merge dev on feature/ui-table

src/backend/Dockerfile

@@ -1,4 +1,4 @@
-FROM logspace/backend_build as backend_build
+FROM langflowai/backend_build as backend_build
 
 FROM python:3.10-slim
 WORKDIR /app

src/backend/base/langflow/alembic/versions/1f4d6df60295_add_default_fields_column.py

@@ -1,7 +1,7 @@
 """Add default_fields column
 
 Revision ID: 1f4d6df60295
-Revises: 58b28437a398
+Revises: 6e7b581b5648
 Create Date: 2024-04-29 09:49:46.864145
 
 """
@@ -14,7 +14,7 @@ from sqlalchemy.engine.reflection import Inspector
 
 # revision identifiers, used by Alembic.
 revision: str = "1f4d6df60295"
-down_revision: Union[str, None] = "58b28437a398"
+down_revision: Union[str, None] = "6e7b581b5648"
 branch_labels: Union[str, Sequence[str], None] = None
 depends_on: Union[str, Sequence[str], None] = None
 

src/backend/base/langflow/alembic/versions/6e7b581b5648_fix_nullable.py

@@ -0,0 +1,59 @@
+"""Fix nullable
+
+Revision ID: 6e7b581b5648
+Revises: 58b28437a398
+Create Date: 2024-04-30 09:17:45.024688
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "6e7b581b5648"
+down_revision: Union[str, None] = "58b28437a398"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    # ### commands auto generated by Alembic - please adjust! ###
+    columns = inspector.get_columns("apikey")
+    column_names = {column["name"]: column for column in columns}
+    with op.batch_alter_table("apikey", schema=None) as batch_op:
+        created_at_column = [column for column in columns if column["name"] == "created_at"][0]
+        if "created_at" in column_names and created_at_column.get("nullable"):
+            batch_op.alter_column(
+                "created_at",
+                existing_type=sa.DATETIME(),
+                nullable=False,
+                existing_server_default=sa.text("(CURRENT_TIMESTAMP)"),  # type: ignore
+            )
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    columns = inspector.get_columns("apikey")
+    column_names = {column["name"]: column for column in columns}
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table("apikey", schema=None) as batch_op:
+        created_at_column = [column for column in columns if column["name"] == "created_at"][0]
+        if "created_at" in column_names and not created_at_column.get("nullable"):
+            batch_op.alter_column(
+                "created_at",
+                existing_type=sa.DATETIME(),
+                nullable=True,
+                existing_server_default=sa.text("(CURRENT_TIMESTAMP)"),  # type: ignore
+            )
+
+    # ### end Alembic commands ###

src/backend/base/langflow/api/utils.py

@@ -201,7 +201,7 @@ def format_elapsed_time(elapsed_time: float) -> str:
         return f"{minutes} {minutes_unit}, {seconds} {seconds_unit}"
 
 
-async def build_and_cache_graph(
+async def build_and_cache_graph_from_db(
     flow_id: str,
     session: Session,
     chat_service: "ChatService",
@@ -220,6 +220,17 @@ async def build_and_cache_graph(
     return graph
 
 
+async def build_and_cache_graph_from_data(
+    flow_id: str,
+    chat_service: "ChatService",
+    graph_data: dict,
+):  # -> Graph | Any:
+    """Build and cache the graph."""
+    graph = Graph.from_payload(graph_data, flow_id)
+    await chat_service.set_cache(flow_id, graph)
+    return graph
+
+
 def format_syntax_error_message(exc: SyntaxError) -> str:
     """Format a SyntaxError message for returning to the frontend."""
     if exc.text is None:

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

@@ -8,13 +8,15 @@ from fastapi.responses import StreamingResponse
 from loguru import logger
 
 from langflow.api.utils import (
-    build_and_cache_graph,
+    build_and_cache_graph_from_data,
+    build_and_cache_graph_from_db,
     format_elapsed_time,
     format_exception_message,
     get_top_level_vertices,
     parse_exception,
 )
 from langflow.api.v1.schemas import (
+    FlowDataRequest,
     InputValueRequest,
     ResultDataResponse,
     StreamData,
@@ -49,9 +51,10 @@ async def try_running_celery_task(vertex, user_id):
     return vertex
 
 
-@router.get("/build/{flow_id}/vertices", response_model=VerticesOrderResponse)
-async def get_vertices(
+@router.post("/build/{flow_id}/vertices", response_model=VerticesOrderResponse)
+async def retrieve_vertices_order(
     flow_id: str,
+    data: Annotated[Optional[FlowDataRequest], Body(embed=True)] = None,
     stop_component_id: Optional[str] = None,
     start_component_id: Optional[str] = None,
     chat_service: "ChatService" = Depends(get_chat_service),
@@ -62,6 +65,7 @@ async def get_vertices(
 
     Args:
         flow_id (str): The ID of the flow.
+        data (Optional[FlowDataRequest], optional): The flow data. Defaults to None.
         stop_component_id (str, optional): The ID of the stop component. Defaults to None.
         start_component_id (str, optional): The ID of the start component. Defaults to None.
         chat_service (ChatService, optional): The chat service dependency. Defaults to Depends(get_chat_service).
@@ -76,9 +80,16 @@ async def get_vertices(
     try:
         # First, we need to check if the flow_id is in the cache
         graph = None
-        if cache := await chat_service.get_cache(flow_id):
-            graph = cache.get("result")
-        graph = await build_and_cache_graph(flow_id, session, chat_service, graph)
+        if not data:
+            if cache := await chat_service.get_cache(flow_id):
+                graph = cache.get("result")
+            graph = await build_and_cache_graph_from_db(
+                flow_id=flow_id, session=session, chat_service=chat_service, graph=graph
+            )
+        else:
+            graph = await build_and_cache_graph_from_data(
+                flow_id=flow_id, graph_data=data.model_dump(), chat_service=chat_service
+            )
         if stop_component_id or start_component_id:
             try:
                 first_layer = graph.sort_vertices(stop_component_id, start_component_id)
@@ -144,7 +155,9 @@ async def build_vertex(
         if not cache:
             # If there's no cache
             logger.warning(f"No cache found for {flow_id}. Building graph starting at {vertex_id}")
-            graph = await build_and_cache_graph(flow_id=flow_id, session=next(get_session()), chat_service=chat_service)
+            graph = await build_and_cache_graph_from_db(
+                flow_id=flow_id, session=next(get_session()), chat_service=chat_service
+            )
         else:
             graph = cache.get("result")
         result_data_response = ResultDataResponse(results={})

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

@@ -130,7 +130,7 @@ async def simplified_run_flow(
             graph_data = flow.data
 
             graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
-            graph = Graph.from_payload(graph_data, flow_id=flow_id, user_id=api_key_user.id)
+            graph = Graph.from_payload(graph_data, flow_id=flow_id, user_id=str(api_key_user.id))
         inputs = [
             InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type)
         ]

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

@@ -26,7 +26,7 @@ class BuildStatus(Enum):
 
 
 class TweaksRequest(BaseModel):
-    tweaks: Optional[Dict[str, Dict[str, str]]] = Field(default_factory=dict)
+    tweaks: Optional[Dict[str, Dict[str, Any]]] = Field(default_factory=dict)
 
 
 class UpdateTemplateRequest(BaseModel):
@@ -294,3 +294,15 @@ class SimplifiedAPIRequest(BaseModel):
     )
     tweaks: Optional[Tweaks] = Field(default=None, description="The tweaks")
     session_id: Optional[str] = Field(default=None, description="The session id")
+
+
+# (alias) type ReactFlowJsonObject<NodeData = any, EdgeData = any> = {
+#     nodes: Node<NodeData>[];
+#     edges: Edge<EdgeData>[];
+#     viewport: Viewport;
+# }
+# import ReactFlowJsonObject
+class FlowDataRequest(BaseModel):
+    nodes: List[dict]
+    edges: List[dict]
+    viewport: Optional[dict] = None

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

@@ -1,10 +1,9 @@
-import warnings
 from typing import Optional, Union
 
 from langflow.field_typing import Text
 from langflow.helpers.record import records_to_text
 from langflow.interface.custom.custom_component import CustomComponent
-from langflow.memory import add_messages
+from langflow.memory import store_message
 from langflow.schema import Record
 
 
@@ -50,34 +49,16 @@ class ChatComponent(CustomComponent):
         sender: Optional[str] = None,
         sender_name: Optional[str] = None,
     ) -> list[Record]:
-        if not message:
-            warnings.warn("No message provided.")
-            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.")
-        if isinstance(message, Record):
-            record = message
-            record.data.update(
-                {
-                    "session_id": session_id,
-                    "sender": sender,
-                    "sender_name": sender_name,
-                }
-            )
-        else:
-            record = Record(
-                data={
-                    "text": message,
-                    "session_id": session_id,
-                    "sender": sender,
-                    "sender_name": sender_name,
-                },
-            )
+        records = store_message(
+            message,
+            session_id=session_id,
+            sender=sender,
+            sender_name=sender_name,
+        )
 
-        self.status = record
-        records = add_messages([record])
-        return records[0]
+        self.status = records
+        return records
 
     def build_with_record(
         self,

src/backend/base/langflow/base/memory/memory.py

@@ -0,0 +1,51 @@
+from typing import Optional
+
+from langflow.field_typing import Text
+from langflow.helpers.record import records_to_text
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.schema.schema import Record
+
+
+class BaseMemoryComponent(CustomComponent):
+    display_name = "Chat Memory"
+    description = "Retrieves stored chat messages given a specific Session ID."
+    beta: bool = True
+    icon = "history"
+
+    def build_config(self):
+        return {
+            "sender": {
+                "options": ["Machine", "User", "Machine and User"],
+                "display_name": "Sender Type",
+            },
+            "sender_name": {"display_name": "Sender Name", "advanced": True},
+            "n_messages": {
+                "display_name": "Number of Messages",
+                "info": "Number of messages to retrieve.",
+            },
+            "session_id": {
+                "display_name": "Session ID",
+                "info": "Session ID of the chat history.",
+                "input_types": ["Text"],
+            },
+            "order": {
+                "options": ["Ascending", "Descending"],
+                "display_name": "Order",
+                "info": "Order of the messages.",
+                "advanced": True,
+            },
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
+                "advanced": True,
+            },
+        }
+
+    def get_messages(self, **kwargs) -> list[Record]:
+        raise NotImplementedError
+
+    def add_message(
+        self, sender: str, sender_name: str, text: str, session_id: str, metadata: Optional[dict] = None, **kwargs
+    ):
+        raise NotImplementedError

src/backend/base/langflow/components/experimental/StoreMessage.py

@@ -0,0 +1,44 @@
+from typing import List, Optional
+
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.memory import get_messages, store_message
+from langflow.schema import Record
+
+
+class StoreMessageComponent(CustomComponent):
+    display_name = "Store Message"
+    description = "Stores a chat message given a Session ID."
+    beta: bool = True
+
+    def build_config(self):
+        return {
+            "sender": {
+                "options": ["Machine", "User"],
+                "display_name": "Sender Type",
+            },
+            "sender_name": {"display_name": "Sender Name"},
+            "message": {"display_name": "Message"},
+            "session_id": {
+                "display_name": "Session ID",
+                "info": "Session ID of the chat history.",
+                "input_types": ["Text"],
+            },
+        }
+
+    def build(
+        self,
+        sender: str = "User",
+        sender_name: Optional[str] = None,
+        session_id: Optional[str] = None,
+        message: str = "",
+    ) -> List[Record]:
+
+        store_message(
+            sender=sender,
+            sender_name=sender_name,
+            session_id=session_id,
+            message=message,
+        )
+
+        self.status = get_messages(session_id=session_id)
+        return get_messages(session_id=session_id)

src/backend/base/langflow/components/experimental/TextOperator.py

@@ -0,0 +1,55 @@
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.schema import Record
+from langflow.field_typing import Text
+
+class TextOperatorComponent(CustomComponent):
+    display_name = "Text Operator"
+    description = "Compares two text inputs based on a specified condition such as equality or inequality, with optional case sensitivity."
+
+    def build_config(self) -> dict:
+        return {
+            "input_text": {
+                "display_name": "Input Text",
+                "info": "The primary text input for the operation.",
+            },
+            "match_text": {
+                "display_name": "Match Text",
+                "info": "The text input to compare against.",
+            },
+            "operator": {
+                "display_name": "Operator",
+                "info": "The operator to apply for comparing the texts.",
+                "options": ["equals", "not equals", "contains", "starts with", "ends with"],
+            },
+            "case_sensitive": {
+                "display_name": "Case Sensitive",
+                "info": "If true, the comparison will be case sensitive.",
+                "field_type": "bool",
+                "default": False,
+            }
+        }
+
+    def build(self, input_text: Text, match_text: Text, operator: Text, case_sensitive: bool = False) -> Text:
+        if not input_text or not match_text:
+            raise ValueError("Both 'input_text' and 'match_text' must be provided and non-empty.")
+
+        if not case_sensitive:
+            input_text = input_text.lower()
+            match_text = match_text.lower()
+
+        result = False
+        if operator == "equals":
+            result = input_text == match_text
+        elif operator == "not equals":
+            result = input_text != match_text
+        elif operator == "contains":
+            result = match_text in input_text
+        elif operator == "starts with":
+            result = input_text.startswith(match_text)
+        elif operator == "ends with":
+            result = input_text.endswith(match_text)
+
+        if not result:
+            self.stop()
+        self.status = f"{result} \n\n {input_text}"
+        return input_text

src/backend/base/langflow/components/helpers/CombineTextsUnsorted.py

@@ -0,0 +1,25 @@
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.field_typing import Text
+
+
+class CombineTextsUnsortedComponent(CustomComponent):
+    display_name = "Combine Texts (Unsorted)"
+    description = "Concatenate text sources into a single text chunk using a specified delimiter."
+    icon = "merge"
+
+    def build_config(self):
+        return {
+            "texts": {
+                "display_name": "Texts",
+                "info": "The first text input to concatenate.",
+            },
+            "delimiter": {
+                "display_name": "Delimiter",
+                "info": "A string used to separate the two text inputs. Defaults to a whitespace.",
+            },
+        }
+
+    def build(self, texts: list[str], delimiter: str = " ") -> Text:
+        combined = delimiter.join(texts)
+        self.status = combined
+        return combined

src/backend/base/langflow/components/helpers/MemoryComponent.py

@@ -1,12 +1,13 @@
 from typing import Optional
 
+from langflow.base.memory.memory import BaseMemoryComponent
 from langflow.field_typing import Text
 from langflow.helpers.record import records_to_text
-from langflow.interface.custom.custom_component import CustomComponent
 from langflow.memory import get_messages
+from langflow.schema.schema import Record
 
 
-class MemoryComponent(CustomComponent):
+class MemoryComponent(BaseMemoryComponent):
     display_name = "Chat Memory"
     description = "Retrieves stored chat messages given a specific Session ID."
     beta: bool = True
@@ -42,6 +43,24 @@ class MemoryComponent(CustomComponent):
             },
         }
 
+    def get_messages(self, **kwargs) -> list[Record]:
+        # Validate kwargs by checking if it contains the correct keys
+        if "sender" not in kwargs:
+            kwargs["sender"] = None
+        if "sender_name" not in kwargs:
+            kwargs["sender_name"] = None
+        if "session_id" not in kwargs:
+            kwargs["session_id"] = None
+        if "limit" not in kwargs:
+            kwargs["limit"] = 5
+        if "order" not in kwargs:
+            kwargs["order"] = "Descending"
+
+        kwargs["order"] = "DESC" if kwargs["order"] == "Descending" else "ASC"
+        if kwargs["sender"] == "Machine and User":
+            kwargs["sender"] = None
+        return get_messages(**kwargs)
+
     def build(
         self,
         sender: Optional[str] = "Machine and User",
@@ -51,10 +70,7 @@ class MemoryComponent(CustomComponent):
         order: Optional[str] = "Descending",
         record_template: Optional[str] = "{sender_name}: {text}",
     ) -> Text:
-        order = "DESC" if order == "Descending" else "ASC"
-        if sender == "Machine and User":
-            sender = None
-        messages = get_messages(
+        messages = self.get_messages(
             sender=sender,
             sender_name=sender_name,
             session_id=session_id,

src/backend/base/langflow/components/helpers/ShouldRunNext.py

@@ -0,0 +1,30 @@
+from langchain_core.messages import BaseMessage
+from langchain_core.prompts import PromptTemplate
+
+from langflow.custom import CustomComponent
+from langflow.field_typing import BaseLanguageModel, Text
+
+
+class ShouldRunNextComponent(CustomComponent):
+    display_name = "Should Run Next"
+    description = "Determines if a vertex is runnable."
+
+    def build(self, llm: BaseLanguageModel, question: str, context: str, retries: int = 3) -> Text:
+        template = "Given the following question and the context below, answer with a yes or no.\n\n{error_message}\n\nQuestion: {question}\n\nContext: {context}\n\nAnswer:"
+
+        prompt = PromptTemplate.from_template(template)
+        chain = prompt | llm
+        error_message = ""
+        for i in range(retries):
+            result = chain.invoke(dict(question=question, context=context, error_message=error_message))
+            if isinstance(result, BaseMessage):
+                content = result.content
+            elif isinstance(result, str):
+                content = result
+            if isinstance(content, str) and content.lower().strip() in ["yes", "no"]:
+                break
+        condition = str(content).lower().strip() == "yes"
+        self.status = f"Should Run Next: {condition}"
+        if condition is False:
+            self.stop()
+        return context

src/backend/base/langflow/components/inputs/ChatInput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatInput(ChatComponent):
     display_name = "Chat Input"
-    description = "Get chat inputs from the Interaction Panel."
+    description = "Get chat inputs from the Playground."
     icon = "ChatInput"
 
     def build_config(self):

src/backend/base/langflow/components/inputs/FileInput.py

@@ -0,0 +1,48 @@
+from pathlib import Path
+from typing import Any, Dict
+
+from langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_record
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.schema import Record
+
+
+class FileInput(CustomComponent):
+    display_name = "File Input"
+    description = "A generic file input."
+    icon = "file-text"
+
+    def build_config(self) -> Dict[str, Any]:
+        return {
+            "path": {
+                "display_name": "Path",
+                "field_type": "file",
+                "file_types": TEXT_FILE_TYPES,
+                "info": f"Supported file types: {', '.join(TEXT_FILE_TYPES)}",
+            },
+            "silent_errors": {
+                "display_name": "Silent Errors",
+                "advanced": True,
+                "info": "If true, errors will not raise an exception.",
+            },
+        }
+
+    def load_file(self, path: str, silent_errors: bool = False) -> Record:
+        resolved_path = self.resolve_path(path)
+        path_obj = Path(resolved_path)
+        extension = path_obj.suffix[1:].lower()
+        if extension == "doc":
+            raise ValueError("doc files are not supported. Please save as .docx")
+        if extension not in TEXT_FILE_TYPES:
+            raise ValueError(f"Unsupported file type: {extension}")
+        record = parse_text_file_to_record(resolved_path, silent_errors)
+        self.status = record if record else "No data"
+        return record or Record()
+
+    def build(
+        self,
+        path: str,
+        silent_errors: bool = False,
+    ) -> Record:
+        record = self.load_file(path, silent_errors)
+        self.status = record
+        return record

src/backend/base/langflow/components/inputs/JsonInput.py

@@ -0,0 +1,17 @@
+from langflow.base.io.text import TextComponent
+from langflow.field_typing.constants import Data, NestedDict
+
+class JsonInput(TextComponent):
+    display_name = "JSON Input"  
+    description = "JSON Input."
+
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "JSON",
+                "field_type": "NestedDict"
+            }
+        }
+
+    def build(self, input_value: NestedDict) -> NestedDict:
+        return input_value

src/backend/base/langflow/components/inputs/KeyPairInput.py

@@ -0,0 +1,19 @@
+from langflow.base.io.text import TextComponent
+from langflow.field_typing.constants import Data
+
+
+class KeyPairInput(TextComponent):
+    display_name = "Dictionary Input"  
+    description = "Dictionary Input."
+
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "Dictionaries",
+                "field_type": "dict",
+                "list": True
+            }
+        }
+
+    def build(self, input_value: dict) -> dict:
+        return input_value

src/backend/base/langflow/components/inputs/StringListInput.py

@@ -0,0 +1,13 @@
+# from langflow.field_typing import Data
+from langflow.schema import Record
+from langflow.interface.custom.custom_component import CustomComponent
+
+
+class StringListInput(CustomComponent):
+    display_name = "String List Input"
+
+    def build_config(self):
+        return {"input_value": {"display_name": "String List Input", "field_type": "str", "list": True}}
+
+    def build(self, input_value: list) -> Record:
+        return Record(data=input_value)

src/backend/base/langflow/components/inputs/TextInput.py

@@ -6,7 +6,7 @@ from langflow.field_typing import Text
 
 class TextInput(TextComponent):
     display_name = "Text Input"
-    description = "Get text inputs from the Interaction Panel."
+    description = "Get text inputs from the Playground."
     icon = "type"
 
     def build_config(self):

src/backend/base/langflow/components/memories/ZepMessageReader.py

@@ -0,0 +1,137 @@
+from typing import Optional, cast
+
+from langchain_community.chat_message_histories.zep import SearchScope, SearchType, ZepChatMessageHistory
+
+from langflow.base.memory.memory import BaseMemoryComponent
+from langflow.field_typing import Text
+from langflow.schema.schema import Record
+
+
+class ZepMessageReaderComponent(BaseMemoryComponent):
+    display_name = "Zep Message Reader"
+    description = "Retrieves stored chat messages from Zep."
+
+    def build_config(self):
+        return {
+            "session_id": {
+                "display_name": "Session ID",
+                "info": "Session ID of the chat history.",
+                "input_types": ["Text"],
+            },
+            "url": {
+                "display_name": "Zep URL",
+                "info": "URL of the Zep instance.",
+                "input_types": ["Text"],
+            },
+            "api_key": {
+                "display_name": "Zep API Key",
+                "info": "API Key for the Zep instance.",
+                "password": True,
+            },
+            "query": {
+                "display_name": "Query",
+                "info": "Query to search for in the chat history.",
+            },
+            "metadata": {
+                "display_name": "Metadata",
+                "info": "Optional metadata to attach to the message.",
+                "advanced": True,
+            },
+            "search_scope": {
+                "options": ["Messages", "Summary"],
+                "display_name": "Search Scope",
+                "info": "Scope of the search.",
+                "advanced": True,
+            },
+            "search_type": {
+                "options": ["Similarity", "MMR"],
+                "display_name": "Search Type",
+                "info": "Type of search.",
+                "advanced": True,
+            },
+            "limit": {
+                "display_name": "Limit",
+                "info": "Limit of search results.",
+                "advanced": True,
+            },
+        }
+
+    def get_messages(self, **kwargs) -> list[Record]:
+        """
+        Retrieves messages from the ZepChatMessageHistory memory.
+
+        If a query is provided, the search method is used to search for messages in the memory, otherwise all messages are returned.
+
+        Args:
+            memory (ZepChatMessageHistory): The ZepChatMessageHistory instance to retrieve messages from.
+            query (str, optional): The query string to search for messages. Defaults to None.
+            metadata (dict, optional): Additional metadata to filter the search results. Defaults to None.
+            search_scope (str, optional): The scope of the search. Can be 'messages' or 'summary'. Defaults to 'messages'.
+            search_type (str, optional): The type of search. Can be 'similarity' or 'exact'. Defaults to 'similarity'.
+            limit (int, optional): The maximum number of search results to return. Defaults to None.
+
+        Returns:
+            list[Record]: A list of Record objects representing the search results.
+        """
+        memory: ZepChatMessageHistory = cast(ZepChatMessageHistory, kwargs.get("memory"))
+        if not memory:
+            raise ValueError("ZepChatMessageHistory instance is required.")
+        query = kwargs.get("query")
+        search_scope = kwargs.get("search_scope", SearchScope.messages).lower()
+        search_type = kwargs.get("search_type", SearchType.similarity).lower()
+        limit = kwargs.get("limit")
+
+        if query:
+            memory_search_results = memory.search(
+                query,
+                search_scope=search_scope,
+                search_type=search_type,
+                limit=limit,
+            )
+            # Get the messages from the search results if the search scope is messages
+            result_dicts = []
+            for result in memory_search_results:
+                result_dict = {}
+                if search_scope == SearchScope.messages:
+                    result_dict["text"] = result.message
+                else:
+                    result_dict["text"] = result.summary
+                result_dict["metadata"] = result.metadata
+                result_dict["score"] = result.score
+                result_dicts.append(result_dict)
+            results = [Record(data=result_dict) for result_dict in result_dicts]
+        else:
+            messages = memory.messages
+            results = [Record.from_lc_message(message) for message in messages]
+        return results
+
+    def build(
+        self,
+        session_id: Text,
+        url: Optional[Text] = None,
+        api_key: Optional[Text] = None,
+        query: Optional[Text] = None,
+        search_scope: SearchScope = SearchScope.messages,
+        search_type: SearchType = SearchType.similarity,
+        limit: Optional[int] = None,
+    ) -> list[Record]:
+        try:
+            from zep_python import ZepClient
+            from zep_python.langchain import ZepChatMessageHistory
+        except ImportError:
+            raise ImportError(
+                "Could not import zep-python package. " "Please install it with `pip install zep-python`."
+            )
+        if url == "":
+            url = None
+        zep_client = ZepClient(api_url=url, api_key=api_key)
+        memory = ZepChatMessageHistory(session_id=session_id, zep_client=zep_client)
+        records = self.get_messages(
+            memory=memory,
+            query=query,
+            search_scope=search_scope,
+            search_type=search_type,
+            limit=limit,
+        )
+        self.status = records
+        return records

src/backend/base/langflow/components/memories/ZepMessageWriter.py

@@ -0,0 +1,96 @@
+from typing import Optional, TYPE_CHECKING
+
+
+from langflow.base.memory.memory import BaseMemoryComponent
+from langflow.field_typing import Text
+from langflow.schema.schema import Record
+
+if TYPE_CHECKING:
+    from zep_python.langchain import ZepChatMessageHistory
+
+
+class ZepMessageWriterComponent(BaseMemoryComponent):
+    display_name = "Zep Message Writer"
+    description = "Writes a message to Zep."
+
+    def build_config(self):
+        return {
+            "session_id": {
+                "display_name": "Session ID",
+                "info": "Session ID of the chat history.",
+                "input_types": ["Text"],
+            },
+            "url": {
+                "display_name": "Zep URL",
+                "info": "URL of the Zep instance.",
+                "input_types": ["Text"],
+            },
+            "api_key": {
+                "display_name": "Zep API Key",
+                "info": "API Key for the Zep instance.",
+                "password": True,
+            },
+            "limit": {
+                "display_name": "Limit",
+                "info": "Limit of search results.",
+                "advanced": True,
+            },
+            "input_value": {
+                "display_name": "Input Record",
+                "info": "Record to write to Zep.",
+            },
+        }
+
+    def add_message(
+        self, sender: Text, sender_name: Text, text: Text, session_id: Text, metadata: dict | None = None, **kwargs
+    ):
+        """
+        Adds a message to the ZepChatMessageHistory memory.
+
+        Args:
+            sender (Text): The type of the message sender. Valid values are "Machine" or "User".
+            sender_name (Text): The name of the message sender.
+            text (Text): The content of the message.
+            session_id (Text): The session ID associated with the message.
+            metadata (dict | None, optional): Additional metadata for the message. Defaults to None.
+            **kwargs: Additional keyword arguments.
+
+        Raises:
+            ValueError: If the ZepChatMessageHistory instance is not provided.
+
+        """
+        memory: ZepChatMessageHistory | None = kwargs.pop("memory", None)
+        if memory is None:
+            raise ValueError("ZepChatMessageHistory instance is required.")
+        if metadata is None:
+            metadata = {}
+        metadata["sender_name"] = sender_name
+        metadata.update(kwargs)
+        if sender == "Machine":
+            memory.add_ai_message(text, metadata=metadata)
+        elif sender == "User":
+            memory.add_user_message(text, metadata=metadata)
+        else:
+            raise ValueError(f"Invalid sender type: {sender}")
+
+    def build(
+        self,
+        input_value: Record,
+        session_id: Text,
+        url: Optional[Text] = None,
+        api_key: Optional[Text] = None,
+    ) -> Record:
+        try:
+            from zep_python import ZepClient
+            from zep_python.langchain import ZepChatMessageHistory
+        except ImportError:
+            raise ImportError(
+                "Could not import zep-python package. " "Please install it with `pip install zep-python`."
+            )
+        if url == "":
+            url = None
+        zep_client = ZepClient(api_url=url, api_key=api_key)
+        memory = ZepChatMessageHistory(session_id=session_id, zep_client=zep_client)
+        self.add_message(**input_value.data, memory=memory)
+        self.status = f"Added message to Zep memory for session {session_id}"
+        return input_value

src/backend/base/langflow/components/outputs/CSVOutput.py

@@ -0,0 +1,17 @@
+from typing import Optional
+
+from langflow.base.io.text import TextComponent
+from langflow.field_typing import Text, Data
+
+
+class CSVOutput(TextComponent):
+    display_name = "CSV Output"
+    description = "Used view csv files"
+
+    field_config = {
+        "input_value": {"display_name": "csv","info":"A csv blob","input_types":["Data"]},
+        "separator": {"display_name": "separator","info":"The separator used in the csv file","input_types":["Text"], "field_type":"Text","default_value":";","options":[";", ",", "|"]},
+    }
+
+    def build(self, input_value: Data, separator) -> Data:
+        return {"data": input_value, "separator": separator}

src/backend/base/langflow/components/outputs/ChatOutput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatOutput(ChatComponent):
     display_name = "Chat Output"
-    description = "Display a chat message in the Interaction Panel."
+    description = "Display a chat message in the Playground."
     icon = "ChatOutput"
 
     def build(

src/backend/base/langflow/components/outputs/ImageOutput.py

@@ -0,0 +1,15 @@
+from typing import Optional
+
+from langflow.base.io.text import TextComponent
+from langflow.field_typing import Text
+
+class ImageOutput(TextComponent):
+    display_name = "Image Output"
+    description = "Used view image files"
+
+    field_config = {
+        "input_value": {"display_name": "image","info":"A image url","input_types":["Text"]},
+    }
+
+    def build(self, input_value: Text) -> Text:
+        return input_value

src/backend/base/langflow/components/outputs/JsonOutput.py

@@ -0,0 +1,17 @@
+from langflow.base.io.text import TextComponent
+from langflow.field_typing.constants import Data, NestedDict
+
+class JsonOutput(TextComponent):
+    display_name = "JSON Output"  
+    description = "JSON Output."
+
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "JSON",
+                "field_type": "NestedDict"
+            }
+        }
+
+    def build(self, input_value: NestedDict) -> NestedDict:
+        return input_value

src/backend/base/langflow/components/outputs/KeyPairOutput.py

@@ -0,0 +1,19 @@
+from langflow.base.io.text import TextComponent
+from langflow.field_typing.constants import Data
+
+
+class KeyPairOutput(TextComponent):
+    display_name = "Dictionary Output"  
+    description = "Dictionary Output."
+
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "Dictionaries",
+                "field_type": "dict",
+                "list": True
+            }
+        }
+
+    def build(self, input_value: dict) -> dict:
+        return input_value

src/backend/base/langflow/components/outputs/PDFOutput.py

@@ -0,0 +1,16 @@
+from typing import Optional
+
+from langflow.base.io.text import TextComponent
+from langflow.field_typing import Text
+
+
+class PDFOutput(TextComponent):
+    display_name = "PDF Output"
+    description = "Used view pdf files"
+
+    field_config = {
+        "input_value": {"display_name": "pdf","info":"A pdf url","input_types":["Text"]},
+    }
+
+    def build(self, input_value: Text) -> Text:
+        return input_value

src/backend/base/langflow/components/outputs/StringListOutput.py

@@ -0,0 +1,13 @@
+# from langflow.field_typing import Data
+from langflow.schema import Record
+from langflow.interface.custom.custom_component import CustomComponent
+
+
+class StringListOutput(CustomComponent):
+    display_name = "String List Output"
+
+    def build_config(self):
+        return {"input_value": {"display_name": "String List Output", "field_type": "str", "list": True}}
+
+    def build(self, input_value: list) -> Record:
+        return Record(data=input_value)

src/backend/base/langflow/components/outputs/TextOutput.py

@@ -6,7 +6,7 @@ from langflow.field_typing import Text
 
 class TextOutput(TextComponent):
     display_name = "Text Output"
-    description = "Display a text output in the Interaction Panel."
+    description = "Display a text output in the Playground."
     icon = "type"
 
     def build_config(self):

src/backend/base/langflow/components/vectorsearch/WeaviateSearch.py

@@ -61,10 +61,10 @@ class WeaviateSearchVectorStore(WeaviateVectorStoreComponent, LCVectorStoreCompo
         input_value: Text,
         search_type: str,
         url: str,
+        index_name: str,
         number_of_results: int = 4,
         search_by_text: bool = False,
         api_key: Optional[str] = None,
-        index_name: Optional[str] = None,
         text_key: str = "text",
         embedding: Optional[Embeddings] = None,
         attributes: Optional[list] = None,

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

@@ -4,6 +4,7 @@ import weaviate  # type: ignore
 from langchain.embeddings.base import Embeddings
 from langchain.schema import BaseRetriever
 from langchain_community.vectorstores import VectorStore, Weaviate
+from langchain_core.documents import Document
 
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema.schema import Record
@@ -50,9 +51,9 @@ class WeaviateVectorStoreComponent(CustomComponent):
     def build(
         self,
         url: str,
+        index_name: str,
         search_by_text: bool = False,
         api_key: Optional[str] = None,
-        index_name: Optional[str] = None,
         text_key: str = "text",
         embedding: Optional[Embeddings] = None,
         inputs: Optional[Record] = None,
@@ -78,11 +79,13 @@ class WeaviateVectorStoreComponent(CustomComponent):
             return pascal_case_word
 
         index_name = _to_pascal_case(index_name) if index_name else None
-        documents = []
+        if not index_name:
+            raise ValueError("Index name is required")
+        documents: list[Document] = []
         for _input in inputs or []:
             if isinstance(_input, Record):
                 documents.append(_input.to_lc_document())
-            else:
+            elif isinstance(_input, Document):
                 documents.append(_input)
 
         if documents and embedding is not None:

src/backend/base/langflow/config.yaml

@@ -232,3 +232,4 @@ output_parsers:
 custom_components:
   CustomComponent:
     documentation: "https://docs.langflow.org/guidelines/custom-component"
+    # documentation: "https://docs.langflow.org/administration/custom-component"

src/backend/base/langflow/graph/graph/base.py

@@ -3,7 +3,7 @@ import uuid
 from collections import defaultdict, deque
 from functools import partial
 from itertools import chain
-from typing import TYPE_CHECKING, Callable, Coroutine, Dict, Generator, List, Optional, Type, Union
+from typing import TYPE_CHECKING, Callable, Coroutine, Dict, Generator, List, Optional, Tuple, Type, Union
 
 from loguru import logger
 
@@ -14,7 +14,7 @@ from langflow.graph.graph.state_manager import GraphStateManager
 from langflow.graph.graph.utils import process_flow
 from langflow.graph.schema import InterfaceComponentTypes, RunOutputs
 from langflow.graph.vertex.base import Vertex
-from langflow.graph.vertex.types import ChatVertex, FileToolVertex, LLMVertex, RoutingVertex, StateVertex, ToolkitVertex
+from langflow.graph.vertex.types import ChatVertex, FileToolVertex, LLMVertex, StateVertex, ToolkitVertex
 from langflow.interface.tools.constants import FILE_TOOLS
 from langflow.schema import Record
 from langflow.schema.schema import INPUT_FIELD_NAME, InputType
@@ -75,7 +75,7 @@ class Graph:
         self.vertices: List[Vertex] = []
         self.run_manager = RunnableVerticesManager()
         self._build_graph()
-        self.build_graph_maps()
+        self.build_graph_maps(self.edges)
         self.define_vertices_lists()
         self.state_manager = GraphStateManager()
 
@@ -130,6 +130,18 @@ class Graph:
             ):
                 vertices_ids.append(vertex_id)
                 successors = self.get_all_successors(vertex, flat=True)
+                # Update run_manager.run_predecessors because we are activating vertices
+                # The run_prdecessors is the predecessor map of the vertices
+                # we remove the vertex_id from the predecessor map whenever we run a vertex
+                # So we need to get all edges of the vertex and successors
+                # and run self.build_adjacency_maps(edges) to get the new predecessor map
+                # that is not complete but we can use to update the run_predecessors
+                edges_set = set()
+                for vertex in [vertex] + successors:
+                    edges_set.update(vertex.edges)
+                edges = list(edges_set)
+                new_predecessor_map, _ = self.build_adjacency_maps(edges)
+                self.run_manager.run_predecessors.update(new_predecessor_map)
                 self.vertices_to_run.update(list(map(lambda x: x.id, successors)))
         self.activated_vertices = vertices_ids
         self.vertices_to_run.update(vertices_ids)
@@ -401,14 +413,20 @@ class Graph:
             "inactivated_vertices": self.inactivated_vertices,
         }
 
-    def build_graph_maps(self):
+    def build_graph_maps(self, edges: Optional[List[ContractEdge]] = None, vertices: Optional[List[Vertex]] = None):
         """
         Builds the adjacency maps for the graph.
         """
-        self.predecessor_map, self.successor_map = self.build_adjacency_maps()
+        if edges is None:
+            edges = self.edges
 
-        self.in_degree_map = self.build_in_degree()
-        self.parent_child_map = self.build_parent_child_map()
+        if vertices is None:
+            vertices = self.vertices
+
+        self.predecessor_map, self.successor_map = self.build_adjacency_maps(edges)
+
+        self.in_degree_map = self.build_in_degree(edges)
+        self.parent_child_map = self.build_parent_child_map(vertices)
 
     def reset_inactivated_vertices(self):
         """
@@ -433,9 +451,9 @@ class Graph:
         for child_id in self.parent_child_map[vertex_id]:
             self.mark_branch(child_id, state)
 
-    def build_parent_child_map(self):
+    def build_parent_child_map(self, vertices: List[Vertex]):
         parent_child_map = defaultdict(list)
-        for vertex in self.vertices:
+        for vertex in vertices:
             parent_child_map[vertex.id] = [child.id for child in self.get_successors(vertex)]
         return parent_child_map
 
@@ -559,6 +577,7 @@ class Graph:
                 self.update_vertex_from_another(self_vertex, other_vertex)
 
         self.build_graph_maps()
+        self.define_vertices_lists()
         self.increment_update_count()
         return self
 
@@ -944,8 +963,6 @@ class Graph:
         node_name = node_id.split("-")[0]
         if node_name in ["ChatOutput", "ChatInput"]:
             return ChatVertex
-        elif node_name in ["ShouldRunNext"]:
-            return RoutingVertex
         elif node_name in ["SharedState", "Notify", "Listen"]:
             return StateVertex
         elif node_base_type in lazy_load_vertex_dict.VERTEX_TYPE_MAP:
@@ -1277,17 +1294,17 @@ class Graph:
     def remove_from_predecessors(self, vertex_id: str):
         self.run_manager.remove_from_predecessors(vertex_id)
 
-    def build_in_degree(self):
-        in_degree = defaultdict(int)
-        for edge in self.edges:
+    def build_in_degree(self, edges: List[ContractEdge]) -> Dict[str, int]:
+        in_degree: Dict[str, int] = defaultdict(int)
+        for edge in edges:
             in_degree[edge.target_id] += 1
         return in_degree
 
-    def build_adjacency_maps(self):
+    def build_adjacency_maps(self, edges: List[ContractEdge]) -> Tuple[Dict[str, List[str]], Dict[str, List[str]]]:
         """Returns the adjacency maps for the graph."""
         predecessor_map = defaultdict(list)
         successor_map = defaultdict(list)
-        for edge in self.edges:
+        for edge in edges:
             predecessor_map[edge.target_id].append(edge.source_id)
             successor_map[edge.source_id].append(edge.target_id)
         return predecessor_map, successor_map

src/backend/base/langflow/graph/graph/constants.py

@@ -15,7 +15,6 @@ from langflow.interface.wrappers.base import wrapper_creator
 from langflow.utils.lazy_load import LazyLoadDictBase
 
 CHAT_COMPONENTS = ["ChatInput", "ChatOutput", "TextInput", "SessionID"]
-ROUTING_COMPONENTS = ["ShouldRunNext"]
 
 
 class VertexTypesDict(LazyLoadDictBase):
@@ -51,7 +50,6 @@ class VertexTypesDict(LazyLoadDictBase):
             **{t: types.CustomComponentVertex for t in custom_component_creator.to_list()},
             **{t: types.RetrieverVertex for t in retriever_creator.to_list()},
             **{t: types.ChatVertex for t in CHAT_COMPONENTS},
-            **{t: types.RoutingVertex for t in ROUTING_COMPONENTS},
         }
 
     def get_custom_component_vertex_type(self):

src/backend/base/langflow/graph/graph/runnable_vertices_manager.py

@@ -15,6 +15,7 @@ class RunnableVerticesManager:
 
     def is_vertex_runnable(self, vertex_id: str) -> bool:
         """Determines if a vertex is runnable."""
+
         return vertex_id in self.vertices_to_run and not self.run_predecessors.get(vertex_id)
 
     def find_runnable_predecessors_for_successors(self, vertex_id: str) -> List[str]:

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

@@ -72,7 +72,6 @@ class Vertex:
         self.load_from_db_fields: List[str] = []
         self.parent_is_top_level = False
         self.layer = None
-        self.should_run = True
         self.result: Optional[ResultData] = None
         try:
             self.is_interface_component = self.vertex_type in InterfaceComponentTypes

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

@@ -1,6 +1,7 @@
 import ast
 import json
 from typing import AsyncIterator, Callable, Dict, Iterator, List, Optional, Union
+
 import yaml
 from langchain_core.messages import AIMessage
 from loguru import logger
@@ -438,41 +439,6 @@ class ChatVertex(Vertex):
         return self.vertex_type == InterfaceComponentTypes.ChatInput and self.is_input
 
 
-class RoutingVertex(Vertex):
-    def __init__(self, data: Dict, graph):
-        super().__init__(data, graph=graph, base_type="custom_components")
-        self.use_result = True
-        self.steps = [self._build]
-
-    def _built_object_repr(self):
-        if self.artifacts and "repr" in self.artifacts:
-            return self.artifacts["repr"] or super()._built_object_repr()
-        return super()._built_object_repr()
-
-    @property
-    def successors_ids(self):
-        if isinstance(self._built_object, bool):
-            ids = super().successors_ids
-            if self._built_object:
-                return ids
-            return []
-        raise ValueError("RoutingVertex should return a boolean value.")
-
-    def _run(self, *args, **kwargs):
-        if self._built_object:
-            condition = self._built_object.get("condition")
-            result = self._built_object.get("result")
-            if condition is None:
-                raise ValueError("Condition is required for the routing vertex.")
-            if result is None:
-                raise ValueError("Result is required for the routing vertex.")
-            if condition is True:
-                self._built_result = result
-            else:
-                self.graph.mark_branch(self.id, "INACTIVE")
-                self._built_result = None
-
-
 class StateVertex(Vertex):
     def __init__(self, data: Dict, graph):
         super().__init__(data, graph=graph, base_type="custom_components")

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json

@@ -421,7 +421,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -565,7 +565,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "Record",
@@ -621,7 +621,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Interaction Panel.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Playground.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -742,7 +742,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get chat inputs from the Interaction Panel.",
+            "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
             "base_classes": [
               "object",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json

@@ -278,7 +278,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -422,7 +422,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "Text",
@@ -836,7 +836,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n    display_name = \"Text Input\"\n    description = \"Get text inputs from the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as input.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Optional[str] = \"\",\n        record_template: Optional[str] = \"\",\n    ) -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n    display_name = \"Text Input\"\n    description = \"Get text inputs from the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as input.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Optional[str] = \"\",\n        record_template: Optional[str] = \"\",\n    ) -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -894,7 +894,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get text inputs from the Interaction Panel.",
+            "description": "Get text inputs from the Playground.",
             "icon": "type",
             "base_classes": [
               "object",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json

@@ -277,7 +277,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Interaction Panel.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Playground.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -398,7 +398,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get chat inputs from the Interaction Panel.",
+            "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
             "base_classes": [
               "str",
@@ -453,7 +453,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -575,7 +575,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "str",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json

@@ -22,7 +22,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Interaction Panel.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Playground.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -144,7 +144,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get chat inputs from the Interaction Panel.",
+            "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
             "base_classes": [
               "Text",
@@ -199,7 +199,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -322,7 +322,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "Text",
@@ -377,7 +377,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.field_typing import Text\nfrom langflow.helpers.record import records_to_text\nfrom langflow.interface.custom.custom_component import CustomComponent\nfrom langflow.memory import get_messages\n\n\nclass MemoryComponent(CustomComponent):\n    display_name = \"Chat Memory\"\n    description = \"Retrieves stored chat messages given a specific Session ID.\"\n    beta: bool = True\n    icon = \"history\"\n\n    def build_config(self):\n        return {\n            \"sender\": {\n                \"options\": [\"Machine\", \"User\", \"Machine and User\"],\n                \"display_name\": \"Sender Type\",\n            },\n            \"sender_name\": {\"display_name\": \"Sender Name\", \"advanced\": True},\n            \"n_messages\": {\n                \"display_name\": \"Number of Messages\",\n                \"info\": \"Number of messages to retrieve.\",\n            },\n            \"session_id\": {\n                \"display_name\": \"Session ID\",\n                \"info\": \"Session ID of the chat history.\",\n                \"input_types\": [\"Text\"],\n            },\n            \"order\": {\n                \"options\": [\"Ascending\", \"Descending\"],\n                \"display_name\": \"Order\",\n                \"info\": \"Order of the messages.\",\n                \"advanced\": True,\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine and User\",\n        sender_name: Optional[str] = None,\n        session_id: Optional[str] = None,\n        n_messages: int = 5,\n        order: Optional[str] = \"Descending\",\n        record_template: Optional[str] = \"{sender_name}: {text}\",\n    ) -> Text:\n        order = \"DESC\" if order == \"Descending\" else \"ASC\"\n        if sender == \"Machine and User\":\n            sender = None\n        messages = get_messages(\n            sender=sender,\n            sender_name=sender_name,\n            session_id=session_id,\n            limit=n_messages,\n            order=order,\n        )\n        messages_str = records_to_text(template=record_template or \"\", records=messages)\n        self.status = messages_str\n        return messages_str\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.memory.memory import BaseMemoryComponent\nfrom langflow.field_typing import Text\nfrom langflow.helpers.record import records_to_text\nfrom langflow.memory import get_messages\nfrom langflow.schema.schema import Record\n\n\nclass MemoryComponent(BaseMemoryComponent):\n    display_name = \"Chat Memory\"\n    description = \"Retrieves stored chat messages given a specific Session ID.\"\n    beta: bool = True\n    icon = \"history\"\n\n    def build_config(self):\n        return {\n            \"sender\": {\n                \"options\": [\"Machine\", \"User\", \"Machine and User\"],\n                \"display_name\": \"Sender Type\",\n            },\n            \"sender_name\": {\"display_name\": \"Sender Name\", \"advanced\": True},\n            \"n_messages\": {\n                \"display_name\": \"Number of Messages\",\n                \"info\": \"Number of messages to retrieve.\",\n            },\n            \"session_id\": {\n                \"display_name\": \"Session ID\",\n                \"info\": \"Session ID of the chat history.\",\n                \"input_types\": [\"Text\"],\n            },\n            \"order\": {\n                \"options\": [\"Ascending\", \"Descending\"],\n                \"display_name\": \"Order\",\n                \"info\": \"Order of the messages.\",\n                \"advanced\": True,\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def get_messages(self, **kwargs) -> list[Record]:\n        # Validate kwargs by checking if it contains the correct keys\n        if \"sender\" not in kwargs:\n            kwargs[\"sender\"] = None\n        if \"sender_name\" not in kwargs:\n            kwargs[\"sender_name\"] = None\n        if \"session_id\" not in kwargs:\n            kwargs[\"session_id\"] = None\n        if \"limit\" not in kwargs:\n            kwargs[\"limit\"] = 5\n        if \"order\" not in kwargs:\n            kwargs[\"order\"] = \"Descending\"\n\n        kwargs[\"order\"] = \"DESC\" if kwargs[\"order\"] == \"Descending\" else \"ASC\"\n        if kwargs[\"sender\"] == \"Machine and User\":\n            kwargs[\"sender\"] = None\n        return get_messages(**kwargs)\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine and User\",\n        sender_name: Optional[str] = None,\n        session_id: Optional[str] = None,\n        n_messages: int = 5,\n        order: Optional[str] = \"Descending\",\n        record_template: Optional[str] = \"{sender_name}: {text}\",\n    ) -> Text:\n        messages = self.get_messages(\n            sender=sender,\n            sender_name=sender_name,\n            session_id=session_id,\n            limit=n_messages,\n            order=order,\n        )\n        messages_str = records_to_text(template=record_template or \"\", records=messages)\n        self.status = messages_str\n        return messages_str\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1032,7 +1032,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1067,7 +1067,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a text output in the Interaction Panel.",
+            "description": "Display a text output in the Playground.",
             "icon": "type",
             "base_classes": [
               "str",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json

@@ -256,7 +256,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -400,7 +400,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "object",
@@ -452,7 +452,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -596,7 +596,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "object",
@@ -647,7 +647,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n    display_name = \"Text Input\"\n    description = \"Get text inputs from the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as input.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Optional[Text] = \"\",\n        record_template: Optional[str] = \"\",\n    ) -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n    display_name = \"Text Input\"\n    description = \"Get text inputs from the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as input.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Optional[Text] = \"\",\n        record_template: Optional[str] = \"\",\n    ) -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -705,7 +705,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get text inputs from the Interaction Panel.",
+            "description": "Get text inputs from the Playground.",
             "icon": "type",
             "base_classes": [
               "str",
@@ -778,7 +778,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -813,7 +813,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a text output in the Interaction Panel.",
+            "description": "Display a text output in the Playground.",
             "icon": "type",
             "base_classes": [
               "str",
@@ -1165,7 +1165,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1200,7 +1200,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a text output in the Interaction Panel.",
+            "description": "Display a text output in the Playground.",
             "icon": "type",
             "base_classes": [
               "str",

src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json

@@ -20,7 +20,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Interaction Panel.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Playground.\"\n    icon = \"ChatInput\"\n\n    def build_config(self):\n        build_config = super().build_config()\n        build_config[\"input_value\"] = {\n            \"input_types\": [],\n            \"display_name\": \"Message\",\n            \"multiline\": True,\n        }\n\n        return build_config\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build_no_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -141,7 +141,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Get chat inputs from the Interaction Panel.",
+            "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
             "base_classes": [
               "Text",
@@ -214,7 +214,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Interaction Panel.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
+                "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n    display_name = \"Text Output\"\n    description = \"Display a text output in the Playground.\"\n    icon = \"type\"\n\n    def build_config(self):\n        return {\n            \"input_value\": {\n                \"display_name\": \"Value\",\n                \"input_types\": [\"Record\", \"Text\"],\n                \"info\": \"Text or Record to be passed as output.\",\n            },\n            \"record_template\": {\n                \"display_name\": \"Record Template\",\n                \"multiline\": True,\n                \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n        return super().build(input_value=input_value, record_template=record_template)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -249,7 +249,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a text output in the Interaction Panel.",
+            "description": "Display a text output in the Playground.",
             "icon": "type",
             "base_classes": [
               "object",
@@ -1256,7 +1256,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Interaction Panel.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n        record_template: Optional[str] = \"{text}\",\n    ) -> Union[Text, Record]:\n        return super().build_with_record(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n            record_template=record_template or \"\",\n        )\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1400,7 +1400,7 @@
               },
               "_type": "CustomComponent"
             },
-            "description": "Display a chat message in the Interaction Panel.",
+            "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
             "base_classes": [
               "object",

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

@@ -87,6 +87,14 @@ class CustomComponent(Component):
         except Exception as e:
             raise ValueError(f"Error updating state: {e}")
 
+    def stop(self):
+        if not self.vertex:
+            raise ValueError("Vertex is not set")
+        try:
+            self.graph.mark_branch(self.vertex.id, "INACTIVE")
+        except Exception as e:
+            raise ValueError(f"Error stopping {self.display_name}: {e}")
+
     def append_state(self, name: str, value: Any):
         if not self.vertex:
             raise ValueError("Vertex is not set")

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

@@ -227,34 +227,11 @@ def initialize_qdrant(class_object: Type[Qdrant], params: dict):
     return class_object.from_documents(**params)
 
 
-def initialize_elasticsearch(class_object: Type[ElasticsearchStore], params: dict):
-    """Initialize elastic and return the class object"""
-    if "index_name" not in params:
-        raise ValueError("Elasticsearch Index must be provided in the params")
-    if "es_url" not in params:
-        raise ValueError("Elasticsearch URL must be provided in the params")
-    if not docs_in_params(params):
-        existing_index_params = {
-            "embedding": params.pop("embedding"),
-        }
-        if "index_name" in params:
-            existing_index_params["index_name"] = params.pop("index_name")
-        if "es_url" in params:
-            existing_index_params["es_url"] = params.pop("es_url")
-
-        return class_object.from_existing_index(**existing_index_params)
-    # If there are docs in the params, create a new index
-    if "texts" in params:
-        params["documents"] = params.pop("texts")
-    return class_object.from_documents(**params)
-
-
 vecstore_initializer: Dict[str, Callable[[Type[Any], dict], Any]] = {
     "Pinecone": initialize_pinecone,
     "Chroma": initialize_chroma,
     "Qdrant": initialize_qdrant,
     "Weaviate": initialize_weaviate,
-    "ElasticsearchStore": initialize_elasticsearch,
     "FAISS": initialize_faiss,
     "SupabaseVectorStore": initialize_supabase,
     "MongoDBAtlasVectorSearch": initialize_mongodb,

src/backend/base/langflow/main.py

@@ -53,6 +53,7 @@ def get_lifespan(fix_migration=False, socketio_server=None):
         except Exception as exc:
             if "langflow migration --fix" not in str(exc):
                 logger.error(exc)
+            raise
         # Shutdown message
         rprint("[bold red]Shutting down Langflow...[/bold red]")
         teardown_services()

src/backend/base/langflow/memory.py

@@ -1,3 +1,4 @@
+import warnings
 from typing import Optional, Union
 
 from loguru import logger
@@ -51,6 +52,7 @@ def get_messages(
                 "sender": row.sender,
                 "sender_name": row.sender_name,
                 "session_id": row.session_id,
+                "timestamp": row.timestamp,
             },
         )
         records.append(record)
@@ -98,3 +100,39 @@ def delete_messages(session_id: str):
     """
     monitor_service = get_monitor_service()
     monitor_service.delete_messages(session_id)
+
+
+def store_message(
+    message: Union[str, Record],
+    session_id: Optional[str] = None,
+    sender: Optional[str] = None,
+    sender_name: Optional[str] = None,
+) -> list[Record]:
+
+    if not message:
+        warnings.warn("No message provided.")
+        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.")
+
+    if isinstance(message, Record):
+        record = message
+        record.data.update(
+            {
+                "session_id": session_id,
+                "sender": sender,
+                "sender_name": sender_name,
+            }
+        )
+    elif isinstance(message, str):
+        record = Record(
+            data={
+                "text": message,
+                "session_id": session_id,
+                "sender": sender,
+                "sender_name": sender_name,
+            },
+        )
+
+    return add_messages([record])

src/backend/base/langflow/processing/load.py

@@ -3,6 +3,8 @@ from pathlib import Path
 from typing import List, Optional, Union
 
 from dotenv import load_dotenv
+from loguru import logger
+
 from langflow.graph import Graph
 from langflow.graph.schema import RunOutputs
 from langflow.processing.process import process_tweaks, run_graph
@@ -101,6 +103,12 @@ def run_flow_from_json(
         List[RunOutputs]: A list of RunOutputs objects representing the results of running the flow.
     """
     # Set all streaming to false
+    try:
+        import nest_asyncio  # type: ignore
+
+        nest_asyncio.apply()
+    except Exception as e:
+        logger.warning(f"Could not apply nest_asyncio: {e}")
     if tweaks is None:
         tweaks = {}
     tweaks["stream"] = False

src/backend/base/langflow/processing/process.py

@@ -1,5 +1,6 @@
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
 
+
 from langchain.agents import AgentExecutor
 from langchain.schema import AgentAction
 from loguru import logger
@@ -13,6 +14,7 @@ from langflow.schema.graph import InputValue, Tweaks
 from langflow.schema.schema import INPUT_FIELD_NAME
 from langflow.services.session.service import SessionService
 
+
 if TYPE_CHECKING:
     from langflow.api.v1.schemas import InputValueRequest
 
@@ -269,16 +271,19 @@ def process_tweaks(
     :return: The modified graph_data dictionary.
     :raises ValueError: If the input is not in the expected format.
     """
+    tweaks_dict = {}
     if not isinstance(tweaks, dict):
-        tweaks = tweaks.model_dump()
-    if "stream" not in tweaks:
-        tweaks["stream"] = stream
-    nodes = validate_input(graph_data, tweaks)
+        tweaks_dict = tweaks.model_dump()
+    else:
+        tweaks_dict = tweaks
+    if "stream" not in tweaks_dict:
+        tweaks_dict["stream"] = stream
+    nodes = validate_input(graph_data, tweaks_dict)
     nodes_map = {node.get("id"): node for node in nodes}
     nodes_display_name_map = {node.get("data", {}).get("node", {}).get("display_name"): node for node in nodes}
 
     all_nodes_tweaks = {}
-    for key, value in tweaks.items():
+    for key, value in tweaks_dict.items():
         if isinstance(value, dict):
             if node := nodes_map.get(key):
                 apply_tweaks(node, value)

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

@@ -1,7 +1,8 @@
-from typing import List, Optional, Union
+from typing import Any, List, Optional, Union
+
+from pydantic import BaseModel, Field, RootModel
 
 from langflow.schema.schema import InputType
-from pydantic import BaseModel, Field, RootModel
 
 
 class InputValue(BaseModel):
@@ -14,7 +15,7 @@ class InputValue(BaseModel):
 
 
 class Tweaks(RootModel):
-    root: dict[str, Union[str, dict[str, str]]] = Field(
+    root: dict[str, Union[str, dict[str, Any]]] = Field(
         description="A dictionary of tweaks to adjust the flow's execution. Allows customizing flow behavior dynamically. All tweaks are overridden by the input values.",
     )
     model_config = {

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

@@ -1,8 +1,8 @@
 import copy
-from typing import Literal, Optional
+from typing import Literal, Optional, cast
 
 from langchain_core.documents import Document
-from langchain_core.messages import BaseMessage
+from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
 from pydantic import BaseModel, model_validator
 from langchain_core.messages import HumanMessage, AIMessage
 
@@ -67,8 +67,8 @@ class Record(BaseModel):
         Returns:
             Record: The converted Record.
         """
-        data = {"text": message.content}
-        data["metadata"] = message.to_json()
+        data: dict = {"text": message.content}
+        data["metadata"] = cast(dict, message.to_json())
         return cls(data=data, text_key="text")
 
     def __add__(self, other: "Record") -> "Record":

src/backend/base/langflow/services/database/models/api_key/model.py

@@ -22,7 +22,7 @@ class ApiKeyBase(SQLModel):
 
 class ApiKey(ApiKeyBase, table=True):
     id: UUID = Field(default_factory=uuid4, primary_key=True, unique=True)
-    created_at: datetime = Field(
+    created_at: Optional[datetime] = Field(
         default=None, sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=False)
     )
     api_key: str = Field(index=True, unique=True)

src/backend/base/langflow/services/database/models/variable/model.py

@@ -26,7 +26,7 @@ class Variable(VariableBase, table=True):
         description="Unique ID for the variable",
     )
     # name is unique per user
-    created_at: datetime = Field(
+    created_at: Optional[datetime] = Field(
         default=None,
         sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=True),
         description="Creation time of the variable",

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

@@ -170,9 +170,7 @@ class DatabaseService(Service):
         except util.exc.AutogenerateDiffsDetected as exc:
             logger.error(f"AutogenerateDiffsDetected: {exc}")
             if not fix:
-                raise RuntimeError(
-                    "Something went wrong running migrations. Please, run `langflow migration --fix`"
-                ) from exc
+                raise RuntimeError(f"There's a mismatch between the models and the database.\n{exc}")
 
         if fix:
             self.try_downgrade_upgrade_until_success(alembic_cfg)

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

@@ -101,10 +101,16 @@ def add_row_to_table(
         conn.execute(insert_sql, values)
     except Exception as e:
         # Log values types
+        column_error_message = ""
         for key, value in validated_dict.items():
             logger.error(f"{key}: {type(value)}")
+            if value in str(e):
+                column_error_message = f"Column: {key} Value: {value} Error: {e}"
 
-        logger.error(f"Error adding row to table: {e}")
+        if column_error_message:
+            logger.error(f"Error adding row to {table_name}: {column_error_message}")
+        else:
+            logger.error(f"Error adding row to {table_name}: {e}")
 
 
 async def log_message(

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

@@ -49,6 +49,27 @@ async def user_data_context(store_service: "StoreService", api_key: Optional[str
         user_data_var.set(None)
 
 
+def get_id_from_search_string(search_string: str) -> Optional[str]:
+    """
+    Extracts the ID from a search string.
+
+    Args:
+        search_string (str): The search string to extract the ID from.
+
+    Returns:
+        Optional[str]: The extracted ID, or None if no ID is found.
+    """
+    possible_id = search_string
+    if "www.langflow.store/store/" in search_string:
+        possible_id = search_string.split("/")[-1]
+
+    try:
+        possible_id = str(UUID(search_string))
+    except ValueError:
+        possible_id = None
+    return possible_id
+
+
 class StoreService(Service):
     """This is a service that integrates langflow with the store which
     is a Directus instance. It allows to search, get and post components to
@@ -183,7 +204,10 @@ class StoreService(Service):
     ):
         filter_conditions = []
 
-        if search is not None:
+        if component_id is None:
+            component_id = get_id_from_search_string(search) if search else None
+
+        if search is not None and component_id is None:
             search_conditions = self.build_search_filter_conditions(search)
             filter_conditions.append(search_conditions)
 

src/backend/base/poetry.lock

@@ -517,13 +517,13 @@ test-randomorder = ["pytest-randomly"]
 
 [[package]]
 name = "dataclasses-json"
-version = "0.6.4"
+version = "0.6.5"
 description = "Easily serialize dataclasses to and from JSON."
 optional = false
-python-versions = ">=3.7,<4.0"
+python-versions = "<4.0,>=3.7"
 files = [
-    {file = "dataclasses_json-0.6.4-py3-none-any.whl", hash = "sha256:f90578b8a3177f7552f4e1a6e535e84293cd5da421fcce0642d49c0d7bdf8df2"},
-    {file = "dataclasses_json-0.6.4.tar.gz", hash = "sha256:73696ebf24936560cca79a2430cbc4f3dd23ac7bf46ed17f38e5e5e7657a6377"},
+    {file = "dataclasses_json-0.6.5-py3-none-any.whl", hash = "sha256:f49c77aa3a85cac5bf5b7f65f4790ca0d2be8ef4d92c75e91ba0103072788a39"},
+    {file = "dataclasses_json-0.6.5.tar.gz", hash = "sha256:1c287594d9fcea72dc42d6d3836cf14848c2dc5ce88f65ed61b36b57f515fe26"},
 ]
 
 [package.dependencies]
@@ -624,13 +624,13 @@ gmpy2 = ["gmpy2"]
 
 [[package]]
 name = "emoji"
-version = "2.11.0"
+version = "2.11.1"
 description = "Emoji for Python"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
 files = [
-    {file = "emoji-2.11.0-py2.py3-none-any.whl", hash = "sha256:63fc9107f06c6c2e48e5078ce9575cef98518f5ac09474f6148a43e989989582"},
-    {file = "emoji-2.11.0.tar.gz", hash = "sha256:772eaa30f4e0b1ce95148a092df4c7dc97644532c03225326b0fd05e8a9f72a3"},
+    {file = "emoji-2.11.1-py2.py3-none-any.whl", hash = "sha256:b7ba25299bbf520cc8727848ae66b986da32aee27dc2887eaea2bff07226ce49"},
+    {file = "emoji-2.11.1.tar.gz", hash = "sha256:062ff0b3154b6219143f8b9f4b3e5c64c35bc2b146e6e2349ab5f29e218ce1ee"},
 ]
 
 [package.extras]
@@ -638,13 +638,13 @@ dev = ["coverage", "coveralls", "pytest"]
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.0"
+version = "1.2.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
-    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
+    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
+    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
 ]
 
 [package.extras]
@@ -652,13 +652,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.110.1"
+version = "0.110.3"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.110.1-py3-none-any.whl", hash = "sha256:5df913203c482f820d31f48e635e022f8cbfe7350e4830ef05a3163925b1addc"},
-    {file = "fastapi-0.110.1.tar.gz", hash = "sha256:6feac43ec359dfe4f45b2c18ec8c94edb8dc2dfc461d417d9e626590c071baad"},
+    {file = "fastapi-0.110.3-py3-none-any.whl", hash = "sha256:fd7600612f755e4050beb74001310b5a7e1796d149c2ee363124abdfa0289d32"},
+    {file = "fastapi-0.110.3.tar.gz", hash = "sha256:555700b0159379e94fdbfc6bb66a0f1c43f4cf7060f25239af3d84b63a656626"},
 ]
 
 [package.dependencies]
@@ -667,7 +667,7 @@ starlette = ">=0.37.2,<0.38.0"
 typing-extensions = ">=4.8.0"
 
 [package.extras]
-all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+all = ["email_validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 
 [[package]]
 name = "frozenlist"
@@ -1064,19 +1064,19 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
 
 [[package]]
 name = "langchain-community"
-version = "0.0.33"
+version = "0.0.35"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_community-0.0.33-py3-none-any.whl", hash = "sha256:830f0d5f4ff9638b99ca01820c26abfa4b65fa705ef89b5ce55ac9aa3a7d83af"},
-    {file = "langchain_community-0.0.33.tar.gz", hash = "sha256:bb56dbc1ef11ca09f258468e11368781adda9219e144073e30cda69496d342b2"},
+    {file = "langchain_community-0.0.35-py3-none-any.whl", hash = "sha256:296c47dcddf8c3c565f41240dc21421620f309ae24db762a5bdaf0c19cbb01ef"},
+    {file = "langchain_community-0.0.35.tar.gz", hash = "sha256:0f8726d9f8e1f369ae1b0c7ec738403063009a78ecb58860d21e5388e238ff0c"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.43,<0.2.0"
+langchain-core = ">=0.1.47,<0.2.0"
 langsmith = ">=0.1.0,<0.2.0"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
@@ -1086,17 +1086,17 @@ tenacity = ">=8.1.0,<9.0.0"
 
 [package.extras]
 cli = ["typer (>=0.9.0,<0.10.0)"]
-extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
+extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-search-documents (==11.4.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.6,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
 
 [[package]]
 name = "langchain-core"
-version = "0.1.44"
+version = "0.1.47"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.1.44-py3-none-any.whl", hash = "sha256:d8772dccef95fc97bfa2dcd19412e620ebe14def1f0e218374971f6e30a46a49"},
-    {file = "langchain_core-0.1.44.tar.gz", hash = "sha256:e313975d9ae2926342e6f2ad760338d31f18b1223e9b8b4dc408daeeade46a83"},
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-html-clean = ["lxml-html-clean"]
 html5 = ["html5lib"]
 htmlsoup = ["BeautifulSoup4"]
-source = ["Cython (>=3.0.10)"]
+source = ["Cython (>=0.29.7)"]
 
 [[package]]
 name = "mako"
@@ -1943,18 +1865,19 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.2.0"
-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
+type = ["mypy (>=1.8)"]
 
 [[package]]
 name = "pyasn1"
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 [[package]]
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+version = "2.7.1"
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 [package.dependencies]
 annotated-types = ">=0.4.0"
-pydantic-core = "2.18.1"
+pydantic-core = "2.18.2"
 typing-extensions = ">=4.6.1"
 
 [package.extras]
@@ -1999,90 +1922,90 @@ email = ["email-validator (>=2.0.0)"]
 
 [[package]]
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 ]
 
 [package.dependencies]
@@ -2159,18 +2082,18 @@ six = ">=1.5"
 
 [[package]]
 name = "python-docx"
-version = "1.1.0"
+version = "1.1.1"
 description = "Create, read, and update Microsoft Word .docx files."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "python-docx-1.1.0.tar.gz", hash = "sha256:5829b722141cf1ab79aedf0c34d9fe9924b29764584c0f2164eb2b02dcdf17c9"},
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 ]
 
 [package.dependencies]
-lxml = ">=3.1.0"
-typing-extensions = "*"
+lxml = ">=3.1.0,<=4.9.2"
+typing-extensions = ">=4.9.0"
 
 [[package]]
 name = "python-dotenv"

src/backend/base/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow-base"
-version = "0.0.36"
+version = "0.0.41"
 description = "A Python package with a built-in web application"
 authors = ["Langflow <contact@langflow.org>"]
 maintainers = [