app.py

import os
import requests
import matplotlib.pyplot as plt
import numpy as np
import gradio as gr

# Define Agent and Swarm classes based on fractal geometry
class Agent:
    def __init__(self, id, api_key=None):
        self.id = id
        self.task = None
        self.results = None
        self.api_key = api_key

    def execute_task(self):
        if self.task:
            print(f"Agent {self.id} is making an API call to '{self.task}'")
            headers = {"Authorization": f"Bearer {self.api_key}"} if self.api_key else {}
            response = requests.get(self.task, headers=headers)
            if response.status_code == 200:
                self.results = response.json().get('data')[0]
            else:
                self.results = "Error: Unable to fetch data"
            print(f"Agent {self.id} received: {self.results}")

    def communicate(self, other_agents):
        # Communication could be extended for more complex scenarios
        pass

class Swarm:
    def __init__(self, num_agents, fractal_pattern, api_key=None):
        self.agents = [Agent(i, api_key) for i in range(num_agents)]
        self.fractal_pattern = fractal_pattern
        print(f"Swarm created with {num_agents} agents using the {fractal_pattern} pattern.")

    def assign_tasks(self, tasks):
        # Assign tasks to agents based on fractal pattern
        for i, task in enumerate(tasks):
            self.agents[i % len(self.agents)].task = task
            print(f"Task assigned to Agent {self.agents[i % len(self.agents)].id}: {task}")

    def execute(self):
        for agent in self.agents:
            agent.execute_task()
        for agent in self.agents:
            agent.communicate(self.agents)

    def gather_results(self):
        return [agent.results for agent in self.agents if agent.results]

# Generate tasks for the swarm
def generate_tasks(api_url, num_tasks):
    return [api_url] * num_tasks

# Function to plot points in a pentagonal pattern and mirror them orthogonally
def plot_pentagonal_and_mirrored(results):
    fig, ax = plt.subplots()
    ax.set_aspect('equal')

    # Define pentagon vertices
    angle = 2 * np.pi / 5
    radius = 1
    pentagon_points = np.array([(radius * np.cos(i * angle), radius * np.sin(i * angle)) for i in range(5)])

    # Plot pentagon
    for i in range(5):
        ax.plot([pentagon_points[i][0], pentagon_points[(i + 1) % 5][0]],
                [pentagon_points[i][1], pentagon_points[(i + 1) % 5][1]], 'k-')

    # Define inner points for 9-agent spread
    center = np.array([0, 0])
    points = [
        center,
        (center + pentagon_points[0]) / 2,
        (center + pentagon_points[1]) / 2,
        (center + pentagon_points[2]) / 2,
        (center + pentagon_points[3]) / 2,
        (center + pentagon_points[4]) / 2,
        (pentagon_points[0] + pentagon_points[1]) / 2,
        (pentagon_points[1] + pentagon_points[2]) / 2,
        (pentagon_points[2] + pentagon_points[3]) / 2
    ]

    # Plot points and results, along with their mirrored counterparts
    for i, point in enumerate(points[:len(results)]):
        ax.plot(point[0], point[1], 'bo')
        ax.text(point[0], point[1], results[i], fontsize=9, ha='right')

        # Mirrored points
        mirrored_x = [-point[0], point[0]]
        mirrored_y = [-point[1], point[1]]

        for mx in mirrored_x:
            for my in mirrored_y:
                if (mx, my) != (point[0], point[1]):
                    ax.plot(mx, my, 'ro')
                    ax.text(mx, my, results[i], fontsize=9, ha='right')

    plt.show()

# Function to run the swarm and plot results
def run_swarm(api_url, api_key, num_agents, num_tasks):
    # Create a swarm with a fractal pattern (Pentagonal spread)
    swarm = Swarm(num_agents=num_agents, fractal_pattern="Pentagonal", api_key=api_key)
    tasks = generate_tasks(api_url, num_tasks)
    swarm.assign_tasks(tasks)
    swarm.execute()

    # Gather results
    results = swarm.gather_results()

    # Print all results
    print("\nAll results retrieved by the swarm:")
    for i, result in enumerate(results):
        print(f"Result {i + 1}: {result}")

    # Plot the results in a pentagonal pattern with mirrored points
    if results:
        plot_pentagonal_and_mirrored(results)

    return results

# Gradio interface
def gradio_interface(api_url, api_key, num_agents, num_tasks):
    results = run_swarm(api_url, api_key, num_agents, num_tasks)
    return results

iface = gr.Interface(
    fn=gradio_interface,
    inputs=[
        gr.Textbox(label="API URL", placeholder="Enter the API URL"),
        gr.Textbox(label="API Key (Optional)", placeholder="Enter the API Key"),
        gr.Number(label="Number of Agents", value=9, precision=0),
        gr.Number(label="Number of API Calls", value=9, precision=0)
    ],
    outputs=gr.Textbox(label="Results"),
    title="Swarm API Call and Plotter",
    description="Enter the API URL, API Key (Optional), number of agents, and number of API calls. The results will be plotted in a pentagonal pattern with mirrored points."
)

iface.launch(share=True)