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https://github.com/camel-ai/owl.git
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update mistral example
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parent
88006b48e4
commit
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@ -2,8 +2,10 @@
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"mcpServers": {
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"playwright": {
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"command": "npx",
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"args": ["-y", "@executeautomation/playwright-mcp-server"]
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"args": [
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"@playwright/mcp@latest"
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]
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}
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}
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}
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}
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@ -11,25 +11,83 @@
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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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"""MCP Multi-Agent System Example
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This example demonstrates how to use MCP (Model Context Protocol) with CAMEL agents
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for advanced information retrieval and processing tasks.
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Environment Setup:
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1. Configure the required dependencies of owl library
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Refer to: https://github.com/camel-ai/owl for installation guide
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2. MCP Server Setup:
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2.1 MCP Playwright Service:
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```bash
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# Install MCP service
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npm install -g @executeautomation/playwright-mcp-server
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npx playwright install-deps
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# Configure in mcp_servers_config.json:
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{
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"mcpServers": {
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"playwright": {
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"command": "npx",
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"args": ["-y", "@executeautomation/playwright-mcp-server"]
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}
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}
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}
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```
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2.2 MCP Fetch Service (Optional - for better retrieval):
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```bash
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# Install MCP service
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pip install mcp-server-fetch
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# Configure in mcp_servers_config.json:
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{
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"mcpServers": {
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"fetch": {
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"command": "python",
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"args": ["-m", "mcp_server_fetch"]
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}
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}
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}
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```
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Usage:
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1. Ensure all MCP servers are properly configured in mcp_servers_config.json
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2. Run this script to create a multi-agent system that can:
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- Access and manipulate files through MCP Desktop Commander
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- Perform web automation tasks using Playwright
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- Process and generate information using Mistral
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- Fetch web content (if fetch service is configured)
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3. The system will execute the specified task while maintaining security through
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controlled access
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Note:
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- All file operations are restricted to configured directories
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- Supports asynchronous operations for efficient processing
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"""
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import asyncio
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import sys
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import pathlib
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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 (
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AudioAnalysisToolkit,
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CodeExecutionToolkit,
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ExcelToolkit,
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ImageAnalysisToolkit,
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SearchToolkit,
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VideoAnalysisToolkit,
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BrowserToolkit,
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FileWriteToolkit,
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)
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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 camel.societies import RolePlaying
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from owl.utils import run_society, DocumentProcessingToolkit
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from owl.utils.enhanced_role_playing import 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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@ -38,17 +96,16 @@ load_dotenv(dotenv_path=str(env_path))
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set_log_level(level="DEBUG")
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def construct_society(question: str) -> RolePlaying:
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r"""Construct a society of agents based on Mistral model(s).
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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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) -> RolePlaying:
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r"""build a multi-agent RolePlaying instance.
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Args:
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question (str): The task or question to be addressed by the society.
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Returns:
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RolePlaying: A configured society of agents ready to address the question.
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question (str): The question to ask.
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tools (List[FunctionTool]): The MCP tools to use.
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"""
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# Create models for different components
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models = {
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"user": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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@ -60,63 +117,19 @@ def construct_society(question: str) -> RolePlaying:
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model_type=ModelType.MISTRAL_LARGE,
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model_config_dict={"temperature": 0},
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),
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"browsing": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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model_type=ModelType.MISTRAL_LARGE,
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model_config_dict={"temperature": 0},
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),
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"planning": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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model_type=ModelType.MISTRAL_LARGE,
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model_config_dict={"temperature": 0},
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),
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"video": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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model_type=ModelType.MISTRAL_PIXTRAL_12B,
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model_config_dict={"temperature": 0},
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),
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"image": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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model_type=ModelType.MISTRAL_PIXTRAL_12B,
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model_config_dict={"temperature": 0},
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),
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"document": ModelFactory.create(
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model_platform=ModelPlatformType.MISTRAL,
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model_type=ModelType.MISTRAL_LARGE,
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model_config_dict={"temperature": 0},
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),
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}
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# Configure toolkits
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tools = [
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*BrowserToolkit(
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headless=True,
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web_agent_model=models["browsing"],
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planning_agent_model=models["planning"],
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).get_tools(),
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*VideoAnalysisToolkit(model=models["video"]).get_tools(),
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*AudioAnalysisToolkit().get_tools(),
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*CodeExecutionToolkit(sandbox="subprocess", verbose=True).get_tools(),
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*ImageAnalysisToolkit(model=models["image"]).get_tools(),
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SearchToolkit().search_duckduckgo,
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SearchToolkit().search_google,
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SearchToolkit().search_wiki,
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*ExcelToolkit().get_tools(),
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*DocumentProcessingToolkit(model=models["document"]).get_tools(),
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*FileWriteToolkit(output_dir="./").get_tools(),
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]
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# Configure agent roles and parameters
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user_agent_kwargs = {"model": models["user"]}
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assistant_agent_kwargs = {"model": models["assistant"], "tools": tools}
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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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# Configure task parameters
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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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# Create and return the society
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society = RolePlaying(
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**task_kwargs,
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user_role_name="user",
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@ -124,25 +137,40 @@ def construct_society(question: str) -> RolePlaying:
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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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def main():
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r"""Main function to run the OWL system with an example question."""
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# Default research question
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default_task = "Open Brave search, summarize the github stars, fork counts, etc. of camel-ai's camel framework, and write the numbers into a python file using the plot package, save it locally, and run the generated python file. Note: You have been provided with the necessary tools to complete this task."
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async def main():
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config_path = Path(__file__).parent / "mcp_servers_config.json"
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mcp_toolkit = MCPToolkit(config_path=str(config_path))
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# Override default task if command line argument is provided
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task = sys.argv[1] if len(sys.argv) > 1 else default_task
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try:
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await mcp_toolkit.connect()
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# Construct and run the society
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society = construct_society(task)
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answer, chat_history, token_count = run_society(society)
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# Default task
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default_task = (
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"I'd like a academic report about Andrew Ng, including "
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"his research direction, published papers (At least 3), "
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"institutions, etc. You have been provided with tools to do "
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"browser operation. Open browser to finish the task."
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)
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# Output the result
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print(f"\033[94mAnswer: {answer}\033[0m")
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# Override default task if command line argument is provided
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task = sys.argv[1] if len(sys.argv) > 1 else default_task
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# Connect to all MCP toolkits
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tools = [*mcp_toolkit.get_tools()]
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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"\033[94mAnswer: {answer}\033[0m")
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finally:
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# Make sure to disconnect safely after all operations are completed.
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try:
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await mcp_toolkit.disconnect()
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except Exception:
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print("Disconnect failed")
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if __name__ == "__main__":
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main()
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asyncio.run(main())
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@ -28,6 +28,7 @@ dependencies = [
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"mcp-server-fetch==2025.1.17",
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"xmltodict>=0.14.2",
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"firecrawl>=2.5.3",
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"mistralai>=1.7.0",
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]
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[project.urls]
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18
uv.lock
generated
18
uv.lock
generated
@ -1832,6 +1832,22 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979 },
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]
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[[package]]
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name = "mistralai"
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version = "1.7.0"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "eval-type-backport" },
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{ name = "httpx" },
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{ name = "pydantic" },
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{ name = "python-dateutil" },
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{ name = "typing-inspection" },
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]
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sdist = { url = "https://files.pythonhosted.org/packages/98/d0/11e0116a02aa88701422ccc048185ed8834754f3b94140bfad09620c9d11/mistralai-1.7.0.tar.gz", hash = "sha256:94e3eb23c1d3ed398a95352062fd8c92993cc3754ed18e9a35b60aa3db0bd103", size = 141981 }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/60/77/eb7519ddfccb6428ac430129e7b42cc662e710cb719f82c0ffe79ab50859/mistralai-1.7.0-py3-none-any.whl", hash = "sha256:e0e75ab8508598d69ae19b14d9d7e905db6259a2de3cf9204946a27e9bf81c5d", size = 301483 },
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]
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[[package]]
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name = "more-itertools"
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version = "10.7.0"
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@ -2389,6 +2405,7 @@ dependencies = [
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{ name = "gradio" },
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{ name = "mcp-server-fetch" },
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{ name = "mcp-simple-arxiv" },
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{ name = "mistralai" },
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{ name = "xmltodict" },
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]
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@ -2400,6 +2417,7 @@ requires-dist = [
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{ name = "gradio", specifier = ">=3.50.2" },
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{ name = "mcp-server-fetch", specifier = "==2025.1.17" },
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{ name = "mcp-simple-arxiv", specifier = "==0.2.2" },
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{ name = "mistralai", specifier = ">=1.7.0" },
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{ name = "xmltodict", specifier = ">=0.14.2" },
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]
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