Feat : Add example in Community Use Cases (#434)

community_usecase/Mcp_use_case/Content_curator.py

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+import asyncio
+import sys
+from pathlib import Path
+from typing import List, Dict
+
+
+from dotenv import load_dotenv
+
+from camel.models import ModelFactory
+from camel.toolkits import FunctionTool, MCPToolkit
+from camel.types import ModelPlatformType, ModelType
+from camel.logger import set_log_level
+
+from owl.utils.enhanced_role_playing import OwlRolePlaying, arun_society
+
+import pathlib
+
+set_log_level(level="DEBUG")
+
+# Load environment variables from .env file if available
+load_dotenv()
+
+
+async def construct_society(
+    question: str,
+    tools: List[FunctionTool],
+) -> OwlRolePlaying:
+    """Build a multi-agent OwlRolePlaying instance with enhanced content curation capabilities."""
+    models = {
+        "user": ModelFactory.create(
+            model_platform=ModelPlatformType.OPENAI,
+            model_type=ModelType.GPT_4O,
+            model_config_dict={
+                "temperature": 0.7,
+                # "max_tokens": 4000  # Add token limit to prevent overflow
+            },
+        ),
+        "assistant": ModelFactory.create(
+            model_platform=ModelPlatformType.OPENAI,
+            model_type=ModelType.GPT_4O,
+            model_config_dict={
+                "temperature": 0.7,
+                #"max_tokens": 4000
+            },
+        ),
+    }
+
+    user_agent_kwargs = {"model": models["user"]}
+    assistant_agent_kwargs = {
+        "model": models["assistant"],
+        "tools": tools,
+    }
+
+    task_kwargs = {
+        "task_prompt": question,
+        "with_task_specify": False,
+    }
+
+    return OwlRolePlaying(
+        **task_kwargs,
+        user_role_name="content_curator",
+        user_agent_kwargs=user_agent_kwargs,
+        assistant_role_name="research_assistant",
+        assistant_agent_kwargs=assistant_agent_kwargs,
+    )
+
+async def main():
+    config_path = Path(__file__).parent / "mcp_servers_config.json"
+    mcp_toolkit = MCPToolkit(config_path=str(config_path))
+
+    try:
+        await mcp_toolkit.connect()
+
+        default_task = (
+            "Content Curation Task:\n"
+            "1. Search for these tech websites:\n"
+            "   - TechCrunch\n"
+            "   - The Verge\n"
+            "   - Wired\n"
+            "2. For each site:\n"
+            "   - Use the firecrawl_scrape tool with proper extraction options\n"
+            "   - Extract the homepage content\n"
+            "   - Focus on headlines and recent articles\n"
+            "3. For each article found:\n"
+            "   - Extract title and summary\n"
+            "   - Note the publication date if available\n"
+            "4. Create a summary report including:\n"
+            "   - Top stories from each source\n"
+            "   - Common themes or trends\n"
+            "5. Save the report as 'Latest_tech_digest.md'\n"
+        )
+
+        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(task, tools)
+        
+        try:
+            # Add error handling for the society execution
+            result = await arun_society(society)
+            
+            # Handle the result properly
+            if isinstance(result, tuple) and len(result) == 3:
+                answer, chat_history, token_count = result
+            else:
+                answer = str(result)
+                chat_history = []
+                token_count = 0
+
+        except Exception as e:
+            print(f"Error during society execution: {str(e)}")
+            raise
+
+    finally:
+        # Cleanup
+        await asyncio.sleep(1)
+        tasks = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()]
+        for task in tasks:
+            task.cancel()
+            try:
+                await task
+            except asyncio.CancelledError:
+                pass
+        
+        try:
+            await mcp_toolkit.disconnect()
+        except Exception as e:
+            print(f"Cleanup error (can be ignored): {e}")
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\nShutting down gracefully...")
+    finally:
+        if sys.platform == 'win32':
+            try:
+                import asyncio.windows_events
+                asyncio.windows_events._overlapped = None
+            except (ImportError, AttributeError):
+                pass

community_usecase/Mcp_use_case/Readme.md

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+# Content Curation with OWL & MCP
+
+This project leverages **OWL (Optimized Workforce Learning)** and **MCP (Multi-Agent Content Processing)** to automate content curation. The system scrapes top tech news websites, extracts relevant information, and compiles a summary report.
+
+## Features
+
+- Uses **MCPToolkit** for managing toolkits and performing web scraping.
+- Implements **OwlRolePlaying** for enhanced multi-agent task execution.
+- Scrapes **TechCrunch, The Verge, and Wired**.
+- Extracts and summarizes **headlines, article summaries, and publication dates**.
+- Generates a digest report **(Latest_tech_digest.md)** based on trends from these sources.
+
+## Installation
+
+1. Clone this repository:
+   ```sh
+   git clone https://github.com/your-repo.git
+   cd your-repo
+   ```
+2. Install dependencies:
+   ```sh
+   pip install -r requirements.txt
+   ```
+3. Set up environment variables:
+   - Create a `.env` file and add your API keys/configuration as needed.
+
+## Usage
+
+Run the script using:
+
+```sh
+python script.py "Your Custom Task Here"
+```
+
+Or use the default task defined in the script.
+
+## Configuration
+
+- The script reads from `mcp_servers_config.json` to configure MCP.
+- Modify the `default_task` section to adjust scraping and summarization behavior.
+
+## Error Handling
+
+- The script ensures **graceful cleanup** in case of failures.
+- Implements **try-except** blocks to handle tool execution errors.
+
+## Cleanup & Shutdown
+
+- The script **automatically disconnects MCP** after execution.
+- Cancels running async tasks to **prevent memory leaks**.
+- Handles **KeyboardInterrupt** for a graceful shutdown.
+
+## Future Improvements
+
+- Add support for more tech news sources.
+- Implement NLP-based **sentiment analysis** on extracted news.
+- Enable storing summaries in structured formats like JSON/CSV.
+
+

community_usecase/Mcp_use_case/mcp_servers_config.json

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+{
+    "mcpServers": {
+      "desktop-commander": {
+        "command": "npx",
+        "args": [
+          "-y",
+          "@wonderwhy-er/desktop-commander"
+        ]
+      },
+      
+      "playwright": {
+        "command": "npx",
+        "args": ["-y", "@executeautomation/playwright-mcp-server", "--browser", "chromium"]
+      },
+
+      "mcp-server-firecrawl": {
+        "command": "npx",
+        "args": ["-y", "firecrawl-mcp"]
+      }
+    }
+  }