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| from loguru import logger | |
| from swarms.structs.agent import Agent | |
| from swarms.structs.graph_swarm import GraphSwarm | |
| if __name__ == "__main__": | |
| try: | |
| # Create agents | |
| data_collector = Agent( | |
| agent_name="Market-Data-Collector", | |
| model_name="openai/gpt-4o", | |
| max_loops=1, | |
| streaming_on=True, | |
| ) | |
| trend_analyzer = Agent( | |
| agent_name="Market-Trend-Analyzer", | |
| model_name="openai/gpt-4o", | |
| max_loops=1, | |
| streaming_on=True, | |
| ) | |
| report_generator = Agent( | |
| agent_name="Investment-Report-Generator", | |
| model_name="openai/gpt-4o", | |
| max_loops=1, | |
| streaming_on=True, | |
| ) | |
| # Create swarm | |
| swarm = GraphSwarm( | |
| agents=[ | |
| (data_collector, []), | |
| (trend_analyzer, ["Market-Data-Collector"]), | |
| (report_generator, ["Market-Trend-Analyzer"]), | |
| ], | |
| swarm_name="Market Analysis Intelligence Network", | |
| ) | |
| # Run the swarm | |
| result = swarm.run( | |
| "Analyze current market trends for tech stocks and provide investment recommendations" | |
| ) | |
| # Print results | |
| print(f"Execution success: {result.success}") | |
| print(f"Total time: {result.execution_time:.2f} seconds") | |
| for agent_name, output in result.outputs.items(): | |
| print(f"\nAgent: {agent_name}") | |
| print(f"Output: {output.output}") | |
| if output.error: | |
| print(f"Error: {output.error}") | |
| except Exception as error: | |
| logger.error(error) | |
| raise error | |