mirror of
https://github.com/camel-ai/owl.git
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122 lines
3.7 KiB
Python
122 lines
3.7 KiB
Python
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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import asyncio
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import sys
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from pathlib import Path
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from typing import List
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from dotenv import load_dotenv
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from camel.models import ModelFactory
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from camel.toolkits import FunctionTool
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from camel.types import ModelPlatformType, ModelType
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from camel.logger import set_log_level
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from camel.toolkits import MCPToolkit
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from owl.utils.enhanced_role_playing import OwlRolePlaying, arun_society
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import pathlib
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base_dir = pathlib.Path(__file__).parent.parent
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env_path = base_dir / "owl" / ".env"
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load_dotenv(dotenv_path=str(env_path))
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set_log_level(level="DEBUG")
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async def construct_society(
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question: str,
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tools: List[FunctionTool],
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) -> OwlRolePlaying:
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r"""Build a multi-agent OwlRolePlaying instance for GitHub information retrieval.
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Args:
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question (str): The GitHub-related question to ask.
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tools (List[FunctionTool]): The MCP tools to use for GitHub interaction.
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"""
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models = {
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"user": ModelFactory.create(
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model_platform=ModelPlatformType.OPENAI,
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model_type=ModelType.GPT_4O,
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model_config_dict={"temperature": 0},
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),
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"assistant": ModelFactory.create(
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model_platform=ModelPlatformType.OPENAI,
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model_type=ModelType.GPT_4O,
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model_config_dict={"temperature": 0},
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),
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}
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user_agent_kwargs = {"model": models["user"]}
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assistant_agent_kwargs = {
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"model": models["assistant"],
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"tools": tools,
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}
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task_kwargs = {
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"task_prompt": question,
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"with_task_specify": False,
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}
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society = OwlRolePlaying(
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**task_kwargs,
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user_role_name="user",
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user_agent_kwargs=user_agent_kwargs,
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assistant_role_name="assistant",
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assistant_agent_kwargs=assistant_agent_kwargs,
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)
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return society
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async def main():
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# Load SSE server configuration
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config_path = Path(__file__).parent / "mcp_sse_config.json"
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mcp_toolkit = MCPToolkit(config_path=str(config_path))
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try:
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# Connect to MCP server
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await mcp_toolkit.connect()
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print("Successfully connected to SSE server")
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# Get available tools
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tools = [*mcp_toolkit.get_tools()]
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# Set default task - a simple example query
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default_task = (
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"What are the most recent pull requests in camel-ai/camel repository?"
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)
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# Use command line argument if provided, otherwise use default task
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task = sys.argv[1] if len(sys.argv) > 1 else default_task
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# Build and run society
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society = await construct_society(task, tools)
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answer, chat_history, token_count = await arun_society(society)
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print(f"\nResult: {answer}")
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except KeyboardInterrupt:
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print("\nReceived exit signal, shutting down...")
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except Exception as e:
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print(f"Error occurred: {e}")
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finally:
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# Ensure safe disconnection
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try:
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await mcp_toolkit.disconnect()
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except Exception as e:
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print(f"Error during disconnect: {e}")
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if __name__ == "__main__":
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asyncio.run(main())
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