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| 2025-03-08 21:53:38.593 | DEBUG | camel.toolkits.web_toolkit:browser_simulation:1047 - Detailed plan: ### Restated Task:
The task is to visit the webpage `https://www.secondstate.io/articles/infra-for-llms/` and extract relevant information about Rust's ecosystem and its development in large language models (LLMs) over the past year. The process should be considered as a Partially Observable Markov Decision Process (POMDP), meaning that not all information may be directly observable, and decisions must be made based on partial information.
### Detailed Plan:
#### Step 1: Access the Webpage
- **Action:** Navigate to the URL `https://www.secondstate.io/articles/infra-for-llms/`.
- **Observation:** Confirm that the page has loaded successfully and identify the main sections of the article.
- **Decision Point:** If the page does not load or if there are issues accessing the content, consider alternative actions such as refreshing the page or checking for network connectivity.
#### Step 2: Scan the Article for Relevant Sections
- **Action:** Perform a quick scan of the article by looking at headings, subheadings, and any highlighted text that might relate to Rust's ecosystem and LLMs.
- **Observation:** Identify sections that mention Rust, its ecosystem, and developments related to LLMs.
- **Decision Point:** If no relevant sections are immediately apparent, consider using the browser's search function (Ctrl+F) to look for keywords like "Rust," "ecosystem," "development," and "large models."
#### Step 3: Extract Information
- **Action:** Carefully read through the identified sections and extract pertinent information. Look for details about how Rust has been used in developing LLMs, any new tools or libraries introduced, performance improvements, community contributions, and other relevant advancements.
- **Observation:** Take notes of specific points, dates, statistics, and quotes that highlight Rust's role and progress in the field of LLMs over the past year.
- **Decision Point:** If the information is scattered or not clearly presented, decide whether to continue searching within the article or to seek additional sources for more comprehensive data.
#### Step 4: Summarize Findings
- **Action:** Compile the extracted information into a coherent summary. Ensure that the summary covers the key aspects of Rust's ecosystem and its development in LLMs over the past year.
- **Observation:** Review the summary to ensure it accurately reflects the findings from the article and provides a clear understanding of Rust's contributions to LLMs.
- **Decision Point:** If the summary seems incomplete or lacks depth, revisit the article or consider consulting other resources to fill in any gaps.
#### Step 5: Validate and Report
- **Action:** Double-check the accuracy of the summarized information against the original article. Prepare the final report or presentation of the findings.
- **Observation:** Ensure that all claims are supported by evidence from the article and that the report is well-organized and easy to understand.
- **Decision Point:** Before finalizing the report, consider having it reviewed by a peer or expert to catch any potential errors or omissions.
By following this plan, we can systematically approach the task while accounting for the uncertainties inherent in a POMDP framework. Each step involves making decisions based on the available observations, which allows for flexibility and adaptability throughout the process.
Traceback (most recent call last):
File "D:\proj\owl\owl\camel\toolkits\function_tool.py", line 349, in __call__
result = self.func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\proj\owl\owl\camel\toolkits\web_toolkit.py", line 1049, in browser_simulation
self.browser.init()
File "D:\proj\owl\owl\camel\toolkits\web_toolkit.py", line 305, in init
self.browser = self.playwright.chromium.launch(headless=self.headless) # launch the browser, if the headless is False, the browser will be displayed
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\qbug\miniconda3\envs\owl\Lib\site-packages\playwright\sync_api\_generated.py", line 14461, in launch
self._sync(
File "C:\Users\qbug\miniconda3\envs\owl\Lib\site-packages\playwright\_impl\_sync_base.py", line 104, in _sync
raise Error("Event loop is closed! Is Playwright already stopped?")
playwright._impl._errors.Error: Event loop is closed! Is Playwright already stopped?
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\proj\owl\owl\run_qwq_demo.py", line 85, in <module>
answer, chat_history, token_count = run_society(society)
^^^^^^^^^^^^^^^^^^^^
File "D:\proj\owl\owl\utils\enhanced_role_playing.py", line 412, in run_society
assistant_response, user_response = society.step(input_msg)
^^^^^^^^^^^^^^^^^^^^^^^
File "D:\proj\owl\owl\utils\enhanced_role_playing.py", line 253, in step
assistant_response = self.assistant_agent.step(modified_user_msg)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\proj\owl\owl\camel\agents\chat_agent.py", line 705, in step
self._step_tool_call_and_update(response)
File "D:\proj\owl\owl\camel\agents\chat_agent.py", line 882, in _step_tool_call_and_update
self.step_tool_call(response)
File "D:\proj\owl\owl\camel\agents\chat_agent.py", line 1294, in step_tool_call
result = tool(**args)
^^^^^^^^^^^^
File "D:\proj\owl\owl\camel\toolkits\function_tool.py", line 352, in __call__
raise ValueError(
ValueError: Execution of function browser_simulation failed with arguments () and {'start_url': 'https://www.secondstate.io/articles/infra-for-llms/', 'task_prompt': "Visit the link and extract relevant information about Rust's ecosystem and development in large models over the past year."}. Error: Event loop is closed! Is Playwright already stopped?
|
