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| import gradio as gr | |
| from agent import Agent | |
| # Initialize the agent | |
| agent = Agent("Problem Solver") | |
| # Set the persona | |
| agent.persona = """You are an analytical problem-solving assistant. | |
| You excel at breaking down complex problems and explaining your thought process. | |
| You are thorough, logical, and clear in your explanations.""" | |
| # Set a global instruction | |
| agent.instruction = "Ensure your responses are clear, detailed, and well-structured and should finished in 70 words." | |
| def execute_task(task, strategy): | |
| """Execute the given task using the selected strategy.""" | |
| agent.strategy = strategy | |
| agent.task = task | |
| response = agent.execute() | |
| return response | |
| # Define available strategies | |
| strategies = agent.available_strategies() | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=execute_task, | |
| inputs=[ | |
| gr.Textbox(lines=5, label="Task"), | |
| gr.Dropdown(choices=strategies, label="Strategy") | |
| ], | |
| outputs=gr.Textbox(label="Response"), | |
| title="Problem Solver Agent", | |
| description="Provide a task and select a strategy to see how the agent responds." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |