Pavan Kumar
3 months ago
committed by
ascender1729
parent
eef1a5384c
commit
eedcab4d08
@ -1,144 +1,49 @@
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from swarms import Agent
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from swarms.tools.mcp_integration import MCPServerSseParams
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import asyncio
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import logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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class MCPClient:
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def __init__(self):
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# Configure MCP servers
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self.math_server = MCPServerSseParams(
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def main():
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# Configure MCP server connection
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math_server = MCPServerSseParams(
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url="http://0.0.0.0:8000/mcp",
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headers={"Content-Type": "application/json"},
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timeout=5.0,
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sse_read_timeout=30.0
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)
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self.stock_server = MCPServerSseParams(
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url="http://0.0.0.0:8001/mcp",
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headers={"Content-Type": "application/json"},
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timeout=5.0,
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sse_read_timeout=30.0
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)
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# Initialize agents with specific servers
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self.math_agent = Agent(
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# Initialize agent with MCP server
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agent = Agent(
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agent_name="Math Agent",
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system_prompt="""You are a mathematical computation specialist with access to the following capabilities through the MCP server:
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- Addition of two numbers
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- Multiplication of two numbers
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- Power/exponent calculations
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- Square root calculations
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Always follow these rules:
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1. Only use tools that are available from the MCP server
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2. First list the available tools when asked
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3. Explain your mathematical approach before using tools
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4. Provide clear step-by-step explanations of calculations""",
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mcp_servers=[self.math_server],
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max_loops=1,
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streaming_on=True,
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model_name="gpt-4o-mini",
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temperature=0.1
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)
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self.stock_agent = Agent(
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agent_name="Stock Agent",
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system_prompt="""You are a stock market analysis specialist with access to the following capabilities through the MCP server:
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- Get current stock prices
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- Get trading volumes
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- Calculate market capitalization
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- Generate price statistics across multiple stocks
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Always follow these rules:
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1. Only use tools that are available from the MCP server
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2. First list the available tools when asked
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3. Explain your analysis approach before using tools
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4. Provide clear explanations of market metrics""",
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mcp_servers=[self.stock_server],
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agent_description="Agent for performing mathematical operations",
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system_prompt="""You are a mathematical computation specialist. Use the available MCP server tools to:
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- Add numbers
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- Multiply numbers
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- Divide numbers
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Always:
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1. Use only tools available from the MCP server
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2. Explain your mathematical approach
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3. Show your work step by step""",
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max_loops=1,
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mcp_servers=[math_server],
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streaming_on=True,
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model_name="gpt-4o-mini",
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temperature=0.1
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)
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async async def process_query(self, query: str):
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try:
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if query.lower() in ["capabilities", "what can you do", "what kind of problems you can solve"]:
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return [
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{"agent": "Math Agent", "response": """I can help with mathematical computations including:
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- Addition of two numbers
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- Multiplication of two numbers
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- Power/exponent calculations
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- Square root calculations"""},
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{"agent": "Stock Agent", "response": """I can help with stock market analysis including:
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- Get current stock prices
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- Get trading volumes
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- Calculate market capitalization
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- Generate price statistics across stocks"""}
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]
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# Run agents concurrently
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results = await asyncio.gather(
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self.math_agent.arun(query),
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self.stock_agent.arun(query)
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model_name="gpt-4o-mini"
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)
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# Format results
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formatted_results = []
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for idx, result in enumerate(results):
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agent_name = "Math Agent" if idx == 0 else "Stock Agent"
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if isinstance(result, dict):
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formatted_results.append({
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"agent": agent_name,
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"response": result.get("response", str(result))
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})
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else:
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formatted_results.append({
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"agent": agent_name,
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"response": str(result)
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})
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return formatted_results
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except Exception as e:
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logger.error(f"Error processing query: {e}")
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return None
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def main():
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client = MCPClient()
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print("\nAvailable Agents and Capabilities:")
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print("\nMath Agent:")
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print("- Addition of two numbers")
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print("- Multiplication of two numbers")
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print("- Power/exponent calculations")
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print("- Square root calculations")
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print("\nStock Agent:")
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print("- Get current stock prices")
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print("- Get trading volumes")
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print("- Calculate market capitalization")
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print("- Generate price statistics")
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print("\nMath Agent initialized with MCP capabilities")
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print("Available operations:")
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print("- Addition")
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print("- Multiplication")
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print("- Division")
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while True:
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query = input("\nEnter your query (or 'exit' to quit): ")
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query = input("\nEnter a math problem (or 'exit' to quit): ")
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if query.lower() == 'exit':
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break
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results = asyncio.run(client.process_query(query))
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if results:
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print("\nResults:")
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for result in results:
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if not result:
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continue
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print(f"\n{result['agent']}:")
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print("-" * 50)
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print(result['response'])
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print("-" * 50)
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# Process query through agent
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result = agent.run(query)
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print("\nResult:", result)
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if __name__ == "__main__":
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main()
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