Create app.py

app.py

@@ -0,0 +1,64 @@
+import streamlit as st
+import pandas as pd
+import openai
+import matplotlib.pyplot as plt
+import seaborn as sns
+import os
+
+
+openai.api_key = os.getenv("openapikey")
+
+def generate_insight(df, question):
+    """Generates insights using an LLM."""
+    prompt = f"Given the following dataset (first 5 rows):\n{df.head().to_string()}\n\nQuestion: {question}\n\nAnswer:"
+    try:
+        response = openai.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=300,
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"Error: {e}"
+def generate_visualization(df, column_x, column_y=None, vis_type="hist"):
+    """Generates a visualization."""
+    try:
+        plt.figure(figsize=(10, 6))
+        if vis_type == "hist":
+            sns.histplot(df[column_x])
+        elif vis_type == "scatter" and column_y:
+            sns.scatterplot(x=column_x, y=column_y, data=df)
+        else:
+            return "Invalid visualization request."
+        st.pyplot(plt)
+        return "Visualization generated."
+    except Exception as e:
+        return f"Error generating visualization: {e}"
+
+st.title("Data Exploration and Insight Generation")
+
+uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])
+
+if uploaded_file:
+    df = pd.read_csv(uploaded_file)
+    st.write("### Dataset Preview")
+    st.dataframe(df.head())
+
+    st.write("### Dataset Information")
+    st.write(f"Number of rows: {df.shape[0]}")
+    st.write(f"Number of columns: {df.shape[1]}")
+    st.write(f"Column names: {', '.join(df.columns)}")
+
+    question = st.text_input("Ask a question about the data:")
+    if question:
+        insight = generate_insight(df, question)
+        st.write("### Generated Insight")
+        st.write(insight)
+
+    st.write("### Data Visualization")
+    col_x = st.selectbox("Select X-axis column", df.columns)
+    col_y = st.selectbox("Select Y-axis column (for scatter plot)", [None] + list(df.columns))
+    vis_type = st.selectbox("Select visualization type", ["hist", "scatter"])
+    if st.button("Generate Visualization"):
+        vis_result = generate_visualization(df, col_x, col_y if vis_type == "scatter" else None, vis_type)
+        st.write(vis_result)