usecase：smart city usecase using TerminalToolkit, PyAutoGUIToolkit, and BrowserToolkit

community_usecase/Smart_city_research/main.py

@@ -0,0 +1,155 @@
+# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# 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.configs import MistralConfig
+from camel.models import ModelFactory
+from camel.toolkits import (
+    SearchToolkit,
+    BrowserToolkit,
+    FileWriteToolkit,
+    TerminalToolkit,
+    PyAutoGUIToolkit,
+
+)
+from camel.types import ModelPlatformType, ModelType
+
+from camel.societies import RolePlaying
+import os
+from camel.logger import get_logger, set_log_file,set_log_level
+from owl.utils import run_society, DocumentProcessingToolkit
+
+# Set logging
+set_log_file("product.log")
+logger = get_logger(__name__)
+set_log_level(level="DEBUG")
+
+
+# Load environment variables
+load_dotenv(os.path.join(os.path.dirname(__file__), '../../owl/.env'))
+base_dir = os.path.dirname(os.path.abspath(__file__))
+workspace_dir = os.path.join(
+    os.path.dirname(os.path.dirname(base_dir)), "workspace"
+)
+
+
+def construct_society(question: str) -> RolePlaying:
+    r"""Construct a society of agents based on the given question.
+
+    Args:
+        question (str): The task or question to be addressed by the society.
+
+    Returns:
+        RolePlaying: A configured society of agents ready to address the question.
+    """
+
+    # Create models for different components
+    models = {
+        "user": ModelFactory.create(
+            model_platform=ModelPlatformType.MISTRAL,
+            model_type="pixtral-large-latest",
+            model_config_dict=MistralConfig(temperature=0.0).as_dict(),
+        ),
+        "assistant": ModelFactory.create(
+            model_platform=ModelPlatformType.MISTRAL,
+            model_type="pixtral-large-latest",
+            model_config_dict=MistralConfig(temperature=0.0).as_dict(),
+        ),
+        "document": ModelFactory.create(
+            model_platform=ModelPlatformType.MISTRAL,
+            model_type="pixtral-large-latest",
+            model_config_dict=MistralConfig(temperature=0.0).as_dict(),
+        ),
+        "browsing": ModelFactory.create(
+            model_platform=ModelPlatformType.MISTRAL,
+            model_type="pixtral-large-latest",
+            model_config_dict=MistralConfig(temperature=0.0).as_dict(),
+        ),
+        "planning": ModelFactory.create(
+            model_platform=ModelPlatformType.MISTRAL,
+            model_type=ModelType.MISTRAL_LARGE,
+            model_config_dict=MistralConfig(temperature=0.0).as_dict(),
+        ),
+
+
+    }
+
+    # Configure toolkits
+    tools = [
+        *BrowserToolkit(
+            headless=False,  # Set to True for headless mode (e.g., on remote servers)
+            web_agent_model=models["browsing"],
+            planning_agent_model=models["planning"],
+        ).get_tools(),
+        *PyAutoGUIToolkit().get_tools(),
+        *TerminalToolkit(working_dir=workspace_dir).get_tools(),
+        SearchToolkit().search_duckduckgo,
+        # SearchToolkit().search_google,  # Comment this out if you don't have google search
+        *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,
+    )
+
+    return society
+
+
+def main():
+    r"""Main function to run the OWL system with an example question."""
+    # Default research question
+    default_task = """
+please help me to make a research on smart city technology.
+Fisrtly, please use the duckduckgo search  to search the following topic:
+What are the current trends in smart city technology?
+and then,only browse the most related website urls to get the information.
+
+secondly, make a pdf for me to present the research results.
+
+finally, open the pdf and take screenshot for me.
+if there are some packages that are not installed, please install them 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(task)
+    answer, chat_history, token_count = run_society(society)
+
+    # Output the result
+    print(f"\033[94mAnswer: {answer}\033[0m")
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

@@ -21,7 +21,7 @@ keywords = [
     "learning-systems"
 ]
 dependencies = [
-    "camel-ai[owl]==0.2.52",
+    "camel-ai[owl]==0.2.54",
     "docx2markdown>=0.1.1",
     "gradio>=3.50.2",
     "mcp-simple-arxiv==0.2.2",

requirements.txt

@@ -1,4 +1,4 @@
-camel-ai[owl]==0.2.52
+camel-ai[owl]==0.2.54
 docx2markdown>=0.1.1
 gradio>=3.50.2
 mcp-simple-arxiv==0.2.2