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setup
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from functools import cached_property
from typing import Literal
from pydantic import Field
from proxy_lite.history import MessageHistory, MessageLabel, SystemMessage, Text
from proxy_lite.tools import Tool
from .agent_base import Agents, BaseAgent, BaseAgentConfig
MODEL_SYSTEM_PROMPT = """You are Proxy-Lite, an AI assistant that can perform actions on a computer screen.
You were developed by Convergence AI.
The user will instuct you to perform a task.
You will be shown a screen as well as relevant interactable elements highlighted by mark_ids and you will be given a set of tools to use to perform the task.
You should make observations about the screen, putting them in <observation></observation> tags.
You should then reason about what needs to be done to complete the task, putting your thoughts in <thinking></thinking> tags.
You should then use the tools to perform the task, putting the tool calls in <tool_call></tool_call> tags.
""" # noqa: E501
MAX_MESSAGES_FOR_CONTEXT_WINDOW = {
MessageLabel.SCREENSHOT: 1,
}
@Agents.register_agent_config("proxy_lite")
class ProxyLiteAgentConfig(BaseAgentConfig):
name: Literal["proxy_lite"] = "proxy_lite"
history_messages_limit: dict[MessageLabel, int] = Field(
default_factory=lambda: MAX_MESSAGES_FOR_CONTEXT_WINDOW,
)
@Agents.register_agent("proxy_lite")
class ProxyLiteAgent(BaseAgent):
config: ProxyLiteAgentConfig
message_label: MessageLabel = MessageLabel.AGENT_MODEL_RESPONSE
def __init__(self, **data):
super().__init__(**data)
@property
def system_prompt(self) -> str:
return MODEL_SYSTEM_PROMPT
@cached_property
def tools(self) -> list[Tool]:
return self.env_tools
async def get_history_view(self) -> MessageHistory:
return MessageHistory(
messages=[SystemMessage(content=[Text(text=self.system_prompt)])],
) + self.history.history_view(
limits=self.config.history_messages_limit,
)