danswer/backend/onyx/llm/models.py
2025-02-19 15:52:16 -08:00

62 lines
2.1 KiB
Python

from typing import TYPE_CHECKING
from langchain.schema.messages import AIMessage
from langchain.schema.messages import BaseMessage
from langchain.schema.messages import HumanMessage
from langchain.schema.messages import SystemMessage
from pydantic import BaseModel
from onyx.configs.constants import MessageType
from onyx.file_store.models import InMemoryChatFile
from onyx.llm.utils import build_content_with_imgs
from onyx.tools.models import ToolCallFinalResult
if TYPE_CHECKING:
from onyx.db.models import ChatMessage
class PreviousMessage(BaseModel):
"""Simplified version of `ChatMessage`"""
message: str
token_count: int
message_type: MessageType
files: list[InMemoryChatFile]
tool_call: ToolCallFinalResult | None
refined_answer_improvement: bool | None
@classmethod
def from_chat_message(
cls, chat_message: "ChatMessage", available_files: list[InMemoryChatFile]
) -> "PreviousMessage":
message_file_ids = (
[file["id"] for file in chat_message.files] if chat_message.files else []
)
return cls(
message=chat_message.message,
token_count=chat_message.token_count,
message_type=chat_message.message_type,
files=[
file
for file in available_files
if str(file.file_id) in message_file_ids
],
tool_call=ToolCallFinalResult(
tool_name=chat_message.tool_call.tool_name,
tool_args=chat_message.tool_call.tool_arguments,
tool_result=chat_message.tool_call.tool_result,
)
if chat_message.tool_call
else None,
refined_answer_improvement=chat_message.refined_answer_improvement,
)
def to_langchain_msg(self) -> BaseMessage:
content = build_content_with_imgs(self.message, self.files)
if self.message_type == MessageType.USER:
return HumanMessage(content=content)
elif self.message_type == MessageType.ASSISTANT:
return AIMessage(content=content)
else:
return SystemMessage(content=content)