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6eb9915 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | from __future__ import annotations
import logging
from typing import List, Optional, Type
from browser_use.agent.message_manager.service import MessageManager
from browser_use.agent.message_manager.views import MessageHistory
from browser_use.agent.prompts import SystemPrompt, AgentMessagePrompt
from browser_use.agent.views import ActionResult, AgentStepInfo, ActionModel
from browser_use.browser.views import BrowserState
from langchain_core.language_models import BaseChatModel
from langchain_anthropic import ChatAnthropic
from langchain_core.language_models import BaseChatModel
from langchain_core.messages import (
AIMessage,
BaseMessage,
HumanMessage,
ToolMessage
)
from langchain_openai import ChatOpenAI
from ..utils.llm import DeepSeekR1ChatOpenAI
from .custom_prompts import CustomAgentMessagePrompt
logger = logging.getLogger(__name__)
class CustomMessageManager(MessageManager):
def __init__(
self,
llm: BaseChatModel,
task: str,
action_descriptions: str,
system_prompt_class: Type[SystemPrompt],
agent_prompt_class: Type[AgentMessagePrompt],
max_input_tokens: int = 128000,
estimated_characters_per_token: int = 3,
image_tokens: int = 800,
include_attributes: list[str] = [],
max_error_length: int = 400,
max_actions_per_step: int = 10,
message_context: Optional[str] = None
):
super().__init__(
llm=llm,
task=task,
action_descriptions=action_descriptions,
system_prompt_class=system_prompt_class,
max_input_tokens=max_input_tokens,
estimated_characters_per_token=estimated_characters_per_token,
image_tokens=image_tokens,
include_attributes=include_attributes,
max_error_length=max_error_length,
max_actions_per_step=max_actions_per_step,
message_context=message_context
)
self.agent_prompt_class = agent_prompt_class
# Custom: Move Task info to state_message
self.history = MessageHistory()
self._add_message_with_tokens(self.system_prompt)
if self.message_context:
context_message = HumanMessage(content=self.message_context)
self._add_message_with_tokens(context_message)
def cut_messages(self):
"""Get current message list, potentially trimmed to max tokens"""
diff = self.history.total_tokens - self.max_input_tokens
min_message_len = 2 if self.message_context is not None else 1
while diff > 0 and len(self.history.messages) > min_message_len:
self.history.remove_message(min_message_len) # alway remove the oldest message
diff = self.history.total_tokens - self.max_input_tokens
def add_state_message(
self,
state: BrowserState,
actions: Optional[List[ActionModel]] = None,
result: Optional[List[ActionResult]] = None,
step_info: Optional[AgentStepInfo] = None,
) -> None:
"""Add browser state as human message"""
# otherwise add state message and result to next message (which will not stay in memory)
state_message = self.agent_prompt_class(
state,
actions,
result,
include_attributes=self.include_attributes,
max_error_length=self.max_error_length,
step_info=step_info,
).get_user_message()
self._add_message_with_tokens(state_message)
def _count_text_tokens(self, text: str) -> int:
if isinstance(self.llm, (ChatOpenAI, ChatAnthropic, DeepSeekR1ChatOpenAI)):
try:
tokens = self.llm.get_num_tokens(text)
except Exception:
tokens = (
len(text) // self.estimated_characters_per_token
) # Rough estimate if no tokenizer available
else:
tokens = (
len(text) // self.estimated_characters_per_token
) # Rough estimate if no tokenizer available
return tokens
def _remove_state_message_by_index(self, remove_ind=-1) -> None:
"""Remove last state message from history"""
i = len(self.history.messages) - 1
remove_cnt = 0
while i >= 0:
if isinstance(self.history.messages[i].message, HumanMessage):
remove_cnt += 1
if remove_cnt == abs(remove_ind):
self.history.remove_message(i)
break
i -= 1 |