Merge pull request #248 from vvincent1234/fix/deep-research
add stop button and use own browser
This commit is contained in:
warmshao
@@ -13,16 +13,18 @@ from uuid import uuid4
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from src.utils import utils
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from src.agent.custom_agent import CustomAgent
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import json
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import re
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from browser_use.agent.service import Agent
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from browser_use.browser.browser import BrowserConfig, Browser
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from langchain.schema import SystemMessage, HumanMessage
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from json_repair import repair_json
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from src.agent.custom_prompts import CustomSystemPrompt, CustomAgentMessagePrompt
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from src.controller.custom_controller import CustomController
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from src.browser.custom_browser import CustomBrowser
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logger = logging.getLogger(__name__)
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async def deep_research(task, llm, **kwargs):
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async def deep_research(task, llm, agent_state, **kwargs):
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task_id = str(uuid4())
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save_dir = kwargs.get("save_dir", os.path.join(f"./tmp/deep_research/{task_id}"))
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logger.info(f"Save Deep Research at: {save_dir}")
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@@ -113,12 +115,20 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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"""
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record_messages = [SystemMessage(content=record_system_prompt)]
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browser = Browser(
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config=BrowserConfig(
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disable_security=True,
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headless=kwargs.get("headless", False), # Set to False to see browser actions
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)
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)
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use_own_browser = kwargs.get("use_own_browser", False)
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extra_chromium_args = []
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if use_own_browser:
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# if use own browser, max query num should be 1 per iter
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max_query_num = 1
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chrome_path = os.getenv("CHROME_PATH", None)
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if chrome_path == "":
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chrome_path = None
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chrome_user_data = os.getenv("CHROME_USER_DATA", None)
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if chrome_user_data:
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extra_chromium_args += [f"--user-data-dir={chrome_user_data}"]
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else:
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chrome_path = None
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browser = None
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controller = CustomController()
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search_iteration = 0
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@@ -151,6 +161,7 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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if not query_tasks:
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break
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else:
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query_tasks = query_tasks[:max_query_num]
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history_query.extend(query_tasks)
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logger.info("Query tasks:")
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logger.info(query_tasks)
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@@ -159,6 +170,15 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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# Paralle BU agents
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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" \
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"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."
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if use_own_browser:
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browser = CustomBrowser(
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config=BrowserConfig(
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headless=kwargs.get("headless", False),
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disable_security=kwargs.get("disable_security", True),
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chrome_instance_path=chrome_path,
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extra_chromium_args=extra_chromium_args,
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)
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)
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agents = [CustomAgent(
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task=task,
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llm=llm,
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@@ -168,15 +188,24 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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system_prompt_class=CustomSystemPrompt,
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agent_prompt_class=CustomAgentMessagePrompt,
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max_actions_per_step=5,
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controller=controller
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controller=controller,
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agent_state=agent_state
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) for task in query_tasks]
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query_results = await asyncio.gather(*[agent.run(max_steps=kwargs.get("max_steps", 10)) for agent in agents])
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if browser:
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await browser.close()
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browser = None
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logger.info("Browser closed.")
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if agent_state and agent_state.is_stop_requested():
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# Stop
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break
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# 3. Summarize Search Result
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query_result_dir = os.path.join(save_dir, "query_results")
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os.makedirs(query_result_dir, exist_ok=True)
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for i in range(len(query_tasks)):
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query_result = query_results[i].final_result()
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if not query_result:
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continue
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querr_save_path = os.path.join(query_result_dir, f"{search_iteration}-{i}.md")
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logger.info(f"save query: {query_tasks[i]} at {querr_save_path}")
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with open(querr_save_path, "w", encoding="utf-8") as fw:
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@@ -244,7 +273,9 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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logger.info(ai_report_msg.reasoning_content)
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logger.info("🤯 End Report Deep Thinking")
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report_content = ai_report_msg.content
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# Remove ```markdown or ``` at the *very beginning* and ``` at the *very end*, with optional whitespace
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report_content = re.sub(r"^```\s*markdown\s*|^\s*```|```\s*$", "", report_content, flags=re.MULTILINE)
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report_content = report_content.strip()
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report_file_path = os.path.join(save_dir, "final_report.md")
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with open(report_file_path, "w", encoding="utf-8") as f:
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f.write(report_content)
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@@ -257,4 +288,5 @@ Provide your output as a JSON formatted list. Each item in the list must adhere
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finally:
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if browser:
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await browser.close()
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browser = None
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logger.info("Browser closed.")
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154
webui.py
154
webui.py
@@ -69,6 +69,31 @@ async def stop_agent():
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gr.update(value="Stop", interactive=True),
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gr.update(interactive=True)
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)
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async def stop_research_agent():
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"""Request the agent to stop and update UI with enhanced feedback"""
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global _global_agent_state, _global_browser_context, _global_browser
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try:
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# Request stop
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_global_agent_state.request_stop()
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# Update UI immediately
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message = "Stop requested - the agent will halt at the next safe point"
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logger.info(f"🛑 {message}")
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# Return UI updates
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return ( # errors_output
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gr.update(value="Stopping...", interactive=False), # stop_button
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gr.update(interactive=False), # run_button
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)
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except Exception as e:
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error_msg = f"Error during stop: {str(e)}"
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logger.error(error_msg)
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return (
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gr.update(value="Stop", interactive=True),
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gr.update(interactive=True)
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)
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async def run_browser_agent(
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agent_type,
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@@ -598,8 +623,12 @@ async def close_global_browser():
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await _global_browser.close()
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_global_browser = None
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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):
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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):
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from src.utils.deep_research import deep_research
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global _global_agent_state
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# Clear any previous stop request
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_global_agent_state.clear_stop()
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llm = utils.get_llm_model(
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provider=llm_provider,
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@@ -608,12 +637,15 @@ async def run_deep_search(research_task, max_search_iteration_input, max_query_p
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base_url=llm_base_url,
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api_key=llm_api_key,
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)
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markdown_content, file_path = await deep_research(research_task, llm,
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markdown_content, file_path = await deep_research(research_task, llm, _global_agent_state,
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max_search_iterations=max_search_iteration_input,
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max_query_num=max_query_per_iter_input,
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use_vision=use_vision,
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headless=headless)
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return markdown_content, file_path
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headless=headless,
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use_own_browser=use_own_browser
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)
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return markdown_content, file_path, gr.update(value="Stop", interactive=True), gr.update(interactive=True)
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def create_ui(config, theme_name="Ocean"):
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@@ -815,58 +847,18 @@ def create_ui(config, theme_name="Ocean"):
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label="Live Browser View",
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)
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with gr.TabItem("🧐 Deep Research"):
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with gr.Group():
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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.")
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with gr.Row():
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max_search_iteration_input = gr.Number(label="Max Search Iteration", value=20, precision=0) # precision=0 确保是整数
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max_query_per_iter_input = gr.Number(label="Max Query per Iteration", value=5, precision=0) # precision=0 确保是整数
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research_button = gr.Button("Run Deep Research")
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markdown_output_display = gr.Markdown(label="Research Report")
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markdown_download = gr.File(label="Download Research Report")
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with gr.TabItem("🧐 Deep Research", id=5):
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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.")
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with gr.Row():
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max_search_iteration_input = gr.Number(label="Max Search Iteration", value=20, precision=0) # precision=0 确保是整数
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max_query_per_iter_input = gr.Number(label="Max Query per Iteration", value=5, precision=0) # precision=0 确保是整数
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with gr.Row():
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research_button = gr.Button("▶️ Run Deep Research", variant="primary", scale=2)
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stop_research_button = gr.Button("⏹️ Stop", variant="stop", scale=1)
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markdown_output_display = gr.Markdown(label="Research Report")
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markdown_download = gr.File(label="Download Research Report")
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with gr.TabItem("📁 Configuration", id=5):
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with gr.Group():
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config_file_input = gr.File(
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label="Load Config File",
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file_types=[".pkl"],
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interactive=True
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)
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load_config_button = gr.Button("Load Existing Config From File", variant="primary")
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save_config_button = gr.Button("Save Current Config", variant="primary")
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config_status = gr.Textbox(
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label="Status",
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lines=2,
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interactive=False
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)
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load_config_button.click(
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fn=update_ui_from_config,
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inputs=[config_file_input],
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outputs=[
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agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
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llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
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use_own_browser, keep_browser_open, headless, disable_security, enable_recording,
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window_w, window_h, save_recording_path, save_trace_path, save_agent_history_path,
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task, config_status
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]
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)
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save_config_button.click(
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fn=save_current_config,
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inputs=[
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agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
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llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
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use_own_browser, keep_browser_open, headless, disable_security,
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enable_recording, window_w, window_h, save_recording_path, save_trace_path,
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save_agent_history_path, task,
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],
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outputs=[config_status]
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)
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with gr.TabItem("📊 Results", id=6):
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with gr.Group():
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@@ -929,9 +921,15 @@ def create_ui(config, theme_name="Ocean"):
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# Run Deep Research
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research_button.click(
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fn=run_deep_search,
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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],
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outputs=[markdown_output_display, markdown_download]
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)
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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],
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outputs=[markdown_output_display, markdown_download, stop_research_button, research_button]
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)
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# Bind the stop button click event after errors_output is defined
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stop_research_button.click(
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fn=stop_research_agent,
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inputs=[],
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outputs=[stop_research_button, research_button],
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)
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with gr.TabItem("🎥 Recordings", id=7):
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def list_recordings(save_recording_path):
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@@ -966,6 +964,48 @@ def create_ui(config, theme_name="Ocean"):
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inputs=save_recording_path,
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outputs=recordings_gallery
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)
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with gr.TabItem("📁 Configuration", id=8):
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with gr.Group():
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config_file_input = gr.File(
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label="Load Config File",
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file_types=[".pkl"],
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interactive=True
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)
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load_config_button = gr.Button("Load Existing Config From File", variant="primary")
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save_config_button = gr.Button("Save Current Config", variant="primary")
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config_status = gr.Textbox(
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label="Status",
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lines=2,
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interactive=False
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)
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load_config_button.click(
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fn=update_ui_from_config,
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inputs=[config_file_input],
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outputs=[
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agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
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llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
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use_own_browser, keep_browser_open, headless, disable_security, enable_recording,
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window_w, window_h, save_recording_path, save_trace_path, save_agent_history_path,
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task, config_status
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]
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)
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save_config_button.click(
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fn=save_current_config,
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inputs=[
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agent_type, max_steps, max_actions_per_step, use_vision, tool_calling_method,
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llm_provider, llm_model_name, llm_temperature, llm_base_url, llm_api_key,
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use_own_browser, keep_browser_open, headless, disable_security,
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enable_recording, window_w, window_h, save_recording_path, save_trace_path,
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save_agent_history_path, task,
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],
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outputs=[config_status]
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)
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# Attach the callback to the LLM provider dropdown
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llm_provider.change(
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