Update app.py

app.py

@@ -2,63 +2,27 @@ import streamlit as st
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
+from io import StringIO
+import openai
 import os
 
-# Try importing openpyxl, and install if not present
-try:
-    import openpyxl
-except ImportError:
-    st.error("openpyxl module is required to read Excel files. Attempting to install...")
-    os.system('pip install openpyxl')
-    st.success("openpyxl installed successfully. Please restart the app.")
+# Groq API key from secrets
+GROQ_API_KEY = os.getenv("HUGGINGFACE_KEY")
 
-# Import the Groq SDK (after installing it)
-try:
-    from groq import Groq
-except ImportError:
-    st.error("The 'groq' library is required but not installed. Please ensure it's included in requirements.txt.")
-    raise
-
-# Configure page
-st.set_page_config(page_title="Data Augmentation App", layout="wide")
-st.markdown(
-    f"""
-    <style>
-        .reportview-container {{
-            background: url("https://cdn.pixabay.com/photo/2016/06/02/02/33/triangles-1430105_1280.png");
-            background-size: cover;
-        }}
-        footer {{
-            text-align: left;
-        }}
-    </style>
-    """,
-    unsafe_allow_html=True,
-)
-
-st.title("Data Augmentation and Analysis App")
-st.sidebar.title("Upload Your File")
-st.sidebar.markdown("Supported formats: CSV, Excel")
-
-# Fetch Groq API key from Streamlit secrets
-groq_api_key = st.secrets.get("HUGGINGFACE_KEY")  # Fetch Groq API key stored in secrets.json
-if not groq_api_key:
-    st.error("Groq API key not found in secrets.")
-else:
-    st.success("Groq API Key Loaded Successfully!")
-
-# Initialize Groq client
-client = Groq(api_key=groq_api_key)
-
-# Function to load data from file (CSV/Excel)
+# Function to load the uploaded file (CSV or Excel)
 def load_file(uploaded_file):
-    """Load the uploaded file."""
-    if uploaded_file.name.endswith('.csv'):
-        return pd.read_csv(uploaded_file)
-    elif uploaded_file.name.endswith('.xlsx'):
-        return pd.read_excel(uploaded_file)
-    else:
-        st.error("Unsupported file format. Please upload a CSV or Excel file.")
+    """Load data from an uploaded file."""
+    try:
+        if uploaded_file.type == "text/csv":
+            data = pd.read_csv(uploaded_file)
+        elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
+            data = pd.read_excel(uploaded_file)
+        else:
+            st.error("Unsupported file type.")
+            return None
+        return data
+    except Exception as e:
+        st.error(f"Error loading file: {e}")
         return None
 
 # Function to generate graph based on user query
@@ -80,7 +44,7 @@ def generate_graph(data, query):
             # Bar chart for countries and units sold
             if 'country' in data.columns and 'units sold' in data.columns:
                 country_data = data[['country', 'units sold']].groupby('country').sum().reset_index()
-                sns.barplot(x='country', y='units sold', data=country_data, ax=ax)
+                sns.barplot(x='country', y='units sold', data=country_data, ax=ax, color='skyblue')
                 ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
                 st.pyplot(fig)
             else:
@@ -90,44 +54,68 @@ def generate_graph(data, query):
     except Exception as e:
         st.error(f"Error generating graph: {e}")
 
-# Function to handle user queries using the Groq model
-def handle_query(query):
-    """Handle user query using the Groq model."""
+# Function to query the Groq model (Groq API)
+def query_groq_model(prompt):
+    """Send a query to the Groq model and get a response."""
     try:
-        # Send user query to Groq model using Groq SDK
+        # Initialize Groq client
+        client = Groq(api_key=GROQ_API_KEY)
+
+        # Query Groq model for response
         chat_completion = client.chat.completions.create(
-            messages=[{"role": "user", "content": query}],
-            model="llama3-8b-8192",  # Model name as per your Groq model
+            messages=[{"role": "user", "content": prompt}],
+            model="llama-3.1-8b-instant",  # Replace with your model
         )
-        
-        # Display the response
-        st.write("Response from Groq Model:", chat_completion.choices[0].message.content)
-        
+
+        return chat_completion.choices[0].message.content
     except Exception as e:
-        st.error(f"Error in Groq processing: {e}")
+        st.error(f"Error querying Groq model: {e}")
+        return None
 
-# Main App
-uploaded_file = st.sidebar.file_uploader("Upload your file here", type=["csv", "xlsx"])
-if uploaded_file:
-    data = load_file(uploaded_file)
-    if data is not None:
-        st.write("Dataset Preview")
-        st.dataframe(data)
+# Streamlit App Interface
+def main():
+    st.set_page_config(page_title="Data Augmentation and Visualization", page_icon="📊", layout="wide")
+    
+    # Set background image
+    st.markdown(
+        """
+        <style>
+        .stApp {
+            background-image: url('https://cdn.pixabay.com/photo/2016/06/02/02/33/triangles-1430105_1280.png');
+            background-size: cover;
+        }
+        </style>
+        """, unsafe_allow_html=True
+    )
+    
+    st.title("Data Augmentation and Visualization with Groq API")
+    st.markdown("Created by: Shamil Shahbaz", unsafe_allow_html=True)
+    
+    # File upload section
+    uploaded_file = st.file_uploader("Upload a CSV or Excel file", type=["csv", "xlsx"])
+    
+    if uploaded_file is not None:
+        # Load and display data
+        data = load_file(uploaded_file)
+        
+        if data is not None:
+            st.write("Dataset preview:", data.head())
+
+            # User input for graph generation
+            query = st.text_input("Enter your query (e.g., 'Generate a bar chart for countries and units sold')")
 
-        query = st.text_area("Ask your question about the dataset")
-        if query:
-            if "table" in query.lower():
-                st.write("Table Preview")
-                st.write(data)
-            elif "graph" in query.lower():
+            if query:
+                # Generate the graph based on the query
                 generate_graph(data, query)
-            else:
-                handle_query(query)  # Use Groq model for query processing
 
-# Footer
-footer = """
-    <div style='text-align: left; padding: 10px;'>
-        <footer>Created by: Shamil Shahbaz</footer>
-    </div>
-"""
-st.markdown(footer, unsafe_allow_html=True)
+            # User input for Groq model query
+            model_query = st.text_input("Ask Groq model a question:")
+            
+            if model_query:
+                # Query the Groq model and display response
+                response = query_groq_model(model_query)
+                if response:
+                    st.write("Groq Model Response:", response)
+
+if __name__ == "__main__":
+    main()