alihan/browser-use-web-ui
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

add stop button and use own browser

Browse Source
This commit is contained in:
vincent
2025-02-07 22:28:10 +08:00
parent 037f8e5cc0
commit fbd748e1b9
2 changed files with 139 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

52
src/utils/deep_research.py
View File

@@ -13,16 +13,18 @@ from uuid import uuid4
from src.utils import utils
from src.agent.custom_agent import CustomAgent
import json
import re
from browser_use.agent.service import Agent
from browser_use.browser.browser import BrowserConfig, Browser
from langchain.schema import SystemMessage, HumanMessage
from json_repair import repair_json
from src.agent.custom_prompts import CustomSystemPrompt, CustomAgentMessagePrompt
from src.controller.custom_controller import CustomController
from src.browser.custom_browser import CustomBrowser
logger = logging.getLogger(__name__)
async def deep_research(task, llm, **kwargs):
async def deep_research(task, llm, agent_state, **kwargs):
task_id = str(uuid4())
save_dir = kwargs.get("save_dir", os.path.join(f"./tmp/deep_research/{task_id}"))
logger.info(f"Save Deep Research at: {save_dir}")
@@ -113,12 +115,20 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
"""
record_messages = [SystemMessage(content=record_system_prompt)]
browser = Browser(
config=BrowserConfig(
disable_security=True,
headless=kwargs.get("headless", False), # Set to False to see browser actions
)
)
use_own_browser = kwargs.get("use_own_browser", False)
extra_chromium_args = []
if use_own_browser:
# if use own browser, max query num should be 1 per iter
max_query_num = 1
chrome_path = os.getenv("CHROME_PATH", None)
if chrome_path == "":
chrome_path = None
chrome_user_data = os.getenv("CHROME_USER_DATA", None)
if chrome_user_data:
extra_chromium_args += [f"--user-data-dir={chrome_user_data}"]
else:
chrome_path = None
browser = None
controller = CustomController()
search_iteration = 0
@@ -151,6 +161,7 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
if not query_tasks:
break
else:
query_tasks = query_tasks[:max_query_num]
history_query.extend(query_tasks)
logger.info("Query tasks:")
logger.info(query_tasks)
@@ -159,6 +170,15 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
# Paralle BU agents
add_infos = "1. Please click on the most relevant link to get information and go deeper, instead of just staying on the search page. \n" \
"2. When opening a PDF file, please remember to extract the content using extract_content instead of simply opening it for the user to view."
if use_own_browser:
browser = CustomBrowser(
config=BrowserConfig(
headless=kwargs.get("headless", False),
disable_security=kwargs.get("disable_security", True),
chrome_instance_path=chrome_path,
extra_chromium_args=extra_chromium_args,
)
)
agents = [CustomAgent(
task=task,
llm=llm,
@@ -168,15 +188,24 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
system_prompt_class=CustomSystemPrompt,
agent_prompt_class=CustomAgentMessagePrompt,
max_actions_per_step=5,
controller=controller
controller=controller,
agent_state=agent_state
) for task in query_tasks]
query_results = await asyncio.gather(*[agent.run(max_steps=kwargs.get("max_steps", 10)) for agent in agents])
if browser:
await browser.close()
browser = None
logger.info("Browser closed.")
if agent_state and agent_state.is_stop_requested():
# Stop
break
# 3. Summarize Search Result
query_result_dir = os.path.join(save_dir, "query_results")
os.makedirs(query_result_dir, exist_ok=True)
for i in range(len(query_tasks)):
query_result = query_results[i].final_result()
if not query_result:
continue
querr_save_path = os.path.join(query_result_dir, f"{search_iteration}-{i}.md")
logger.info(f"save query: {query_tasks[i]} at {querr_save_path}")
with open(querr_save_path, "w", encoding="utf-8") as fw:
@@ -244,7 +273,9 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
logger.info(ai_report_msg.reasoning_content)
logger.info("🤯 End Report Deep Thinking")
report_content = ai_report_msg.content
# Remove ```markdown or ``` at the *very beginning* and ``` at the *very end*, with optional whitespace
report_content = re.sub(r"^```\s*markdown\s*|^\s*```|```\s*$", "", report_content, flags=re.MULTILINE)
report_content = report_content.strip()
report_file_path = os.path.join(save_dir, "final_report.md")
with open(report_file_path, "w", encoding="utf-8") as f:
f.write(report_content)
@@ -257,4 +288,5 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
finally:
if browser:
await browser.close()
browser = None
logger.info("Browser closed.")

154
webui.py
View File

@@ -69,6 +69,31 @@ async def stop_agent():
gr.update(value="Stop", interactive=True),
gr.update(interactive=True)
)
async def stop_research_agent():
"""Request the agent to stop and update UI with enhanced feedback"""
global _global_agent_state, _global_browser_context, _global_browser
try:
# Request stop
_global_agent_state.request_stop()
# Update UI immediately
message = "Stop requested - the agent will halt at the next safe point"
logger.info(f"🛑 {message}")
# Return UI updates
return ( # errors_output
gr.update(value="Stopping...", interactive=False), # stop_button
gr.update(interactive=False), # run_button
)
except Exception as e:
error_msg = f"Error during stop: {str(e)}"
logger.error(error_msg)
return (
gr.update(value="Stop", interactive=True),
gr.update(interactive=True)
)
async def run_browser_agent(
agent_type,
@@ -598,8 +623,12 @@ async def close_global_browser():
await _global_browser.close()
_global_browser = None
async def run_deep_search(research_task, max_search_iteration_input, max_query_per_iter_input, llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key, use_vision, headless):
async def run_deep_search(research_task, max_search_iteration_input, max_query_per_iter_input, llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key, use_vision, use_own_browser, headless):
from src.utils.deep_research import deep_research
global _global_agent_state
# Clear any previous stop request
_global_agent_state.clear_stop()
llm = utils.get_llm_model(
provider=llm_provider,
@@ -608,12 +637,15 @@ async def run_deep_search(research_task, max_search_iteration_input, max_query_p
base_url=llm_base_url,
api_key=llm_api_key,
)
markdown_content, file_path = await deep_research(research_task, llm,
markdown_content, file_path = await deep_research(research_task, llm, _global_agent_state,
max_search_iterations=max_search_iteration_input,
max_query_num=max_query_per_iter_input,
use_vision=use_vision,
headless=headless)
return markdown_content, file_path
headless=headless,
use_own_browser=use_own_browser
)
return markdown_content, file_path, gr.update(value="Stop", interactive=True), gr.update(interactive=True)
def create_ui(config, theme_name="Ocean"):
@@ -815,58 +847,18 @@ def create_ui(config, theme_name="Ocean"):
label="Live Browser View",
)
with gr.TabItem("🧐 Deep Research"):
with gr.Group():
research_task_input = gr.Textbox(label="Research Task", lines=5, value="Compose a report on the use of Reinforcement Learning for training Large Language Models, encompassing its origins, current advancements, and future prospects, substantiated with examples of relevant models and techniques. The report should reflect original insights and analysis, moving beyond mere summarization of existing literature.")
with gr.Row():
max_search_iteration_input = gr.Number(label="Max Search Iteration", value=20, precision=0) # precision=0 确保是整数
max_query_per_iter_input = gr.Number(label="Max Query per Iteration", value=5, precision=0) # precision=0 确保是整数
research_button = gr.Button("Run Deep Research")
markdown_output_display = gr.Markdown(label="Research Report")
markdown_download = gr.File(label="Download Research Report")
with gr.TabItem("🧐 Deep Research", id=5):
research_task_input = gr.Textbox(label="Research Task", lines=5, value="Compose a report on the use of Reinforcement Learning for training Large Language Models, encompassing its origins, current advancements, and future prospects, substantiated with examples of relevant models and techniques. The report should reflect original insights and analysis, moving beyond mere summarization of existing literature.")
with gr.Row():
max_search_iteration_input = gr.Number(label="Max Search Iteration", value=20, precision=0) # precision=0 确保是整数
max_query_per_iter_input = gr.Number(label="Max Query per Iteration", value=5, precision=0) # precision=0 确保是整数
with gr.Row():
research_button = gr.Button("▶️ Run Deep Research", variant="primary", scale=2)
stop_research_button = gr.Button("⏹️ Stop", variant="stop", scale=1)
markdown_output_display = gr.Markdown(label="Research Report")
markdown_download = gr.File(label="Download Research Report")
with gr.TabItem("📁 Configuration", id=5):
with gr.Group():
config_file_input = gr.File(
label="Load Config File",
file_types=[".pkl"],
interactive=True
)
load_config_button = gr.Button("Load Existing Config From File", variant="primary")
save_config_button = gr.Button("Save Current Config", variant="primary")
config_status = gr.Textbox(
label="Status",
lines=2,
interactive=False
)
load_config_button.click(
fn=update_ui_from_config,
inputs=[config_file_input],
outputs=[
agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
use_own_browser, keep_browser_open, headless, disable_security, enable_recording,
window_w, window_h, save_recording_path, save_trace_path, save_agent_history_path,
task, config_status
]
)
save_config_button.click(
fn=save_current_config,
inputs=[
agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
use_own_browser, keep_browser_open, headless, disable_security,
enable_recording, window_w, window_h, save_recording_path, save_trace_path,
save_agent_history_path, task,
],
outputs=[config_status]
)
with gr.TabItem("📊 Results", id=6):
with gr.Group():
@@ -929,9 +921,15 @@ def create_ui(config, theme_name="Ocean"):
# Run Deep Research
research_button.click(
fn=run_deep_search,
inputs=[research_task_input, max_search_iteration_input, max_query_per_iter_input, llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key, use_vision, headless],
outputs=[markdown_output_display, markdown_download]
)
inputs=[research_task_input, max_search_iteration_input, max_query_per_iter_input, llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key, use_vision, use_own_browser, headless],
outputs=[markdown_output_display, markdown_download, stop_research_button, research_button]
)
# Bind the stop button click event after errors_output is defined
stop_research_button.click(
fn=stop_research_agent,
inputs=[],
outputs=[stop_research_button, research_button],
)
with gr.TabItem("🎥 Recordings", id=7):
def list_recordings(save_recording_path):
@@ -966,6 +964,48 @@ def create_ui(config, theme_name="Ocean"):
inputs=save_recording_path,
outputs=recordings_gallery
)
with gr.TabItem("📁 Configuration", id=8):
with gr.Group():
config_file_input = gr.File(
label="Load Config File",
file_types=[".pkl"],
interactive=True
)
load_config_button = gr.Button("Load Existing Config From File", variant="primary")
save_config_button = gr.Button("Save Current Config", variant="primary")
config_status = gr.Textbox(
label="Status",
lines=2,
interactive=False
)
load_config_button.click(
fn=update_ui_from_config,
inputs=[config_file_input],
outputs=[
agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
use_own_browser, keep_browser_open, headless, disable_security, enable_recording,
window_w, window_h, save_recording_path, save_trace_path, save_agent_history_path,
task, config_status
]
)
save_config_button.click(
fn=save_current_config,
inputs=[
agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
use_own_browser, keep_browser_open, headless, disable_security,
enable_recording, window_w, window_h, save_recording_path, save_trace_path,
save_agent_history_path, task,
],
outputs=[config_status]
)
# Attach the callback to the LLM provider dropdown
llm_provider.change(