            ]
         loaded_records = list(filter(None, loaded_records))
         self.status = loaded_records
         return loaded_records

src/backend/langflow/components/io/base/chat.py

@@ -45,7 +45,9 @@ class ChatComponent(CustomComponent):
             return []
 
         if not session_id or not sender or not sender_name:
-            raise ValueError("All of session_id, sender, and sender_name must be provided.")
+            raise ValueError(
+                "All of session_id, sender, and sender_name must be provided."
+            )
         if isinstance(message, Record):
             record = message
             record.data.update(

src/backend/langflow/components/utilities/SharedState.py

@@ -0,0 +1,38 @@
+from typing import Union
+
+from langflow import CustomComponent
+from langflow.field_typing import Text
+from langflow.schema import Record
+
+
+class SharedState(CustomComponent):
+    display_name = "Shared State"
+    description = "A component to share state between components."
+
+    def build_config(self):
+        return {
+            "name": {"display_name": "Name", "info": "The name of the state."},
+            "record": {"display_name": "Record", "info": "The record to store."},
+            "append": {
+                "display_name": "Append",
+                "info": "If True, the record will be appended to the state.",
+            },
+        }
+
+    def build(
+        self, name: str, record: Union[Text, Record], append: bool = False
+    ) -> Record:
+        if append:
+            self.append_state(name, record)
+        else:
+            self.update_state(name, record)
+
+        state = self.get_state(name)
+        if not isinstance(state, Record):
+            if isinstance(state, str):
+                state = Record(text=state)
+            elif isinstance(state, dict):
+                state = Record(data=state)
+            else:
+                state = Record(text=str(state))
+        return state

src/backend/langflow/components/vectorstores/ChromaSearch.py

@@ -93,7 +93,8 @@ class ChromaSearchComponent(LCVectorStoreComponent):
 
         if chroma_server_host is not None:
             chroma_settings = chromadb.config.Settings(
-                chroma_server_cors_allow_origins=chroma_server_cors_allow_origins or None,
+                chroma_server_cors_allow_origins=chroma_server_cors_allow_origins
+                or None,
                 chroma_server_host=chroma_server_host,
                 chroma_server_port=chroma_server_port or None,
                 chroma_server_grpc_port=chroma_server_grpc_port or None,

src/backend/langflow/components/vectorstores/FAISSSearch.py

@@ -34,7 +34,9 @@ class FAISSSearchComponent(LCVectorStoreComponent):
         if not folder_path:
             raise ValueError("Folder path is required to save the FAISS index.")
         path = self.resolve_path(folder_path)
-        vector_store = FAISS.load_local(folder_path=Text(path), embeddings=embedding, index_name=index_name)
+        vector_store = FAISS.load_local(
+            folder_path=Text(path), embeddings=embedding, index_name=index_name
+        )
         if not vector_store:
             raise ValueError("Failed to load the FAISS index.")
 

src/backend/langflow/components/vectorstores/SupabaseVectorStoreSearch.py

@@ -38,7 +38,9 @@ class SupabaseSearchComponent(LCVectorStoreComponent):
         supabase_url: str = "",
         table_name: str = "",
     ) -> List[Record]:
-        supabase: Client = create_client(supabase_url, supabase_key=supabase_service_key)
+        supabase: Client = create_client(
+            supabase_url, supabase_key=supabase_service_key
+        )
         vector_store = SupabaseVectorStore(
             client=supabase,
             embedding=embedding,

src/backend/langflow/components/vectorstores/VectaraSearch.py

@@ -11,7 +11,9 @@ from langflow.schema import Record
 class VectaraSearchComponent(VectaraComponent, LCVectorStoreComponent):
     display_name: str = "Vectara Search"
     description: str = "Search a Vectara Vector Store for similar documents."
-    documentation = "https://python.langchain.com/docs/integrations/vectorstores/vectara"
+    documentation = (
+        "https://python.langchain.com/docs/integrations/vectorstores/vectara"
+    )
     beta = True
     icon = "Vectara"
 

src/backend/langflow/components/vectorstores/WeaviateSearch.py

@@ -11,7 +11,9 @@ from langflow.schema import Record
 class WeaviateSearchVectorStore(WeaviateVectorStoreComponent, LCVectorStoreComponent):
     display_name: str = "Weaviate Search"
     description: str = "Search a Weaviate Vector Store for similar documents."
-    documentation = "https://python.langchain.com/docs/integrations/vectorstores/weaviate"
+    documentation = (
+        "https://python.langchain.com/docs/integrations/vectorstores/weaviate"
+    )
     beta = True
     icon = "Weaviate"
 

src/backend/langflow/components/vectorstores/base/model.py

@@ -6,7 +6,8 @@ from langchain_core.vectorstores import VectorStore
 
 from langflow import CustomComponent
 from langflow.field_typing import Text
-from langflow.schema import Record, docs_to_records
+from langflow.helpers.record import docs_to_records
+from langflow.schema import Record
 
 
 class LCVectorStoreComponent(CustomComponent):

src/backend/langflow/components/vectorstores/pgvectorSearch.py

@@ -15,7 +15,9 @@ class PGVectorSearchComponent(PGVectorComponent, LCVectorStoreComponent):
 
     display_name: str = "PGVector Search"
     description: str = "Search a PGVector Store for similar documents."
-    documentation = "https://python.langchain.com/docs/integrations/vectorstores/pgvector"
+    documentation = (
+        "https://python.langchain.com/docs/integrations/vectorstores/pgvector"
+    )
 
     def build_config(self):
         """

src/backend/langflow/graph/vertex/types.py

@@ -123,9 +123,11 @@ class DocumentLoaderVertex(StatefulVertex):
         # show how many documents are in the list?
 
         if not isinstance(self._built_object, UnbuiltObject):
-            avg_length = sum(len(doc.page_content) for doc in self._built_object if hasattr(doc, "page_content")) / len(
-                self._built_object
-            )
+            avg_length = sum(
+                len(doc.page_content)
+                for doc in self._built_object
+                if hasattr(doc, "page_content")
+            ) / len(self._built_object)
             return f"""{self.display_name}({len(self._built_object)} documents)
             \nAvg. Document Length (characters): {int(avg_length)}
             Documents: {self._built_object[:3]}..."""
@@ -198,7 +200,9 @@ class TextSplitterVertex(StatefulVertex):
         # show how many documents are in the list?
 
         if not isinstance(self._built_object, UnbuiltObject):
-            avg_length = sum(len(doc.page_content) for doc in self._built_object) / len(self._built_object)
+            avg_length = sum(len(doc.page_content) for doc in self._built_object) / len(
+                self._built_object
+            )
             return f"""{self.vertex_type}({len(self._built_object)} documents)
             \nAvg. Document Length (characters): {int(avg_length)}
             \nDocuments: {self._built_object[:3]}..."""
@@ -245,18 +249,27 @@ class PromptVertex(StatelessVertex):
         user_id = kwargs.get("user_id", None)
         tools = kwargs.get("tools", [])
         if not self._built or force:
-            if "input_variables" not in self.params or self.params["input_variables"] is None:
+            if (
+                "input_variables" not in self.params
+                or self.params["input_variables"] is None
+            ):
                 self.params["input_variables"] = []
             # Check if it is a ZeroShotPrompt and needs a tool
             if "ShotPrompt" in self.vertex_type:
-                tools = [tool_node.build(user_id=user_id) for tool_node in tools] if tools is not None else []
+                tools = (
+                    [tool_node.build(user_id=user_id) for tool_node in tools]
+                    if tools is not None
+                    else []
+                )
                 # flatten the list of tools if it is a list of lists
                 # first check if it is a list
                 if tools and isinstance(tools, list) and isinstance(tools[0], list):
                     tools = flatten_list(tools)
                 self.params["tools"] = tools
                 prompt_params = [
-                    key for key, value in self.params.items() if isinstance(value, str) and key != "format_instructions"
+                    key
+                    for key, value in self.params.items()
+                    if isinstance(value, str) and key != "format_instructions"
                 ]
             else:
                 prompt_params = ["template"]
@@ -266,14 +279,20 @@ class PromptVertex(StatelessVertex):
                     prompt_text = self.params[param]
                     variables = extract_input_variables_from_prompt(prompt_text)
                     self.params["input_variables"].extend(variables)
-                self.params["input_variables"] = list(set(self.params["input_variables"]))
+                self.params["input_variables"] = list(
+                    set(self.params["input_variables"])
+                )
             elif isinstance(self.params, dict):
                 self.params.pop("input_variables", None)
 
             await self._build(user_id=user_id)
 
     def _built_object_repr(self):
-        if not self.artifacts or self._built_object is None or not hasattr(self._built_object, "format"):
+        if (
+            not self.artifacts
+            or self._built_object is None
+            or not hasattr(self._built_object, "format")
+        ):
             return super()._built_object_repr()
         elif isinstance(self._built_object, UnbuiltObject):
             return super()._built_object_repr()
@@ -285,7 +304,9 @@ class PromptVertex(StatelessVertex):
         # so the prompt format doesn't break
         artifacts.pop("handle_keys", None)
         try:
-            if not hasattr(self._built_object, "template") and hasattr(self._built_object, "prompt"):
+            if not hasattr(self._built_object, "template") and hasattr(
+                self._built_object, "prompt"
+            ):
                 template = self._built_object.prompt.template
             else:
                 template = self._built_object.template
@@ -293,7 +314,11 @@ class PromptVertex(StatelessVertex):
                 if value:
                     replace_key = "{" + key + "}"
                     template = template.replace(replace_key, value)
-            return template if isinstance(template, str) else f"{self.vertex_type}({template})"
+            return (
+                template
+                if isinstance(template, str)
+                else f"{self.vertex_type}({template})"
+            )
         except KeyError:
             return str(self._built_object)
 

src/backend/langflow/memory.py

@@ -1,9 +1,10 @@
 from typing import Optional, Union
 
+from loguru import logger
+
 from langflow.schema import Record
 from langflow.services.deps import get_monitor_service
 from langflow.services.monitor.schema import MessageModel
-from loguru import logger
 
 
 def get_messages(

src/backend/langflow/services/monitor/schema.py

@@ -10,7 +10,9 @@ if TYPE_CHECKING:
 
 class TransactionModel(BaseModel):
     id: Optional[int] = Field(default=None, alias="id")
-    timestamp: Optional[datetime] = Field(default_factory=datetime.now, alias="timestamp")
+    timestamp: Optional[datetime] = Field(
+        default_factory=datetime.now, alias="timestamp"
+    )
     source: str
     target: str
     target_args: dict
@@ -51,8 +53,12 @@ class MessageModel(BaseModel):
     @classmethod
     def from_record(cls, record: "Record"):
         # first check if the record has all the required fields
-        if not record.data or ("sender" not in record.data and "sender_name" not in record.data):
-            raise ValueError("The record does not have the required fields 'sender' and 'sender_name' in the data.")
+        if not record.data or (
+            "sender" not in record.data and "sender_name" not in record.data
+        ):
+            raise ValueError(
+                "The record does not have the required fields 'sender' and 'sender_name' in the data."
+            )
         return cls(
             sender=record.data["sender"],
             sender_name=record.data["sender_name"],