Update app.py

app.py

@@ -1,13 +1,16 @@
 import streamlit as st
 import pandas as pd
 import plotly.express as px
-import random
+import json
 import time
 
 st.set_page_config(layout="wide")
 
-# Specify the radius within which the dots should appear
-radius = 5
+# Load the positions data
+positions_df = pd.read_csv('./data/positions.csv')
+
+# Preprocess the 'Positions' column to convert from string to dictionary
+positions_df['Positions'] = positions_df['Positions'].apply(json.loads)
 
 # Create two columns in the Streamlit app
 left_column, right_column = st.columns(2)
@@ -15,49 +18,36 @@ left_column, right_column = st.columns(2)
 # In the left column, allow the user to input a common goal for all agents
 common_goal = left_column.text_area("Common Goal for the Agents", "Enter a goal")
 
-# Number of dots is set to 4
-num_dots = 4
-
-# Initialize lists to hold agent names, tasks, and backstories. Limited to 4 agents.
-agent_names = []
-tasks = []
-backstories = []
-
-# Loop fixed to 4 for the four agents
-for i in range(4):
-    agent_names.append(left_column.text_input(f"Agent {i+1} Name", key=f"name_{i}"))
-    tasks.append(left_column.text_input(f"Agent {i+1} Task", key=f"task_{i}"))
-    backstories.append(left_column.text_area(f"Agent {i+1} Backstory", key=f"backstory_{i}"))
+# Initialize lists to hold agent names, tasks, and backstories from the dataframe
+agent_names = list(positions_df['Agent'].unique())
+tasks = list(positions_df['Task'].unique())
+backstories = list(positions_df['Backstory'].unique())
 
 # Placeholder for the Plotly chart in the right column
 chart_placeholder = right_column.empty()
 
-# Define colors for the dots
-colors = ['red', 'green', 'blue', 'purple']
+# Index for accessing rows in positions_df, starting with the first row after the header
+current_index = 0
 
 while True:  # This loop will simulate real-time data updates
-    # Create a list to hold the new data points
-    new_data_points = []
+    # Fetch the current row's position data
+    current_positions = positions_df.iloc[current_index % len(positions_df)]['Positions']
     
-    # Generate random x and y positions within the specified radius for 4 dots
-    for i in range(num_dots):
-        new_x = random.uniform(-radius, radius)
-        new_y = random.uniform(-radius, radius)
-        # Append the new data point as a dictionary to the list
-        new_data_points.append({'x': new_x, 'y': new_y, 'color': colors[i]})
+    # Convert current_positions into a list of dicts suitable for DataFrame creation
+    new_data_points = [{'Agent': agent, 'x': pos[0], 'y': pos[1]} for agent, pos in current_positions.items()]
     
     # Create a new DataFrame from the list of new data points
     new_data = pd.DataFrame(new_data_points)
     
-    # Create a new Plotly figure for the scatter plot
-    fig = px.scatter(new_data, x='x', y='y', color='color', title="Random Dots with Assigned Agents", color_discrete_sequence=colors)
+    # Create a new Plotly figure for the scatter plot, using Agent names for colors
+    fig = px.scatter(new_data, x='x', y='y', color='Agent', title="Random Dots with Assigned Agents")
     
     # Update the figure layout to better visualize the dots
     fig.update_layout(xaxis_title='X Axis',
                       yaxis_title='Y Axis',
                       autosize=True,
-                      xaxis=dict(range=[-radius, radius]),
-                      yaxis=dict(range=[-radius, radius]))
+                      xaxis=dict(range=[-5, 5]),
+                      yaxis=dict(range=[-5, 5]))
     
     # Update traces to adjust the appearance of the dots, setting radius to 10
     fig.update_traces(marker=dict(size=20))  # Size adjusted for radius of 10
@@ -65,5 +55,8 @@ while True:  # This loop will simulate real-time data updates
     # Display the figure in the right column
     chart_placeholder.plotly_chart(fig, use_container_width=True)
 
+    # Increment the index to move to the next row for the next update
+    current_index += 1
+
     # Pause for a moment before updating the chart with new dots
     time.sleep(1)