refactor: reorganize memory components and enhance model inputs with improved documentation (#4529)

* new components improvements

* ✨ (create_data.py): introduce a new 'legacy' attribute to mark the component as legacy code

* [autofix.ci] apply automated fixes

* chaing langchain hub name

* 📝 (run_flow.py): remove beta flag from RunFlowComponent to indicate it is no longer in beta
📝 (extract_key.py): remove beta flag from ExtractDataKeyComponent to indicate it is no longer in beta

* Updated generic icon component to load icons if already not lazy imported

* [autofix.ci] apply automated fixes

* merge fix

* 📝 (store_message.py): add 'advanced' parameter to the 'Session ID' field to indicate it is an advanced setting

* [autofix.ci] apply automated fixes

* new components sweep

* [autofix.ci] apply automated fixes

* fix tests

* [autofix.ci] apply automated fixes

* ✨ (filterSidebar.spec.ts): Update test descriptions to reflect the correct component names for better clarity and maintainability
♻️ (freeze.spec.ts): Refactor test to use the correct component name for consistency and readability
♻️ (stop-building.spec.ts): Refactor test to use the correct component name for consistency and readability
♻️ (generalBugs-shard-9.spec.ts): Refactor test to use the correct component name for consistency and readability
♻️ (filterEdge-shard-1.spec.ts): Refactor test to use the correct component name for consistency and readability

* style: Improve YahooFinanceToolComponent description and code readability

Enhance clarity in the component's purpose and refine inline formatting to boost maintainability.

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Lucas Oliveira <lucas.edu.oli@hotmail.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

src/backend/base/langflow/components/agents/agent.py

@@ -4,8 +4,8 @@ from langflow.base.agents.agent import LCToolsAgentComponent
 from langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT
 from langflow.base.models.model_utils import get_model_name
 from langflow.components.helpers import CurrentDateComponent
+from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent
-from langflow.components.memories.memory import MemoryComponent
 from langflow.io import BoolInput, DropdownInput, MultilineInput, Output
 from langflow.schema.dotdict import dotdict
 from langflow.schema.message import Message

src/backend/base/langflow/components/data/csv_to_data.py

@@ -11,8 +11,8 @@ class CSVToDataComponent(Component):
     display_name = "Load CSV"
     description = "Load a CSV file, CSV from a file path, or a valid CSV string and convert it to a list of Data"
     icon = "file-spreadsheet"
-    beta = True
     name = "CSVtoData"
+    legacy = True
 
     inputs = [
         FileInput(

src/backend/base/langflow/components/data/json_to_data.py

@@ -14,8 +14,8 @@ class JSONToDataComponent(Component):
         "Convert a JSON file, JSON from a file path, or a JSON string to a Data object or a list of Data objects"
     )
     icon = "braces"
-    beta = True
     name = "JSONtoData"
+    legacy = True
 
     inputs = [
         FileInput(

src/backend/base/langflow/components/data/sql_executor.py

@@ -6,7 +6,7 @@ from langflow.field_typing import Text
 
 
 class SQLExecutorComponent(CustomComponent):
-    display_name = "SQL Executor"
+    display_name = "SQL Query"
     description = "Execute SQL query."
     name = "SQLExecutor"
     beta: bool = True

src/backend/base/langflow/components/data/webhook.py

@@ -14,7 +14,7 @@ class WebhookComponent(Component):
         MultilineInput(
             name="data",
             display_name="Payload",
-            info="Use this field to quickly test the webhook component by providing a JSON payload.",
+            info="Receives a payload from external systems via HTTP POST.",
         )
     ]
     outputs = [

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

@@ -1,8 +1,9 @@
 from .create_list import CreateListComponent
 from .current_date import CurrentDateComponent
 from .id_generator import IDGeneratorComponent
+from .memory import MemoryComponent
 from .output_parser import OutputParserComponent
-from .split_text import SplitTextComponent
+from .store_message import StoreMessageComponent
 from .structured_output import StructuredOutputComponent
 
 __all__ = [
@@ -10,6 +11,7 @@ __all__ = [
     "CurrentDateComponent",
     "IDGeneratorComponent",
     "OutputParserComponent",
-    "SplitTextComponent",
     "StructuredOutputComponent",
+    "StoreMessageComponent",
+    "MemoryComponent",
 ]

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

@@ -12,7 +12,7 @@ from langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER
 
 
 class MemoryComponent(Component):
-    display_name = "Chat Memory"
+    display_name = "Message History"
     description = "Retrieves stored chat messages from Langflow tables or an external memory."
     icon = "message-square-more"
     name = "Memory"

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

@@ -11,6 +11,7 @@ class OutputParserComponent(Component):
     description = "Transforms the output of an LLM into a specified format."
     icon = "type"
     name = "OutputParser"
+    legacy = True
 
     inputs = [
         DropdownInput(

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

@@ -39,6 +39,7 @@ class StoreMessageComponent(Component):
             display_name="Session ID",
             info="The session ID of the chat. If empty, the current session ID parameter will be used.",
             value="",
+            advanced=True,
         ),
     ]
 

src/backend/base/langflow/components/langchain_utilities/langchain_hub.py

@@ -9,7 +9,7 @@ from langflow.schema.message import Message
 
 
 class LangChainHubPromptComponent(Component):
-    display_name: str = "LangChain Hub"
+    display_name: str = "Prompt Hub"
     description: str = "Prompt Component that uses LangChain Hub prompts"
     beta = True
     icon = "LangChain"

src/backend/base/langflow/components/logic/conditional_router.py

@@ -8,7 +8,6 @@ class ConditionalRouterComponent(Component):
     description = "Routes an input message to a corresponding output based on text comparison."
     icon = "split"
     name = "ConditionalRouter"
-    legacy = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)

src/backend/base/langflow/components/logic/data_conditional_router.py

@@ -9,7 +9,6 @@ class DataConditionalRouterComponent(Component):
     display_name = "Condition"
     description = "Route Data object(s) based on a condition applied to a specified key, including boolean validation."
     icon = "split"
-    beta = True
     name = "DataConditionalRouter"
     legacy = True
 

src/backend/base/langflow/components/logic/run_flow.py

@@ -15,7 +15,6 @@ class RunFlowComponent(Component):
     display_name = "Run Flow"
     description = "A component to run a flow."
     name = "RunFlow"
-    beta: bool = True
     legacy: bool = True
     icon = "workflow"
 

src/backend/base/langflow/components/mem0/__init__.py

@@ -1,5 +0,0 @@
-from .mem0_chat_memory import Mem0MemoryComponent
-
-__all__ = [
-    "Mem0MemoryComponent",
-]

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

@@ -1,15 +1,13 @@
 from .astra_db import AstraDBChatMemory
 from .cassandra import CassandraChatMemory
-from .memory import MemoryComponent
+from .mem0_chat_memory import Mem0MemoryComponent
 from .redis import RedisIndexChatMemory
-from .store_message import StoreMessageComponent
 from .zep import ZepChatMemory
 
 __all__ = [
     "AstraDBChatMemory",
     "CassandraChatMemory",
-    "MemoryComponent",
     "RedisIndexChatMemory",
     "ZepChatMemory",
-    "StoreMessageComponent",
+    "Mem0MemoryComponent",
 ]

src/backend/base/langflow/components/models/ollama.py

@@ -70,7 +70,6 @@ class ChatOllamaComponent(LCModelComponent):
             raise ValueError(msg) from e
 
     inputs = [
-        *LCModelComponent._base_inputs,
         StrInput(
             name="base_url",
             display_name="Base URL",
@@ -151,7 +150,7 @@ class ChatOllamaComponent(LCModelComponent):
             name="top_k", display_name="Top K", info="Limits token selection to top K. (Default: 40)", advanced=True
         ),
         FloatInput(name="top_p", display_name="Top P", info="Works together with top-k. (Default: 0.9)", advanced=True),
-        BoolInput(name="verbose", display_name="Verbose", info="Whether to print out response text."),
+        BoolInput(name="verbose", display_name="Verbose", info="Whether to print out response text.", advanced=True),
         StrInput(
             name="tags",
             display_name="Tags",
@@ -173,6 +172,7 @@ class ChatOllamaComponent(LCModelComponent):
             advanced=True,
             input_types=["OutputParser"],
         ),
+        *LCModelComponent._base_inputs,
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

src/backend/base/langflow/components/processing/__init__.py

@@ -8,6 +8,7 @@ from .message_to_data import MessageToDataComponent
 from .parse_data import ParseDataComponent
 from .parse_json_data import ParseJSONDataComponent
 from .select_data import SelectDataComponent
+from .split_text import SplitTextComponent
 from .update_data import UpdateDataComponent
 
 __all__ = [
@@ -22,4 +23,5 @@ __all__ = [
     "ParseJSONDataComponent",
     "JSONCleaner",
     "CombineTextComponent",
+    "SplitTextComponent",
 ]

src/backend/base/langflow/components/processing/create_data.py

@@ -13,6 +13,7 @@ class CreateDataComponent(Component):
     description: str = "Dynamically create a Data with a specified number of fields."
     name: str = "CreateData"
     MAX_FIELDS = 15  # Define a constant for maximum number of fields
+    legacy = True
 
     inputs = [
         IntInput(

src/backend/base/langflow/components/processing/extract_key.py

@@ -10,8 +10,8 @@ class ExtractDataKeyComponent(Component):
         "Data objects and return the extracted value(s) as Data object(s)."
     )
     icon = "key"
-    beta = True
     name = "ExtractaKey"
+    legacy = True
 
     inputs = [
         DataInput(

src/backend/base/langflow/components/processing/select_data.py

@@ -10,6 +10,7 @@ class SelectDataComponent(Component):
     description: str = "Select a single data from a list of data."
     name: str = "SelectData"
     icon = "prototypes"
+    legacy = True
 
     inputs = [
         DataInput(

src/backend/base/langflow/components/tools/astradb.py

@@ -10,7 +10,7 @@ from langflow.schema import Data
 
 
 class AstraDBToolComponent(LCToolComponent):
-    display_name: str = "Astra DB Tool"
+    display_name: str = "Astra DB"
     description: str = "Create a tool to get data from DataStax Astra DB Collection"
     documentation: str = "https://astra.datastax.com"
     icon: str = "AstraDB"

src/backend/base/langflow/components/tools/astradb_cql.py

@@ -12,7 +12,7 @@ from langflow.schema import Data
 
 
 class AstraDBCQLToolComponent(LCToolComponent):
-    display_name: str = "Astra DB CQL Tool"
+    display_name: str = "Astra DB CQL"
     description: str = "Create a tool to get data from DataStax Astra DB CQL Table"
     documentation: str = "https://astra.datastax.com"
     icon: str = "AstraDB"

src/backend/base/langflow/components/tools/python_code_structured_tool.py

@@ -37,7 +37,7 @@ class PythonCodeStructuredTool(LCToolComponent):
         "_classes",
         "_functions",
     ]
-    display_name = "Python Code Structured Tool"
+    display_name = "Python Code Structured"
     description = "structuredtool dataclass code to tool"
     documentation = "https://python.langchain.com/docs/modules/tools/custom_tools/#structuredtool-dataclass"
     name = "PythonCodeStructuredTool"

src/backend/base/langflow/components/tools/python_repl.py

@@ -13,7 +13,7 @@ from langflow.schema import Data
 
 
 class PythonREPLToolComponent(LCToolComponent):
-    display_name = "Python REPL Tool"
+    display_name = "Python REPL"
     description = "A tool for running Python code in a REPL environment."
     name = "PythonREPLTool"
 

src/backend/base/langflow/components/tools/searxng.py

@@ -16,7 +16,7 @@ from langflow.schema.dotdict import dotdict
 
 class SearXNGToolComponent(LCToolComponent):
     search_headers: dict = {}
-    display_name = "SearXNG Search Tool"
+    display_name = "SearXNG Search"
     description = "A component that searches for tools using SearXNG."
     name = "SearXNGTool"
     legacy: bool = True

src/backend/base/langflow/components/tools/wolfram_alpha_api.py

@@ -9,13 +9,12 @@ from langflow.schema import Data
 class WolframAlphaAPIComponent(LCToolComponent):
     display_name = "WolframAlpha API"
     description = """Enables queries to Wolfram Alpha for computational data, facts, and calculations across various \
-topics, delivering structured responses. Example query: 'What is the population of France?'"""
+topics, delivering structured responses."""
     name = "WolframAlphaAPI"
 
     inputs = [
         MultilineInput(
-            name="input_value",
-            display_name="Input Query",
+            name="input_value", display_name="Input Query", info="Example query: 'What is the population of France?'"
         ),
         SecretStrInput(name="app_id", display_name="App ID", required=True),
     ]

src/backend/base/langflow/components/tools/yahoo_finance.py

@@ -50,7 +50,8 @@ class YahooFinanceSchema(BaseModel):
 
 class YfinanceToolComponent(LCToolComponent):
     display_name = "Yahoo Finance"
-    description = "Access financial data and market information using Yahoo Finance."
+    description = """Uses [yfinance](https://pypi.org/project/yfinance/) (unofficial package) \
+to access financial data and market information from Yahoo Finance."""
     icon = "trending-up"
     name = "YahooFinanceTool"
 

src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json

@@ -2956,7 +2956,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "import ast\nimport pprint\nfrom enum import Enum\n\nimport yfinance as yf\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DropdownInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass YahooFinanceMethod(Enum):\n    GET_INFO = \"get_info\"\n    GET_NEWS = \"get_news\"\n    GET_ACTIONS = \"get_actions\"\n    GET_ANALYSIS = \"get_analysis\"\n    GET_BALANCE_SHEET = \"get_balance_sheet\"\n    GET_CALENDAR = \"get_calendar\"\n    GET_CASHFLOW = \"get_cashflow\"\n    GET_INSTITUTIONAL_HOLDERS = \"get_institutional_holders\"\n    GET_RECOMMENDATIONS = \"get_recommendations\"\n    GET_SUSTAINABILITY = \"get_sustainability\"\n    GET_MAJOR_HOLDERS = \"get_major_holders\"\n    GET_MUTUALFUND_HOLDERS = \"get_mutualfund_holders\"\n    GET_INSIDER_PURCHASES = \"get_insider_purchases\"\n    GET_INSIDER_TRANSACTIONS = \"get_insider_transactions\"\n    GET_INSIDER_ROSTER_HOLDERS = \"get_insider_roster_holders\"\n    GET_DIVIDENDS = \"get_dividends\"\n    GET_CAPITAL_GAINS = \"get_capital_gains\"\n    GET_SPLITS = \"get_splits\"\n    GET_SHARES = \"get_shares\"\n    GET_FAST_INFO = \"get_fast_info\"\n    GET_SEC_FILINGS = \"get_sec_filings\"\n    GET_RECOMMENDATIONS_SUMMARY = \"get_recommendations_summary\"\n    GET_UPGRADES_DOWNGRADES = \"get_upgrades_downgrades\"\n    GET_EARNINGS = \"get_earnings\"\n    GET_INCOME_STMT = \"get_income_stmt\"\n\n\nclass YahooFinanceSchema(BaseModel):\n    symbol: str = Field(..., description=\"The stock symbol to retrieve data for.\")\n    method: YahooFinanceMethod = Field(YahooFinanceMethod.GET_INFO, description=\"The type of data to retrieve.\")\n    num_news: int | None = Field(5, description=\"The number of news articles to retrieve.\")\n\n\nclass YfinanceToolComponent(LCToolComponent):\n    display_name = \"Yahoo Finance\"\n    description = \"Access financial data and market information using Yahoo Finance.\"\n    icon = \"trending-up\"\n    name = \"YahooFinanceTool\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"symbol\",\n            display_name=\"Stock Symbol\",\n            info=\"The stock symbol to retrieve data for (e.g., AAPL, GOOG).\",\n        ),\n        DropdownInput(\n            name=\"method\",\n            display_name=\"Data Method\",\n            info=\"The type of data to retrieve.\",\n            options=list(YahooFinanceMethod),\n            value=\"get_news\",\n        ),\n        IntInput(\n            name=\"num_news\",\n            display_name=\"Number of News\",\n            info=\"The number of news articles to retrieve (only applicable for get_news).\",\n            value=5,\n        ),\n    ]\n\n    def run_model(self) -> list[Data]:\n        return self._yahoo_finance_tool(\n            self.symbol,\n            self.method,\n            self.num_news,\n        )\n\n    def build_tool(self) -> Tool:\n        return StructuredTool.from_function(\n            name=\"yahoo_finance\",\n            description=\"Access financial data and market information from Yahoo Finance.\",\n            func=self._yahoo_finance_tool,\n            args_schema=YahooFinanceSchema,\n        )\n\n    def _yahoo_finance_tool(\n        self,\n        symbol: str,\n        method: YahooFinanceMethod,\n        num_news: int | None = 5,\n    ) -> list[Data]:\n        ticker = yf.Ticker(symbol)\n\n        try:\n            if method == YahooFinanceMethod.GET_INFO:\n                result = ticker.info\n            elif method == YahooFinanceMethod.GET_NEWS:\n                result = ticker.news[:num_news]\n            else:\n                result = getattr(ticker, method.value)()\n\n            result = pprint.pformat(result)\n\n            if method == YahooFinanceMethod.GET_NEWS:\n                data_list = [Data(data=article) for article in ast.literal_eval(result)]\n            else:\n                data_list = [Data(data={\"result\": result})]\n\n        except Exception as e:\n            error_message = f\"Error retrieving data: {e}\"\n            logger.debug(error_message)\n            self.status = error_message\n            raise ToolException(error_message) from e\n\n        return data_list\n"
+                "value": "import ast\nimport pprint\nfrom enum import Enum\n\nimport yfinance as yf\nfrom langchain.tools import StructuredTool\nfrom langchain_core.tools import ToolException\nfrom loguru import logger\nfrom pydantic import BaseModel, Field\n\nfrom langflow.base.langchain_utilities.model import LCToolComponent\nfrom langflow.field_typing import Tool\nfrom langflow.inputs import DropdownInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass YahooFinanceMethod(Enum):\n    GET_INFO = \"get_info\"\n    GET_NEWS = \"get_news\"\n    GET_ACTIONS = \"get_actions\"\n    GET_ANALYSIS = \"get_analysis\"\n    GET_BALANCE_SHEET = \"get_balance_sheet\"\n    GET_CALENDAR = \"get_calendar\"\n    GET_CASHFLOW = \"get_cashflow\"\n    GET_INSTITUTIONAL_HOLDERS = \"get_institutional_holders\"\n    GET_RECOMMENDATIONS = \"get_recommendations\"\n    GET_SUSTAINABILITY = \"get_sustainability\"\n    GET_MAJOR_HOLDERS = \"get_major_holders\"\n    GET_MUTUALFUND_HOLDERS = \"get_mutualfund_holders\"\n    GET_INSIDER_PURCHASES = \"get_insider_purchases\"\n    GET_INSIDER_TRANSACTIONS = \"get_insider_transactions\"\n    GET_INSIDER_ROSTER_HOLDERS = \"get_insider_roster_holders\"\n    GET_DIVIDENDS = \"get_dividends\"\n    GET_CAPITAL_GAINS = \"get_capital_gains\"\n    GET_SPLITS = \"get_splits\"\n    GET_SHARES = \"get_shares\"\n    GET_FAST_INFO = \"get_fast_info\"\n    GET_SEC_FILINGS = \"get_sec_filings\"\n    GET_RECOMMENDATIONS_SUMMARY = \"get_recommendations_summary\"\n    GET_UPGRADES_DOWNGRADES = \"get_upgrades_downgrades\"\n    GET_EARNINGS = \"get_earnings\"\n    GET_INCOME_STMT = \"get_income_stmt\"\n\n\nclass YahooFinanceSchema(BaseModel):\n    symbol: str = Field(..., description=\"The stock symbol to retrieve data for.\")\n    method: YahooFinanceMethod = Field(YahooFinanceMethod.GET_INFO, description=\"The type of data to retrieve.\")\n    num_news: int | None = Field(5, description=\"The number of news articles to retrieve.\")\n\n\nclass YfinanceToolComponent(LCToolComponent):\n    display_name = \"Yahoo Finance\"\n    description = \"\"\"Uses [yfinance](https://pypi.org/project/yfinance/) (unofficial package) \\\nto access financial data and market information from Yahoo Finance.\"\"\"\n    icon = \"trending-up\"\n    name = \"YahooFinanceTool\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"symbol\",\n            display_name=\"Stock Symbol\",\n            info=\"The stock symbol to retrieve data for (e.g., AAPL, GOOG).\",\n        ),\n        DropdownInput(\n            name=\"method\",\n            display_name=\"Data Method\",\n            info=\"The type of data to retrieve.\",\n            options=list(YahooFinanceMethod),\n            value=\"get_news\",\n        ),\n        IntInput(\n            name=\"num_news\",\n            display_name=\"Number of News\",\n            info=\"The number of news articles to retrieve (only applicable for get_news).\",\n            value=5,\n        ),\n    ]\n\n    def run_model(self) -> list[Data]:\n        return self._yahoo_finance_tool(\n            self.symbol,\n            self.method,\n            self.num_news,\n        )\n\n    def build_tool(self) -> Tool:\n        return StructuredTool.from_function(\n            name=\"yahoo_finance\",\n            description=\"Access financial data and market information from Yahoo Finance.\",\n            func=self._yahoo_finance_tool,\n            args_schema=YahooFinanceSchema,\n        )\n\n    def _yahoo_finance_tool(\n        self,\n        symbol: str,\n        method: YahooFinanceMethod,\n        num_news: int | None = 5,\n    ) -> list[Data]:\n        ticker = yf.Ticker(symbol)\n\n        try:\n            if method == YahooFinanceMethod.GET_INFO:\n                result = ticker.info\n            elif method == YahooFinanceMethod.GET_NEWS:\n                result = ticker.news[:num_news]\n            else:\n                result = getattr(ticker, method.value)()\n\n            result = pprint.pformat(result)\n\n            if method == YahooFinanceMethod.GET_NEWS:\n                data_list = [Data(data=article) for article in ast.literal_eval(result)]\n            else:\n                data_list = [Data(data={\"result\": result})]\n\n        except Exception as e:\n            error_message = f\"Error retrieving data: {e}\"\n            logger.debug(error_message)\n            self.status = error_message\n            raise ToolException(error_message) from e\n\n        return data_list\n"
               },
               "method": {
                 "_input_type": "DropdownInput",

src/backend/base/langflow/initial_setup/starter_projects/memory_chatbot.py

@@ -1,5 +1,5 @@
+from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.inputs import ChatInput
-from langflow.components.memories import MemoryComponent
 from langflow.components.models import OpenAIModelComponent
 from langflow.components.outputs import ChatOutput
 from langflow.components.prompts import PromptComponent

src/backend/base/langflow/initial_setup/starter_projects/vector_store_rag.py

@@ -2,11 +2,11 @@ from textwrap import dedent
 
 from langflow.components.data import FileComponent
 from langflow.components.embeddings import OpenAIEmbeddingsComponent
-from langflow.components.helpers import SplitTextComponent
 from langflow.components.inputs import ChatInput
 from langflow.components.models import OpenAIModelComponent
 from langflow.components.outputs import ChatOutput
 from langflow.components.processing import ParseDataComponent
+from langflow.components.processing.split_text import SplitTextComponent
 from langflow.components.prompts import PromptComponent
 from langflow.components.vectorstores import AstraVectorStoreComponent
 from langflow.graph import Graph

src/backend/tests/unit/graph/graph/test_graph_state_model.py

@@ -1,8 +1,8 @@
 from typing import TYPE_CHECKING
 
 import pytest
+from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.inputs import ChatInput
-from langflow.components.memories import MemoryComponent
 from langflow.components.models import OpenAIModelComponent
 from langflow.components.outputs import ChatOutput
 from langflow.components.prompts import PromptComponent

src/backend/tests/unit/initial_setup/starter_projects/test_memory_chatbot.py

@@ -3,8 +3,8 @@ from collections import deque
 from typing import TYPE_CHECKING
 
 import pytest
+from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.inputs import ChatInput
-from langflow.components.memories import MemoryComponent
 from langflow.components.models import OpenAIModelComponent
 from langflow.components.outputs import ChatOutput
 from langflow.components.prompts import PromptComponent

src/backend/tests/unit/initial_setup/starter_projects/test_vector_store_rag.py

@@ -5,11 +5,11 @@ from textwrap import dedent
 import pytest
 from langflow.components.data import FileComponent
 from langflow.components.embeddings import OpenAIEmbeddingsComponent
-from langflow.components.helpers import SplitTextComponent
 from langflow.components.inputs import ChatInput
 from langflow.components.models import OpenAIModelComponent
 from langflow.components.outputs import ChatOutput
 from langflow.components.processing import ParseDataComponent
+from langflow.components.processing.split_text import SplitTextComponent
 from langflow.components.prompts import PromptComponent
 from langflow.components.vectorstores import AstraVectorStoreComponent
 from langflow.graph import Graph

src/frontend/src/components/genericIconComponent/index.tsx

@@ -32,7 +32,14 @@ export const ForwardedIconComponent = memo(
         return () => clearTimeout(timer);
       }, []);
 
-      let TargetIcon = nodeIconsLucide[name];
+      let TargetIcon =
+        nodeIconsLucide[name] ||
+        nodeIconsLucide[
+          name
+            .split("-")
+            .map((x) => String(x[0]).toUpperCase() + String(x).slice(1))
+            .join("")
+        ];
       if (!TargetIcon) {
         if (!dynamicIconImports[name]) {
           TargetIcon = nodeIconsLucide["unknown"];

src/frontend/src/utils/styleUtils.ts

@@ -470,8 +470,8 @@ export const SIDEBAR_CATEGORIES = [
   { display_name: "Outputs", name: "outputs", icon: "Upload" },
   { display_name: "Prompts", name: "prompts", icon: "TerminalSquare" },
   { display_name: "Data", name: "data", icon: "Database" },
+  { display_name: "Processing", name: "processing", icon: "ListFilter" },
   { display_name: "Models", name: "models", icon: "BrainCircuit" },
-  { display_name: "Helpers", name: "helpers", icon: "Wand2" },
   { display_name: "Vector Stores", name: "vectorstores", icon: "Layers" },
   { display_name: "Embeddings", name: "embeddings", icon: "Binary" },
   { display_name: "Agents", name: "agents", icon: "Bot" },
@@ -486,7 +486,7 @@ export const SIDEBAR_CATEGORIES = [
   { display_name: "Toolkits", name: "toolkits", icon: "Package2" },
   { display_name: "Tools", name: "tools", icon: "Hammer" },
   { display_name: "Logic", name: "logic", icon: "ArrowRightLeft" },
-  { display_name: "Processing", name: "processing", icon: "ListFilter" },
+  { display_name: "Helpers", name: "helpers", icon: "Wand2" },
 ];
 
 export const SIDEBAR_BUNDLES = [

src/frontend/tests/core/features/filterSidebar.spec.ts

@@ -84,7 +84,7 @@ test("user must see on handle click the possibility connections - LLMChain", asy
   await expect(page.getByTestId("outputsChat Output")).toBeVisible();
   await expect(page.getByTestId("promptsPrompt")).toBeVisible();
   await expect(page.getByTestId("modelsAmazon Bedrock")).toBeVisible();
-  await expect(page.getByTestId("memoriesChat Memory")).toBeVisible();
+  await expect(page.getByTestId("helpersMessage History")).toBeVisible();
   await expect(page.getByTestId("langchain_utilitiesCSVAgent")).toBeVisible();
   await expect(
     page.getByTestId("langchain_utilitiesConversationChain"),
@@ -106,7 +106,7 @@ test("user must see on handle click the possibility connections - LLMChain", asy
   await expect(page.getByTestId("outputsChat Output")).not.toBeVisible();
   await expect(page.getByTestId("promptsPrompt")).not.toBeVisible();
   await expect(page.getByTestId("modelsAmazon Bedrock")).not.toBeVisible();
-  await expect(page.getByTestId("memoriesChat Memory")).not.toBeVisible();
+  await expect(page.getByTestId("helpersMessage History")).not.toBeVisible();
   await expect(page.getByTestId("agentsTool Calling Agent")).not.toBeVisible();
   await expect(
     page.getByTestId("langchain_utilitiesConversationChain"),
@@ -123,7 +123,7 @@ test("user must see on handle click the possibility connections - LLMChain", asy
   await expect(page.getByTestId("disclosure-tools")).toBeVisible();
 
   await expect(page.getByTestId("dataAPI Request")).toBeVisible();
-  await expect(page.getByTestId("memoriesChat Memory")).toBeVisible();
+  await expect(page.getByTestId("helpersMessage History")).toBeVisible();
   await expect(page.getByTestId("vectorstoresAstra DB")).toBeVisible();
   await expect(page.getByTestId("toolsSearch API")).toBeVisible();
   await expect(page.getByTestId("logicSub Flow")).not.toBeVisible();
@@ -136,17 +136,17 @@ test("user must see on handle click the possibility connections - LLMChain", asy
 
   await expect(page.getByTestId("logicSub Flow")).toBeVisible();
 
-  await expect(page.getByTestId("helpersSplit Text")).toBeVisible();
+  await expect(page.getByTestId("processingSplit Text")).toBeVisible();
   await expect(page.getByTestId("toolsSearch API")).toBeVisible();
 
   await page.getByTestId("icon-X").first().click();
 
   await expect(page.getByTestId("dataAPI Request")).not.toBeVisible();
-  await expect(page.getByTestId("memoriesChat Memory")).not.toBeVisible();
+  await expect(page.getByTestId("helpersMessage History")).not.toBeVisible();
   await expect(page.getByTestId("vectorstoresAstra DB")).not.toBeVisible();
   await expect(page.getByTestId("toolsSearch API")).not.toBeVisible();
   await expect(page.getByTestId("logicSub Flow")).not.toBeVisible();
 
-  await expect(page.getByTestId("helpersSplit Text")).not.toBeVisible();
+  await expect(page.getByTestId("processingSplit Text")).not.toBeVisible();
   await expect(page.getByTestId("toolsSearch API")).not.toBeVisible();
 });

src/frontend/tests/core/features/freeze.spec.ts

@@ -77,7 +77,7 @@ test("user must be able to freeze a component", async ({ page }) => {
   await page.waitForTimeout(1000);
 
   await page
-    .getByTestId("helpersSplit Text")
+    .getByTestId("processingSplit Text")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
 
   await page.getByTestId("zoom_out").click();

src/frontend/tests/core/features/stop-building.spec.ts

@@ -82,7 +82,7 @@ test("user must be able to stop a building", async ({ page }) => {
   // await page.waitForTimeout(1000);
 
   await page
-    .getByTestId("helpersSplit Text")
+    .getByTestId("processingSplit Text")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
 
   await page.getByTestId("zoom_out").click();

src/frontend/tests/core/regression/generalBugs-shard-9.spec.ts

@@ -76,7 +76,7 @@ test("memory should work as expect", async ({ page }) => {
   await page.mouse.up();
 
   await page
-    .getByTestId("memoriesChat Memory")
+    .getByTestId("helpersMessage History")
     .first()
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
 

src/frontend/tests/extended/features/filterEdge-shard-1.spec.ts

@@ -97,7 +97,7 @@ test("user must see on handle click the possibility connections - RetrievalQA",
     "outputsChat Output",
     "dataAPI Request",
     "modelsAmazon Bedrock",
-    "memoriesChat Memory",
+    "helpersMessage History",
     "vectorstoresAstra DB",
     "embeddingsAmazon Bedrock Embeddings",
     "langchain_utilitiesTool Calling Agent",