feat: add cli mode

examples/run_cli.py

@@ -0,0 +1,181 @@
+from dotenv import load_dotenv
+
+from camel.models import ModelFactory
+from camel.toolkits import (
+    ExcelToolkit,
+    SearchToolkit,
+    FileWriteToolkit,
+    CodeExecutionToolkit,
+    BrowserToolkit,
+    VideoAnalysisToolkit,
+    ImageAnalysisToolkit,
+)
+from camel.types import ModelPlatformType, ModelType
+from camel.societies import RolePlaying
+from camel.logger import set_log_level
+
+from owl.utils import run_society, DocumentProcessingToolkit
+
+import pathlib
+
+# Set the log level to DEBUG for detailed debugging information
+set_log_level(level="DEBUG")
+
+# Get the parent directory of the current file and construct the path to the .env file
+base_dir = pathlib.Path(__file__).parent.parent
+env_path = base_dir / "owl" / ".env"
+load_dotenv(dotenv_path=str(env_path))
+
+
+def get_user_input(prompt):
+    # Get user input and strip leading/trailing whitespace
+    return input(prompt).strip()
+
+
+def get_construct_params() -> dict[str, any]:
+    # Welcome message
+    print("Welcome to owl! Have fun!")
+
+    # Select model platform type
+    model_platforms = ModelPlatformType
+    print("Please select the model platform type:")
+    for i, platform in enumerate(model_platforms, 1):
+        print(f"{i}. {platform}")
+    model_platform_choice = int(
+        get_user_input("Please enter the model platform number:")
+    )
+    selected_model_platform = list(model_platforms)[model_platform_choice - 1]
+    print(f"The model platform you selected is: {selected_model_platform}")
+
+    # Select model type
+    models = ModelType
+    print("Please select the model type:")
+    for i, model in enumerate(models, 1):
+        print(f"{i}. {model}")
+    model_choice = int(get_user_input("Please enter the model number:"))
+    selected_model = list(models)[model_choice - 1]
+    print(f"The model you selected is: {selected_model}")
+
+    # Select language
+    languages = ["English", "Chinese"]
+    print("Please select the language:")
+    for i, lang in enumerate(languages, 1):
+        print(f"{i}. {lang}")
+    language_choice = int(get_user_input("Please enter the language number:"))
+    selected_language = languages[language_choice - 1]
+    print(f"The language you selected is: {selected_language}")
+
+    # Enter the question
+    question = get_user_input("Please enter your question:")
+    print(f"Your question is: {question}")
+
+    return {
+        "language": selected_language,
+        "model_type": selected_model,
+        "model_platform": selected_model_platform,
+        "question": question,
+    }
+
+
+def construct_society() -> RolePlaying:
+    # Get user input parameters
+    params = get_construct_params()
+    question = params["question"]
+    selected_model_type = params["model_type"]
+    selected_model_platform = params["model_platform"]
+    selected_language = params["language"]
+
+    # Create model instances for different roles
+    models = {
+        "user": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "assistant": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "web": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "planning": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "video": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "image": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+        "document": ModelFactory.create(
+            model_platform=selected_model_platform,
+            model_type=selected_model_type,
+            model_config_dict={"temperature": 0},
+        ),
+    }
+
+    # Configure toolkits
+    tools = [
+        *BrowserToolkit(
+            headless=False,  # Set to True for headless mode (e.g., on remote servers)
+            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(),
+        *ImageAnalysisToolkit(model=models["image"]).get_tools(),
+        SearchToolkit().search_duckduckgo,
+        SearchToolkit().search_google,  # Comment this out if you don't have Google search
+        SearchToolkit().search_wiki,
+        SearchToolkit().search_baidu,
+        SearchToolkit().search_bing,
+        *ExcelToolkit().get_tools(),
+        *DocumentProcessingToolkit(model=models["document"]).get_tools(),
+        *FileWriteToolkit(output_dir="./").get_tools(),
+    ]
+
+    # Configure agent roles and parameters
+    user_agent_kwargs = {"model": models["user"]}
+    assistant_agent_kwargs = {"model": models["assistant"], "tools": tools}
+
+    # Configure task parameters
+    task_kwargs = {
+        "task_prompt": question,
+        "with_task_specify": False,
+    }
+
+    # Create and return the society
+    society = RolePlaying(
+        **task_kwargs,
+        user_role_name="user",
+        user_agent_kwargs=user_agent_kwargs,
+        assistant_role_name="assistant",
+        assistant_agent_kwargs=assistant_agent_kwargs,
+        output_language=selected_language,
+    )
+
+    return society
+
+
+def main():
+    # Construct the society
+    society = construct_society()
+    # Run the society and get the answer, chat history, and token count
+    answer, chat_history, token_count = run_society(society)
+    # Print the answer
+    print(f"\033[94mAnswer: {answer}\033[0m")
+
+
+if __name__ == "__main__":
+    main()