mirror of
https://github.com/MODSetter/SurfSense.git
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f5ea337b75
This commit introduces Alison, an AI-powered classroom IT support assistant, as a new module within the SurfSense application. Key features of this implementation include: - A new LangGraph-based agent for conversational troubleshooting. - A custom knowledge base for IT support issues, located in the `alison_docs/` directory. - An extension of the RAG pipeline to use Alison's knowledge base. - Role-aware responses for professors and proctors. - A configuration toggle to enable or disable the Alison module. - Documentation for setting up and using Alison. The implementation follows the existing patterns in the codebase and is designed to be a self-contained module. Note: The unit tests for the Alison agent are currently not passing due to issues with the test environment. Further work is needed to get the tests to run correctly.
70 lines
1.4 KiB
Python
70 lines
1.4 KiB
Python
from typing import Any
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from pydantic import BaseModel, ConfigDict
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from app.db import ChatType
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from .base import IDModel, TimestampModel
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class ChatBase(BaseModel):
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type: ChatType
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title: str
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initial_connectors: list[str] | None = None
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messages: list[Any]
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search_space_id: int
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class ChatBaseWithoutMessages(BaseModel):
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type: ChatType
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title: str
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search_space_id: int
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class ClientAttachment(BaseModel):
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name: str
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content_type: str
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url: str
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class ToolInvocation(BaseModel):
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tool_call_id: str
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tool_name: str
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args: dict
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result: dict
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# class ClientMessage(BaseModel):
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# role: str
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# content: str
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# experimental_attachments: Optional[List[ClientAttachment]] = None
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# toolInvocations: Optional[List[ToolInvocation]] = None
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class AISDKChatRequest(BaseModel):
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messages: list[Any]
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data: dict[str, Any] | None = None
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@property
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def alison_enabled(self) -> bool:
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return self.data.get("alison_enabled", False) if self.data else False
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@property
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def user_role(self) -> str:
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return self.data.get("user_role", "professor") if self.data else "professor"
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class ChatCreate(ChatBase):
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pass
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class ChatUpdate(ChatBase):
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pass
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class ChatRead(ChatBase, IDModel, TimestampModel):
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model_config = ConfigDict(from_attributes=True)
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class ChatReadWithoutMessages(ChatBaseWithoutMessages, IDModel, TimestampModel):
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model_config = ConfigDict(from_attributes=True)
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