Update app.py

app.py

@@ -4,11 +4,6 @@ import matplotlib.pyplot as plt
 import seaborn as sns
 import os
 from io import StringIO
-import openai
-from groq import Groq
-
-# 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):
@@ -41,33 +36,47 @@ def generate_graph(data, query):
                 st.pyplot(fig)
             else:
                 st.error("The dataset must contain 'country' and 'gross_sales' columns.")
-        else:
-            st.error("Unsupported graph type. Try asking for a 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)
+        elif "line" in query.lower() and "sales trend" in query.lower():
+            # Line chart for sales trend over time
+            if 'date' in data.columns and 'sales' in data.columns:
+                data['date'] = pd.to_datetime(data['date'])
+                sales_trend = data.groupby('date')['sales'].sum().reset_index()
+                sns.lineplot(x='date', y='sales', data=sales_trend, ax=ax)
+                ax.set_title("Sales Trend Over Time")
+                st.pyplot(fig)
+            else:
+                st.error("The dataset must contain 'date' and 'sales' columns.")
+        elif "scatter" in query.lower() and "relationship" in query.lower():
+            # Scatter plot for relationships
+            columns = query.lower().split("between")[-1].strip().split("and")
+            x_col = columns[0].strip()
+            y_col = columns[1].strip()
 
-        # 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
-        )
+            if x_col in data.columns and y_col in data.columns:
+                sns.scatterplot(x=x_col, y=y_col, data=data, ax=ax)
+                ax.set_title(f"Scatter Plot: {x_col} vs {y_col}")
+                st.pyplot(fig)
+            else:
+                st.error(f"The dataset must contain '{x_col}' and '{y_col}' columns.")
+        elif "histogram" in query.lower():
+            # Histogram for a specified column
+            column = query.lower().split("for")[-1].strip()
 
-        return chat_completion.choices[0].message.content
+            if column in data.columns:
+                sns.histplot(data[column], bins=20, kde=True, ax=ax, color='green')
+                ax.set_title(f"Histogram of {column}")
+                st.pyplot(fig)
+            else:
+                st.error(f"The dataset must contain the column '{column}'.")
+        else:
+            st.error("Unsupported graph type. Try asking for a bar chart, line chart, scatter plot, or histogram.")
     except Exception as e:
-        st.error(f"Error querying Groq model: {e}")
-        return None
+        st.error(f"Error generating graph: {e}")
 
 # Streamlit App Interface
 def main():
-    st.set_page_config(page_title="Data Augmentation and Visualization", page_icon="📊", layout="wide")
-    
+    st.set_page_config(page_title="Data Visualization App", page_icon="📊", layout="wide")
+
     # Set background image
     st.markdown(
         """
@@ -79,17 +88,17 @@ def main():
         </style>
         """, unsafe_allow_html=True
     )
-    
-    st.title("Data Augmentation and Visualization with Groq API")
+
+    st.title("Data Visualization App")
     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())
 
@@ -100,14 +109,5 @@ def main():
                 # 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()