Files
browser-use-web-ui/webui.py
2025-01-10 01:58:47 +07:00

678 lines
25 KiB
Python

# -*- coding: utf-8 -*-
# @Time : 2025/1/1
# @Author : wenshao
# @Email : wenshaoguo1026@gmail.com
# @Project : browser-use-webui
# @FileName: webui.py
import pdb
import glob
from dotenv import load_dotenv
load_dotenv()
import argparse
import gradio as gr
import os
import asyncio
from playwright.async_api import async_playwright
from browser_use.browser.browser import Browser, BrowserConfig
from browser_use.browser.context import (
BrowserContextConfig,
BrowserContextWindowSize,
)
from browser_use.agent.service import Agent
from src.browser.custom_browser import CustomBrowser
from src.controller.custom_controller import CustomController
from src.agent.custom_agent import CustomAgent
from src.agent.custom_prompts import CustomSystemPrompt
from src.browser.custom_browser import CustomBrowser
from src.browser.custom_context import BrowserContextConfig
from src.controller.custom_controller import CustomController
from src.utils import utils
from src.utils.utils import update_model_dropdown
from src.utils.file_utils import get_latest_files
from src.utils.stream_utils import capture_screenshot
async def run_browser_agent(
agent_type,
llm_provider,
llm_model_name,
llm_temperature,
llm_base_url,
llm_api_key,
use_own_browser,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
save_trace_path,
enable_recording,
task,
add_infos,
max_steps,
use_vision,
max_actions_per_step,
tool_call_in_content,
browser_context=None
):
"""Run the browser agent with proper browser context initialization"""
browser = None
try:
# Run the agent
llm = utils.get_llm_model(
provider=llm_provider,
model_name=llm_model_name,
temperature=llm_temperature,
base_url=llm_base_url,
api_key=llm_api_key,
)
if agent_type == "org":
result = await run_org_agent(
llm=llm,
headless=headless,
disable_security=disable_security,
window_w=window_w,
window_h=window_h,
save_recording_path=save_recording_path,
task=task,
max_steps=max_steps,
use_vision=use_vision,
max_actions_per_step=max_actions_per_step,
tool_call_in_content=tool_call_in_content,
browser_context=browser_context,
)
elif agent_type == "custom":
result = await run_custom_agent(
llm=llm,
use_own_browser=use_own_browser,
headless=headless,
disable_security=disable_security,
window_w=window_w,
window_h=window_h,
save_recording_path=save_recording_path,
save_trace_path=save_trace_path,
task=task,
add_infos=add_infos,
max_steps=max_steps,
use_vision=use_vision,
max_actions_per_step=max_actions_per_step,
tool_call_in_content=tool_call_in_content,
browser_context=browser_context,
)
else:
raise ValueError(f"Invalid agent type: {agent_type}")
return result
finally:
if browser:
await browser.close()
async def run_org_agent(
llm,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
save_trace_path,
task,
max_steps,
use_vision,
max_actions_per_step,
tool_call_in_content,
browser_context=None, # receive context
):
browser = None
if browser_context is None:
browser = Browser(
config=BrowserConfig(
headless=headless, # Force non-headless for streaming
disable_security=disable_security,
extra_chromium_args=[f'--window-size={window_w},{window_h}'],
)
)
async with await browser.new_context(
config=BrowserContextConfig(
trace_path=save_trace_path if save_trace_path else None,
save_recording_path=save_recording_path if save_recording_path else None,
no_viewport=False,
browser_window_size=BrowserContextWindowSize(width=window_w, height=window_h),
)
) as browser_context_in:
agent = Agent(
task=task,
llm=llm,
use_vision=use_vision,
browser_context=browser_context_in,
)
history = await agent.run(max_steps=max_steps)
final_result = history.final_result()
errors = history.errors()
model_actions = history.model_actions()
model_thoughts = history.model_thoughts()
recorded_files = get_latest_files(save_recording_path)
trace_file = get_latest_files(save_recording_path + "/../traces")
await browser.close()
return final_result, errors, model_actions, model_thoughts, recorded_files.get('.webm'), trace_file.get('.zip')
else:
# Reuse existing context
agent = Agent(
task=task,
llm=llm,
use_vision=use_vision,
max_actions_per_step=max_actions_per_step,
browser_context=browser_context,
)
history = await agent.run(max_steps=max_steps)
final_result = history.final_result()
errors = history.errors()
model_actions = history.model_actions()
model_thoughts = history.model_thoughts()
recorded_files = get_latest_files(save_recording_path)
trace_file = get_latest_files(save_recording_path + "/../traces")
return final_result, errors, model_actions, model_thoughts, recorded_files.get('.webm'), trace_file.get('.zip')
async def run_custom_agent(
llm,
use_own_browser,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
save_trace_path,
task,
add_infos,
max_steps,
use_vision,
max_actions_per_step,
tool_call_in_content,
browser_context=None, # receive context
):
controller = CustomController()
playwright = None
browser = None
try:
if use_own_browser:
playwright = await async_playwright().start()
chrome_exe = os.getenv("CHROME_PATH", "")
chrome_use_data = os.getenv("CHROME_USER_DATA", "")
if chrome_exe == "":
chrome_exe = None
elif not os.path.exists(chrome_exe):
raise ValueError(f"Chrome executable not found at {chrome_exe}")
if chrome_use_data == "":
chrome_use_data = None
browser_context_ = await playwright.chromium.launch_persistent_context(
user_data_dir=chrome_use_data if chrome_use_data else "",
executable_path=chrome_exe,
no_viewport=False,
headless=headless, # 保持浏览器窗口可见
user_agent=(
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/85.0.4183.102 Safari/537.36"
),
java_script_enabled=True,
bypass_csp=disable_security,
ignore_https_errors=disable_security,
record_video_dir=save_recording_path if save_recording_path else None,
record_video_size={"width": window_w, "height": window_h},
)
else:
browser_context_ = None
if browser_context is not None:
# Reuse context
agent = CustomAgent(
task=task,
add_infos=add_infos,
use_vision=use_vision,
llm=llm,
browser_context=browser_context,
controller=controller,
system_prompt_class=CustomSystemPrompt
)
history = await agent.run(max_steps=max_steps)
final_result = history.final_result()
errors = history.errors()
model_actions = history.model_actions()
model_thoughts = history.model_thoughts()
recorded_files = get_latest_files(save_recording_path)
trace_file = get_latest_files(save_recording_path + "/../traces")
return final_result, errors, model_actions, model_thoughts, recorded_files.get('.webm'), trace_file.get('.zip')
else:
browser = CustomBrowser(
config=BrowserConfig(
headless=headless,
disable_security=disable_security,
extra_chromium_args=[f"--window-size={window_w},{window_h}"],
)
)
async with await browser.new_context(
config=BrowserContextConfig(
trace_path=save_trace_path if save_trace_path else None,
save_recording_path=save_recording_path
if save_recording_path
else None,
no_viewport=False,
browser_window_size=BrowserContextWindowSize(
width=window_w, height=window_h
),
),
context=browser_context_,
) as browser_context:
agent = CustomAgent(
task=task,
add_infos=add_infos,
use_vision=use_vision,
llm=llm,
browser_context=browser_context,
controller=controller,
system_prompt_class=CustomSystemPrompt,
max_actions_per_step=max_actions_per_step,
tool_call_in_content=tool_call_in_content
)
history = await agent.run(max_steps=max_steps)
final_result = history.final_result()
errors = history.errors()
model_actions = history.model_actions()
model_thoughts = history.model_thoughts()
recorded_files = get_latest_files(save_recording_path)
trace_file = get_latest_files(save_recording_path + "/../traces")
return final_result, errors, model_actions, model_thoughts, recorded_files.get('.webm'), trace_file.get('.zip')
except Exception as e:
import traceback
traceback.print_exc()
final_result = ""
errors = str(e) + "\n" + traceback.format_exc()
model_actions = ""
model_thoughts = ""
recorded_files = {}
trace_file = {}
finally:
# 显式关闭持久化上下文
if browser_context_:
await browser_context_.close()
# 关闭 Playwright 对象
if playwright:
await playwright.stop()
if browser:
await browser.close()
return final_result, errors, model_actions, model_thoughts, trace_file.get('.webm'), recorded_files.get('.zip')
async def run_with_stream(
agent_type,
llm_provider,
llm_model_name,
llm_temperature,
llm_base_url,
llm_api_key,
use_own_browser,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
save_trace_path,
enable_recording,
task,
add_infos,
max_steps,
use_vision,
max_actions_per_step,
tool_call_in_content,
):
"""Wrapper to run the agent and handle streaming."""
browser = None
try:
# Initialize the browser
browser = CustomBrowser(
config=BrowserConfig(
headless=False,
disable_security=disable_security,
extra_chromium_args=[f"--window-size={window_w},{window_h}"],
)
)
# Create a new browser context
async with await browser.new_context(
config=BrowserContextConfig(
trace_path=save_trace_path if save_trace_path else None,
save_recording_path=save_recording_path if save_recording_path else None,
no_viewport=False,
browser_window_size=BrowserContextWindowSize(
width=window_w, height=window_h
),
)
) as browser_context:
# Run the browser agent in the background
agent_task = asyncio.create_task(
run_browser_agent(
agent_type=agent_type,
llm_provider=llm_provider,
llm_model_name=llm_model_name,
llm_temperature=llm_temperature,
llm_base_url=llm_base_url,
llm_api_key=llm_api_key,
use_own_browser=use_own_browser,
headless=headless,
disable_security=disable_security,
window_w=window_w,
window_h=window_h,
save_recording_path=save_recording_path,
save_trace_path=save_trace_path,
enable_recording=enable_recording,
task=task,
add_infos=add_infos,
max_steps=max_steps,
use_vision=use_vision,
max_actions_per_step=max_actions_per_step,
tool_call_in_content=tool_call_in_content,
browser_context=browser_context # Explicit keyword argument
)
)
# Initialize values for streaming
html_content = "<div>Starting browser...</div>"
final_result = errors = model_actions = model_thoughts = ""
recording = trace = None
# Periodically update the stream while the agent task is running
while not agent_task.done():
try:
html_content = await capture_screenshot(browser_context)
except Exception as e:
html_content = f"<div class='error'>Screenshot error: {str(e)}</div>"
yield [
html_content,
final_result,
errors,
model_actions,
model_thoughts,
recording,
trace,
]
await asyncio.sleep(0.01)
# Once the agent task completes, get the results
try:
result = await agent_task
if isinstance(result, tuple) and len(result) == 6:
(
final_result,
errors,
model_actions,
model_thoughts,
recording,
trace,
) = result
else:
errors = "Unexpected result format from agent"
except Exception as e:
errors = f"Agent error: {str(e)}"
yield [
html_content,
final_result,
errors,
model_actions,
model_thoughts,
recording,
trace,
]
except Exception as e:
import traceback
yield [
f"<div class='error'>Browser error: {str(e)}</div>",
"",
f"Error: {str(e)}\n{traceback.format_exc()}",
"",
"",
None,
None,
]
finally:
if browser:
await browser.close()
from gradio.themes import Citrus, Default, Glass, Monochrome, Ocean, Origin, Soft, Base
# Define the theme map globally
theme_map = {
"Default": Default(),
"Soft": Soft(),
"Monochrome": Monochrome(),
"Glass": Glass(),
"Origin": Origin(),
"Citrus": Citrus(),
"Ocean": Ocean(),
"Base": Base()
}
# Create the Gradio UI
def create_ui(theme_name="Ocean"):
css = """
.gradio-container {
max-width: 1200px !important;
margin: auto !important;
padding-top: 20px !important;
}
.header-text {
text-align: center;
margin-bottom: 30px;
}
.theme-section {
margin-bottom: 20px;
padding: 15px;
border-radius: 10px;
}
"""
with gr.Blocks(title="Browser Use WebUI", theme=theme_map[theme_name], css=css) as demo:
# Header
with gr.Row():
gr.Markdown(
"""
# 🌐 Browser Use WebUI
### Control your browser with AI assistance
""",
elem_classes=["header-text"],
)
with gr.Tabs() as tabs:
with gr.TabItem("⚙️ Agent Settings", id=1):
with gr.Group():
agent_type = gr.Radio(
["org", "custom"],
label="Agent Type",
value="custom",
info="Select the type of agent to use",
)
max_steps = gr.Slider(
minimum=1,
maximum=200,
value=100,
step=1,
label="Max Run Steps",
info="Maximum number of steps the agent will take",
)
max_actions_per_step = gr.Slider(
minimum=1,
maximum=20,
value=10,
step=1,
label="Max Actions per Step",
info="Maximum number of actions the agent will take per step",
)
use_vision = gr.Checkbox(
label="Use Vision",
value=True,
info="Enable visual processing capabilities",
)
tool_call_in_content = gr.Checkbox(
label="Use Tool Calls in Content",
value=True,
info="Enable Tool Calls in content",
)
with gr.TabItem("🔧 LLM Configuration", id=2):
with gr.Group():
llm_provider = gr.Dropdown(
["anthropic", "openai", "deepseek", "gemini", "ollama", "azure_openai"],
label="LLM Provider",
value="",
info="Select your preferred language model provider"
)
llm_model_name = gr.Dropdown(
label="Model Name",
value="",
interactive=True,
allow_custom_value=True, # Allow users to input custom model names
info="Select a model from the dropdown or type a custom model name"
)
llm_temperature = gr.Slider(
minimum=0.0,
maximum=2.0,
value=1.0,
step=0.1,
label="Temperature",
info="Controls randomness in model outputs"
)
with gr.Row():
llm_base_url = gr.Textbox(
label="Base URL",
value=os.getenv(f"{llm_provider.value.upper()}_BASE_URL ", ""), # Default to .env value
info="API endpoint URL (if required)"
)
llm_api_key = gr.Textbox(
label="API Key",
type="password",
value=os.getenv(f"{llm_provider.value.upper()}_API_KEY", ""), # Default to .env value
info="Your API key (leave blank to use .env)"
)
with gr.TabItem("🌐 Browser Settings", id=3):
with gr.Group():
with gr.Row():
use_own_browser = gr.Checkbox(
label="Use Own Browser",
value=False,
info="Use your existing browser instance",
)
headless = gr.Checkbox(
label="Headless Mode",
value=False,
info="Run browser without GUI",
)
disable_security = gr.Checkbox(
label="Disable Security",
value=True,
info="Disable browser security features",
)
enable_recording = gr.Checkbox(
label="Enable Recording",
value=True,
info="Enable saving browser recordings",
)
with gr.Row():
window_w = gr.Number(
label="Window Width",
value=1280,
info="Browser window width",
)
window_h = gr.Number(
label="Window Height",
value=1100,
info="Browser window height",
)
save_recording_path = gr.Textbox(
label="Recording Path",
placeholder="e.g. ./tmp/record_videos",
value="./tmp/record_videos",
info="Path to save browser recordings",
interactive=True, # Allow editing only if recording is enabled
)
save_trace_path = gr.Textbox(
label="Trace Path",
placeholder="e.g. ./tmp/traces",
value="./tmp/traces",
info="Path to save Agent traces",
interactive=True,
)
with gr.TabItem("🤖 Run Agent", id=4):
task = gr.Textbox(
lines=4,
value="go to google.com and type 'OpenAI' click search and give me the first url",
info="Describe what you want the agent to do",
)
add_infos = gr.Textbox(lines=3, label="Additional Information")
# Results
with gr.Tab("📊 Results"):
browser_view = gr.HTML(
value="<div>Waiting for browser session...</div>",
label="Live Browser View",
)
final_result_output = gr.Textbox(label="Final Result", lines=3)
errors_output = gr.Textbox(label="Errors", lines=3)
model_actions_output = gr.Textbox(label="Model Actions", lines=3)
model_thoughts_output = gr.Textbox(label="Model Thoughts", lines=3)
recording_file = gr.Video(label="Latest Recording")
trace_file = gr.File(label="Trace File")
with gr.Row():
run_button = gr.Button("▶️ Run Agent", variant="primary")
# Button logic
run_button.click(
fn=run_with_stream,
inputs=[
agent_type, llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
use_own_browser, headless, disable_security, window_w, window_h, save_recording_path, save_trace_path,
enable_recording, task, add_infos, max_steps, use_vision, max_actions_per_step, tool_call_in_content
],
outputs=[
browser_view,
final_result_output,
errors_output,
model_actions_output,
model_thoughts_output,
recording_file,
trace_file
],
queue=True,
)
return demo
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="Gradio UI for Browser Agent")
parser.add_argument("--ip", type=str, default="0.0.0.0", help="IP address to bind to")
parser.add_argument("--port", type=int, default=7860, help="Port to listen on")
parser.add_argument("--theme", type=str, default="Ocean", choices=theme_map.keys())
args = parser.parse_args()
ui = create_ui(theme_name=args.theme)
ui.launch(server_name=args.ip, server_port=args.port, share=True)