forked from browser-use/web-ui
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathwebui.py
315 lines (285 loc) · 10.6 KB
/
webui.py
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
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
# -*- coding: utf-8 -*-
# @Time : 2025/1/1
# @Author : wenshao
# @Email : [email protected]
# @Project : browser-use-webui
# @FileName: webui.py
import pdb
from dotenv import load_dotenv
load_dotenv()
import argparse
import asyncio
import gradio as gr
import asyncio
import os
from pprint import pprint
from typing import List, Dict, Any
from playwright.async_api import async_playwright
from browser_use.browser.browser import Browser, BrowserConfig
from browser_use.browser.context import (
BrowserContext,
BrowserContextConfig,
BrowserContextWindowSize,
)
from browser_use.agent.service import Agent
from src.browser.custom_browser import CustomBrowser, BrowserConfig
from src.browser.custom_context import BrowserContext, BrowserContextConfig
from src.controller.custom_controller import CustomController
from src.agent.custom_agent import CustomAgent
from src.agent.custom_prompts import CustomSystemPrompt
from src.utils import utils
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,
task,
add_infos,
max_steps,
use_vision
):
"""
Runs the browser agent based on user configurations.
"""
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":
return 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
)
elif agent_type == "custom":
return 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,
task=task,
add_infos=add_infos,
max_steps=max_steps,
use_vision=use_vision
)
else:
raise ValueError(f"Invalid agent type: {agent_type}")
async def run_org_agent(
llm,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
task,
max_steps,
use_vision
):
browser = Browser(
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='./tmp/traces',
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:
agent = Agent(
task=task,
llm=llm,
use_vision=use_vision,
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()
await browser.close()
return final_result, errors, model_actions, model_thoughts
async def run_custom_agent(
llm,
use_own_browser,
headless,
disable_security,
window_w,
window_h,
save_recording_path,
task,
add_infos,
max_steps,
use_vision
):
controller = CustomController()
playwright = None
browser_context_ = 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", "")
browser_context_ = await playwright.chromium.launch_persistent_context(
user_data_dir=chrome_use_data,
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
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='./tmp/result_processing',
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
)
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()
except Exception as e:
import traceback
traceback.print_exc()
final_result = ""
errors = str(e) + "\n" + traceback.format_exc()
model_actions = ""
model_thoughts = ""
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()
await browser.close()
return final_result, errors, model_actions, model_thoughts
def main():
parser = argparse.ArgumentParser(description="Gradio UI for Browser Agent")
parser.add_argument("--ip", type=str, default="127.0.0.1", help="IP address to bind to")
parser.add_argument("--port", type=int, default=7788, help="Port to listen on")
args = parser.parse_args()
js_func = """
function refresh() {
const url = new URL(window.location);
if (url.searchParams.get('__theme') !== 'dark') {
url.searchParams.set('__theme', 'dark');
window.location.href = url.href;
}
}
"""
# Gradio UI setup
with gr.Blocks(title="Browser Use WebUI", theme=gr.themes.Soft(font=[gr.themes.GoogleFont("Plus Jakarta Sans")]),
js=js_func) as demo:
gr.Markdown("<center><h1>Browser Use WebUI</h1></center>")
with gr.Row():
agent_type = gr.Radio(["org", "custom"], label="Agent Type", value="custom")
max_steps = gr.Number(label="max run steps", value=100)
use_vision = gr.Checkbox(label="use vision", value=True)
with gr.Row():
llm_provider = gr.Dropdown(
["anthropic", "openai", "gemini", "azure_openai", "deepseek", "ollama"], label="LLM Provider",
value="gemini"
)
llm_model_name = gr.Textbox(label="LLM Model Name", value="gemini-2.0-flash-exp")
llm_temperature = gr.Number(label="LLM Temperature", value=1.0)
with gr.Row():
llm_base_url = gr.Textbox(label="LLM Base URL")
llm_api_key = gr.Textbox(label="LLM API Key", type="password")
with gr.Accordion("Browser Settings", open=False):
use_own_browser = gr.Checkbox(label="Use Own Browser", value=False)
headless = gr.Checkbox(label="Headless", value=False)
disable_security = gr.Checkbox(label="Disable Security", value=True)
with gr.Row():
window_w = gr.Number(label="Window Width", value=1920)
window_h = gr.Number(label="Window Height", value=1080)
save_recording_path = gr.Textbox(label="Save Recording Path", placeholder="e.g. ./tmp/record_videos",
value="./tmp/record_videos")
with gr.Accordion("Task Settings", open=True):
task = gr.Textbox(label="Task", lines=10,
value="go to google.com and type 'OpenAI' click search and give me the first url")
add_infos = gr.Textbox(label="Additional Infos(Optional): Hints to help LLM complete Task", lines=5)
run_button = gr.Button("Run Agent", variant="primary")
with gr.Column():
final_result_output = gr.Textbox(label="Final Result", lines=5)
errors_output = gr.Textbox(label="Errors", lines=5, )
model_actions_output = gr.Textbox(label="Model Actions", lines=5)
model_thoughts_output = gr.Textbox(label="Model Thoughts", lines=5)
run_button.click(
fn=run_browser_agent,
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,
task,
add_infos,
max_steps,
use_vision
],
outputs=[final_result_output, errors_output, model_actions_output, model_thoughts_output],
)
demo.launch(server_name=args.ip, server_port=args.port)
if __name__ == '__main__':
main()