minor update

README.md

@@ -384,7 +384,7 @@ 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)
@@ -396,7 +396,7 @@ 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)

README_zh.md

@@ -377,7 +377,7 @@ 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)
@@ -389,7 +389,7 @@ 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)

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},
@@ -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

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),
     }
@@ -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

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},
@@ -143,7 +143,6 @@ def construct_society() -> RolePlaying:
             headless=False,
             web_agent_model=models["web"],
             planning_agent_model=models["planning"],
-            output_language="Chinese",
         ).get_tools(),
         *VideoAnalysisToolkit(model=models["video"]).get_tools(),
         *CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),

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

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(),

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},
@@ -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

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")
 

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},
@@ -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

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",
@@ -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

examples/run_openai_compatiable_model.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.models import ModelFactory
@@ -64,7 +65,7 @@ def construct_society(question: str) -> RolePlaying:
             url="https://dashscope.aliyuncs.com/compatible-mode/v1",
             model_config_dict={"temperature": 0.4, "max_tokens": 4096},
         ),
-        "web": ModelFactory.create(
+        "browsing": ModelFactory.create(
             model_platform=ModelPlatformType.OPENAI_COMPATIBLE_MODEL,
             model_type="qwen-vl-max",
             api_key=os.getenv("QWEN_API_KEY"),
@@ -128,10 +129,14 @@ 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_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

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")

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},
@@ -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

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},
@@ -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

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},
@@ -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