app.py

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

# Groq API key from secrets
GROQ_API_KEY = os.getenv("HUGGINGFACE_KEY")

# Function to load the uploaded file (CSV or Excel)
def load_file(uploaded_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
def generate_graph(data, query):
    """Generate a graph based on user query."""
    try:
        fig, ax = plt.subplots(figsize=(10, 6))
        
        if "correlation" in query.lower():
            # Correlation matrix
            sns.heatmap(data.corr(), annot=True, cmap="coolwarm", ax=ax)
            st.pyplot(fig)
        elif "histogram" in query.lower():
            # Histogram
            column = st.selectbox("Select a column for the histogram", data.columns)
            sns.histplot(data[column], kde=True, ax=ax)
            st.pyplot(fig)
        elif "bar" in query.lower() and "country" in query.lower():
            # 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, color='skyblue')
                ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
                st.pyplot(fig)
            else:
                st.error("The dataset must contain 'country' and 'units sold' columns.")
        else:
            st.error("Unsupported graph type. Try asking for a correlation matrix, histogram, or bar chart.")
    except Exception as e:
        st.error(f"Error generating graph: {e}")

# 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:
        # 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": prompt}],
            model="llama-3.1-8b-instant",  # Replace with your model
        )

        return chat_completion.choices[0].message.content
    except Exception as e:
        st.error(f"Error querying Groq model: {e}")
        return None

# 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')")

            if query:
                # Generate the graph based on the query
                generate_graph(data, query)

            # 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()