Update app.py

app.py

@@ -1,7 +1,6 @@
 import os
 import pandas as pd
 import numpy as np
-import matplotlib.pyplot as plt
 import streamlit as st
 import requests
 
@@ -53,15 +52,6 @@ def analyze_file(uploaded_file):
             st.write(f"Median Gain: {median_gain}")
             st.write(f"Standard Deviation of Gain: {std_dev_gain}")
 
-            # Plotting the data
-            fig, ax = plt.subplots()
-            ax.plot(freq_values, gain_values, label='Gain (dB)', color='blue')
-            ax.set_xlabel('Frequency (GHz)')
-            ax.set_ylabel('Gain (dB)')
-            ax.set_title('Gain vs Frequency')
-            ax.legend()
-            st.pyplot(fig)
-
             # Send summary to Groq API for analysis
             data_summary = f"""
             The dataset contains simulation results for antennas. The frequency range is from 1 GHz to 10 GHz. 
@@ -96,7 +86,7 @@ def analyze_file(uploaded_file):
 
 
 # Streamlit Interface
-st.title("Data Analysis and Visualization with Groq API")
+st.title("Data Analysis with Groq API")
 st.write("Upload a CSV or Excel file to analyze the antenna data and get insights.")
 
 # File upload
@@ -106,14 +96,12 @@ if uploaded_file is not None:
     results = analyze_file(uploaded_file)
     
     if isinstance(results, tuple):  # If it's a valid result (tuple)
-        mean_gain, median_gain, std_dev_gain, fig, groq_analysis = results
+        mean_gain, median_gain, std_dev_gain, groq_analysis = results
         
         st.write(f"Mean Gain: {mean_gain}")
         st.write(f"Median Gain: {median_gain}")
         st.write(f"Standard Deviation of Gain: {std_dev_gain}")
         
-        st.pyplot(fig)  # Show plot
-        
         st.write("Groq's Analysis:")
         st.write(groq_analysis)
     else: