Merge branch 'main' into tj-scripts

2026-03-22 05:57:17 +08:00 · 2025-03-21 15:38:23 +08:00
parent c9a7426f49 106a169ee9
commit 2e034d95e1
19 changed files with 116 additions and 63 deletions
--- a/README.md
+++ b/README.md
@@ -386,7 +386,7 @@ You can run OWL agent with your own task by modifying the `examples/run.py` scri

 ```python
 # Define your own task
-question = "Task description here."
+task = "Task description here."

 society = construct_society(question)
 answer, chat_history, token_count = run_society(society)
@@ -398,7 +398,7 @@ For uploading files, simply provide the file path along with your question:

 ```python
 # Task with a local file (e.g., file path: `tmp/example.docx`)
-question = "What is in the given DOCX file? Here is the file path: tmp/example.docx"
+task = "What is in the given DOCX file? Here is the file path: tmp/example.docx"

 society = construct_society(question)
 answer, chat_history, token_count = run_society(society)
--- a/README_zh.md
+++ b/README_zh.md
@@ -379,7 +379,7 @@ python examples/run_ollama.py

 ```python
 # Define your own task
-question = "Task description here."
+task = "Task description here."

 society = construct_society(question)
 answer, chat_history, token_count = run_society(society)
@@ -391,7 +391,7 @@ print(f"\033[94mAnswer: {answer}\033[0m")

 ```python
 # 处理本地文件（例如，文件路径为 `tmp/example.docx`）
-question = "给定的 DOCX 文件中有什么内容？文件路径如下：tmp/example.docx"
+task = "给定的 DOCX 文件中有什么内容？文件路径如下：tmp/example.docx"

 society = construct_society(question)
 answer, chat_history, token_count = run_society(society)
--- a/examples/run.py
+++ b/examples/run.py
@@ -11,6 +11,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
+import sys
+import pathlib
 from dotenv import load_dotenv
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -29,8 +31,6 @@ from camel.societies import RolePlaying

 from owl.utils import run_society, DocumentProcessingToolkit

-import pathlib
-
 base_dir = pathlib.Path(__file__).parent.parent
 env_path = base_dir / "owl" / ".env"
 load_dotenv(dotenv_path=str(env_path))
@@ -60,7 +60,7 @@ def construct_society(question: str) -> RolePlaying:
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI,
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
@@ -91,7 +91,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *VideoAnalysisToolkit(model=models["video"]).get_tools(),
@@ -130,11 +130,14 @@ def construct_society(question: str) -> RolePlaying:

 def main():
    r"""Main function to run the OWL system with an example question."""
-    # Example research question
-    question = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+    # Default research question
+    default_task = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_azure_openai.py
+++ b/examples/run_azure_openai.py
@@ -12,6 +12,7 @@
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 import os
+import sys
 from dotenv import load_dotenv
 from camel.configs import ChatGPTConfig
 from camel.models import ModelFactory
@@ -58,7 +59,7 @@ def construct_society(question: str) -> OwlRolePlaying:
    models = {
        "user": ModelFactory.create(**base_model_config),
        "assistant": ModelFactory.create(**base_model_config),
-        "web": ModelFactory.create(**base_model_config),
+        "browsing": ModelFactory.create(**base_model_config),
        "planning": ModelFactory.create(**base_model_config),
        "image": ModelFactory.create(**base_model_config),
    }
@@ -67,7 +68,7 @@ def construct_society(question: str) -> OwlRolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),
@@ -104,10 +105,14 @@ def construct_society(question: str) -> OwlRolePlaying:
 def main():
    r"""Main function to run the OWL system with Azure OpenAI."""
    # Example question
-    question = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+    default_task = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
+
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_cli.py
+++ b/examples/run_cli.py
@@ -110,7 +110,7 @@ def construct_society() -> RolePlaying:
            model_type=selected_model_type,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=selected_model_platform,
            model_type=selected_model_type,
            model_config_dict={"temperature": 0},
@@ -141,9 +141,8 @@ def construct_society() -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
-            output_language="Chinese",
        ).get_tools(),
        *VideoAnalysisToolkit(model=models["video"]).get_tools(),
        *CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),
--- a/examples/run_deepseek_zh.py
+++ b/examples/run_deepseek_zh.py
@@ -17,7 +17,7 @@
 # You can obtain your API key from DeepSeek platform: https://platform.deepseek.com/api_keys
 # Set it as DEEPSEEK_API_KEY="your-api-key" in your .env file or add it to your environment variables

-
+import sys
 from dotenv import load_dotenv

 from camel.models import ModelFactory
@@ -102,10 +102,14 @@ def construct_society(question: str) -> RolePlaying:
 def main():
    r"""Main function to run the OWL system with an example question."""
    # Example research question
-    question = "搜索OWL项目最近的新闻并生成一篇报告，最后保存到本地。"
+    default_task = "搜索OWL项目最近的新闻并生成一篇报告，最后保存到本地。"
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
+
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_gaia_roleplaying.py
+++ b/examples/run_gaia_roleplaying.py
@@ -71,7 +71,7 @@ def main():
            model_type=ModelType.GPT_4O,
            model_config_dict=ChatGPTConfig(temperature=0, top_p=1).as_dict(),
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI,
            model_type=ModelType.GPT_4O,
            model_config_dict=ChatGPTConfig(temperature=0, top_p=1).as_dict(),
@@ -97,7 +97,7 @@ def main():
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *VideoAnalysisToolkit(
--- a/examples/run_groq.py
+++ b/examples/run_groq.py
@@ -26,6 +26,7 @@ To use this module:
 3. Run with: python -m examples.run_groq
 """

+import sys
 from dotenv import load_dotenv
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -70,7 +71,7 @@ def construct_society(question: str) -> OwlRolePlaying:
            model_type=ModelType.GROQ_LLAMA_3_3_70B,  # Main assistant needs tool capability
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.GROQ,
            model_type=ModelType.GROQ_LLAMA_3_3_70B,  # Web browsing requires tool usage
            model_config_dict={"temperature": 0},
@@ -101,7 +102,7 @@ def construct_society(question: str) -> OwlRolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *VideoAnalysisToolkit(model=models["video"]).get_tools(),
@@ -141,13 +142,18 @@ def construct_society(question: str) -> OwlRolePlaying:
 def main():
    r"""Main function to run the OWL system with an example question."""
    # Example research question
-    question = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+    default_task = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."

    # Construct and run the society
    # Note: This configuration uses GROQ_LLAMA_3_3_70B for tool-intensive roles (assistant, web, planning, video, image)
    # and GROQ_MIXTRAL_8_7B for document processing. GROQ_LLAMA_3_1_8B is used only for the user role
    # which doesn't require tool usage capabilities.
-    society = construct_society(question)
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task
+
+    # Construct and run the society
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_mcp.py
+++ b/examples/run_mcp.py
@@ -73,6 +73,7 @@ Note:
 """

 import asyncio
+import sys
 from pathlib import Path
 from typing import List

@@ -146,15 +147,19 @@ async def main():
    try:
        await mcp_toolkit.connect()

-        question = (
+        # Default task
+        default_task = (
            "I'd like a academic report about Andrew Ng, including "
            "his research direction, published papers (At least 3),"
            " institutions, etc. "
        )

+        # Override default task if command line argument is provided
+        task = sys.argv[1] if len(sys.argv) > 1 else default_task
+
        # Connect to all MCP toolkits
        tools = [*mcp_toolkit.get_tools()]
-        society = await construct_society(question, tools)
+        society = await construct_society(task, tools)
        answer, chat_history, token_count = await arun_society(society)
        print(f"\033[94mAnswer: {answer}\033[0m")

--- a/examples/run_mini.py
+++ b/examples/run_mini.py
@@ -11,6 +11,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
+import sys
 from dotenv import load_dotenv

 from camel.models import ModelFactory
@@ -58,7 +59,7 @@ def construct_society(question: str) -> RolePlaying:
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI,
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
@@ -74,7 +75,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        SearchToolkit().search_duckduckgo,
@@ -106,11 +107,14 @@ def construct_society(question: str) -> RolePlaying:

 def main():
    r"""Main function to run the OWL system with an example question."""
-    # Example research question
-    question = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+    # Default research question
+    default_task = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_ollama.py
+++ b/examples/run_ollama.py
@@ -13,6 +13,7 @@
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 # run_ollama.py by tj-scripts（https://github.com/tj-scripts）

+import sys
 from dotenv import load_dotenv
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -64,7 +65,7 @@ def construct_society(question: str) -> RolePlaying:
            url="http://localhost:11434/v1",
            model_config_dict={"temperature": 0.2, "max_tokens": 1000000},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OLLAMA,
            model_type="llava:latest",
            url="http://localhost:11434/v1",
@@ -88,7 +89,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),
@@ -124,11 +125,14 @@ def construct_society(question: str) -> RolePlaying:

 def main():
    r"""Main function to run the OWL system with an example question."""
-    # Example research question
-    question = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+    # Default research question
+    default_task = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_openai_compatiable_model.py
+++ b/examples/run_openai_compatiable_model.py
@@ -53,6 +53,7 @@ def construct_society(question: str) -> RolePlaying:
    models = {
        "user": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI_COMPATIBLE_MODEL,
+
            model_type=os.getenv("USER_ROLE_API_MODEL_TYPE", os.getenv("LLM_ROLE_API_MODEL_TYPE", "qwen-max")),
            api_key=os.getenv("USER_ROLE_API_KEY", os.getenv("LLM_ROLE_API_KEY", os.getenv("QWEN_API_KEY", "Your_Key"))),
            url=os.getenv("USER_ROLE_API_BASE_URL", os.getenv("LLM_ROLE_API_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")),
@@ -70,9 +71,11 @@ def construct_society(question: str) -> RolePlaying:
                "temperature": float(os.getenv("ASSISTANT_ROLE_API_MODEL_TEMPERATURE", os.getenv("LLM_ROLE_API_MODEL_TEMPERATURE", "0.4"))), 
                "max_tokens": int(os.getenv("ASSISTANT_ROLE_API_MODEL_MAX_TOKENS", os.getenv("LLM_ROLE_API_MODEL_MAX_TOKENS", "4096")))
            },
+
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI_COMPATIBLE_MODEL,
+
            model_type=os.getenv("WEB_ROLE_API_BASE_URL", os.getenv("VLLM_ROLE_API_MODEL_TYPE", "qwen-vl-max")),
            api_key=os.getenv("WEB_ROLE_API_KEY", os.getenv("VLLM_ROLE_API_KEY", os.getenv("QWEN_API_KEY", "Your_Key"))),
            url=os.getenv("USER_ROLE_API_BASE_URL", os.getenv("VLLM_ROLE_API_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")),
@@ -107,7 +110,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        *CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),
@@ -141,6 +144,7 @@ def construct_society(question: str) -> RolePlaying:
    return society


+
 def main(question: str = "Navigate to Amazon.com and identify one product that is attractive to coders. Please provide me with the product name and price. No need to verify your answer."):
    r"""Main function to run the OWL system with an example question.
    Args:
@@ -150,8 +154,10 @@ def main(question: str = "Navigate to Amazon.com and identify one product that i
    Returns:
        None
    """
+
    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
+
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_qwen_mini_zh.py
+++ b/examples/run_qwen_mini_zh.py
@@ -17,7 +17,7 @@
 # Set it as QWEN_API_KEY="your-api-key" in your .env file or add it to your environment variables

 from dotenv import load_dotenv
-
+import sys
 from camel.models import ModelFactory
 from camel.toolkits import BrowserToolkit, SearchToolkit, FileWriteToolkit
 from camel.types import ModelPlatformType, ModelType
@@ -101,9 +101,14 @@ def construct_society(question: str) -> RolePlaying:


 # Example case
-question = "浏览亚马逊并找出一款对程序员有吸引力的产品。请提供产品名称和价格"
+default_task = "浏览亚马逊并找出一款对程序员有吸引力的产品。请提供产品名称和价格"
+
+# Override default task if command line argument is provided
+task = sys.argv[1] if len(sys.argv) > 1 else default_task
+
+# Construct and run the society
+society = construct_society(task)

-society = construct_society(question)
 answer, chat_history, token_count = run_society(society)

 print(f"\033[94mAnswer: {answer}\033[0m")
--- a/examples/run_qwen_zh.py
+++ b/examples/run_qwen_zh.py
@@ -16,6 +16,7 @@
 # You can obtain your API key from Bailian platform: bailian.console.aliyun.com
 # Set it as QWEN_API_KEY="your-api-key" in your .env file or add it to your environment variables

+import sys
 from dotenv import load_dotenv
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -67,7 +68,7 @@ def construct_society(question: str) -> RolePlaying:
            model_type=ModelType.QWEN_MAX,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.QWEN,
            model_type=ModelType.QWEN_VL_MAX,
            model_config_dict={"temperature": 0},
@@ -98,7 +99,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
            output_language="Chinese",
        ).get_tools(),
@@ -140,10 +141,13 @@ def construct_society(question: str) -> RolePlaying:
 def main():
    r"""Main function to run the OWL system with an example question."""
    # Example research question
-    question = "浏览亚马逊并找出一款对程序员有吸引力的产品。请提供产品名称和价格"
+    default_task = "浏览亚马逊并找出一款对程序员有吸引力的产品。请提供产品名称和价格"
+
+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task

    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_terminal.py
+++ b/examples/run_terminal.py
@@ -12,6 +12,7 @@
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 from dotenv import load_dotenv
+import sys
 import os
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -58,7 +59,7 @@ def construct_society(question: str) -> RolePlaying:
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI,
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
@@ -74,7 +75,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        SearchToolkit().search_duckduckgo,
@@ -108,13 +109,16 @@ def construct_society(question: str) -> RolePlaying:
 def main():
    r"""Main function to run the OWL system with an example question."""
    # Example research question
-    question = f"""Open Google Search, summarize the number of GitHub stars, forks, etc., of the camel framework of camel-ai, 
+    default_task = f"""Open Google Search, summarize the number of GitHub stars, forks, etc., of the camel framework of camel-ai, 
    and write the numbers into a Python file using the plot package, 
    save it to "+{os.path.join(base_dir, 'final_output')}+", 
    and execute the Python file with the local terminal to display the graph for me."""

+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task
+
    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/examples/run_terminal_zh.py
+++ b/examples/run_terminal_zh.py
@@ -12,6 +12,7 @@
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 from dotenv import load_dotenv
+import sys
 import os
 from camel.models import ModelFactory
 from camel.toolkits import (
@@ -58,7 +59,7 @@ def construct_society(question: str) -> RolePlaying:
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
        ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
            model_platform=ModelPlatformType.OPENAI,
            model_type=ModelType.GPT_4O,
            model_config_dict={"temperature": 0},
@@ -74,7 +75,7 @@ def construct_society(question: str) -> RolePlaying:
    tools = [
        *BrowserToolkit(
            headless=False,  # Set to True for headless mode (e.g., on remote servers)
-            web_agent_model=models["web"],
+            web_agent_model=models["browsing"],
            planning_agent_model=models["planning"],
        ).get_tools(),
        SearchToolkit().search_duckduckgo,
@@ -108,11 +109,14 @@ def construct_society(question: str) -> RolePlaying:
 def main():
    r"""Main function to run the OWL system with an example question."""
    # Example research question
-    question = f"""打开百度搜索，总结一下camel-ai的camel框架的github star、fork数目等，并把数字用plot包写成python文件保存到"+{os.path.join
+    default_task = f"""打开百度搜索，总结一下camel-ai的camel框架的github star、fork数目等，并把数字用plot包写成python文件保存到"+{os.path.join
 (base_dir, 'final_output')}+"，用本地终端执行python文件显示图出来给我"""

+    # Override default task if command line argument is provided
+    task = sys.argv[1] if len(sys.argv) > 1 else default_task
+
    # Construct and run the society
-    society = construct_society(question)
+    society = construct_society(task)
    answer, chat_history, token_count = run_society(society)

    # Output the result
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,7 +21,7 @@ keywords = [
    "learning-systems"
 ]
 dependencies = [
-    "camel-ai[all]==0.2.34",
+    "camel-ai[all]==0.2.35",
    "chunkr-ai>=0.0.41",
    "docx2markdown>=0.1.1",
    "gradio>=3.50.2",
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-camel-ai[all]==0.2.34
+camel-ai[all]==0.2.35
 chunkr-ai>=0.0.41
 docx2markdown>=0.1.1
 gradio>=3.50.2
--- a/uv.lock
+++ b/uv.lock
@@ -482,7 +482,7 @@ wheels = [

 [[package]]
 name = "camel-ai"
-version = "0.2.34"
+version = "0.2.35"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama" },
@@ -496,9 +496,9 @@ dependencies = [
    { name = "pyyaml" },
    { name = "tiktoken" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/8c/52/ec6271bad0af4160bb4510f1039722346cfacb4117f8d049672dd383f3e4/camel_ai-0.2.34.tar.gz", hash = "sha256:d1a4965c1cb46c4bfcf79c49849f27e21636a88bc88172f831eb9566168db5e1", size = 444800 }
+sdist = { url = "https://files.pythonhosted.org/packages/6b/9d/fac44260ebec63b9199d170fc22b5f3b77a5ab51fb6014fa962b0173f524/camel_ai-0.2.35.tar.gz", hash = "sha256:b90e54a81a73c473a0e673b14db5a32fb3eeec394d61a071cf510d87490f4d49", size = 451009 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/92/f9/3b4dd1badff092507a380a46b5d3f721e21b9d2bfd934e9d8542d52aa62f/camel_ai-0.2.34-py3-none-any.whl", hash = "sha256:6cf4e0d00a6f67d79965dc578a4cee57b31ae08e2702ebed2fe6204be0be8102", size = 755831 },
+    { url = "https://files.pythonhosted.org/packages/cb/6a/c38145134e6e1a92e553c336d9bb51286bc94c1334e8bc311daa37c6a742/camel_ai-0.2.35-py3-none-any.whl", hash = "sha256:3778da315e7e4893d4d841b561f9d4e0fa6e7976b430daa52e0c887ae18431ec", size = 765923 },
 ]

 [package.optional-dependencies]
@@ -3601,7 +3601,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "camel-ai", extras = ["all"], specifier = "==0.2.34" },
+    { name = "camel-ai", extras = ["all"], specifier = "==0.2.35" },
    { name = "chunkr-ai", specifier = ">=0.0.41" },
    { name = "docx2markdown", specifier = ">=0.1.1" },
    { name = "gradio", specifier = ">=3.50.2" },