Interactive demo

from gerenciador_agentes_ia.core import AgentManager
from gerenciador_agentes_ia.agents import Agent

# Initialise the agent manager
agent_manager = AgentManager()

# Create a custom agent for data analysis
data_agent = Agent(
    id="agent_data_analysis",
    name="Data Analysis Agent",
    description="Specialist in data analysis and visualisation",
    specialty="data_analysis",
    base_prompt="""
    You are a data analysis specialist with deep experience in statistics, data
    visualisation and interpreting results. Your job is to pull useful findings out of a
    dataset and present them clearly enough to act on.
    
    When analysing data you should:
    1. Identify trends, patterns and anomalies
    2. Apply the appropriate statistical methods
    3. Build informative visualisations
    4. Interpret the results clearly
    5. Suggest actions based on what you found
    
    Your answers should be structured, precise and focused on findings that can be acted on.
    """,
    tools=[
        "data_import",
        "statistical_analysis",
        "data_visualization",
        "report_generation"
    ],
    config={
        "model": "gpt-4",
        "temperature": 0.2,
        "max_tokens": 2000,
        "supported_formats": ["csv", "excel", "json", "sql"]
    }
)

# Register the agent with the system
agent_manager.register_agent(data_agent)

# Check the agent registered correctly
registered_agent = agent_manager.get_agent("agent_data_analysis")
print(f"Agent registered: {registered_agent.name}")
                            

from gerenciador_agentes_ia.core import ToolRegistry
from gerenciador_agentes_ia.tools import Tool
import requests

# Build a tool that talks to a weather API
class WeatherTool(Tool):
    def __init__(self, api_key):
        super().__init__(
            name="weather_tool",
            description="Fetches weather information for a given location",
            parameters={
                "location": {
                    "type": "string",
                    "description": "Nome da cidade ou coordenadas (latitude,longitude)"
                },
                "units": {
                    "type": "string",
                    "description": "Unidades de medida (metric, imperial)",
                    "default": "metric"
                }
            }
        )
        self.api_key = api_key
        self.base_url = "https://api.openweathermap.org/data/2.5/weather"
    
    def execute(self, parameters):
        """
        Executa a ferramenta com os parâmetros fornecidos.
        
        Args:
            parameters (dict): parameters for the call
            
        Returns:
            dict: the result of the call
        """
        try:
            # Build the request parameters
            params = {
                "q": parameters.get("location"),
                "units": parameters.get("units", "metric"),
                "appid": self.api_key
            }
            
            # Call the API
            response = requests.get(self.base_url, params=params)
            response.raise_for_status()
            
            # Processar resposta
            data = response.json()
            
            # Formatar resultado
            result = {
                "location": f"{data['name']}, {data['sys']['country']}",
                "temperature": {
                    "current": data["main"]["temp"],
                    "feels_like": data["main"]["feels_like"],
                    "min": data["main"]["temp_min"],
                    "max": data["main"]["temp_max"]
                },
                "humidity": data["main"]["humidity"],
                "pressure": data["main"]["pressure"],
                "wind": {
                    "speed": data["wind"]["speed"],
                    "direction": data["wind"]["deg"]
                },
                "weather": {
                    "main": data["weather"][0]["main"],
                    "description": data["weather"][0]["description"]
                }
            }
            
            return {
                "status": "success",
                "data": result
            }
            
        except Exception as e:
            return {
                "status": "error",
                "message": str(e)
            }

# Registrar a ferramenta no sistema
tool_registry = ToolRegistry()
weather_tool = WeatherTool(api_key="your_api_key_here")
tool_registry.register_tool(weather_tool)

# Atribuir a ferramenta a um agente
agent_manager = AgentManager()
agent = agent_manager.get_agent("agent_operations_1")
agent.add_tool("weather_tool")