File size: 5,380 Bytes
db4810d | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 | import datetime
import importlib.resources
from datetime import datetime
from typing import TYPE_CHECKING, List, Optional
from langchain_core.messages import HumanMessage, SystemMessage
if TYPE_CHECKING:
from browser_use.agent.views import ActionResult, AgentStepInfo
from browser_use.browser.views import BrowserState
class SystemPrompt:
def __init__(
self,
action_description: str,
max_actions_per_step: int = 10,
override_system_message: Optional[str] = None,
extend_system_message: Optional[str] = None,
):
self.default_action_description = action_description
self.max_actions_per_step = max_actions_per_step
prompt = ''
if override_system_message:
prompt = override_system_message
else:
self._load_prompt_template()
prompt = self.prompt_template.format(max_actions=self.max_actions_per_step)
if extend_system_message:
prompt += f'\n{extend_system_message}'
self.system_message = SystemMessage(content=prompt)
def _load_prompt_template(self) -> None:
"""Load the prompt template from the markdown file."""
try:
# This works both in development and when installed as a package
with importlib.resources.files('browser_use.agent').joinpath('system_prompt.md').open('r') as f:
self.prompt_template = f.read()
except Exception as e:
raise RuntimeError(f'Failed to load system prompt template: {e}')
def get_system_message(self) -> SystemMessage:
"""
Get the system prompt for the agent.
Returns:
SystemMessage: Formatted system prompt
"""
return self.system_message
# Functions:
# {self.default_action_description}
# Example:
# {self.example_response()}
# Your AVAILABLE ACTIONS:
# {self.default_action_description}
class AgentMessagePrompt:
def __init__(
self,
state: 'BrowserState',
result: Optional[List['ActionResult']] = None,
include_attributes: list[str] = [],
step_info: Optional['AgentStepInfo'] = None,
):
self.state = state
self.result = result
self.include_attributes = include_attributes
self.step_info = step_info
def get_user_message(self, use_vision: bool = True) -> HumanMessage:
elements_text = self.state.element_tree.clickable_elements_to_string(include_attributes=self.include_attributes)
has_content_above = (self.state.pixels_above or 0) > 0
has_content_below = (self.state.pixels_below or 0) > 0
if elements_text != '':
if has_content_above:
elements_text = (
f'... {self.state.pixels_above} pixels above - scroll or extract content to see more ...\n{elements_text}'
)
else:
elements_text = f'[Start of page]\n{elements_text}'
if has_content_below:
elements_text = (
f'{elements_text}\n... {self.state.pixels_below} pixels below - scroll or extract content to see more ...'
)
else:
elements_text = f'{elements_text}\n[End of page]'
else:
elements_text = 'empty page'
if self.step_info:
step_info_description = f'Current step: {self.step_info.step_number + 1}/{self.step_info.max_steps}'
else:
step_info_description = ''
time_str = datetime.now().strftime('%Y-%m-%d %H:%M')
step_info_description += f'Current date and time: {time_str}'
state_description = f"""
[Task history memory ends]
[Current state starts here]
The following is one-time information - if you need to remember it write it to memory:
Current url: {self.state.url}
Available tabs:
{self.state.tabs}
Interactive elements from top layer of the current page inside the viewport:
{elements_text}
{step_info_description}
"""
if self.result:
for i, result in enumerate(self.result):
if result.extracted_content:
state_description += f'\nAction result {i + 1}/{len(self.result)}: {result.extracted_content}'
if result.error:
# only use last line of error
error = result.error.split('\n')[-1]
state_description += f'\nAction error {i + 1}/{len(self.result)}: ...{error}'
if self.state.screenshot and use_vision == True:
# Format message for vision model
return HumanMessage(
content=[
{'type': 'text', 'text': state_description},
{
'type': 'image_url',
'image_url': {'url': f'data:image/png;base64,{self.state.screenshot}'}, # , 'detail': 'low'
},
]
)
return HumanMessage(content=state_description)
class PlannerPrompt(SystemPrompt):
def get_system_message(self) -> SystemMessage:
return SystemMessage(
content="""You are a planning agent that helps break down tasks into smaller steps and reason about the current state.
Your role is to:
1. Analyze the current state and history
2. Evaluate progress towards the ultimate goal
3. Identify potential challenges or roadblocks
4. Suggest the next high-level steps to take
Inside your messages, there will be AI messages from different agents with different formats.
Your output format should be always a JSON object with the following fields:
{
"state_analysis": "Brief analysis of the current state and what has been done so far",
"progress_evaluation": "Evaluation of progress towards the ultimate goal (as percentage and description)",
"challenges": "List any potential challenges or roadblocks",
"next_steps": "List 2-3 concrete next steps to take",
"reasoning": "Explain your reasoning for the suggested next steps"
}
Ignore the other AI messages output structures.
Keep your responses concise and focused on actionable insights."""
)
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