feat!: rename the type BaseChatMessageHistory to Memory (#5190)

* chore: rename the type BaseChatMessageHistory to Memory

* Added Memory type with same color as BaseChatMessageHistory

* [autofix.ci] apply automated fixes

---------

Co-authored-by: Lucas Oliveira <lucas.edu.oli@hotmail.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

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

@@ -3,7 +3,8 @@ from abc import abstractmethod
 from langchain.memory import ConversationBufferMemory
 
 from langflow.custom import Component
-from langflow.field_typing import BaseChatMemory, BaseChatMessageHistory
+from langflow.field_typing import BaseChatMemory
+from langflow.field_typing.constants import Memory
 from langflow.template import Output
 
 
@@ -32,5 +33,5 @@ class LCChatMemoryComponent(Component):
         return ConversationBufferMemory(chat_memory=self.build_message_history())
 
     @abstractmethod
-    def build_message_history(self) -> BaseChatMessageHistory:
+    def build_message_history(self) -> Memory:
         """Builds the chat message history memory."""

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

@@ -18,7 +18,7 @@ class MemoryComponent(Component):
         HandleInput(
             name="memory",
             display_name="External Memory",
-            input_types=["BaseChatMessageHistory"],
+            input_types=["Memory"],
             info="Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
         ),
         DropdownInput(

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

@@ -20,7 +20,7 @@ class StoreMessageComponent(Component):
         HandleInput(
             name="memory",
             display_name="External Memory",
-            input_types=["BaseChatMessageHistory"],
+            input_types=["Memory"],
             info="The external memory to store the message. If empty, it will use the Langflow tables.",
         ),
         MessageTextInput(

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

@@ -3,7 +3,7 @@ import os
 from astrapy.admin import parse_api_endpoint
 
 from langflow.base.memory.model import LCChatMemoryComponent
-from langflow.field_typing import BaseChatMessageHistory
+from langflow.field_typing.constants import Memory
 from langflow.inputs import MessageTextInput, SecretStrInput, StrInput
 
 
@@ -49,7 +49,7 @@ class AstraDBChatMemory(LCChatMemoryComponent):
         ),
     ]
 
-    def build_message_history(self) -> BaseChatMessageHistory:
+    def build_message_history(self) -> Memory:
         try:
             from langchain_astradb.chat_message_histories import AstraDBChatMessageHistory
         except ImportError as e:

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

@@ -1,5 +1,5 @@
 from langflow.base.memory.model import LCChatMemoryComponent
-from langflow.field_typing import BaseChatMessageHistory
+from langflow.field_typing.constants import Memory
 from langflow.inputs import DictInput, MessageTextInput, SecretStrInput
 
 
@@ -49,7 +49,7 @@ class CassandraChatMemory(LCChatMemoryComponent):
         ),
     ]
 
-    def build_message_history(self) -> BaseChatMessageHistory:
+    def build_message_history(self) -> Memory:
         from langchain_community.chat_message_histories import CassandraChatMessageHistory
 
         try:

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

@@ -3,7 +3,7 @@ from urllib import parse
 from langchain_community.chat_message_histories.redis import RedisChatMessageHistory
 
 from langflow.base.memory.model import LCChatMemoryComponent
-from langflow.field_typing import BaseChatMessageHistory
+from langflow.field_typing.constants import Memory
 from langflow.inputs import IntInput, MessageTextInput, SecretStrInput, StrInput
 
 
@@ -31,7 +31,7 @@ class RedisIndexChatMemory(LCChatMemoryComponent):
         ),
     ]
 
-    def build_message_history(self) -> BaseChatMessageHistory:
+    def build_message_history(self) -> Memory:
         kwargs = {}
         password: str | None = self.password
         if self.key_prefix:

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

@@ -1,5 +1,5 @@
 from langflow.base.memory.model import LCChatMemoryComponent
-from langflow.field_typing import BaseChatMessageHistory
+from langflow.field_typing.constants import Memory
 from langflow.inputs import DropdownInput, MessageTextInput, SecretStrInput
 
 
@@ -24,7 +24,7 @@ class ZepChatMemory(LCChatMemoryComponent):
         ),
     ]
 
-    def build_message_history(self) -> BaseChatMessageHistory:
+    def build_message_history(self) -> Memory:
         try:
             # Monkeypatch API_BASE_PATH to
             # avoid 404

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

@@ -25,6 +25,8 @@ from langflow.schema.message import Message
 NestedDict: TypeAlias = dict[str, str | dict]
 LanguageModel = TypeVar("LanguageModel", BaseLanguageModel, BaseLLM, BaseChatModel)
 ToolEnabledLanguageModel = TypeVar("ToolEnabledLanguageModel", BaseLanguageModel, BaseLLM, BaseChatModel)
+Memory = TypeVar("Memory", bound=BaseChatMessageHistory)
+
 Retriever = TypeVar(
     "Retriever",
     BaseRetriever,
@@ -65,7 +67,7 @@ LANGCHAIN_BASE_TYPES = {
     "BaseMemory": BaseMemory,
     "BaseChatMemory": BaseChatMemory,
     "BaseChatModel": BaseChatModel,
-    "BaseChatMessageHistory": BaseChatMessageHistory,
+    "Memory": Memory,
 }
 # Langchain base types plus Python base types
 CUSTOM_COMPONENT_SUPPORTED_TYPES = {

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -573,7 +573,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import aget_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n    display_name = \"Message History\"\n    description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n    icon = \"message-square-more\"\n    name = \"Memory\"\n\n    inputs = [\n        HandleInput(\n            name=\"memory\",\n            display_name=\"External Memory\",\n            input_types=[\"BaseChatMessageHistory\"],\n            info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n            value=\"Machine and User\",\n            info=\"Filter by sender type.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Filter by sender name.\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"n_messages\",\n            display_name=\"Number of Messages\",\n            value=100,\n            info=\"Number of messages to retrieve.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"order\",\n            display_name=\"Order\",\n            options=[\"Ascending\", \"Descending\"],\n            value=\"Ascending\",\n            info=\"Order of the messages.\",\n            advanced=True,\n            tool_mode=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n            value=\"{sender_name}: {text}\",\n            advanced=True,\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n        Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n    ]\n\n    async def retrieve_messages(self) -> Data:\n        sender = self.sender\n        sender_name = self.sender_name\n        session_id = self.session_id\n        n_messages = self.n_messages\n        order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n        if sender == \"Machine and User\":\n            sender = None\n\n        if self.memory:\n            # override session_id\n            self.memory.session_id = session_id\n\n            stored = await self.memory.aget_messages()\n            # langchain memories are supposed to return messages in ascending order\n            if order == \"DESC\":\n                stored = stored[::-1]\n            if n_messages:\n                stored = stored[:n_messages]\n            stored = [Message.from_lc_message(m) for m in stored]\n            if sender:\n                expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n                stored = [m for m in stored if m.type == expected_type]\n        else:\n            stored = await aget_messages(\n                sender=sender,\n                sender_name=sender_name,\n                session_id=session_id,\n                limit=n_messages,\n                order=order,\n            )\n        self.status = stored\n        return stored\n\n    async def retrieve_messages_as_text(self) -> Message:\n        stored_text = data_to_text(self.template, await self.retrieve_messages())\n        self.status = stored_text\n        return Message(text=stored_text)\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import aget_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n    display_name = \"Message History\"\n    description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n    icon = \"message-square-more\"\n    name = \"Memory\"\n\n    inputs = [\n        HandleInput(\n            name=\"memory\",\n            display_name=\"External Memory\",\n            input_types=[\"Memory\"],\n            info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n            value=\"Machine and User\",\n            info=\"Filter by sender type.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Filter by sender name.\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"n_messages\",\n            display_name=\"Number of Messages\",\n            value=100,\n            info=\"Number of messages to retrieve.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"order\",\n            display_name=\"Order\",\n            options=[\"Ascending\", \"Descending\"],\n            value=\"Ascending\",\n            info=\"Order of the messages.\",\n            advanced=True,\n            tool_mode=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n            value=\"{sender_name}: {text}\",\n            advanced=True,\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n        Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n    ]\n\n    async def retrieve_messages(self) -> Data:\n        sender = self.sender\n        sender_name = self.sender_name\n        session_id = self.session_id\n        n_messages = self.n_messages\n        order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n        if sender == \"Machine and User\":\n            sender = None\n\n        if self.memory:\n            # override session_id\n            self.memory.session_id = session_id\n\n            stored = await self.memory.aget_messages()\n            # langchain memories are supposed to return messages in ascending order\n            if order == \"DESC\":\n                stored = stored[::-1]\n            if n_messages:\n                stored = stored[:n_messages]\n            stored = [Message.from_lc_message(m) for m in stored]\n            if sender:\n                expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n                stored = [m for m in stored if m.type == expected_type]\n        else:\n            stored = await aget_messages(\n                sender=sender,\n                sender_name=sender_name,\n                session_id=session_id,\n                limit=n_messages,\n                order=order,\n            )\n        self.status = stored\n        return stored\n\n    async def retrieve_messages_as_text(self) -> Message:\n        stored_text = data_to_text(self.template, await self.retrieve_messages())\n        self.status = stored_text\n        return Message(text=stored_text)\n"
               },
               "memory": {
                 "_input_type": "HandleInput",
@@ -582,7 +582,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json

@@ -1838,7 +1838,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Market Research.json

@@ -2082,7 +2082,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json

@@ -1128,7 +1128,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import aget_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n    display_name = \"Message History\"\n    description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n    icon = \"message-square-more\"\n    name = \"Memory\"\n\n    inputs = [\n        HandleInput(\n            name=\"memory\",\n            display_name=\"External Memory\",\n            input_types=[\"BaseChatMessageHistory\"],\n            info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n            value=\"Machine and User\",\n            info=\"Filter by sender type.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Filter by sender name.\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"n_messages\",\n            display_name=\"Number of Messages\",\n            value=100,\n            info=\"Number of messages to retrieve.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"order\",\n            display_name=\"Order\",\n            options=[\"Ascending\", \"Descending\"],\n            value=\"Ascending\",\n            info=\"Order of the messages.\",\n            advanced=True,\n            tool_mode=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n            value=\"{sender_name}: {text}\",\n            advanced=True,\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n        Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n    ]\n\n    async def retrieve_messages(self) -> Data:\n        sender = self.sender\n        sender_name = self.sender_name\n        session_id = self.session_id\n        n_messages = self.n_messages\n        order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n        if sender == \"Machine and User\":\n            sender = None\n\n        if self.memory:\n            # override session_id\n            self.memory.session_id = session_id\n\n            stored = await self.memory.aget_messages()\n            # langchain memories are supposed to return messages in ascending order\n            if order == \"DESC\":\n                stored = stored[::-1]\n            if n_messages:\n                stored = stored[:n_messages]\n            stored = [Message.from_lc_message(m) for m in stored]\n            if sender:\n                expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n                stored = [m for m in stored if m.type == expected_type]\n        else:\n            stored = await aget_messages(\n                sender=sender,\n                sender_name=sender_name,\n                session_id=session_id,\n                limit=n_messages,\n                order=order,\n            )\n        self.status = stored\n        return stored\n\n    async def retrieve_messages_as_text(self) -> Message:\n        stored_text = data_to_text(self.template, await self.retrieve_messages())\n        self.status = stored_text\n        return Message(text=stored_text)\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import aget_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n    display_name = \"Message History\"\n    description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n    icon = \"message-square-more\"\n    name = \"Memory\"\n\n    inputs = [\n        HandleInput(\n            name=\"memory\",\n            display_name=\"External Memory\",\n            input_types=[\"Memory\"],\n            info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n            value=\"Machine and User\",\n            info=\"Filter by sender type.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Filter by sender name.\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"n_messages\",\n            display_name=\"Number of Messages\",\n            value=100,\n            info=\"Number of messages to retrieve.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"order\",\n            display_name=\"Order\",\n            options=[\"Ascending\", \"Descending\"],\n            value=\"Ascending\",\n            info=\"Order of the messages.\",\n            advanced=True,\n            tool_mode=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {sender} or any other key in the message data.\",\n            value=\"{sender_name}: {text}\",\n            advanced=True,\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Data\", name=\"messages\", method=\"retrieve_messages\"),\n        Output(display_name=\"Text\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n    ]\n\n    async def retrieve_messages(self) -> Data:\n        sender = self.sender\n        sender_name = self.sender_name\n        session_id = self.session_id\n        n_messages = self.n_messages\n        order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n        if sender == \"Machine and User\":\n            sender = None\n\n        if self.memory:\n            # override session_id\n            self.memory.session_id = session_id\n\n            stored = await self.memory.aget_messages()\n            # langchain memories are supposed to return messages in ascending order\n            if order == \"DESC\":\n                stored = stored[::-1]\n            if n_messages:\n                stored = stored[:n_messages]\n            stored = [Message.from_lc_message(m) for m in stored]\n            if sender:\n                expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n                stored = [m for m in stored if m.type == expected_type]\n        else:\n            stored = await aget_messages(\n                sender=sender,\n                sender_name=sender_name,\n                session_id=session_id,\n                limit=n_messages,\n                order=order,\n            )\n        self.status = stored\n        return stored\n\n    async def retrieve_messages_as_text(self) -> Message:\n        stored_text = data_to_text(self.template, await self.retrieve_messages())\n        self.status = stored_text\n        return Message(text=stored_text)\n"
               },
               "memory": {
                 "_input_type": "HandleInput",
@@ -1137,7 +1137,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json

@@ -2329,7 +2329,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json

@@ -903,7 +903,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

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

@@ -848,7 +848,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",
@@ -1424,7 +1424,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",
@@ -3315,7 +3315,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json

@@ -384,7 +384,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json

@@ -1477,7 +1477,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",
@@ -2053,7 +2053,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",
@@ -2629,7 +2629,7 @@
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                 "input_types": [
-                  "BaseChatMessageHistory"
+                  "Memory"
                 ],
                 "list": false,
                 "name": "memory",

src/frontend/src/utils/styleUtils.ts

@@ -65,7 +65,6 @@ import {
   CopyPlus,
   CornerDownLeft,
   Cpu,
-  CpuIcon,
   Database,
   DatabaseZap,
   Delete,
@@ -477,6 +476,7 @@ export const nodeColorsName: { [char: string]: string } = {
   Tool: "cyan",
   BaseChatMemory: "cyan",
   BaseChatMessageHistory: "orange",
+  Memory: "orange",
 };
 
 export const SIDEBAR_CATEGORIES = [