ref: Remove unused build_lc_memory (#5228)
This commit is contained in:
Christophe Bornet
GitHub
parent
e8667009b7
commit
8d66754380
5 changed files with 24 additions and 311 deletions
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@ -1,11 +1,8 @@
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from langchain.memory import ConversationBufferMemory
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from langflow.custom import Component
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from langflow.field_typing import BaseChatMemory
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from langflow.helpers.data import data_to_text
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from langflow.inputs import HandleInput
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from langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output
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from langflow.memory import LCBuiltinChatMemory, aget_messages
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from langflow.memory import aget_messages
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from langflow.schema import Data
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from langflow.schema.message import Message
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from langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER
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@ -114,7 +111,3 @@ class MemoryComponent(Component):
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stored_text = data_to_text(self.template, await self.retrieve_messages())
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self.status = stored_text
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return Message(text=stored_text)
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def build_lc_memory(self) -> BaseChatMemory:
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chat_memory = self.memory or LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)
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return ConversationBufferMemory(chat_memory=chat_memory)
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@ -573,7 +573,7 @@
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"show": true,
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"title_case": false,
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"type": "code",
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"value": "from langchain.memory import ConversationBufferMemory\n\nfrom langflow.custom import Component\nfrom langflow.field_typing import BaseChatMemory\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 LCBuiltinChatMemory, 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\n def build_lc_memory(self) -> BaseChatMemory:\n chat_memory = self.memory or LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n"
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"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"
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},
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"memory": {
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"_input_type": "HandleInput",
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@ -1128,7 +1128,7 @@
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"show": true,
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"title_case": false,
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"type": "code",
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"value": "from langchain.memory import ConversationBufferMemory\n\nfrom langflow.custom import Component\nfrom langflow.field_typing import BaseChatMemory\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 LCBuiltinChatMemory, 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\n def build_lc_memory(self) -> BaseChatMemory:\n chat_memory = self.memory or LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n"
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"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"
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},
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"memory": {
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"_input_type": "HandleInput",
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@ -6,13 +6,13 @@ from langchain_core.chat_history import BaseChatMessageHistory
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from langchain_core.messages import BaseMessage
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from loguru import logger
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from sqlalchemy import delete
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from sqlmodel import Session, col, select
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from sqlmodel import col, select
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from sqlmodel.ext.asyncio.session import AsyncSession
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from langflow.schema.message import Message
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from langflow.services.database.models.message.model import MessageRead, MessageTable
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from langflow.services.deps import async_session_scope, session_scope
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from langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER
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from langflow.services.deps import async_session_scope
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from langflow.utils.async_helpers import run_until_complete
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def _get_variable_query(
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@ -50,7 +50,9 @@ def get_messages(
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flow_id: UUID | None = None,
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limit: int | None = None,
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) -> list[Message]:
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"""Retrieves messages from the monitor service based on the provided filters.
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"""DEPRECATED - Retrieves messages from the monitor service based on the provided filters.
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DEPRECATED: Use `aget_messages` instead.
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Args:
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sender (Optional[str]): The sender of the messages (e.g., "Machine" or "User")
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@ -64,10 +66,7 @@ def get_messages(
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Returns:
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List[Data]: A list of Data objects representing the retrieved messages.
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"""
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with session_scope() as session:
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stmt = _get_variable_query(sender, sender_name, session_id, order_by, order, flow_id, limit)
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messages = session.exec(stmt)
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return [Message(**d.model_dump()) for d in messages]
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return run_until_complete(aget_messages(sender, sender_name, session_id, order_by, order, flow_id, limit))
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async def aget_messages(
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@ -100,27 +99,11 @@ async def aget_messages(
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def add_messages(messages: Message | list[Message], flow_id: str | UUID | None = None):
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"""Add a message to the monitor service."""
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if not isinstance(messages, list):
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messages = [messages]
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"""DEPRECATED - Add a message to the monitor service.
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if not all(isinstance(message, Message) for message in messages):
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types = ", ".join([str(type(message)) for message in messages])
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msg = f"The messages must be instances of Message. Found: {types}"
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raise ValueError(msg)
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try:
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# Convert flow_id to UUID if it's a string
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if isinstance(flow_id, str):
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flow_id = UUID(flow_id)
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messages_models = [MessageTable.from_message(msg, flow_id=flow_id) for msg in messages]
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with session_scope() as session:
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messages_models = add_messagetables(messages_models, session)
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return [Message(**message.model_dump()) for message in messages_models]
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except Exception as e:
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logger.exception(e)
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raise
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DEPRECATED: Use `aadd_messages` instead.
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"""
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return run_until_complete(aadd_messages(messages, flow_id=flow_id))
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async def aadd_messages(messages: Message | list[Message], flow_id: str | UUID | None = None):
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@ -143,31 +126,6 @@ async def aadd_messages(messages: Message | list[Message], flow_id: str | UUID |
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raise
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def update_messages(messages: Message | list[Message]) -> list[Message]:
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if not isinstance(messages, list):
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messages = [messages]
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with session_scope() as session:
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updated_messages: list[MessageTable] = []
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for message in messages:
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message_id = UUID(message.id) if isinstance(message.id, str) else message.id
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msg = session.get(MessageTable, message_id)
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if msg:
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if hasattr(message, "data"):
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msg = msg.sqlmodel_update(message.data)
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else:
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msg = msg.sqlmodel_update(message.model_dump(exclude_unset=True, exclude_none=True))
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if isinstance(msg.flow_id, str):
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msg.flow_id = UUID(msg.flow_id)
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session.add(msg)
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session.commit()
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session.refresh(msg)
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updated_messages.append(msg)
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else:
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logger.warning(f"Message with id {message.id} not found")
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return [MessageRead.model_validate(message, from_attributes=True) for message in updated_messages]
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async def aupdate_messages(messages: Message | list[Message]) -> list[Message]:
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if not isinstance(messages, list):
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messages = [messages]
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@ -190,26 +148,6 @@ async def aupdate_messages(messages: Message | list[Message]) -> list[Message]:
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return [MessageRead.model_validate(message, from_attributes=True) for message in updated_messages]
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def add_messagetables(messages: list[MessageTable], session: Session):
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for message in messages:
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try:
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session.add(message)
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session.commit()
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session.refresh(message)
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except Exception as e:
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logger.exception(e)
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raise
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new_messages = []
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for msg in messages:
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msg.properties = json.loads(msg.properties) if isinstance(msg.properties, str) else msg.properties # type: ignore[arg-type]
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msg.content_blocks = [json.loads(j) if isinstance(j, str) else j for j in msg.content_blocks] # type: ignore[arg-type]
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msg.category = msg.category or ""
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new_messages.append(msg)
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return [MessageRead.model_validate(message, from_attributes=True) for message in new_messages]
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async def aadd_messagetables(messages: list[MessageTable], session: AsyncSession):
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try:
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for message in messages:
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@ -232,17 +170,14 @@ async def aadd_messagetables(messages: list[MessageTable], session: AsyncSession
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def delete_messages(session_id: str) -> None:
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"""Delete messages from the monitor service based on the provided session ID.
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"""DEPRECATED - Delete messages from the monitor service based on the provided session ID.
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DEPRECATED: Use `adelete_messages` instead.
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Args:
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session_id (str): The session ID associated with the messages to delete.
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"""
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with session_scope() as session:
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session.exec(
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delete(MessageTable)
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.where(col(MessageTable.session_id) == session_id)
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.execution_options(synchronize_session="fetch")
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)
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return run_until_complete(adelete_messages(session_id))
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async def adelete_messages(session_id: str) -> None:
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@ -277,7 +212,9 @@ def store_message(
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message: Message,
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flow_id: str | UUID | None = None,
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) -> list[Message]:
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"""Stores a message in the memory.
|
||||
"""DEPRECATED: Stores a message in the memory.
|
||||
|
||||
DEPRECATED: Use `astore_message` instead.
|
||||
|
||||
Args:
|
||||
message (Message): The message to store.
|
||||
|
|
@ -290,31 +227,7 @@ def store_message(
|
|||
Raises:
|
||||
ValueError: If any of the required parameters (session_id, sender, sender_name) is not provided.
|
||||
"""
|
||||
if not message:
|
||||
logger.warning("No message provided.")
|
||||
return []
|
||||
|
||||
# Convert flow_id to UUID if it's a string
|
||||
if isinstance(flow_id, str):
|
||||
flow_id = UUID(flow_id)
|
||||
|
||||
required_fields = ["session_id", "sender", "sender_name"]
|
||||
missing_fields = [field for field in required_fields if not getattr(message, field)]
|
||||
if missing_fields:
|
||||
missing_descriptions = {
|
||||
"session_id": "session_id (unique conversation identifier)",
|
||||
"sender": f"sender (e.g., '{MESSAGE_SENDER_USER}' or '{MESSAGE_SENDER_AI}')",
|
||||
"sender_name": "sender_name (display name, e.g., 'User' or 'Assistant')",
|
||||
}
|
||||
missing = ", ".join(missing_descriptions[field] for field in missing_fields)
|
||||
msg = (
|
||||
f"It looks like we're missing some important information: {missing}. "
|
||||
"Please ensure that your message includes all the required fields."
|
||||
)
|
||||
raise ValueError(msg)
|
||||
if hasattr(message, "id") and message.id:
|
||||
return update_messages([message])
|
||||
return add_messages([message], flow_id=flow_id)
|
||||
return run_until_complete(astore_message(message, flow_id=flow_id))
|
||||
|
||||
|
||||
async def astore_message(
|
||||
|
|
@ -349,6 +262,8 @@ async def astore_message(
|
|||
|
||||
|
||||
class LCBuiltinChatMemory(BaseChatMessageHistory):
|
||||
"""DEPRECATED: Kept for backward compatibility."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
flow_id: str,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue