Update app.py

app.py

@@ -4,7 +4,6 @@ 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
@@ -16,15 +15,18 @@ class Agent:
         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}")
+            try:
+                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}")
+            except Exception as e:
+                self.results = f"Error: {str(e)}"
+                print(f"Agent {self.id} encountered an error: {str(e)}")
 
     def communicate(self, other_agents):
-        # Communication could be extended for more complex scenarios
         pass
 
 class Swarm:
@@ -34,7 +36,6 @@ class Swarm:
         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}")
@@ -48,26 +49,21 @@ class Swarm:
     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,
@@ -81,12 +77,10 @@ def plot_pentagonal_and_mirrored(results):
         (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]]
 
@@ -98,32 +92,26 @@ def plot_pentagonal_and_mirrored(results):
 
     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
+    return "\n".join(str(result) for result in results)
 
 iface = gr.Interface(
     fn=gradio_interface,
@@ -138,4 +126,4 @@ iface = gr.Interface(
     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)
+iface.launch()