Update app.py

app.py

@@ -2,19 +2,28 @@ import os
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
-import gradio as gr
-from groq import Groq
+import streamlit as st
+import requests
 
-GROQ_API_KEY = "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"
+# Groq API Setup
+API_KEY = "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"
+API_URL = "https://api.groq.com/openai/v1/chat/completions"
 
-client = Groq(api_key= GROQ_API_KEY)
+# Streamlit UI Setup
+st.title("Data Analysis and Visualization with Groq API")
 
-def analyze_file(uploaded_file):
+# File upload section
+uploaded_file = st.file_uploader("Upload CSV or Excel File", type=["csv", "xlsx"])
+
+if uploaded_file is not None:
     # Load the file into a pandas DataFrame
     if uploaded_file.name.endswith('.csv'):
-        df = pd.read_csv(uploaded_file.name)
+        df = pd.read_csv(uploaded_file)
     elif uploaded_file.name.endswith('.xlsx'):
-        df = pd.read_excel(uploaded_file.name)
+        df = pd.read_excel(uploaded_file)
+    
+    # Display Data Preview
+    st.write("Data Preview", df.head())
 
     # Perform basic data analysis
     if 'Gain (dB)' in df.columns and 'Frequency (GHz)' in df.columns:
@@ -22,15 +31,19 @@ def analyze_file(uploaded_file):
         median_gain = df['Gain (dB)'].median()
         std_dev_gain = df['Gain (dB)'].std()
         
-        # Plot the data
+        st.write(f"Mean Gain: {mean_gain}")
+        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(df['Frequency (GHz)'], df['Gain (dB)'], label='Gain (dB)', color='blue')
         ax.set_xlabel('Frequency (GHz)')
         ax.set_ylabel('Gain (dB)')
         ax.set_title('Gain vs Frequency')
         ax.legend()
-        plt.close(fig)  # Close to avoid inline display
-        
+        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. 
@@ -38,34 +51,25 @@ def analyze_file(uploaded_file):
         - Efficiency is consistently above 90%, with the highest reaching 99%.
         """
         
-        chat_completion = client.chat.completions.create(
-            messages=[{
-                "role": "user",
-                "content": f"Analyze this data summary: {data_summary}",
-            }],
-            model="llama-3.3-70b-versatile",  # Ensure this model is supported by Groq
-        )
-        
-        groq_analysis = chat_completion.choices[0].message.content
-        
-        return mean_gain, median_gain, std_dev_gain, fig, groq_analysis
-    else:
-        return "Required columns 'Gain (dB)' or 'Frequency (GHz)' not found in the dataset."
+        # Setup headers and payload for the API request
+        headers = {
+            "Authorization": f"Bearer {API_KEY}",
+            "Content-Type": "application/json"
+        }
 
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=analyze_file,
-    inputs=gr.inputs.File(label="Upload CSV or Excel File"),
-    outputs=[
-        gr.outputs.Textbox(label="Mean Gain"),
-        gr.outputs.Textbox(label="Median Gain"),
-        gr.outputs.Textbox(label="Standard Deviation of Gain"),
-        gr.outputs.Image(label="Plot"),
-        gr.outputs.Textbox(label="Groq's Analysis")
-    ],
-    title="Data Analysis and Visualization with Groq API",
-    description="Upload a CSV or Excel file to analyze the antenna data and get insights."
-)
+        payload = {
+            "messages": [{"role": "user", "content": data_summary}],
+            "model": "llama-3.3-70b-versatile"  # Ensure this model is supported by Groq
+        }
 
-# Launch the interface
-iface.launch()
+        # Send request to Groq API
+        response = requests.post(API_URL, json=payload, headers=headers)
+
+        if response.status_code == 200:
+            groq_analysis = response.json()["choices"][0]["message"]["content"]
+            st.write("Groq's Analysis:")
+            st.write(groq_analysis)
+        else:
+            st.write(f"Error: {response.status_code}, {response.text}")
+    else:
+        st.write("Required columns 'Gain (dB)' or 'Frequency (GHz)' not found in the dataset.")